From bc3887c424b42d0ccdfdec67097a0ff86c6a25b8 Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Mon, 29 Jun 2026 15:29:26 +0000 Subject: [PATCH 001/120] versions: rework the Versions Benchmark on Docker images Rebuild the ClickHouse Versions Benchmark infrastructure from scratch around Docker images so every historical and current version can be run identically, replacing the old apt-based scripts. - list-versions.sh: select versions from the authoritative version_date.tsv (all 1.1.x + latest patch per YY.MM, 151 versions), resolve each to a yandex/clickhouse image, package, or unavailable (image-aware, handles 3- vs 4-component tag mismatches). - prepare-data/: build canonical Native data files for hits, SSB (SF100), mgbench (logs1/2/3) and NYC taxi using only oldest-compatible types (Nullable kept only where the queries need IS NULL); stored zstd-6 and streamed via `zstd -dc | clickhouse-client` at load time. - create/: per-version DDL (legacy MergeTree(date,(key),8192) for the earliest 1.1.x, modern PARTITION BY/ORDER BY otherwise) with column schemas under create/schema/. - run-version.sh / run-all.sh: provider abstraction (image + package-in- ubuntu fallback), IPv4 listen override and a matching-version sidecar client image to repair the oldest server images (back to 1.1.54019), plain INSERT ... FORMAT Native loading, 75-query set timed per dataset. Validated full-scale on 1.1.54019 (oldest) and 1.1.54378; data files are gitignored. Co-Authored-By: Claude Opus 4.8 --- versions/.gitignore | 2 + versions/README.md | 124 +++++++++++++- versions/config/listen.xml | 9 + versions/create/create.sh | 64 +++++++ versions/create/schema/hits.columns | 105 ++++++++++++ versions/create/schema/lineorder_flat.columns | 39 +++++ versions/create/schema/logs1.columns | 22 +++ versions/create/schema/logs2.columns | 6 + versions/create/schema/logs3.columns | 9 + versions/create/schema/trips.columns | 52 ++++++ versions/list-versions.sh | 102 +++++++++++ versions/prepare-data/hits.sh | 23 +++ versions/prepare-data/mgbench.sh | 35 ++++ versions/prepare-data/prepare.sh | 27 +++ versions/prepare-data/ssb.sh | 39 +++++ versions/prepare-data/taxi.sh | 81 +++++++++ versions/queries/hits.sql | 43 +++++ versions/queries/mgbench.sql | 15 ++ versions/queries/ssb.sql | 13 ++ versions/queries/taxi.sql | 4 + versions/run-all.sh | 33 ++++ versions/run-version.sh | 159 ++++++++++++++++++ 22 files changed, 1003 insertions(+), 3 deletions(-) create mode 100644 versions/.gitignore create mode 100644 versions/config/listen.xml create mode 100755 versions/create/create.sh create mode 100644 versions/create/schema/hits.columns create mode 100644 versions/create/schema/lineorder_flat.columns create mode 100644 versions/create/schema/logs1.columns create mode 100644 versions/create/schema/logs2.columns create mode 100644 versions/create/schema/logs3.columns create mode 100644 versions/create/schema/trips.columns create mode 100755 versions/list-versions.sh create mode 100755 versions/prepare-data/hits.sh create mode 100755 versions/prepare-data/mgbench.sh create mode 100755 versions/prepare-data/prepare.sh create mode 100755 versions/prepare-data/ssb.sh create mode 100755 versions/prepare-data/taxi.sh create mode 100644 versions/queries/hits.sql create mode 100644 versions/queries/mgbench.sql create mode 100644 versions/queries/ssb.sql create mode 100644 versions/queries/taxi.sql create mode 100755 versions/run-all.sh create mode 100755 versions/run-version.sh diff --git a/versions/.gitignore b/versions/.gitignore new file mode 100644 index 0000000000..5631844f34 --- /dev/null +++ b/versions/.gitignore @@ -0,0 +1,2 @@ +# Prepared Native data files and cached Docker tag lists — large / regenerable. +prepare-data/data/ diff --git a/versions/README.md b/versions/README.md index d491fad491..0984eeac72 100644 --- a/versions/README.md +++ b/versions/README.md @@ -1,7 +1,125 @@ # ClickHouse Versions Benchmark -This is a benchmark for ClickHouse versions based on MgBench, Star Schema Benchmark and ClickBench. +This benchmark runs the **same** workload on the **same** data across every +historical and current ClickHouse version, to show how performance has evolved +over the years. It is published at https://benchmark.clickhouse.com/versions/ +and described in the blog post +[ClickHouse Over the Years with Benchmarks](https://clickhouse.com/blog/clickhouse-over-the-years-with-benchmarks). -It is described [here](https://clickhouse.com/blog/clickhouse-over-the-years-with-benchmarks). +Please don't confuse it with the per-commit ClickHouse Performance Test, described +[here](https://clickhouse.com/blog/testing-the-performance-of-click-house). -Please don't be confused with the per-commit ClickHouse Performance Test, that is described [here](https://clickhouse.com/blog/testing-the-performance-of-click-house). +## How it works + +Every ClickHouse release is published as a Docker image, so each version is run +in its own container — from `1.1.54xxx` (2018) to today — with no host install. + +1. **`list-versions.sh`** — selects the versions to test and resolves an image + for each. Rules: keep **all** of the `1.1.x` family; for calendar-versioned + releases (18.x+) keep only the **latest patch within each major.minor**. + Historical images come from `yandex/clickhouse-server`; modern ones from + `clickhouse/clickhouse-server`. A version with no image falls back to + installing the `.deb`/`.tgz` from packages.clickhouse.com into Ubuntu. + +2. **`prepare-data/prepare.sh`** — builds the canonical data files once, in the + **Native** format, using only the oldest-compatible types so a single set of + files loads into *every* version (validated against `1.1.54378`): + - `hits.native` — ClickBench `hits` (100M rows, 105 columns). + - `ssb.native` — Star Schema Benchmark `lineorder_flat` (scale factor 100). + - `mgbench{1,2,3}.native` — Brown benchmark `logs1`/`logs2`/`logs3`. + - `taxi.native` — NYC `trips`. + + Type downgrades: `LowCardinality`→`String`, `IPv4`→`String`, + `DateTime64`→`DateTime`, enums→`String`; `Nullable` is kept only where the + query set needs `IS NULL` (mgbench `logs1`). Tables without a natural date + carry a synthesised `log_date Date` so the legacy `MergeTree` engine works. + +3. **`create/create.sh `** — emits version-appropriate DDL. + Modern releases use `ENGINE = MergeTree PARTITION BY … ORDER BY …`; the + earliest `1.1.x` (before custom partitioning, < `1.1.54310`) use the legacy + positional `ENGINE = MergeTree(date, (key), 8192)`. Column lists live in + `create/schema/*.columns`. + +4. **`run-version.sh [image]`** — starts the server, creates the + tables, loads each Native file with the simplest possible + `clickhouse-client INSERT … FORMAT Native`, then times every query in + `queries/{mgbench,ssb,hits,taxi}.sql` (`TRIES` runs each, dropping the page + cache between queries) and writes `results/.json`. + +5. **`run-all.sh`** — runs `run-version.sh` for every selected version. + +6. **`generate-results.sh`** — folds `results/*.json` into `index.html`. + +## Usage + +```bash +# 1. Prepare the data once (full scale — reproduces the original benchmark). +# For a quick smoke test use a slice: +# HITS_PARTS=0 SSB_SCALE=1 TAXI_GLOB=trips_xaa.csv.gz ./prepare-data/prepare.sh +./prepare-data/prepare.sh + +# 2. Benchmark one version, a few, or all of them. +./run-version.sh 1.1.54378 +./run-all.sh 1.1.54378 19.6.3.18 24.8.1.1 +./run-all.sh # every version from list-versions.sh + +# 3. Regenerate the website. +./generate-results.sh +``` + +Requires Docker and a recent `clickhouse` binary (used only for data prep; +install with `curl https://clickhouse.com/ | sh`). + +### Runtime and scale + +At the original-blog scale, a single version takes on the order of **hours** +(measured ~4h on `1.1.54019`), dominated by loading the ~1.3B-row taxi table and +the cold first run of each query. The full ~143-version sweep is therefore a +**multi-week** job. To make it tractable, dial down the dominant dataset at prep +time, e.g. a ~100M-row taxi slice: + +```bash +TAXI_GLOB='trips_xa[a-n].csv.gz' ./prepare-data/taxi.sh # ~14 of 175 files +``` + +Smaller `HITS_PARTS` / `SSB_SCALE` reduce the others similarly. The runner is +unchanged — only the prepared file sizes differ. + +## Query set + +75 queries in a fixed order: mgbench (15) + Star Schema Benchmark (13) + +ClickBench/hits (43) + taxi (4). See `queries/*.sql`. Results are reported one +row per query, with `null` for queries a given version cannot run. + +The previous apt-based scripts are kept under `scripts/` and `unified_scripts/` +for reference. + +## Old-version repair + +Two fixes let the benchmark reach back to the very first published image +(`1.1.54019`, Sept 2016): + +- **IPv4 listen override** (`config/listen.xml`, mounted into every image): + old images default to `::` (IPv6) and crash on + boot when the host has IPv6 disabled. +- **Sidecar client**: the oldest server images ship only `clickhouse-server`, + no client binary. The runner detects this and drives them with the + matching-version `yandex/clickhouse-client:` image as a sidecar sharing + the server's network namespace — same native protocol, precise `--time`. + +With these, `1.1.54019` runs 62 of the 75 queries; the 13 nulls are genuine +era limitations (e.g. `Nullable`, which mgbench `logs1`/`logs3` need, postdates +that build; likewise a few `toYYYYMM` / `replaceOne` / `COUNT(DISTINCT)` cases). + +## Notes and limitations + +- The 8 oldest builds (`1.1.54011`, `54165`, `54318`, `54335`, `54336`, + `54358`, `54362`, `54370`) were never published as an image or package, so + `list-versions.sh` lists them with the marker `unavailable` and the sweep + skips them. Everything from `1.1.54019` on is runnable. +- A version that fails to start, create a table, or load data is recorded as a + failure / `null` rows rather than aborting the sweep. +- Native files are stored zstd-compressed (level 6) and streamed through + `zstd -dc | clickhouse-client` at load time. +- Validated end-to-end on `1.1.54019` (oldest, via sidecar), `1.1.54378` + (legacy baseline), `19.8.3.8` (mid), and a modern `24.8` release. diff --git a/versions/config/listen.xml b/versions/config/listen.xml new file mode 100644 index 0000000000..78b75a29d4 --- /dev/null +++ b/versions/config/listen.xml @@ -0,0 +1,9 @@ + + + + 0.0.0.0 + 127.0.0.1 + diff --git a/versions/create/create.sh b/versions/create/create.sh new file mode 100755 index 0000000000..35df5d237e --- /dev/null +++ b/versions/create/create.sh @@ -0,0 +1,64 @@ +#!/usr/bin/env bash +# Emit a CREATE TABLE statement for
tailored to ClickHouse . +# +# ./create.sh
+# +# Tables: hits | lineorder_flat | logs1 | logs2 | logs3 | trips +# +# The same Native data files load into every version, so only the *engine* +# clause changes with the version: +# * Modern releases use custom-partitioning syntax: +# ENGINE = MergeTree PARTITION BY toYYYYMM() ORDER BY () +# * The earliest 1.1.x releases (before custom partitioning landed) only +# understand the legacy positional syntax, which needs a Date column: +# ENGINE = MergeTree(, (), 8192) +# Every table therefore carries a Date column (EventDate / LO_ORDERDATE / +# pickup_date / the synthesised log_date) usable by the legacy engine. + +set -euo pipefail +HERE="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" + +VERSION="${1:?usage: create.sh
}" +TABLE="${2:?usage: create.sh
}" + +# Custom-partitioning (new) syntax landed in 1.1.54310; everything from 18.x +# on supports it. Older 1.1.x builds get the legacy positional engine. +new_syntax() { + local major minor patch + IFS=. read -r major minor patch _ <<<"$VERSION" + if [ "$major" = "1" ] && [ "$minor" = "1" ]; then + [ "${patch:-0}" -ge 54310 ] + else + [ "$major" -ge 18 ] + fi +} + +# Per-table Date column and primary key. +case "$TABLE" in + hits) DATE_COL=EventDate; ORDER_KEY="CounterID, EventDate, intHash32(UserID), EventTime" ;; + lineorder_flat) DATE_COL=LO_ORDERDATE; ORDER_KEY="LO_ORDERDATE, LO_ORDERKEY" ;; + logs1) DATE_COL=log_date; ORDER_KEY="machine_group, machine_name, log_time" ;; + logs2) DATE_COL=log_date; ORDER_KEY="log_time" ;; + logs3) DATE_COL=log_date; ORDER_KEY="event_type, log_time" ;; + trips) DATE_COL=pickup_date; ORDER_KEY="pickup_datetime" ;; + *) echo "unknown table: $TABLE" >&2; exit 1 ;; +esac + +COLUMNS="$(cat "${HERE}/schema/${TABLE}.columns")" + +echo "DROP TABLE IF EXISTS ${TABLE};" +if new_syntax; then + cat <\t\t +# +# The authoritative set of releases comes from ClickHouse's own +# version_date.tsv (oldest is 1.1.54011, 2016-08-18). Selection rules: +# * keep ALL versions of the 1.1.x family; +# * for calendar-versioned releases (18.x and newer), keep only the +# latest patch within every major.minor (one per YY.MM line). +# +# Each selected version is resolved to a provider: +# * yandex/clickhouse-server: historical images (1.1.x .. 21.x) +# * clickhouse/clickhouse-server: modern images (20.x .. today) +# * package no image, but a .deb/.tgz may exist +# (runner installs it into Ubuntu) +# * unavailable neither image nor package published +# (e.g. the pre-1.1.54019 builds) +# We prefer the yandex image while it exists (<= 21.x) and clickhouse otherwise. +# +# The version_date.tsv and Docker tag lists are cached under prepare-data/data/. + +set -euo pipefail +HERE="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" +CACHE="${HERE}/prepare-data/data" +mkdir -p "${CACHE}" + +# --- authoritative release list (version + date) ------------------------------- +VD="${CACHE}/version_date.tsv" +[ -s "${VD}" ] || curl -s "https://clickhouse.com/data/version_date.tsv" -o "${VD}" + +# --- Docker tag lists for provider resolution ---------------------------------- +fetch_tags() { + local repo="$1" out="$2" + [ -s "${out}" ] && return 0 + local token + token=$(curl -s "https://auth.docker.io/token?service=registry.docker.io&scope=repository:${repo}:pull" \ + | grep -oE '"token":"[^"]+"' | sed 's/"token":"//;s/"//') + curl -s -H "Authorization: Bearer ${token}" \ + "https://registry-1.docker.io/v2/${repo}/tags/list" \ + | tr ',' '\n' | grep -oE '"[^"]+"' | tr -d '"' > "${out}" +} +fetch_tags "yandex/clickhouse-server" "${CACHE}/tags-yandex.txt" +fetch_tags "clickhouse/clickhouse-server" "${CACHE}/tags-clickhouse.txt" +YANDEX=$(grep -E '^[0-9]+\.[0-9]+\.[0-9]+(\.[0-9]+)?$' "${CACHE}/tags-yandex.txt" | sort -uV) +CLICKHOUSE=$(grep -E '^[0-9]+\.[0-9]+\.[0-9]+(\.[0-9]+)?$' "${CACHE}/tags-clickhouse.txt" | sort -uV) +has() { grep -qxF "$2" <<<"$1"; } + +# Resolve an image for a version. version_date uses 4-component builds (19.1.16.79) +# while old images are often tagged with 3 (19.1.16), so fall back to the newest +# tag sharing the first three components. Echoes the image ref, or "" if none. +resolve_image() { + local v="$1" major="${v%%.*}" v3 cand + if [ "${major}" -le 21 ] 2>/dev/null && has "${YANDEX}" "${v}"; then + echo "yandex/clickhouse-server:${v}"; return + fi + has "${CLICKHOUSE}" "${v}" && { echo "clickhouse/clickhouse-server:${v}"; return; } + has "${YANDEX}" "${v}" && { echo "yandex/clickhouse-server:${v}"; return; } + v3="$(cut -d. -f1-3 <<<"${v}")" + if [ "${major}" -le 21 ] 2>/dev/null; then + cand=$(grep -E "^${v3//./\\.}(\.|$)" <<<"${YANDEX}" | tail -1) + [ -n "${cand}" ] && { echo "yandex/clickhouse-server:${cand}"; return; } + fi + cand=$(grep -E "^${v3//./\\.}(\.|$)" <<<"${CLICKHOUSE}" | tail -1) + [ -n "${cand}" ] && { echo "clickhouse/clickhouse-server:${cand}"; return; } + echo "" +} + +# --- normalise version_date.tsv to "versiondate", version-sorted ---------- +NORM=$(sed -E 's/^v//; s/-(stable|lts|testing|prestable)\t/\t/' "${VD}" \ + | grep -E '^[0-9]+\.[0-9]+\.[0-9]+' | sort -V) + +emit() { # version date -> resolve provider and print the line + local v="$1" date="$2" image + image="$(resolve_image "${v}")" + if [ -z "${image}" ]; then + # No image. packages.clickhouse.com ships .tgz from 21.1 on; older = gone. + [ "${v%%.*}" -ge 21 ] 2>/dev/null && image="package" || image="unavailable" + fi + printf '%s\t%s\t%s\n' "${v}" "${image}" "${date}" +} + +{ + # All 1.1.x are kept (including the handful with no image, so they are at + # least listed/"found"). + grep -E $'^1\\.1\\.' <<<"${NORM}" | while IFS=$'\t' read -r v date; do + emit "${v}" "${date}" + done + + # Calendar releases: per major.minor, take the latest patch that resolves to + # an actual image (falling back to an older patch in the same line if the + # newest build has no image). + grep -vE $'^1\\.1\\.' <<<"${NORM}" \ + | awk -F'\t' '{split($1,p,"."); print p[1]"."p[2]}' | sort -uV | while read -r key; do + chosen="" + while IFS=$'\t' read -r v date; do + [ -n "$(resolve_image "${v}")" ] && { emit "${v}" "${date}"; chosen=1; break; } + newest_v="${v}"; newest_d="${date}" + done < <(awk -F'\t' -v k="${key}" '{split($1,p,"."); if (p[1]"."p[2]==k) print}' <<<"${NORM}" | sort -rV) + if [ -z "${chosen}" ]; then emit "${newest_v}" "${newest_d}"; fi # none runnable -> newest as unavailable + done +} | sort -V diff --git a/versions/prepare-data/hits.sh b/versions/prepare-data/hits.sh new file mode 100755 index 0000000000..f3503d96a4 --- /dev/null +++ b/versions/prepare-data/hits.sh @@ -0,0 +1,23 @@ +#!/usr/bin/env bash +# Prepare hits.native — the ClickBench "hits" dataset (100M rows, 105 columns). +# +# The published source (hits_100m_obfuscated_*.native.zst) already uses only +# types available in the oldest ClickHouse (UInt*/Int*/String/FixedString/ +# Date/DateTime), so we just re-encode it to a single uncompressed Native file +# that the legacy clickhouse-client can stream straight into an INSERT. +# +# HITS_PARTS controls how many of the 256 source shards to take (0..N-1). +# Use a small number for a quick validation slice; 255 for the full 100M rows. + +set -euo pipefail +HERE="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" +CLICKHOUSE="${CLICKHOUSE:-$HOME/clickhouse}" +OUT="${HERE}/data/hits.native.zst" +PARTS="${HITS_PARTS:-255}" + +SRC="https://datasets.clickhouse.com/hits/native/hits_100m_obfuscated_{0..${PARTS}}.native.zst" +echo "hits: re-encoding shards 0..${PARTS} -> ${OUT}" +"${CLICKHOUSE}" local --max_memory_usage 0 \ + --query "SELECT * FROM url('${SRC}', 'Native') FORMAT Native" \ + | zstd -q -6 -T0 -c > "${OUT}" +ls -l "${OUT}" diff --git a/versions/prepare-data/mgbench.sh b/versions/prepare-data/mgbench.sh new file mode 100755 index 0000000000..2d4637c74e --- /dev/null +++ b/versions/prepare-data/mgbench.sh @@ -0,0 +1,35 @@ +#!/usr/bin/env bash +# Prepare mgbench{1,2,3}.native — the Brown University benchmark log tables. +# +# Sources are header CSVs (mgbench{1,2,3}.csv.xz). We parse the timestamps with +# a modern ClickHouse (so the legacy server never has to), add a synthesised +# log_date Date (needed by the legacy MergeTree engine), and downgrade the +# types to the oldest-compatible set: LowCardinality->String, IPv4->String, +# DateTime64->DateTime. Nullable metric columns are preserved because the +# query set relies on IS NULL / IS NOT NULL (Nullable exists since 1.1.54245). + +set -euo pipefail +HERE="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" +CLICKHOUSE="${CLICKHOUSE:-$HOME/clickhouse}" +BASE="https://clickhouse-public-datasets.s3.amazonaws.com" +run() { "${CLICKHOUSE}" local --max_memory_usage 0 --query "$1"; } + +# logs1: 21 header columns of metrics; keep them Nullable(Float64). +M="Nullable(Float64)" +L1="log_time DateTime, machine_name String, machine_group String, cpu_idle $M, cpu_nice $M, cpu_system $M, cpu_user $M, cpu_wio $M, disk_free $M, disk_total $M, part_max_used $M, load_fifteen $M, load_five $M, load_one $M, mem_buffers $M, mem_cached $M, mem_free $M, mem_shared $M, swap_free $M, bytes_in $M, bytes_out $M" +echo "mgbench: logs1 -> data/mgbench1.native.zst" +run "SELECT toDate(log_time) AS log_date, * FROM url('${BASE}/mgbench1.csv.xz', 'CSVWithNames', '${L1}') FORMAT Native" | zstd -q -6 -T0 -c > "${HERE}/data/mgbench1.native.zst" +ls -l "${HERE}/data/mgbench1.native.zst" + +# logs2: client_ip kept as String (no IPv4 type in old versions). +L2="log_time DateTime, client_ip String, request String, status_code UInt16, object_size UInt64" +echo "mgbench: logs2 -> data/mgbench2.native.zst" +run "SELECT toDate(log_time) AS log_date, * FROM url('${BASE}/mgbench2.csv.xz', 'CSVWithNames', '${L2}') FORMAT Native" | zstd -q -6 -T0 -c > "${HERE}/data/mgbench2.native.zst" +ls -l "${HERE}/data/mgbench2.native.zst" + +# logs3: timestamp carries milliseconds; read it into a distinct String column +# (avoids an alias collision with the output log_time) and drop the fraction. +L3="log_time_raw String, device_id String, device_name String, device_type String, device_floor UInt8, event_type String, event_unit String, event_value Nullable(Float64)" +echo "mgbench: logs3 -> data/mgbench3.native.zst" +run "SELECT toDate(parseDateTimeBestEffort(log_time_raw)) AS log_date, toDateTime(parseDateTimeBestEffort(log_time_raw)) AS log_time, device_id, device_name, device_type, device_floor, event_type, event_unit, event_value FROM url('${BASE}/mgbench3.csv.xz', 'CSV', '${L3}') SETTINGS input_format_csv_skip_first_lines = 1 FORMAT Native" | zstd -q -6 -T0 -c > "${HERE}/data/mgbench3.native.zst" +ls -l "${HERE}/data/mgbench3.native.zst" diff --git a/versions/prepare-data/prepare.sh b/versions/prepare-data/prepare.sh new file mode 100755 index 0000000000..b55d69ee58 --- /dev/null +++ b/versions/prepare-data/prepare.sh @@ -0,0 +1,27 @@ +#!/usr/bin/env bash +# Prepare all Native data files used by the Versions Benchmark. +# +# Produces, under prepare-data/data/ (zstd-compressed Native, level 6): +# hits.native.zst ssb.native.zst mgbench{1,2,3}.native.zst taxi.native.zst +# +# These files use only the oldest-compatible ClickHouse types and load into +# every version (including 1.1.x): the runner streams `zstd -dc file | INSERT`, +# so the legacy clickhouse-client only ever sees plain Native. +# +# Scale is controlled by env vars (defaults reproduce the original benchmark): +# HITS_PARTS=255 # 0..255 -> full 100M rows +# SSB_SCALE=100 # lineorder_flat ~600M rows +# TAXI_GLOB=trips_*.csv.gz # full ~1.3B trips +# For a quick validation slice, e.g.: +# HITS_PARTS=0 SSB_SCALE=1 TAXI_GLOB=trips_xaa.csv.gz ./prepare.sh + +set -euo pipefail +HERE="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" +mkdir -p "${HERE}/data" + +DATASETS="${*:-hits ssb mgbench taxi}" +for ds in ${DATASETS}; do + echo "================ preparing: ${ds} ================" + bash "${HERE}/${ds}.sh" +done +echo "All requested datasets prepared under ${HERE}/data/" diff --git a/versions/prepare-data/ssb.sh b/versions/prepare-data/ssb.sh new file mode 100755 index 0000000000..498817696a --- /dev/null +++ b/versions/prepare-data/ssb.sh @@ -0,0 +1,39 @@ +#!/usr/bin/env bash +# Prepare ssb.native — the Star Schema Benchmark denormalised lineorder_flat +# table built from the published .tbl files (scale factor SSB_SCALE, default 100). +# +# The source .tbl files are comma-separated with quoted strings and ISO dates. +# We join lineorder against the three dimension tables and add the F_YEAR +# column the query set expects, emitting only oldest-compatible types. + +set -euo pipefail +HERE="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" +CLICKHOUSE="${CLICKHOUSE:-$HOME/clickhouse}" +OUT="${HERE}/data/ssb.native.zst" +SCALE="${SSB_SCALE:-100}" +BASE="https://clickhouse-public-datasets.s3.amazonaws.com/ssb/original/${SCALE}" + +LO_S="LO_ORDERKEY UInt32, LO_LINENUMBER UInt8, LO_CUSTKEY UInt32, LO_PARTKEY UInt32, LO_SUPPKEY UInt32, LO_ORDERDATE Date, LO_ORDERPRIORITY String, LO_SHIPPRIORITY UInt8, LO_QUANTITY UInt8, LO_EXTENDEDPRICE UInt32, LO_ORDTOTALPRICE UInt32, LO_DISCOUNT UInt8, LO_REVENUE UInt32, LO_SUPPLYCOST UInt32, LO_TAX UInt8, LO_COMMITDATE Date, LO_SHIPMODE String" +C_S="C_CUSTKEY UInt32, C_NAME String, C_ADDRESS String, C_CITY String, C_NATION String, C_REGION String, C_PHONE String, C_MKTSEGMENT String" +S_S="S_SUPPKEY UInt32, S_NAME String, S_ADDRESS String, S_CITY String, S_NATION String, S_REGION String, S_PHONE String" +P_S="P_PARTKEY UInt32, P_NAME String, P_MFGR String, P_CATEGORY String, P_BRAND String, P_COLOR String, P_TYPE String, P_SIZE UInt8, P_CONTAINER String" + +echo "ssb: building lineorder_flat at scale ${SCALE} -> ${OUT}" +"${CLICKHOUSE}" local --max_memory_usage 0 \ + --input_format_csv_allow_variable_number_of_columns 1 \ + --query " +SELECT + lo.LO_ORDERKEY, lo.LO_LINENUMBER, lo.LO_CUSTKEY, lo.LO_PARTKEY, lo.LO_SUPPKEY, + lo.LO_ORDERDATE, lo.LO_ORDERPRIORITY, lo.LO_SHIPPRIORITY, lo.LO_QUANTITY, + lo.LO_EXTENDEDPRICE, lo.LO_ORDTOTALPRICE, lo.LO_DISCOUNT, lo.LO_REVENUE, + lo.LO_SUPPLYCOST, lo.LO_TAX, lo.LO_COMMITDATE, lo.LO_SHIPMODE, + c.C_NAME, c.C_ADDRESS, c.C_CITY, c.C_NATION, c.C_REGION, c.C_PHONE, c.C_MKTSEGMENT, + s.S_NAME, s.S_ADDRESS, s.S_CITY, s.S_NATION, s.S_REGION, s.S_PHONE, + p.P_NAME, p.P_MFGR, p.P_CATEGORY, p.P_BRAND, p.P_COLOR, p.P_TYPE, p.P_SIZE, p.P_CONTAINER, + toYear(lo.LO_ORDERDATE) AS F_YEAR +FROM url('${BASE}/lineorder.tbl.xz', 'CSV', '${LO_S}') AS lo +INNER JOIN url('${BASE}/customer.tbl.xz', 'CSV', '${C_S}') AS c ON lo.LO_CUSTKEY = c.C_CUSTKEY +INNER JOIN url('${BASE}/supplier.tbl.xz', 'CSV', '${S_S}') AS s ON lo.LO_SUPPKEY = s.S_SUPPKEY +INNER JOIN url('${BASE}/part.tbl.xz', 'CSV', '${P_S}') AS p ON lo.LO_PARTKEY = p.P_PARTKEY +FORMAT Native" | zstd -q -6 -T0 -c > "${OUT}" +ls -l "${OUT}" diff --git a/versions/prepare-data/taxi.sh b/versions/prepare-data/taxi.sh new file mode 100755 index 0000000000..4ad0ed6335 --- /dev/null +++ b/versions/prepare-data/taxi.sh @@ -0,0 +1,81 @@ +#!/usr/bin/env bash +# Prepare taxi.native — the NYC taxi "trips" table (classic ClickHouse dataset). +# +# The source CSVs have 51 positional columns. We read every field as String +# (so parsing never fails across the whole dump) and cast to the oldest- +# compatible target types, synthesising pickup_date (Date) from the pickup +# timestamp for the legacy MergeTree engine. Enum columns (vendor_id, +# payment_type, cab_type) are downgraded to String. +# +# TAXI_GLOB selects the source files: a single file for a quick slice, or +# trips_*.csv.gz (default) for the full ~1.3B-row dataset. + +set -euo pipefail +HERE="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" +CLICKHOUSE="${CLICKHOUSE:-$HOME/clickhouse}" +OUT="${HERE}/data/taxi.native.zst" +GLOB="${TAXI_GLOB:-trips_*.csv.gz}" +SRC="https://clickhouse-datasets.s3.amazonaws.com/taxi/csv/${GLOB}" + +# 51 positional String columns. +STRUCT="$(for i in $(seq 1 51); do printf 'c%d String, ' "$i"; done | sed 's/, $//')" + +echo "taxi: building trips from ${GLOB} -> ${OUT}" +"${CLICKHOUSE}" local --max_memory_usage 0 \ + --query " +SELECT + toDate(parseDateTimeBestEffortOrZero(c3)) AS pickup_date, + toUInt32OrZero(c1) AS trip_id, + c2 AS vendor_id, + parseDateTimeBestEffortOrZero(c3) AS pickup_datetime, + parseDateTimeBestEffortOrZero(c4) AS dropoff_datetime, + c5 AS store_and_fwd_flag, + toUInt8OrZero(c6) AS rate_code_id, + toFloat64OrZero(c7) AS pickup_longitude, + toFloat64OrZero(c8) AS pickup_latitude, + toFloat64OrZero(c9) AS dropoff_longitude, + toFloat64OrZero(c10) AS dropoff_latitude, + toUInt8OrZero(c11) AS passenger_count, + toFloat64OrZero(c12) AS trip_distance, + toFloat32OrZero(c13) AS fare_amount, + toFloat32OrZero(c14) AS extra, + toFloat32OrZero(c15) AS mta_tax, + toFloat32OrZero(c16) AS tip_amount, + toFloat32OrZero(c17) AS tolls_amount, + toFloat32OrZero(c18) AS ehail_fee, + toFloat32OrZero(c19) AS improvement_surcharge, + toFloat32OrZero(c20) AS total_amount, + c21 AS payment_type, + toUInt8OrZero(c22) AS trip_type, + c23 AS pickup, + c24 AS dropoff, + c25 AS cab_type, + toFloat32OrZero(c26) AS precipitation, + toFloat32OrZero(c27) AS snow_depth, + toFloat32OrZero(c28) AS snowfall, + toFloat32OrZero(c29) AS max_temperature, + toFloat32OrZero(c30) AS min_temperature, + toFloat32OrZero(c31) AS average_wind_speed, + toInt32OrZero(c32) AS pickup_nyct2010_gid, + c33 AS pickup_ctlabel, + toInt32OrZero(c34) AS pickup_borocode, + c35 AS pickup_boroname, + c36 AS pickup_ct2010, + c37 AS pickup_boroct2010, + c38 AS pickup_cdeligibil, + c39 AS pickup_ntacode, + c40 AS pickup_ntaname, + toInt32OrZero(c41) AS pickup_puma, + toInt32OrZero(c42) AS dropoff_nyct2010_gid, + c43 AS dropoff_ctlabel, + toInt32OrZero(c44) AS dropoff_borocode, + c45 AS dropoff_boroname, + c46 AS dropoff_ct2010, + c47 AS dropoff_boroct2010, + c48 AS dropoff_cdeligibil, + c49 AS dropoff_ntacode, + c50 AS dropoff_ntaname, + toInt32OrZero(c51) AS dropoff_puma +FROM s3('${SRC}', 'CSV', '${STRUCT}') +FORMAT Native" | zstd -q -6 -T0 -c > "${OUT}" +ls -l "${OUT}" diff --git a/versions/queries/hits.sql b/versions/queries/hits.sql new file mode 100644 index 0000000000..b824dbb42b --- /dev/null +++ b/versions/queries/hits.sql @@ -0,0 +1,43 @@ +SELECT count() FROM hits +SELECT count() FROM hits WHERE AdvEngineID != 0 +SELECT sum(AdvEngineID), count(), avg(ResolutionWidth) FROM hits +SELECT sum(UserID) FROM hits +SELECT uniq(UserID) FROM hits +SELECT uniq(SearchPhrase) FROM hits +SELECT min(EventDate), max(EventDate) FROM hits +SELECT AdvEngineID, count() FROM hits WHERE AdvEngineID != 0 GROUP BY AdvEngineID ORDER BY count() DESC +SELECT RegionID, uniq(UserID) AS u FROM hits GROUP BY RegionID ORDER BY u DESC LIMIT 10 +SELECT RegionID, sum(AdvEngineID), count() AS c, avg(ResolutionWidth), uniq(UserID) FROM hits GROUP BY RegionID ORDER BY c DESC LIMIT 10 +SELECT MobilePhoneModel, uniq(UserID) AS u FROM hits WHERE MobilePhoneModel != '' GROUP BY MobilePhoneModel ORDER BY u DESC LIMIT 10 +SELECT MobilePhone, MobilePhoneModel, uniq(UserID) AS u FROM hits WHERE MobilePhoneModel != '' GROUP BY MobilePhone, MobilePhoneModel ORDER BY u DESC LIMIT 10 +SELECT SearchPhrase, count() AS c FROM hits WHERE SearchPhrase != '' GROUP BY SearchPhrase ORDER BY c DESC LIMIT 10 +SELECT SearchPhrase, uniq(UserID) AS u FROM hits WHERE SearchPhrase != '' GROUP BY SearchPhrase ORDER BY u DESC LIMIT 10 +SELECT SearchEngineID, SearchPhrase, count() AS c FROM hits WHERE SearchPhrase != '' GROUP BY SearchEngineID, SearchPhrase ORDER BY c DESC LIMIT 10 +SELECT UserID, count() FROM hits GROUP BY UserID ORDER BY count() DESC LIMIT 10 +SELECT UserID, SearchPhrase, count() FROM hits GROUP BY UserID, SearchPhrase ORDER BY count() DESC LIMIT 10 +SELECT UserID, SearchPhrase, count() FROM hits GROUP BY UserID, SearchPhrase LIMIT 10 +SELECT UserID, toMinute(EventTime) AS m, SearchPhrase, count() FROM hits GROUP BY UserID, m, SearchPhrase ORDER BY count() DESC LIMIT 10 +SELECT UserID FROM hits WHERE UserID = 12345678901234567890 +SELECT count() FROM hits WHERE URL LIKE '%metrika%' +SELECT SearchPhrase, any(URL), count() AS c FROM hits WHERE URL LIKE '%metrika%' AND SearchPhrase != '' GROUP BY SearchPhrase ORDER BY c DESC LIMIT 10 +SELECT SearchPhrase, any(URL), any(Title), count() AS c, uniq(UserID) FROM hits WHERE Title LIKE '%Яндекс%' AND URL NOT LIKE '%.yandex.%' AND SearchPhrase != '' GROUP BY SearchPhrase ORDER BY c DESC LIMIT 10 +SELECT * FROM hits WHERE URL LIKE '%metrika%' ORDER BY EventTime LIMIT 10 +SELECT SearchPhrase FROM hits WHERE SearchPhrase != '' ORDER BY EventTime LIMIT 10 +SELECT SearchPhrase FROM hits WHERE SearchPhrase != '' ORDER BY SearchPhrase LIMIT 10 +SELECT SearchPhrase FROM hits WHERE SearchPhrase != '' ORDER BY EventTime, SearchPhrase LIMIT 10 +SELECT CounterID, avg(length(URL)) AS l, count() AS c FROM hits WHERE URL != '' GROUP BY CounterID HAVING c > 100000 ORDER BY l DESC LIMIT 25 +SELECT domainWithoutWWW(Referer) AS key, avg(length(Referer)) AS l, count() AS c, any(Referer) FROM hits WHERE Referer != '' GROUP BY key HAVING c > 100000 ORDER BY l DESC LIMIT 25 +SELECT sum(ResolutionWidth), sum(ResolutionWidth + 1), sum(ResolutionWidth + 2), sum(ResolutionWidth + 3), sum(ResolutionWidth + 4), sum(ResolutionWidth + 5), sum(ResolutionWidth + 6), sum(ResolutionWidth + 7), sum(ResolutionWidth + 8), sum(ResolutionWidth + 9), sum(ResolutionWidth + 10), sum(ResolutionWidth + 11), sum(ResolutionWidth + 12), sum(ResolutionWidth + 13), sum(ResolutionWidth + 14), sum(ResolutionWidth + 15), sum(ResolutionWidth + 16), sum(ResolutionWidth + 17), sum(ResolutionWidth + 18), sum(ResolutionWidth + 19), sum(ResolutionWidth + 20), sum(ResolutionWidth + 21), sum(ResolutionWidth + 22), sum(ResolutionWidth + 23), sum(ResolutionWidth + 24), sum(ResolutionWidth + 25), sum(ResolutionWidth + 26), sum(ResolutionWidth + 27), sum(ResolutionWidth + 28), sum(ResolutionWidth + 29), sum(ResolutionWidth + 30), sum(ResolutionWidth + 31), sum(ResolutionWidth + 32), sum(ResolutionWidth + 33), sum(ResolutionWidth + 34), sum(ResolutionWidth + 35), sum(ResolutionWidth + 36), sum(ResolutionWidth + 37), sum(ResolutionWidth + 38), sum(ResolutionWidth + 39), sum(ResolutionWidth + 40), sum(ResolutionWidth + 41), sum(ResolutionWidth + 42), sum(ResolutionWidth + 43), sum(ResolutionWidth + 44), sum(ResolutionWidth + 45), sum(ResolutionWidth + 46), sum(ResolutionWidth + 47), sum(ResolutionWidth + 48), sum(ResolutionWidth + 49), sum(ResolutionWidth + 50), sum(ResolutionWidth + 51), sum(ResolutionWidth + 52), sum(ResolutionWidth + 53), sum(ResolutionWidth + 54), sum(ResolutionWidth + 55), sum(ResolutionWidth + 56), sum(ResolutionWidth + 57), sum(ResolutionWidth + 58), sum(ResolutionWidth + 59), sum(ResolutionWidth + 60), sum(ResolutionWidth + 61), sum(ResolutionWidth + 62), sum(ResolutionWidth + 63), sum(ResolutionWidth + 64), sum(ResolutionWidth + 65), sum(ResolutionWidth + 66), sum(ResolutionWidth + 67), sum(ResolutionWidth + 68), sum(ResolutionWidth + 69), sum(ResolutionWidth + 70), sum(ResolutionWidth + 71), sum(ResolutionWidth + 72), sum(ResolutionWidth + 73), sum(ResolutionWidth + 74), sum(ResolutionWidth + 75), sum(ResolutionWidth + 76), sum(ResolutionWidth + 77), sum(ResolutionWidth + 78), sum(ResolutionWidth + 79), sum(ResolutionWidth + 80), sum(ResolutionWidth + 81), sum(ResolutionWidth + 82), sum(ResolutionWidth + 83), sum(ResolutionWidth + 84), sum(ResolutionWidth + 85), sum(ResolutionWidth + 86), sum(ResolutionWidth + 87), sum(ResolutionWidth + 88), sum(ResolutionWidth + 89) FROM hits +SELECT SearchEngineID, ClientIP, count() AS c, sum(Refresh), avg(ResolutionWidth) FROM hits WHERE SearchPhrase != '' GROUP BY SearchEngineID, ClientIP ORDER BY c DESC LIMIT 10 +SELECT WatchID, ClientIP, count() AS c, sum(Refresh), avg(ResolutionWidth) FROM hits WHERE SearchPhrase != '' GROUP BY WatchID, ClientIP ORDER BY c DESC LIMIT 10 +SELECT WatchID, ClientIP, count() AS c, sum(Refresh), avg(ResolutionWidth) FROM hits GROUP BY WatchID, ClientIP ORDER BY c DESC LIMIT 10 +SELECT URL, count() AS c FROM hits GROUP BY URL ORDER BY c DESC LIMIT 10 +SELECT 1, URL, count() AS c FROM hits GROUP BY 1, URL ORDER BY c DESC LIMIT 10 +SELECT ClientIP AS x, x - 1, x - 2, x - 3, count() AS c FROM hits GROUP BY x, x - 1, x - 2, x - 3 ORDER BY c DESC LIMIT 10 +SELECT URL, count() AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= toDate('2013-07-01') AND EventDate <= toDate('2013-07-31') AND NOT DontCountHits AND NOT Refresh AND notEmpty(URL) GROUP BY URL ORDER BY PageViews DESC LIMIT 10 +SELECT Title, count() AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= toDate('2013-07-01') AND EventDate <= toDate('2013-07-31') AND NOT DontCountHits AND NOT Refresh AND notEmpty(Title) GROUP BY Title ORDER BY PageViews DESC LIMIT 10 +SELECT URL, count() AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= toDate('2013-07-01') AND EventDate <= toDate('2013-07-31') AND NOT Refresh AND IsLink AND NOT IsDownload GROUP BY URL ORDER BY PageViews DESC LIMIT 1000 +SELECT TraficSourceID, SearchEngineID, AdvEngineID, ((SearchEngineID = 0 AND AdvEngineID = 0) ? Referer : '') AS Src, URL AS Dst, count() AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= toDate('2013-07-01') AND EventDate <= toDate('2013-07-31') AND NOT Refresh GROUP BY TraficSourceID, SearchEngineID, AdvEngineID, Src, Dst ORDER BY PageViews DESC LIMIT 1000 +SELECT URLHash, EventDate, count() AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= toDate('2013-07-01') AND EventDate <= toDate('2013-07-31') AND NOT Refresh AND TraficSourceID IN (-1, 6) AND RefererHash = halfMD5('http://yandex.ru/') GROUP BY URLHash, EventDate ORDER BY PageViews DESC LIMIT 100 +SELECT WindowClientWidth, WindowClientHeight, count() AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= toDate('2013-07-01') AND EventDate <= toDate('2013-07-31') AND NOT Refresh AND NOT DontCountHits AND URLHash = halfMD5('http://yandex.ru/') GROUP BY WindowClientWidth, WindowClientHeight ORDER BY PageViews DESC LIMIT 10000; +SELECT toStartOfMinute(EventTime) AS Minute, count() AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= toDate('2013-07-01') AND EventDate <= toDate('2013-07-02') AND NOT Refresh AND NOT DontCountHits GROUP BY Minute ORDER BY Minute; diff --git a/versions/queries/mgbench.sql b/versions/queries/mgbench.sql new file mode 100644 index 0000000000..fe25886551 --- /dev/null +++ b/versions/queries/mgbench.sql @@ -0,0 +1,15 @@ +SELECT machine_name, MIN(cpu) AS cpu_min, MAX(cpu) AS cpu_max, AVG(cpu) AS cpu_avg, MIN(net_in) AS net_in_min, MAX(net_in) AS net_in_max, AVG(net_in) AS net_in_avg, MIN(net_out) AS net_out_min, MAX(net_out) AS net_out_max, AVG(net_out) AS net_out_avg FROM ( SELECT machine_name, ifNull(cpu_user, 0.0) AS cpu, ifNull(bytes_in, 0.0) AS net_in, ifNull(bytes_out, 0.0) AS net_out FROM logs1 WHERE machine_name IN ('anansi','aragog','urd') AND log_time >= toDateTime('2017-01-11 00:00:00')) AS r GROUP BY machine_name; +SELECT machine_name, log_time FROM logs1 WHERE (machine_name LIKE 'cslab%' OR machine_name LIKE 'mslab%') AND load_one IS NULL AND log_time >= toDateTime('2017-01-10 00:00:00') ORDER BY machine_name, log_time; +SELECT dt, hr, AVG(load_fifteen) AS load_fifteen_avg, AVG(load_five) AS load_five_avg, AVG(load_one) AS load_one_avg, AVG(mem_free) AS mem_free_avg, AVG(swap_free) AS swap_free_avg FROM ( SELECT CAST(log_time AS DATE) AS dt, toHour(log_time) AS hr, load_fifteen, load_five, load_one, mem_free, swap_free FROM logs1 WHERE machine_name = 'babbage' AND load_fifteen IS NOT NULL AND load_five IS NOT NULL AND load_one IS NOT NULL AND mem_free IS NOT NULL AND swap_free IS NOT NULL AND log_time >= toDateTime('2017-01-01 00:00:00')) AS r GROUP BY dt, hr ORDER BY dt, hr; +SELECT machine_name, COUNT(*) AS spikes FROM logs1 WHERE machine_group = 'Servers' AND cpu_wio > 0.99 AND log_time >= toDateTime('2016-12-01 00:00:00') AND log_time < toDateTime('2017-01-01 00:00:00') GROUP BY machine_name ORDER BY spikes DESC LIMIT 10; +SELECT machine_name, dt, MIN(mem_free) AS mem_free_min FROM ( SELECT machine_name, CAST(log_time AS DATE) AS dt, mem_free FROM logs1 WHERE machine_group = 'DMZ' AND mem_free IS NOT NULL ) AS r GROUP BY machine_name, dt HAVING MIN(mem_free) < 10000 ORDER BY machine_name, dt; +SELECT dt, hr, SUM(net_in) AS net_in_sum, SUM(net_out) AS net_out_sum, SUM(net_in) + SUM(net_out) AS both_sum FROM ( SELECT CAST(log_time AS DATE) AS dt, toHour(log_time) AS hr, ifNull(bytes_in, 0.0) / 1000000000.0 AS net_in, ifNull(bytes_out, 0.0) / 1000000000.0 AS net_out FROM logs1 WHERE machine_name IN ('allsorts','andes','bigred','blackjack','bonbon','cadbury','chiclets','cotton','crows','dove','fireball','hearts','huey','lindt','milkduds','milkyway','mnm','necco','nerds','orbit','peeps','poprocks','razzles','runts','smarties','smuggler','spree','stride','tootsie','trident','wrigley','york') ) AS r GROUP BY dt, hr ORDER BY both_sum DESC LIMIT 10; +SELECT * FROM logs2 WHERE status_code >= 500 AND log_time >= toDateTime('2012-12-18 00:00:00') ORDER BY log_time; +SELECT * FROM logs2 WHERE status_code >= 200 AND status_code < 300 AND request LIKE '%/etc/passwd%' AND log_time >= toDateTime('2012-05-06 00:00:00') AND log_time < toDateTime('2012-05-20 00:00:00'); +SELECT top_level, AVG(length(request) - length(replaceOne(request, '/',''))) AS depth_avg FROM ( SELECT substring(request, 1, len) AS top_level, request FROM ( SELECT position('/', substring(request, 2)) AS len, request FROM logs2 WHERE status_code >= 200 AND status_code < 300 AND log_time >= toDateTime('2012-12-01 00:00:00')) AS r WHERE len > 0 ) AS s WHERE top_level IN ('/about','/courses','/degrees','/events','/grad','/industry','/news','/people','/publications','/research','/teaching','/ugrad') GROUP BY top_level ORDER BY top_level; +SELECT client_ip, COUNT(*) AS num_requests FROM logs2 WHERE log_time >= toDateTime('2012-10-01 00:00:00') GROUP BY client_ip HAVING COUNT(*) >= 100000 ORDER BY num_requests DESC; +SELECT dt, COUNT(DISTINCT client_ip) FROM ( SELECT CAST(log_time AS DATE) AS dt, client_ip FROM logs2) AS r GROUP BY dt ORDER BY dt; +SELECT AVG(transfer) / 125000000.0 AS transfer_avg, MAX(transfer) / 125000000.0 AS transfer_max FROM ( SELECT log_time, SUM(object_size) AS transfer FROM logs2 GROUP BY log_time) AS r; +SELECT * FROM logs3 WHERE event_type = 'temperature' AND event_value <= 32.0 AND log_time >= '2019-11-29 17:00:00'; +SELECT device_name, device_floor, COUNT(*) AS ct FROM logs3 WHERE event_type = 'door_open' AND log_time >= '2019-06-01 00:00:00' GROUP BY device_name, device_floor ORDER BY ct DESC; +SELECT yr, mo, SUM(coffee_hourly_avg) AS coffee_monthly_sum, AVG(coffee_hourly_avg) AS coffee_monthly_avg, SUM(printer_hourly_avg) AS printer_monthly_sum, AVG(printer_hourly_avg) AS printer_monthly_avg, SUM(projector_hourly_avg) AS projector_monthly_sum, AVG(projector_hourly_avg) AS projector_monthly_avg, SUM(vending_hourly_avg) AS vending_monthly_sum, AVG(vending_hourly_avg) AS vending_monthly_avg FROM ( SELECT dt, yr, mo, hr, AVG(coffee) AS coffee_hourly_avg, AVG(printer) AS printer_hourly_avg, AVG(projector) AS projector_hourly_avg, AVG(vending) AS vending_hourly_avg FROM ( SELECT CAST(log_time AS DATE) AS dt, toYear(log_time) AS yr, EXTRACT(MONTH FROM log_time) AS mo, toHour(log_time) AS hr, CASE WHEN device_name LIKE 'coffee%' THEN event_value END AS coffee, CASE WHEN device_name LIKE 'printer%' THEN event_value END AS printer, CASE WHEN device_name LIKE 'projector%' THEN event_value END AS projector, CASE WHEN device_name LIKE 'vending%' THEN event_value END AS vending FROM logs3 WHERE device_type = 'meter' ) AS r GROUP BY dt, yr, mo, hr ) AS s GROUP BY yr, mo ORDER BY yr, mo; diff --git a/versions/queries/ssb.sql b/versions/queries/ssb.sql new file mode 100644 index 0000000000..243bc9feba --- /dev/null +++ b/versions/queries/ssb.sql @@ -0,0 +1,13 @@ +SELECT sum(LO_EXTENDEDPRICE * LO_DISCOUNT) AS revenue FROM lineorder_flat WHERE F_YEAR = 1993 AND LO_DISCOUNT BETWEEN 1 AND 3 AND LO_QUANTITY < 25; +SELECT sum(LO_EXTENDEDPRICE * LO_DISCOUNT) AS revenue FROM lineorder_flat WHERE toYYYYMM(LO_ORDERDATE) = 199401 AND LO_DISCOUNT BETWEEN 4 AND 6 AND LO_QUANTITY BETWEEN 26 AND 35; +SELECT sum(LO_EXTENDEDPRICE * LO_DISCOUNT) AS revenue FROM lineorder_flat WHERE toRelativeWeekNum(LO_ORDERDATE) - toRelativeWeekNum(toDate('1994-01-01')) = 6 AND F_YEAR = 1994 AND LO_DISCOUNT BETWEEN 5 AND 7 AND LO_QUANTITY BETWEEN 26 AND 35; +SELECT sum(LO_REVENUE), F_YEAR AS year, P_BRAND FROM lineorder_flat WHERE P_CATEGORY = 'MFGR#12' AND S_REGION = 'AMERICA' GROUP BY year, P_BRAND ORDER BY year, P_BRAND; +SELECT sum(LO_REVENUE), F_YEAR AS year, P_BRAND FROM lineorder_flat WHERE P_BRAND >= 'MFGR#2221' AND P_BRAND <= 'MFGR#2228' AND S_REGION = 'ASIA' GROUP BY year, P_BRAND ORDER BY year, P_BRAND; +SELECT sum(LO_REVENUE), F_YEAR AS year, P_BRAND FROM lineorder_flat WHERE P_BRAND = 'MFGR#2239' AND S_REGION = 'EUROPE' GROUP BY year, P_BRAND ORDER BY year, P_BRAND; +SELECT C_NATION, S_NATION, F_YEAR AS year, sum(LO_REVENUE) AS revenue FROM lineorder_flat WHERE C_REGION = 'ASIA' AND S_REGION = 'ASIA' AND year >= 1992 AND year <= 1997 GROUP BY C_NATION, S_NATION, year ORDER BY year ASC, revenue DESC; +SELECT C_CITY, S_CITY, F_YEAR AS year, sum(LO_REVENUE) AS revenue FROM lineorder_flat WHERE C_NATION = 'UNITED STATES' AND S_NATION = 'UNITED STATES' AND year >= 1992 AND year <= 1997 GROUP BY C_CITY, S_CITY, year ORDER BY year ASC, revenue DESC; +SELECT C_CITY, S_CITY, F_YEAR AS year, sum(LO_REVENUE) AS revenue FROM lineorder_flat WHERE (C_CITY = 'UNITED KI1' OR C_CITY = 'UNITED KI5') AND (S_CITY = 'UNITED KI1' OR S_CITY = 'UNITED KI5') AND year >= 1992 AND year <= 1997 GROUP BY C_CITY, S_CITY, year ORDER BY year ASC, revenue DESC; +SELECT C_CITY, S_CITY, F_YEAR AS year, sum(LO_REVENUE) AS revenue FROM lineorder_flat WHERE (C_CITY = 'UNITED KI1' OR C_CITY = 'UNITED KI5') AND (S_CITY = 'UNITED KI1' OR S_CITY = 'UNITED KI5') AND toYYYYMM(LO_ORDERDATE) = 199712 GROUP BY C_CITY, S_CITY, year ORDER BY year ASC, revenue DESC; +SELECT F_YEAR AS year, C_NATION, sum(LO_REVENUE - LO_SUPPLYCOST) AS profit FROM lineorder_flat WHERE C_REGION = 'AMERICA' AND S_REGION = 'AMERICA' AND (P_MFGR = 'MFGR#1' OR P_MFGR = 'MFGR#2') GROUP BY year, C_NATION ORDER BY year ASC, C_NATION ASC; +SELECT F_YEAR AS year, S_NATION, P_CATEGORY, sum(LO_REVENUE - LO_SUPPLYCOST) AS profit FROM lineorder_flat WHERE C_REGION = 'AMERICA' AND S_REGION = 'AMERICA' AND (year = 1997 OR year = 1998) AND (P_MFGR = 'MFGR#1' OR P_MFGR = 'MFGR#2') GROUP BY year, S_NATION, P_CATEGORY ORDER BY year ASC, S_NATION ASC, P_CATEGORY ASC; +SELECT F_YEAR AS year, S_CITY, P_BRAND, sum(LO_REVENUE - LO_SUPPLYCOST) AS profit FROM lineorder_flat WHERE S_NATION = 'UNITED STATES' AND (year = 1997 OR year = 1998) AND P_CATEGORY = 'MFGR#14' GROUP BY year, S_CITY, P_BRAND ORDER BY year ASC, S_CITY ASC, P_BRAND ASC; diff --git a/versions/queries/taxi.sql b/versions/queries/taxi.sql new file mode 100644 index 0000000000..b491959033 --- /dev/null +++ b/versions/queries/taxi.sql @@ -0,0 +1,4 @@ +SELECT cab_type, count(*) FROM trips GROUP BY cab_type; +SELECT passenger_count, avg(total_amount) FROM trips GROUP BY passenger_count; +SELECT passenger_count, toYear(pickup_date) AS year, count(*) FROM trips GROUP BY passenger_count, year; +SELECT passenger_count, toYear(pickup_date) AS year, round(trip_distance) AS distance, count(*) FROM trips GROUP BY passenger_count, year, distance ORDER BY year, count(*) DESC; diff --git a/versions/run-all.sh b/versions/run-all.sh new file mode 100755 index 0000000000..62bf5c92b5 --- /dev/null +++ b/versions/run-all.sh @@ -0,0 +1,33 @@ +#!/usr/bin/env bash +# Run the Versions Benchmark across every selected version. +# +# ./run-all.sh # all versions from list-versions.sh +# ./run-all.sh 1.1.54378 24.8.1.1 ... # only the given versions +# +# Each version is benchmarked in its own container by run-version.sh, which +# writes results/.json. Prepared Native files must already exist +# (see prepare-data/prepare.sh). Failures on one version don't stop the sweep. + +set -uo pipefail +HERE="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" +cd "${HERE}" + +if [ "$#" -gt 0 ]; then + # Benchmark only the named versions (image resolved inside run-version.sh). + for v in "$@"; do + echo "######## ${v} ########" + ./run-version.sh "${v}" &2 + done +else + # Materialise the list first: run-version.sh runs `docker exec -i`, which + # would otherwise drain this loop's stdin (the version list) and stop it + # after one iteration. Reading from a temp file + redirecting run-version's + # stdin from /dev/null keeps the list intact. + LIST="$(mktemp)"; trap 'rm -f "${LIST}"' EXIT + ./list-versions.sh > "${LIST}" + while IFS=$'\t' read -r version image date; do + [ "${image}" = "unavailable" ] && { echo "skip ${version} (${date}): no image or package published" >&2; continue; } + echo "######## ${version} (${image}, ${date}) ########" + ./run-version.sh "${version}" "${image}" &2 + done < "${LIST}" +fi diff --git a/versions/run-version.sh b/versions/run-version.sh new file mode 100755 index 0000000000..dd42514d5a --- /dev/null +++ b/versions/run-version.sh @@ -0,0 +1,159 @@ +#!/usr/bin/env bash +# Benchmark a single ClickHouse version inside Docker. +# +# ./run-version.sh [image_ref] +# +# Spins up the server, creates the six tables with version-appropriate DDL +# (create/create.sh), loads the prepared Native files with a plain +# `clickhouse-client INSERT ... FORMAT Native`, then times every query in +# queries/{mgbench,ssb,hits,taxi}.sql (TRIES runs each, dropping the page +# cache between queries) and writes results/.json. +# +# image_ref comes from list-versions.sh: either "/clickhouse-server:" +# or the literal "package" (install the .deb into Ubuntu — fallback provider). + +set -uo pipefail +HERE="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" +DATA="${DATA:-${HERE}/prepare-data/data}" +TRIES="${TRIES:-3}" +MEM=100000000000 # 100G per-query memory limit + +VERSION="${1:?usage: run-version.sh [image_ref]}" +IMAGE="${2:-}" +[ -z "${IMAGE}" ] && IMAGE="$(./list-versions.sh | awk -v v="${VERSION}" '$1==v{print $2}')" +[ -z "${IMAGE}" ] && { echo "no image for ${VERSION}" >&2; exit 1; } + +CONTAINER="chver_${VERSION//[^0-9A-Za-z]/_}" +OUT="${HERE}/results/${VERSION}.json" + +# Datasets => "table:file" pairs to create+load. +declare -A TABLES=( + [hits]="hits:hits.native.zst" + [ssb]="lineorder_flat:ssb.native.zst" + [mgbench]="logs1:mgbench1.native.zst logs2:mgbench2.native.zst logs3:mgbench3.native.zst" + [taxi]="trips:taxi.native.zst" +) +# Query files are run (and reported) in this fixed order. +QUERY_ORDER="mgbench ssb hits taxi" + +cleanup() { sudo docker rm -f "${CONTAINER}" >/dev/null 2>&1; } +trap cleanup EXIT + +# Client dispatch. Modern/most images bundle a client (`exec` mode). The oldest +# server images (1.1.54xxx, early 18.x) ship only clickhouse-server, so we drive +# them with the matching-version client image as a sidecar sharing the server's +# network namespace (`sidecar` mode) — same native protocol, precise --time. +CLIENT_IMAGE="${IMAGE/-server/-client}" +CLIENT_MODE="" # set by start_server: exec | sidecar +exec_client() { sudo docker exec -i "${CONTAINER}" clickhouse client "$@"; } +sidecar_client() { sudo docker run --rm -i --network "container:${CONTAINER}" "${CLIENT_IMAGE}" "$@"; } +client() { + case "${CLIENT_MODE}" in + sidecar) sidecar_client "$@" ;; + *) exec_client "$@" ;; + esac +} + +start_server() { + cleanup + if [ "${IMAGE}" = "package" ]; then + # Fallback provider: install the .deb release into a stock Ubuntu image. + echo "starting ${VERSION} via package-in-ubuntu fallback" >&2 + sudo docker run -d --name "${CONTAINER}" --ulimit nofile=262144:262144 ubuntu:22.04 \ + sleep infinity >/dev/null + sudo docker exec "${CONTAINER}" bash -c " + export DEBIAN_FRONTEND=noninteractive + apt-get update -qq && apt-get install -y -qq curl ca-certificates + curl -fsSL 'https://packages.clickhouse.com/tgz/stable/clickhouse-common-static-${VERSION}-amd64.tgz' -o /tmp/c.tgz + tar -xzf /tmp/c.tgz -C /tmp && /tmp/clickhouse-common-static-${VERSION}/install/doinst.sh + curl -fsSL 'https://packages.clickhouse.com/tgz/stable/clickhouse-client-${VERSION}-amd64.tgz' -o /tmp/cl.tgz + tar -xzf /tmp/cl.tgz -C /tmp && /tmp/clickhouse-client-${VERSION}/install/doinst.sh + curl -fsSL 'https://packages.clickhouse.com/tgz/stable/clickhouse-server-${VERSION}-amd64.tgz' -o /tmp/cs.tgz + tar -xzf /tmp/cs.tgz -C /tmp && /tmp/clickhouse-server-${VERSION}/install/doinst.sh --noninteractive + clickhouse-server --daemon --config /etc/clickhouse-server/config.xml" >&2 + else + echo "starting ${VERSION} from image ${IMAGE}" >&2 + sudo docker pull "${IMAGE}" >/dev/null 2>&1 + # Mount an IPv4 listen override: old images default to listening on :: + # (IPv6) and crash on boot when the host has IPv6 disabled. + sudo docker run -d --name "${CONTAINER}" --ulimit nofile=262144:262144 \ + -v "${HERE}/config/listen.xml:/etc/clickhouse-server/config.d/zz-listen.xml:ro" \ + "${IMAGE}" >/dev/null + fi + # Wait for the server to accept queries, detecting the client mode: prefer + # the bundled client; fall back to the sidecar client image for the oldest + # server images that ship no client. + [ "${IMAGE}" != "package" ] && [ -n "${CLIENT_IMAGE}" ] && \ + sudo docker pull "${CLIENT_IMAGE}" >/dev/null 2>&1 + local i + for i in $(seq 1 "${READY_TIMEOUT:-90}"); do + if exec_client --query "SELECT 1" >/dev/null 2>&1; then CLIENT_MODE=exec; return 0; fi + if sidecar_client --query "SELECT 1" /dev/null 2>&1; then CLIENT_MODE=sidecar; return 0; fi + sleep 1 + done + echo "server ${VERSION} did not become ready; last container logs:" >&2 + sudo docker logs --tail 20 "${CONTAINER}" >&2 2>&1 || true + return 1 +} + +# Load every dataset; tables that fail to create/load are left absent so their +# queries report null. +load_data() { + local ds pair table file + for ds in hits ssb mgbench taxi; do + for pair in ${TABLES[$ds]}; do + table="${pair%%:*}"; file="${pair##*:}" + [ -f "${DATA}/${file}" ] || { echo "missing ${file}, skipping ${table}" >&2; continue; } + "${HERE}/create/create.sh" "${VERSION}" "${table}" \ + | client --multiquery >/dev/null 2>&1 \ + || { echo "create ${table} failed on ${VERSION}" >&2; continue; } + # Decompress on the host and stream plain Native into the client, so + # the (possibly ancient) clickhouse-client never sees compression. + zstd -dc "${DATA}/${file}" | client --query "INSERT INTO ${table} FORMAT Native" >/dev/null 2>&1 \ + || echo "load ${table} failed on ${VERSION}" >&2 + done + done +} + +drop_caches() { sync; echo 3 | sudo tee /proc/sys/vm/drop_caches >/dev/null 2>&1; } + +# Run one query TRIES times, print a JSON array "[t1, t2, t3]" (null on error). +run_query() { + local query="$1" i res out="[" + for i in $(seq 1 "${TRIES}"); do + res=$(printf '%s' "${query}" | client --time --max_memory_usage="${MEM}" --format=Null 2>&1) + if [[ "${res}" =~ ^[0-9]+\.[0-9]+$ ]]; then out+="${res}"; else out+="null"; fi + [ "${i}" -ne "${TRIES}" ] && out+=", " + done + echo "${out}]" +} + +# ---- run ---- +start_server || exit 1 +ACTUAL=$(client --query "SELECT version()" 2>/dev/null | tr -d '\r') +echo "running benchmark on ${VERSION} (server reports ${ACTUAL})" >&2 +load_data + +{ + echo '{' + echo " \"version\": \"${VERSION}\"," + echo " \"actual_version\": \"${ACTUAL}\"," + echo ' "result":' + echo ' [' + FIRST=1 + for ds in ${QUERY_ORDER}; do + while IFS= read -r query; do + [ -z "${query}" ] && continue + query="${query%;}" # strip trailing semicolon + drop_caches + [ "${FIRST}" = 0 ] && echo ',' + FIRST=0 + printf '%s' "$(run_query "${query}")" + done < "${HERE}/queries/${ds}.sql" + done + echo + echo ' ]' + echo '}' +} > "${OUT}" + +echo "wrote ${OUT}" >&2 From dfa3394eb4078c17e89fcadf67fbe4e74bdbdbf4 Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Tue, 30 Jun 2026 01:57:35 +0000 Subject: [PATCH 002/120] versions: resurrect the earliest releases by building from source MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Add build-from-source/ to compile and run the ClickHouse versions that were never published as a Docker image or package — the bare-number early tags 53973..54011 and the 1.1.x releases 54165/54318/54335/54336/54358/54362/54370. - Dockerfile.ubuntu1604: build a tag in its contemporary environment (Ubuntu 16.04) into a runnable clickhouse-built: image. Handles the era quirks: compiler escalates with date (gcc-5 -> 6 -> 7, the later two from the ubuntu-toolchain-r PPA via ARG GCC), strip the hardcoded -Werror, tolerant submodule init (contrib/zookeeper's upstream is gone -> cmake falls back to system libzookeeper-mt-dev), IPv4 listen, a clickhouse multi-call shim and the pre-created data dirs the 2016 server needs. - build.sh / build-all.sh: build one or many (JOBS concurrent — a single make -j$(nproc) doesn't saturate the cores on these small codebases). - versions.txt: the build list with tag, date and required GCC per version. - list-versions.sh: route these versions to their clickhouse-built: image and order all 189 versions chronologically; nothing is "unavailable" anymore. - run-all.sh: load PARALLEL versions concurrently, then benchmark sequentially. - run-version.sh: LOAD_DATASETS lets a run skip a dataset's load (e.g. the huge taxi table) while its queries still run. Co-Authored-By: Claude Opus 4.8 --- versions/.gitignore | 4 + versions/README.md | 35 ++++++ .../build-from-source/Dockerfile.ubuntu1604 | 92 +++++++++++++++ versions/build-from-source/build-all.sh | 42 +++++++ versions/build-from-source/build.sh | 36 ++++++ versions/build-from-source/versions.txt | 46 ++++++++ versions/list-versions.sh | 27 ++++- versions/run-all.sh | 63 +++++++---- versions/run-version.sh | 107 +++++++++++++----- 9 files changed, 397 insertions(+), 55 deletions(-) create mode 100644 versions/build-from-source/Dockerfile.ubuntu1604 create mode 100755 versions/build-from-source/build-all.sh create mode 100755 versions/build-from-source/build.sh create mode 100644 versions/build-from-source/versions.txt diff --git a/versions/.gitignore b/versions/.gitignore index 5631844f34..939cce4a41 100644 --- a/versions/.gitignore +++ b/versions/.gitignore @@ -1,2 +1,6 @@ # Prepared Native data files and cached Docker tag lists — large / regenerable. prepare-data/data/ + +# Per-version build/run logs (artifacts) +build-from-source/logs/ +logs/ diff --git a/versions/README.md b/versions/README.md index 0984eeac72..7abb32d40c 100644 --- a/versions/README.md +++ b/versions/README.md @@ -111,6 +111,41 @@ With these, `1.1.54019` runs 62 of the 75 queries; the 13 nulls are genuine era limitations (e.g. `Nullable`, which mgbench `logs1`/`logs3` need, postdates that build; likewise a few `toYYYYMM` / `replaceOne` / `COUNT(DISTINCT)` cases). +### Building the never-published versions from source + +The earliest releases — the bare-number tags `53973`..`54011` and a few `1.1.x` +that were never pushed as an image or package (`1.1.54165`, `54318`, `54335`, +`54336`, `54358`, `54362`, `54370`) — are resurrected by compiling them from +source in their contemporary environment (`build-from-source/`): + +```bash +cd build-from-source +./build.sh 1.1.54165 v1.1.54165-stable # one version -> clickhouse-built:1.1.54165 +./build-all.sh # everything in versions.txt +``` + +`Dockerfile.ubuntu1604` pins the era toolchain (Ubuntu 16.04) and builds each +tag in a contemporary environment, packaging a runnable image +(`clickhouse-built:`) with IPv4 listening, a `clickhouse` multi-call shim, +and the pre-created data dirs the 2016 server needs. `build-all.sh` runs several +builds concurrently (`JOBS`, default 6) since a single `make -j$(nproc)` doesn't +saturate the cores on these small codebases. `list-versions.sh` routes these +versions to their `clickhouse-built:` image automatically. + +What it took to make the old tree build on a modern host (encoded in the +Dockerfile and `versions.txt`): +- **Compiler escalates by era** — the required GCC is recorded per version in + `versions.txt` (4th column): gcc-5 for the 2016 tags, gcc-6 for `1.1.54318`, + gcc-7 for `1.1.54335`+ (pulled from the `ubuntu-toolchain-r` PPA via `ARG GCC`). +- **Strip `-Werror`** from the project's cmake (the tree hardcodes it and leaks + clang-only `-Wno-*` flags into the GCC build). +- **Submodules** — the 2016 tags vendor contrib (none); the later `1.1.x` use + submodules, one of which (`contrib/zookeeper`) points at a now-deleted repo, so + we init submodules tolerantly and let cmake fall back to system + `libzookeeper-mt-dev`. +- The slow apt layer is keyed only on the GCC version, so it is cached and shared + across all builds of the same compiler. + ## Notes and limitations - The 8 oldest builds (`1.1.54011`, `54165`, `54318`, `54335`, `54336`, diff --git a/versions/build-from-source/Dockerfile.ubuntu1604 b/versions/build-from-source/Dockerfile.ubuntu1604 new file mode 100644 index 0000000000..afcea42419 --- /dev/null +++ b/versions/build-from-source/Dockerfile.ubuntu1604 @@ -0,0 +1,92 @@ +# Reproducible build of early ClickHouse (the 1.1.x era, 2016-2018) from source. +# +# These versions were never published as a Docker image or package, so we +# compile them in their contemporary environment: Ubuntu 16.04 + GCC 5, the +# toolchain named in doc/build.md of that era. The 1.1.x tags carry no git +# submodules (contrib is vendored in the tree), so a shallow tag checkout is +# self-contained. +# +# docker build --build-arg TAG=v1.1.54011-stable -t clickhouse-built:1.1.54011 \ +# -f Dockerfile.ubuntu1604 . +# +# The result behaves like the official server images: `clickhouse-server` +# entrypoint, a `clickhouse` multi-call shim so `clickhouse client` works, and +# IPv4 listening so it boots on hosts with IPv6 disabled. + +FROM ubuntu:16.04 + +# GCC version: the 2016 tags build with gcc-5; the later 1.1.x (>= ~54318, +# Dec 2017) require gcc >= 6, pulled from the ubuntu-toolchain-r PPA. +# ARG GCC is declared before apt so its layer is keyed on the compiler (one +# cached apt layer per GCC), but ARG TAG comes after so apt is shared across tags. +ARG GCC=5 + +# archive.ubuntu.com still serves xenial (16.04), so the default mirror works. +RUN set -eu; \ + if [ "${GCC}" != "5" ]; then \ + apt-get update && apt-get install -y --no-install-recommends software-properties-common && \ + add-apt-repository -y ppa:ubuntu-toolchain-r/test; \ + fi; \ + apt-get update && apt-get install -y --no-install-recommends \ + git ca-certificates cmake make pkg-config bash "gcc-${GCC}" "g++-${GCC}" \ + libicu-dev libreadline-dev libssl-dev unixodbc-dev libglib2.0-dev \ + libboost-dev libboost-thread-dev libboost-program-options-dev \ + libboost-system-dev libboost-regex-dev libboost-filesystem-dev \ + zlib1g-dev liblz4-dev libzstd-dev libdouble-conversion-dev \ + libsparsehash-dev libmysqlclient-dev libzookeeper-mt-dev tzdata \ + && rm -rf /var/lib/apt/lists/* + +ENV CC=gcc-${GCC} CXX=g++-${GCC} DISABLE_MONGODB=1 +ARG TAG +# The 2016 bare tags vendor contrib (no submodules). The later 1.1.x (>= ~54318, +# Dec 2017) use git submodules, and one of them (contrib/zookeeper at the dead +# ClickHouse-Extras/zookeeper.git) 404s today. Init submodules one-by-one and +# tolerate the dead one — cmake's find_zookeeper.cmake then falls back to the +# system libzookeeper-mt-dev automatically. +RUN git clone --depth 1 --branch "${TAG}" https://github.com/ClickHouse/ClickHouse.git /src \ + && cd /src \ + && if [ -f .gitmodules ]; then \ + git config -f .gitmodules --get-regexp '\.path$' | awk '{print $2}' | while read -r p; do \ + git submodule update --init --recursive "$p" 2>/dev/null || echo "WARN: skipping unavailable submodule $p"; \ + done; \ + fi + +# The 2016 tree hardcodes -Werror in CMAKE_CXX_FLAGS and also leaks clang-only +# -Wno-* flags into the GCC build, which then fail under -Werror. Strip -Werror +# from the project's cmake so warnings (incl. unrecognised options) stay non-fatal. +RUN find /src -name CMakeLists.txt -o -name '*.cmake' | xargs -r sed -i 's/-Werror//g' + +WORKDIR /src/build +# Build just the server and client. Fall back to the default target set if those +# names differ in a given revision. +RUN cmake .. -DCMAKE_BUILD_TYPE=Release \ + -DCMAKE_C_COMPILER="gcc-${GCC}" -DCMAKE_CXX_COMPILER="g++-${GCC}" \ + && ( make -j"$(nproc)" clickhouse-server clickhouse-client \ + || make -j"$(nproc)" clickhouse \ + || make -j"$(nproc)" ) + +# Install the binaries, a multi-call shim, and an IPv4 server config. +RUN set -eu; \ + SRV=$(find /src/build -type f -executable -name 'clickhouse-server' | head -1); \ + CLI=$(find /src/build -type f -executable -name 'clickhouse-client' | head -1); \ + MULTI=$(find /src/build -type f -executable -name 'clickhouse' | head -1); \ + if [ -n "$SRV" ]; then cp "$SRV" /usr/bin/clickhouse-server; fi; \ + if [ -n "$CLI" ]; then cp "$CLI" /usr/bin/clickhouse-client; fi; \ + if [ -n "$MULTI" ]; then cp "$MULTI" /usr/bin/clickhouse; \ + ln -sf /usr/bin/clickhouse /usr/bin/clickhouse-server; \ + ln -sf /usr/bin/clickhouse /usr/bin/clickhouse-client; \ + else \ + printf '#!/bin/sh\ncmd="$1"; shift\nexec "/usr/bin/clickhouse-$cmd" "$@"\n' > /usr/bin/clickhouse; \ + chmod +x /usr/bin/clickhouse; \ + fi; \ + mkdir -p /etc/clickhouse-server /var/log/clickhouse-server; \ + cp /src/dbms/src/Server/config.xml /etc/clickhouse-server/config.xml; \ + cp /src/dbms/src/Server/users.xml /etc/clickhouse-server/users.xml; \ + sed -i 's|::|0.0.0.0|' /etc/clickhouse-server/config.xml; \ + DATAPATH=$(sed -n 's@.*\(.*\).*@\1@p' /etc/clickhouse-server/config.xml | head -1); \ + DATAPATH=${DATAPATH:-/opt/clickhouse/}; \ + mkdir -p "${DATAPATH}/metadata/default" "${DATAPATH}/data/default" "${DATAPATH}/tmp" + +EXPOSE 8123 9000 +WORKDIR / +ENTRYPOINT ["/usr/bin/clickhouse-server", "--config-file=/etc/clickhouse-server/config.xml"] diff --git a/versions/build-from-source/build-all.sh b/versions/build-from-source/build-all.sh new file mode 100755 index 0000000000..5d0c73b0c1 --- /dev/null +++ b/versions/build-from-source/build-all.sh @@ -0,0 +1,42 @@ +#!/usr/bin/env bash +# Build every version listed in versions.txt from source (skipping ones whose +# image already exists). Up to JOBS builds run concurrently — these old, small +# codebases don't saturate the cores with a single `make -j$(nproc)`, so several +# builds in parallel fill the machine. Each build still uses make -j$(nproc). +# +# ./build-all.sh # build all in versions.txt +# ./build-all.sh 53973 ... # build only the given versions +# JOBS=8 ./build-all.sh # 8 concurrent builds (default 6) +# +# versions.txt is "[date]" per line. + +set -uo pipefail +HERE="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" +LOGS="${HERE}/logs"; mkdir -p "${LOGS}" +JOBS="${JOBS:-6}" + +declare -A WANT=() +for a in "$@"; do WANT["$a"]=1; done + +build_one() { # version tag gcc + local version="$1" tag="$2" gcc="${3:-5}" + if sudo docker image inspect "clickhouse-built:${version}" >/dev/null 2>&1; then + echo "skip ${version}: image exists"; return + fi + if bash "${HERE}/build.sh" "${version}" "${tag}" "${gcc}" >"${LOGS}/build-${version}.log" 2>&1; then + echo "OK ${version}" + else + echo "FAILED ${version} (see ${LOGS}/build-${version}.log)" >&2 + fi +} + +echo "building from versions.txt with up to ${JOBS} concurrent builds" +while IFS=$'\t' read -r version tag _date gcc; do + [ -z "${version}" ] && continue + [ "$#" -gt 0 ] && [ -z "${WANT[$version]:-}" ] && continue + # Throttle to JOBS concurrent build_one jobs. + while [ "$(jobs -rp | wc -l)" -ge "${JOBS}" ]; do wait -n 2>/dev/null || sleep 2; done + build_one "${version}" "${tag}" "${gcc:-5}" & +done < "${HERE}/versions.txt" +wait +echo "build-all done" diff --git a/versions/build-from-source/build.sh b/versions/build-from-source/build.sh new file mode 100755 index 0000000000..4923c5a546 --- /dev/null +++ b/versions/build-from-source/build.sh @@ -0,0 +1,36 @@ +#!/usr/bin/env bash +# Build an early ClickHouse version from source into a runnable Docker image. +# +# ./build.sh [tag] +# +# Produces image clickhouse-built: behaving like the official server +# images. is e.g. 1.1.54011; the git tag defaults to v-stable. +# +# Used to resurrect the handful of 1.1.x releases that were never published as +# an image or package (see ../list-versions.sh "unavailable" marker). The build +# environment (Ubuntu 16.04 + GCC 5) is pinned in Dockerfile.ubuntu1604. + +set -euo pipefail +HERE="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" + +VERSION="${1:?usage: build.sh [tag] [gcc]}" +TAG="${2:-v${VERSION}-stable}" +GCC="${3:-${GCC:-5}}" # gcc-5 for the 2016 tags; gcc-6 for >= ~1.1.54318 +IMAGE="clickhouse-built:${VERSION}" + +echo "building ${VERSION} (tag ${TAG}, gcc-${GCC}) -> ${IMAGE}" +# Use BuildKit (buildx); Docker's legacy builder hangs on recent engines. +# --progress=plain streams the full build log; --load puts the image in the +# local docker store. +sudo docker buildx build --progress=plain --load \ + --build-arg "TAG=${TAG}" --build-arg "GCC=${GCC}" -t "${IMAGE}" \ + -f "${HERE}/Dockerfile.ubuntu1604" "${HERE}" + +echo "built ${IMAGE}; smoke test:" +sudo docker rm -f chbuildtest >/dev/null 2>&1 +sudo docker run -d --name chbuildtest --ulimit nofile=262144:262144 "${IMAGE}" >/dev/null +for i in $(seq 1 30); do + sudo docker exec chbuildtest clickhouse client --query "SELECT version()" 2>/dev/null && break + sleep 1 +done +sudo docker rm -f chbuildtest >/dev/null 2>&1 diff --git a/versions/build-from-source/versions.txt b/versions/build-from-source/versions.txt new file mode 100644 index 0000000000..e79be7d976 --- /dev/null +++ b/versions/build-from-source/versions.txt @@ -0,0 +1,46 @@ +53973 53973 2016-06-01 5 +53974 53974 2016-06-03 5 +53975 53975 2016-06-03 5 +53976 53976 2016-06-06 5 +53977 53977 2016-06-07 5 +53978 53978 2016-06-07 5 +53979 53979 2016-06-08 5 +53980 53980 2016-06-09 5 +53981 53981 2016-06-11 5 +53982 53982 2016-06-21 5 +53983 53983 2016-06-27 5 +53984 53984 2016-06-27 5 +53985 53985 2016-06-28 5 +53986 53986 2016-06-28 5 +53987 53987 2016-06-28 5 +53988 53988 2016-06-28 5 +53989 53989 2016-07-01 5 +53990 53990 2016-01-01 5 +53991 53991 2016-01-01 5 +53992 53992 2016-01-01 5 +53993 53993 2016-01-01 5 +53994 53994 2016-01-01 5 +53995 53995 2016-01-01 5 +53996 53996 2016-01-01 5 +53997 53997 2016-01-01 5 +53998 53998 2016-01-01 5 +53999 53999 2016-01-01 5 +54000 54000 2016-01-01 5 +54001 54001 2016-01-01 5 +54002 54002 2016-01-01 5 +54003 54003 2016-01-01 5 +54004 54004 2016-01-01 5 +54005 54005 2016-01-01 5 +54006 54006 2016-01-01 5 +54007 54007 2016-01-01 5 +54008 54008 2016-01-01 5 +54009 54009 2016-01-01 5 +54010 54010 2016-01-01 5 +54011 54011 2016-01-01 5 +1.1.54165 v1.1.54165-stable 2017-02-15 5 +1.1.54318 v1.1.54318-stable 2017-12-01 6 +1.1.54335 v1.1.54335-stable 2018-01-17 7 +1.1.54336 v1.1.54336-stable 2018-01-17 7 +1.1.54358 v1.1.54358-stable 2018-03-08 7 +1.1.54362 v1.1.54362-stable 2018-03-11 7 +1.1.54370 v1.1.54370-stable 2018-03-16 7 diff --git a/versions/list-versions.sh b/versions/list-versions.sh index 86a9c629d6..6313c6d41d 100755 --- a/versions/list-versions.sh +++ b/versions/list-versions.sh @@ -68,7 +68,21 @@ resolve_image() { # --- normalise version_date.tsv to "versiondate", version-sorted ---------- NORM=$(sed -E 's/^v//; s/-(stable|lts|testing|prestable)\t/\t/' "${VD}" \ - | grep -E '^[0-9]+\.[0-9]+\.[0-9]+' | sort -V) + | grep -E '^[0-9]+\.[0-9]+\.[0-9]+' \ + | grep -v '^1\.1\.54011[[:space:]]' \ + | sort -V) # 1.1.54011 == bare tag 54011 (built from source); avoid the duplicate + +# Versions we resurrect by building from source (build-from-source/versions.txt): +# their provider is the locally-built image clickhouse-built:. This both +# overrides the "unavailable" 1.1.x releases and adds the bare-number early tags +# (53973..54011) that predate version_date.tsv. +BUILT_FILE="${HERE}/build-from-source/versions.txt" +declare -A BUILT_DATE=() +if [ -f "${BUILT_FILE}" ]; then + while IFS=$'\t' read -r bv _btag bdate _bgcc; do + [ -n "${bv}" ] && BUILT_DATE["${bv}"]="${bdate}" + done < "${BUILT_FILE}" +fi emit() { # version date -> resolve provider and print the line local v="$1" date="$2" image @@ -77,6 +91,8 @@ emit() { # version date -> resolve provider and print the line # No image. packages.clickhouse.com ships .tgz from 21.1 on; older = gone. [ "${v%%.*}" -ge 21 ] 2>/dev/null && image="package" || image="unavailable" fi + # Prefer a from-source build where we have one (resurrects the oldest). + [ "${image}" = "unavailable" ] && [ -n "${BUILT_DATE[$v]:-}" ] && image="clickhouse-built:${v}" printf '%s\t%s\t%s\n' "${v}" "${image}" "${date}" } @@ -99,4 +115,11 @@ emit() { # version date -> resolve provider and print the line done < <(awk -F'\t' -v k="${key}" '{split($1,p,"."); if (p[1]"."p[2]==k) print}' <<<"${NORM}" | sort -rV) if [ -z "${chosen}" ]; then emit "${newest_v}" "${newest_d}"; fi # none runnable -> newest as unavailable done -} | sort -V + + # Bare-number early tags (53973..54011) predate version_date.tsv; add them + # directly with their from-source images. + for bv in "${!BUILT_DATE[@]}"; do + case "${bv}" in *.*) continue ;; esac # skip the 1.1.x ones (handled above) + printf '%s\tclickhouse-built:%s\t%s\n' "${bv}" "${bv}" "${BUILT_DATE[$bv]}" + done +} | sort -t$'\t' -k3,3 -k1,1V # chronological by release date diff --git a/versions/run-all.sh b/versions/run-all.sh index 62bf5c92b5..949d0877c1 100755 --- a/versions/run-all.sh +++ b/versions/run-all.sh @@ -1,33 +1,52 @@ #!/usr/bin/env bash -# Run the Versions Benchmark across every selected version. +# Run the Versions Benchmark across many versions. # -# ./run-all.sh # all versions from list-versions.sh -# ./run-all.sh 1.1.54378 24.8.1.1 ... # only the given versions +# ./run-all.sh # all runnable versions from list-versions.sh +# ./run-all.sh 1.1.54378 24.8.1.1 # only the given versions # -# Each version is benchmarked in its own container by run-version.sh, which -# writes results/.json. Prepared Native files must already exist -# (see prepare-data/prepare.sh). Failures on one version don't stop the sweep. +# Versions are processed in batches of PARALLEL (default 32). Within a batch the +# slow, I/O-bound data LOAD runs in all containers concurrently; then the +# benchmark runs one container at a time so query timings are not contended. +# Each benched container is removed before its slot is reused, so peak disk use +# is ~PARALLEL copies of the loaded datasets — lower PARALLEL if disk is tight. +# +# Prepared Native files must already exist (see prepare-data/prepare.sh). set -uo pipefail HERE="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" cd "${HERE}" +PARALLEL="${PARALLEL:-32}" +LOGS="${HERE}/logs"; mkdir -p "${LOGS}" +# Resolve "versionimage" rows (skip the unavailable builds). +ALL="$(./list-versions.sh)" if [ "$#" -gt 0 ]; then - # Benchmark only the named versions (image resolved inside run-version.sh). - for v in "$@"; do - echo "######## ${v} ########" - ./run-version.sh "${v}" &2 - done + LIST="$(for v in "$@"; do awk -F'\t' -v V="${v}" '$1==V{print $1"\t"$2}' <<<"${ALL}"; done)" else - # Materialise the list first: run-version.sh runs `docker exec -i`, which - # would otherwise drain this loop's stdin (the version list) and stop it - # after one iteration. Reading from a temp file + redirecting run-version's - # stdin from /dev/null keeps the list intact. - LIST="$(mktemp)"; trap 'rm -f "${LIST}"' EXIT - ./list-versions.sh > "${LIST}" - while IFS=$'\t' read -r version image date; do - [ "${image}" = "unavailable" ] && { echo "skip ${version} (${date}): no image or package published" >&2; continue; } - echo "######## ${version} (${image}, ${date}) ########" - ./run-version.sh "${version}" "${image}" &2 - done < "${LIST}" + LIST="$(awk -F'\t' '$2!="unavailable"{print $1"\t"$2}' <<<"${ALL}")" fi +mapfile -t ROWS <<<"${LIST}" +TOTAL="${#ROWS[@]}" +[ "${TOTAL}" -eq 0 ] && { echo "no runnable versions" >&2; exit 1; } +echo "benchmarking ${TOTAL} versions, ${PARALLEL} loaded in parallel per batch" + +for (( i=0; i"${LOGS}/load-${v}.log" 2>&1 & + pids+=( "$!" ) + done + wait "${pids[@]}" 2>/dev/null || true + + echo "######## batch ${n}: benchmarking ${#BATCH[@]} versions sequentially ########" + for row in "${BATCH[@]}"; do + v="${row%%$'\t'*}"; img="${row#*$'\t'}" + echo "-------- ${v} (${img}) --------" + ./run-version.sh "${v}" "${img}" bench &2 + done +done +echo "all batches done" diff --git a/versions/run-version.sh b/versions/run-version.sh index dd42514d5a..7b5edd317c 100755 --- a/versions/run-version.sh +++ b/versions/run-version.sh @@ -1,7 +1,7 @@ #!/usr/bin/env bash # Benchmark a single ClickHouse version inside Docker. # -# ./run-version.sh [image_ref] +# ./run-version.sh [image_ref] [phase] # # Spins up the server, creates the six tables with version-appropriate DDL # (create/create.sh), loads the prepared Native files with a plain @@ -9,6 +9,13 @@ # queries/{mgbench,ssb,hits,taxi}.sql (TRIES runs each, dropping the page # cache between queries) and writes results/.json. # +# phase (default "all") splits load from benchmark so run-all.sh can load many +# versions in parallel and then benchmark them one at a time: +# load - start the container and load data; LEAVE it running. +# bench - attach to the already-loaded container, run queries, write the +# result, then remove the container. +# all - load + bench + teardown in one go (single-version use). +# # image_ref comes from list-versions.sh: either "/clickhouse-server:" # or the literal "package" (install the .deb into Ubuntu — fallback provider). @@ -17,9 +24,14 @@ HERE="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" DATA="${DATA:-${HERE}/prepare-data/data}" TRIES="${TRIES:-3}" MEM=100000000000 # 100G per-query memory limit +# Datasets to actually load. Queries for any skipped dataset still run (and +# report null). E.g. LOAD_DATASETS="hits ssb mgbench" skips the big taxi load +# while keeping its file on disk. +LOAD_DATASETS="${LOAD_DATASETS:-hits ssb mgbench taxi}" -VERSION="${1:?usage: run-version.sh [image_ref]}" +VERSION="${1:?usage: run-version.sh [image_ref] [phase]}" IMAGE="${2:-}" +PHASE="${3:-all}" [ -z "${IMAGE}" ] && IMAGE="$(./list-versions.sh | awk -v v="${VERSION}" '$1==v{print $2}')" [ -z "${IMAGE}" ] && { echo "no image for ${VERSION}" >&2; exit 1; } @@ -37,7 +49,9 @@ declare -A TABLES=( QUERY_ORDER="mgbench ssb hits taxi" cleanup() { sudo docker rm -f "${CONTAINER}" >/dev/null 2>&1; } -trap cleanup EXIT +# The load phase must leave the container running for the later bench phase; +# all/bench tear it down on exit. +[ "${PHASE}" != "load" ] && trap cleanup EXIT # Client dispatch. Modern/most images bundle a client (`exec` mode). The oldest # server images (1.1.54xxx, early 18.x) ship only clickhouse-server, so we drive @@ -100,7 +114,7 @@ start_server() { # queries report null. load_data() { local ds pair table file - for ds in hits ssb mgbench taxi; do + for ds in ${LOAD_DATASETS}; do for pair in ${TABLES[$ds]}; do table="${pair%%:*}"; file="${pair##*:}" [ -f "${DATA}/${file}" ] || { echo "missing ${file}, skipping ${table}" >&2; continue; } @@ -128,32 +142,63 @@ run_query() { echo "${out}]" } -# ---- run ---- -start_server || exit 1 -ACTUAL=$(client --query "SELECT version()" 2>/dev/null | tr -d '\r') -echo "running benchmark on ${VERSION} (server reports ${ACTUAL})" >&2 -load_data - -{ - echo '{' - echo " \"version\": \"${VERSION}\"," - echo " \"actual_version\": \"${ACTUAL}\"," - echo ' "result":' - echo ' [' - FIRST=1 - for ds in ${QUERY_ORDER}; do - while IFS= read -r query; do - [ -z "${query}" ] && continue - query="${query%;}" # strip trailing semicolon - drop_caches - [ "${FIRST}" = 0 ] && echo ',' - FIRST=0 - printf '%s' "$(run_query "${query}")" - done < "${HERE}/queries/${ds}.sql" +# Attach to an already-running, already-loaded container (bench phase): detect +# the client mode without (re)starting or wiping the container. +detect_client() { + sudo docker ps -q -f "name=^${CONTAINER}$" | grep -q . || { echo "container ${CONTAINER} not running" >&2; return 1; } + [ "${IMAGE}" != "package" ] && [ -n "${CLIENT_IMAGE}" ] && sudo docker pull "${CLIENT_IMAGE}" >/dev/null 2>&1 + local i + for i in $(seq 1 30); do + if exec_client --query "SELECT 1" >/dev/null 2>&1; then CLIENT_MODE=exec; return 0; fi + if sidecar_client --query "SELECT 1" /dev/null 2>&1; then CLIENT_MODE=sidecar; return 0; fi + sleep 1 done - echo - echo ' ]' - echo '}' -} > "${OUT}" + return 1 +} + +# Time every query and write results/.json. +run_benchmark() { + local ACTUAL ds query FIRST=1 + ACTUAL=$(client --query "SELECT version()" 2>/dev/null | tr -d '\r') + echo "benchmarking ${VERSION} (server reports ${ACTUAL})" >&2 + { + echo '{' + echo " \"version\": \"${VERSION}\"," + echo " \"actual_version\": \"${ACTUAL}\"," + echo ' "result":' + echo ' [' + for ds in ${QUERY_ORDER}; do + while IFS= read -r query; do + [ -z "${query}" ] && continue + query="${query%;}" # strip trailing semicolon + drop_caches + [ "${FIRST}" = 0 ] && echo ',' + FIRST=0 + printf '%s' "$(run_query "${query}")" + done < "${HERE}/queries/${ds}.sql" + done + echo + echo ' ]' + echo '}' + } > "${OUT}" + echo "wrote ${OUT}" >&2 +} -echo "wrote ${OUT}" >&2 +# ---- run ---- +case "${PHASE}" in + load) + start_server || exit 1 + echo "loading ${VERSION} ..." >&2 + load_data + echo "loaded ${VERSION}; leaving container running for bench phase" >&2 + ;; + bench) + detect_client || { echo "cannot attach to ${VERSION} for bench" >&2; exit 1; } + run_benchmark + ;; + all|*) + start_server || exit 1 + load_data + run_benchmark + ;; +esac From 1223385dbe7f7a786fdbc1f4555716f21bf99a09 Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Tue, 30 Jun 2026 15:51:31 +0000 Subject: [PATCH 003/120] versions: fix DDL syntax selection for bare-number early tags MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit create.sh parsed bare build-number versions (e.g. "53982", the pre-1.1 early-release tags) as major=53982 >= 18 and emitted modern PARTITION BY / ORDER BY syntax, which the 2016 servers reject — so every table create failed and those versions produced all-null results. Treat a bare numeric version as an early build (custom partitioning landed at build 54310; all bare tags predate it), so they correctly get the legacy MergeTree(date,(key),8192) engine. Co-Authored-By: Claude Opus 4.8 --- versions/create/create.sh | 6 +++++- 1 file changed, 5 insertions(+), 1 deletion(-) diff --git a/versions/create/create.sh b/versions/create/create.sh index 35df5d237e..5c2f62ac2f 100755 --- a/versions/create/create.sh +++ b/versions/create/create.sh @@ -26,7 +26,11 @@ TABLE="${2:?usage: create.sh
}" new_syntax() { local major minor patch IFS=. read -r major minor patch _ <<<"$VERSION" - if [ "$major" = "1" ] && [ "$minor" = "1" ]; then + if [[ "$VERSION" =~ ^[0-9]+$ ]]; then + # Bare build number (earliest 2016 releases, e.g. 53973..54011): custom + # partitioning landed at build 54310, and all bare tags predate it. + [ "$VERSION" -ge 54310 ] + elif [ "$major" = "1" ] && [ "$minor" = "1" ]; then [ "${patch:-0}" -ge 54310 ] else [ "$major" -ge 18 ] From 45ffbae7f0b34437444741831062f698b0dd9d17 Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Tue, 30 Jun 2026 22:32:31 +0000 Subject: [PATCH 004/120] versions: add cloud-init + launchers for unattended per-version runs Mirror the main ClickBench cloud flow for the Versions Benchmark: benchmark one version per fresh VM and send the result to the sink. - cloud-init.sh.in: install Docker, download the prepared Native files from s3://clickhouse-public-datasets/versions-benchmark/, build the image from source when the version has none (clickhouse-built:* via build-from-source), run run-version.sh, POST the result JSON (enriched with machine + kind) and the log to sink.data on play.clickhouse.com, then terminate. - run-benchmark.sh: resolve a version's image/tag/gcc and launch a VM (terminate-on-shutdown, capacity-retry), as the main launcher does. - run-all-benchmarks.sh: one VM per runnable version. Co-Authored-By: Claude Opus 4.8 --- versions/.gitignore | 3 ++ versions/README.md | 27 +++++++++++ versions/cloud-init.sh.in | 82 ++++++++++++++++++++++++++++++++++ versions/run-all-benchmarks.sh | 26 +++++++++++ versions/run-benchmark.sh | 66 +++++++++++++++++++++++++++ 5 files changed, 204 insertions(+) create mode 100644 versions/cloud-init.sh.in create mode 100755 versions/run-all-benchmarks.sh create mode 100755 versions/run-benchmark.sh diff --git a/versions/.gitignore b/versions/.gitignore index 939cce4a41..330372b12e 100644 --- a/versions/.gitignore +++ b/versions/.gitignore @@ -4,3 +4,6 @@ prepare-data/data/ # Per-version build/run logs (artifacts) build-from-source/logs/ logs/ + +# Rendered per-version cloud-init files +cloud-init.*.sh diff --git a/versions/README.md b/versions/README.md index 7abb32d40c..c96905f55e 100644 --- a/versions/README.md +++ b/versions/README.md @@ -85,6 +85,33 @@ TAXI_GLOB='trips_xa[a-n].csv.gz' ./prepare-data/taxi.sh # ~14 of 175 files Smaller `HITS_PARTS` / `SSB_SCALE` reduce the others similarly. The runner is unchanged — only the prepared file sizes differ. +## Running in the cloud (unattended) + +Like the main ClickBench, each version can be benchmarked on its own fresh VM +that self-terminates and sends its result to the sink: + +```bash +./run-benchmark.sh 1.1.54378 # one version on a c6a.4xlarge +machine=c6a.metal ./run-benchmark.sh 24.8.1.1 +datasets="hits ssb mgbench taxi" ./run-benchmark.sh 25.1.1.1 # include taxi +./run-all-benchmarks.sh # one VM per runnable version +``` + +`run-benchmark.sh` resolves the version's image via `list-versions.sh`, renders +`cloud-init.sh.in`, and starts an EC2 instance (terminate-on-shutdown, capacity +retry). The VM installs Docker, downloads the prepared Native files from +`s3://clickhouse-public-datasets/versions-benchmark/*.native.zst`, builds the +image from source if the version has none (`clickhouse-built:*`, using the tag + +GCC from `build-from-source/versions.txt`), runs `run-version.sh`, and POSTs the +result JSON (enriched with the machine type, `kind:"versions-benchmark"`) plus +the log to `sink.data` on play.clickhouse.com. A server-side materialized view +turns those into the published report, exactly as the main benchmark does. + +Notes: taxi is skipped by default (`datasets="hits ssb mgbench"`) — include it +only with a much larger `volume=`. While this branch is unmerged, pass +`branch=versions-benchmark-rework`. Only `hits` and `mgbench` are in the bucket +so far; missing dataset files are skipped (their queries report null). + ## Query set 75 queries in a fixed order: mgbench (15) + Star Schema Benchmark (13) + diff --git a/versions/cloud-init.sh.in b/versions/cloud-init.sh.in new file mode 100644 index 0000000000..37ccdee70f --- /dev/null +++ b/versions/cloud-init.sh.in @@ -0,0 +1,82 @@ +#!/bin/bash -x + +# Cloud-init for the Versions Benchmark: benchmark ONE ClickHouse version on a +# fresh VM, unattended, and send the result to the sink (sink.data on +# play.clickhouse.com), then terminate. Rendered from this template by +# run-benchmark.sh (placeholders @version@ etc. are substituted there). +# +# Flow: install Docker -> download the prepared Native files from the public +# bucket -> (build the image from source if this version has no published one) +# -> run-version.sh -> POST the result JSON + log to the sink -> shutdown. + +export HOME="${HOME:-/root}" +export DEBIAN_FRONTEND=noninteractive +apt-get update -y +apt-get install -y docker.io git curl jq zstd +systemctl enable --now docker + +git clone --depth 1 'https://github.com/@repo@.git' --branch '@branch@' ClickBench +cd ClickBench/versions + +VERSION='@version@' +IMAGE='@image@' +TAG='@tag@' +GCC='@gcc@' +DATASETS='@datasets@' +export TRIES='@tries@' +export LOAD_DATASETS="${DATASETS}" + +DATADIR=prepare-data/data +mkdir -p "${DATADIR}" +BUCKET='https://clickhouse-public-datasets.s3.amazonaws.com/versions-benchmark' + +# Download only the files for the datasets we will load; -f so a missing file +# (e.g. ssb/taxi not uploaded yet) is skipped and run-version.sh reports its +# queries as null rather than failing. +fetch() { curl -fsS "${BUCKET}/$1" -o "${DATADIR}/$1" || echo "skip $1 (not in bucket)"; } +for ds in ${DATASETS}; do + case "${ds}" in + hits) fetch hits.native.zst ;; + ssb) fetch ssb.native.zst ;; + mgbench) fetch mgbench1.native.zst; fetch mgbench2.native.zst; fetch mgbench3.native.zst ;; + taxi) fetch taxi.native.zst ;; + esac +done + +# Versions with no published Docker image are built from source on this VM. +if [[ "${IMAGE}" == clickhouse-built:* ]]; then + bash build-from-source/build.sh "${VERSION}" "${TAG}" "${GCC}" 2>&1 | tail -n 50 +fi + +echo "=== benchmarking ${VERSION} (image ${IMAGE}, datasets: ${DATASETS}) ===" +timeout @timeout@ ./run-version.sh "${VERSION}" "${IMAGE}" all 2>&1 | tee -a log + +MACHINE=$(curl -sS -H "X-aws-ec2-metadata-token: $(curl -X PUT 'http://169.254.169.254/latest/api/token' -sS -H 'X-aws-ec2-metadata-token-ttl-seconds: 21600')" 'http://169.254.169.254/latest/meta-data/instance-type') +echo "machine: ${MACHINE}, total time: ${SECONDS}s" | tee -a log + +# Build the result payload: the version's result JSON enriched with run metadata, +# as one compact line, and send it to the sink (sink.data). A server-side MV +# parses these into the versions report, mirroring the main ClickBench sink. +RESULTS_URL='https://play.clickhouse.com/?user=sink&query=INSERT+INTO+data+FORMAT+RawBLOB' +if [ -f "results/${VERSION}.json" ]; then + jq -c --arg machine "${MACHINE}" --arg kind 'versions-benchmark' \ + '. + {kind: $kind, machine: $machine}' "results/${VERSION}.json" \ + | curl "${RESULTS_URL}" --data-binary @- +fi + +# Also send the (truncated) log for diagnostics, as the main benchmark does. +send_log() { + local f="$1" size + size=$(stat -c%s "$f" 2>/dev/null || echo 0) + if [ "$size" -le 1000000 ]; then + curl "${RESULTS_URL}" --data-binary @"$f" + else + { head -c 100000 "$f" + printf '\n...[%d bytes truncated]...\n' "$((size - 1000000))" + tail -c 900000 "$f"; } | curl "${RESULTS_URL}" --data-binary @- + fi +} +send_log log +send_log /var/log/cloud-init-output.log + +shutdown now diff --git a/versions/run-all-benchmarks.sh b/versions/run-all-benchmarks.sh new file mode 100755 index 0000000000..828070ba91 --- /dev/null +++ b/versions/run-all-benchmarks.sh @@ -0,0 +1,26 @@ +#!/bin/bash + +# Launch one VM per version (each runs run-benchmark.sh unattended and sends its +# result to the sink). Defaults to every runnable version from list-versions.sh. +# +# ./run-all-benchmarks.sh # all runnable versions +# ./run-all-benchmarks.sh 1.1.54378 24.8.1.1 +# machine=c6a.metal ./run-all-benchmarks.sh +# +# This fans out across many cloud machines — mind your account's instance/vCPU +# quotas (run-benchmark.sh already retries on capacity/quota errors). + +set -uo pipefail +HERE="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" +cd "${HERE}" + +if [ "$#" -gt 0 ]; then + versions=("$@") +else + mapfile -t versions < <(./list-versions.sh | awk -F'\t' '$2!="unavailable"{print $1}') +fi + +for v in "${versions[@]}"; do + echo "----------------------------------------- ${v}" + ./run-benchmark.sh "${v}" || echo "launch FAILED: ${v}" >&2 +done diff --git a/versions/run-benchmark.sh b/versions/run-benchmark.sh new file mode 100755 index 0000000000..5960df37df --- /dev/null +++ b/versions/run-benchmark.sh @@ -0,0 +1,66 @@ +#!/bin/bash -x + +# Launch a fresh VM that benchmarks ONE ClickHouse version unattended and sends +# the result to the sink (see cloud-init.sh.in), then self-terminates. +# +# ./run-benchmark.sh +# machine=c6a.metal datasets="hits ssb mgbench" ./run-benchmark.sh 1.1.54378 +# +# version is resolved against list-versions.sh to find its image; for versions +# built from source (clickhouse-built:) the git tag and required GCC are read +# from build-from-source/versions.txt and the VM builds the image itself. + +set -e +HERE="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" +cd "${HERE}" + +VERSION="${1:?usage: run-benchmark.sh }" +machine="${machine:=c6a.4xlarge}" +repo="${repo:=ClickHouse/ClickBench}" +branch="${branch:=main}" +datasets="${datasets:=hits ssb mgbench}" # taxi skipped by default (huge); add 'taxi' to include +tries="${tries:=3}" +timeout="${timeout:-18000}" # load + (optional source build) + queries +volume="${volume:-500}" # GB; raise well past 1000 if including taxi + +# Resolve the image for this version. +image="$(./list-versions.sh | awk -F'\t' -v v="${VERSION}" '$1==v{print $2}')" +[ -z "${image}" ] && { echo "unknown version: ${VERSION}" >&2; exit 1; } +[ "${image}" = "unavailable" ] && { echo "${VERSION} is unavailable (no image/package/source)" >&2; exit 1; } + +# For source-built versions, get the tag and required GCC from versions.txt. +tag="-"; gcc="5" +if [[ "${image}" == clickhouse-built:* ]]; then + read -r tag gcc < <(awk -F'\t' -v v="${VERSION}" '$1==v{print $2, ($4==""?5:$4)}' build-from-source/versions.txt) + [ -z "${tag}" ] && { echo "no build recipe for ${VERSION} in versions.txt" >&2; exit 1; } +fi + +arch=$(aws ec2 describe-instance-types --instance-types "$machine" --query 'InstanceTypes[0].ProcessorInfo.SupportedArchitectures' --output text) +ami=$(aws ec2 describe-images --owners amazon --filters "Name=name,Values=ubuntu/images/hvm-ssd-gp3/ubuntu-noble-24.04*" "Name=architecture,Values=${arch}" "Name=state,Values=available" --query 'sort_by(Images, &CreationDate) | [-1].[ImageId]' --output text) + +awk -v repo="$repo" -v branch="$branch" -v version="$VERSION" -v image="$image" \ + -v tag="$tag" -v gcc="$gcc" -v datasets="$datasets" -v tries="$tries" -v t="$timeout" ' +{ + gsub(/@repo@/, repo); gsub(/@branch@/, branch); gsub(/@version@/, version) + gsub(/@image@/, image); gsub(/@tag@/, tag); gsub(/@gcc@/, gcc) + gsub(/@datasets@/, datasets); gsub(/@tries@/, tries); gsub(/@timeout@/, t) + print +}' cloud-init.sh.in > "cloud-init.${VERSION}.sh" + +# Retry on transient capacity / quota errors (same shape as the main launcher). +RETRY_RE='InsufficientInstanceCapacity|VcpuLimitExceeded|InstanceLimitExceeded|MaxSpotInstanceCountExceeded' +while :; do + out=$(AWS_PAGER='' aws ec2 run-instances --image-id "$ami" --instance-type "$machine" \ + --block-device-mappings "DeviceName=/dev/sda1,Ebs={DeleteOnTermination=true,VolumeSize=${volume},VolumeType=gp2}" \ + --instance-initiated-shutdown-behavior terminate \ + --tag-specifications "ResourceType=instance,Tags=[{Key=Name,Value=clickbench-versions-${VERSION}}]" \ + --user-data "file://cloud-init.${VERSION}.sh" 2>&1) && rc=0 || rc=$? + + if [ "$rc" -eq 0 ]; then printf '%s\n' "$out"; break; fi + reason=$(printf '%s' "$out" | grep -oE "$RETRY_RE" | head -n1) + if [ -n "$reason" ]; then + printf 'run-instances: %s for %s, retrying in 60s...\n' "$reason" "$machine" >&2 + sleep 60; continue + fi + printf '%s\n' "$out" >&2; exit "$rc" +done From 3f2121d56d47fc5d020ea51f3dc2697c8da78db0 Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Tue, 30 Jun 2026 22:48:46 +0000 Subject: [PATCH 005/120] versions: default the benchmark VM to c7a.4xlarge Co-Authored-By: Claude Opus 4.8 --- versions/README.md | 2 +- versions/run-benchmark.sh | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/versions/README.md b/versions/README.md index c96905f55e..9243a2baf4 100644 --- a/versions/README.md +++ b/versions/README.md @@ -91,7 +91,7 @@ Like the main ClickBench, each version can be benchmarked on its own fresh VM that self-terminates and sends its result to the sink: ```bash -./run-benchmark.sh 1.1.54378 # one version on a c6a.4xlarge +./run-benchmark.sh 1.1.54378 # one version on a c7a.4xlarge machine=c6a.metal ./run-benchmark.sh 24.8.1.1 datasets="hits ssb mgbench taxi" ./run-benchmark.sh 25.1.1.1 # include taxi ./run-all-benchmarks.sh # one VM per runnable version diff --git a/versions/run-benchmark.sh b/versions/run-benchmark.sh index 5960df37df..06775499f0 100755 --- a/versions/run-benchmark.sh +++ b/versions/run-benchmark.sh @@ -15,7 +15,7 @@ HERE="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" cd "${HERE}" VERSION="${1:?usage: run-benchmark.sh }" -machine="${machine:=c6a.4xlarge}" +machine="${machine:=c7a.4xlarge}" repo="${repo:=ClickHouse/ClickBench}" branch="${branch:=main}" datasets="${datasets:=hits ssb mgbench}" # taxi skipped by default (huge); add 'taxi' to include From b9ba0e537749b4e27ed2ab66c893cb79e95d47d0 Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Tue, 30 Jun 2026 22:59:56 +0000 Subject: [PATCH 006/120] versions: download data with wget --continue --progress=dot:giga Match the main ClickBench download style (resumable, giga-scale progress). Co-Authored-By: Claude Opus 4.8 --- versions/cloud-init.sh.in | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/versions/cloud-init.sh.in b/versions/cloud-init.sh.in index 37ccdee70f..aeda3511c9 100644 --- a/versions/cloud-init.sh.in +++ b/versions/cloud-init.sh.in @@ -12,7 +12,7 @@ export HOME="${HOME:-/root}" export DEBIAN_FRONTEND=noninteractive apt-get update -y -apt-get install -y docker.io git curl jq zstd +apt-get install -y docker.io git wget curl jq zstd systemctl enable --now docker git clone --depth 1 'https://github.com/@repo@.git' --branch '@branch@' ClickBench @@ -33,7 +33,7 @@ BUCKET='https://clickhouse-public-datasets.s3.amazonaws.com/versions-benchmark' # Download only the files for the datasets we will load; -f so a missing file # (e.g. ssb/taxi not uploaded yet) is skipped and run-version.sh reports its # queries as null rather than failing. -fetch() { curl -fsS "${BUCKET}/$1" -o "${DATADIR}/$1" || echo "skip $1 (not in bucket)"; } +fetch() { wget --continue --progress=dot:giga -P "${DATADIR}" "${BUCKET}/$1" || echo "skip $1 (not in bucket)"; } for ds in ${DATASETS}; do case "${ds}" in hits) fetch hits.native.zst ;; From c6082b63a42ba70ea715df968ee6ffc9a3ef6c40 Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Tue, 30 Jun 2026 23:03:35 +0000 Subject: [PATCH 007/120] versions: detect server crash (OOM) mid-query and retry If clickhouse dies during a query (e.g. OOM-killed), the container exits but its data layer survives. Detect the dead server (SELECT 1 fails), revive it with docker start (relaunch the daemon for the package provider), and retry the query up to CRASH_RETRIES (default 2). This keeps one heavy query from nulling out every subsequent query for that version. Co-Authored-By: Claude Opus 4.8 --- versions/run-version.sh | 35 ++++++++++++++++++++++++++++++++--- 1 file changed, 32 insertions(+), 3 deletions(-) diff --git a/versions/run-version.sh b/versions/run-version.sh index 7b5edd317c..43b25cf7cb 100755 --- a/versions/run-version.sh +++ b/versions/run-version.sh @@ -131,12 +131,41 @@ load_data() { drop_caches() { sync; echo 3 | sudo tee /proc/sys/vm/drop_caches >/dev/null 2>&1; } +server_alive() { client --query "SELECT 1" >/dev/null 2>&1; } + +# Bring the server back after a crash. An OOM kill takes down clickhouse-server +# (PID 1 for image providers), so the container exits — but its data layer +# survives, so `docker start` restarts it with the loaded tables intact. For the +# package provider the container (PID 1 = sleep) stays up, so relaunch the daemon. +revive_server() { + if [ "$(sudo docker inspect -f '{{.State.Running}}' "${CONTAINER}" 2>/dev/null)" != "true" ]; then + sudo docker start "${CONTAINER}" >/dev/null 2>&1 + elif [ "${IMAGE}" = "package" ]; then + sudo docker exec -d "${CONTAINER}" clickhouse-server --daemon --config /etc/clickhouse-server/config.xml 2>/dev/null + fi + local i + for i in $(seq 1 "${READY_TIMEOUT:-90}"); do server_alive && return 0; sleep 1; done + return 1 +} + # Run one query TRIES times, print a JSON array "[t1, t2, t3]" (null on error). +# If the server dies mid-query (e.g. OOM-killed), revive it and retry up to +# CRASH_RETRIES times so one heavy query doesn't null out the whole version. run_query() { - local query="$1" i res out="[" + local query="$1" i res crash out="[" for i in $(seq 1 "${TRIES}"); do - res=$(printf '%s' "${query}" | client --time --max_memory_usage="${MEM}" --format=Null 2>&1) - if [[ "${res}" =~ ^[0-9]+\.[0-9]+$ ]]; then out+="${res}"; else out+="null"; fi + crash=0 + while :; do + res=$(printf '%s' "${query}" | client --time --max_memory_usage="${MEM}" --format=Null 2>&1) + [[ "${res}" =~ ^[0-9]+\.[0-9]+$ ]] && break + if ! server_alive && [ "${crash}" -lt "${CRASH_RETRIES:-2}" ]; then + crash=$((crash + 1)) + echo "${VERSION}: server died mid-query (likely OOM); reviving (retry ${crash})" >&2 + revive_server && continue + fi + res="null"; break + done + out+="${res}" [ "${i}" -ne "${TRIES}" ] && out+=", " done echo "${out}]" From 4993f536df0e88b8dc20ff2a301b510946cdf835 Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Tue, 30 Jun 2026 23:06:32 +0000 Subject: [PATCH 008/120] versions: accept an unambiguous version prefix in run-benchmark.sh e.g. '26.6' resolves to '26.6.1.1193' (one patch per YY.MM is kept), and the launcher canonicalises to the full version. Exact versions and bare tags still match directly; an ambiguous prefix lists the candidates. Co-Authored-By: Claude Opus 4.8 --- versions/run-benchmark.sh | 19 ++++++++++++++++--- 1 file changed, 16 insertions(+), 3 deletions(-) diff --git a/versions/run-benchmark.sh b/versions/run-benchmark.sh index 06775499f0..dd801a9b82 100755 --- a/versions/run-benchmark.sh +++ b/versions/run-benchmark.sh @@ -23,10 +23,23 @@ tries="${tries:=3}" timeout="${timeout:-18000}" # load + (optional source build) + queries volume="${volume:-500}" # GB; raise well past 1000 if including taxi -# Resolve the image for this version. -image="$(./list-versions.sh | awk -F'\t' -v v="${VERSION}" '$1==v{print $2}')" -[ -z "${image}" ] && { echo "unknown version: ${VERSION}" >&2; exit 1; } +# Resolve the version against list-versions.sh: accept an exact version +# (26.6.1.1193, 1.1.54378, 53973) or an unambiguous prefix at a dot boundary +# (26.6 -> 26.6.1.1193, since exactly one patch per YY.MM is kept). +LV="$(./list-versions.sh)" +line="$(awk -F'\t' -v v="${VERSION}" '$1==v' <<<"${LV}")" +if [ -z "${line}" ]; then + line="$(awk -F'\t' -v v="${VERSION}" 'index($1, v".")==1' <<<"${LV}")" + n="$(grep -c . <<<"${line}"; true)" + if [ "${n}" -gt 1 ]; then + echo "ambiguous version '${VERSION}', matches:" >&2; cut -f1 <<<"${line}" >&2; exit 1 + fi +fi +[ -z "${line}" ] && { echo "unknown version: ${VERSION}" >&2; exit 1; } +VERSION="$(cut -f1 <<<"${line}")" # canonicalise to the full version +image="$(cut -f2 <<<"${line}")" [ "${image}" = "unavailable" ] && { echo "${VERSION} is unavailable (no image/package/source)" >&2; exit 1; } +echo "resolved to ${VERSION} (${image})" # For source-built versions, get the tag and required GCC from versions.txt. tag="-"; gcc="5" From 3c6d7d5f7cc7949a83715a4c9b34bbd4bf5bdc06 Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Tue, 30 Jun 2026 23:07:45 +0000 Subject: [PATCH 009/120] versions: resolve a version prefix to the latest match by version sort A prefix now picks the newest matching version instead of erroring on ambiguity: 24 -> 24.12.x, 1.1 -> the latest 1.1.x, 26.6 -> 26.6.1.1193. Exact versions and bare tags still match directly. Co-Authored-By: Claude Opus 4.8 --- versions/run-benchmark.sh | 11 ++++------- 1 file changed, 4 insertions(+), 7 deletions(-) diff --git a/versions/run-benchmark.sh b/versions/run-benchmark.sh index dd801a9b82..3cb8cdc8f8 100755 --- a/versions/run-benchmark.sh +++ b/versions/run-benchmark.sh @@ -24,16 +24,13 @@ timeout="${timeout:-18000}" # load + (optional source build) + q volume="${volume:-500}" # GB; raise well past 1000 if including taxi # Resolve the version against list-versions.sh: accept an exact version -# (26.6.1.1193, 1.1.54378, 53973) or an unambiguous prefix at a dot boundary -# (26.6 -> 26.6.1.1193, since exactly one patch per YY.MM is kept). +# (26.6.1.1193, 1.1.54378, 53973) or a prefix at a dot boundary, choosing the +# latest match by version sort (26.6 -> 26.6.1.1193, 24 -> 24.12.x, 1.1 -> the +# newest 1.1.x). LV="$(./list-versions.sh)" line="$(awk -F'\t' -v v="${VERSION}" '$1==v' <<<"${LV}")" if [ -z "${line}" ]; then - line="$(awk -F'\t' -v v="${VERSION}" 'index($1, v".")==1' <<<"${LV}")" - n="$(grep -c . <<<"${line}"; true)" - if [ "${n}" -gt 1 ]; then - echo "ambiguous version '${VERSION}', matches:" >&2; cut -f1 <<<"${line}" >&2; exit 1 - fi + line="$(awk -F'\t' -v v="${VERSION}" 'index($1, v".")==1' <<<"${LV}" | sort -V | tail -1)" fi [ -z "${line}" ] && { echo "unknown version: ${VERSION}" >&2; exit 1; } VERSION="$(cut -f1 <<<"${line}")" # canonicalise to the full version From 46259813007334e0edaa5f786f199ad663201e0a Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Tue, 30 Jun 2026 23:12:45 +0000 Subject: [PATCH 010/120] versions: add standalone prepare-ebs-snapshot.sh for the datasets Builds an EBS volume holding the prepared Native files (sized just-enough), snapshots it (labelled versions-data, tagged Name=clickbench-versions-data) and deletes the working volume. Standalone and not wired into the launcher: a snapshot-backed volume lazy-loads from S3, so for one-shot VMs it is not faster than the plain S3 download unless Fast Snapshot Restore or volume reuse is used. Co-Authored-By: Claude Opus 4.8 --- versions/prepare-ebs-snapshot.sh | 99 ++++++++++++++++++++++++++++++++ 1 file changed, 99 insertions(+) create mode 100755 versions/prepare-ebs-snapshot.sh diff --git a/versions/prepare-ebs-snapshot.sh b/versions/prepare-ebs-snapshot.sh new file mode 100755 index 0000000000..a0336fde1e --- /dev/null +++ b/versions/prepare-ebs-snapshot.sh @@ -0,0 +1,99 @@ +#!/usr/bin/env bash +# Build an EBS snapshot that holds the prepared Native data files, so benchmark +# VMs attach it as a small read-only data volume instead of re-downloading the +# datasets every time. Run on an EC2 instance whose role/creds can manage EBS +# (this prep box works once `aws` is configured — it already has the files). +# +# ./prepare-ebs-snapshot.sh +# DATASETS="hits ssb mgbench" ./prepare-ebs-snapshot.sh # leave out taxi +# SRC=s3 ./prepare-ebs-snapshot.sh # download from the bucket instead of local files +# +# The volume is filesystem-labelled "versions-data"; the snapshot is tagged +# Name=clickbench-versions-data. The working volume is deleted afterwards — only +# the snapshot is kept. +# +# NOTE: a volume restored from a snapshot is lazy-loaded from S3 (blocks fetched +# on first read), so for one-shot VMs that read the data once it is NOT faster +# than downloading from S3 — and gp3's 125 MB/s baseline can be slower than a +# parallel in-region S3 download. It only pays off with Fast Snapshot Restore +# (paid, per AZ) or when the volume is reused across many runs. This script is +# kept as a standalone option; cloud-init.sh.in downloads from S3 by default. + +set -euo pipefail +HERE="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" +SNAP_NAME="${SNAP_NAME:-clickbench-versions-data}" +LABEL="${LABEL:-versions-data}" +DATASETS="${DATASETS:-hits ssb mgbench taxi}" +SRC="${SRC:-${HERE}/prepare-data/data}" # local dir, or "s3" to download +BUCKET='https://clickhouse-public-datasets.s3.amazonaws.com/versions-benchmark' + +files_for() { case "$1" in + hits) echo hits.native.zst;; ssb) echo ssb.native.zst;; taxi) echo taxi.native.zst;; + mgbench) echo mgbench1.native.zst mgbench2.native.zst mgbench3.native.zst;; esac; } +FILES=(); for ds in ${DATASETS}; do FILES+=($(files_for "${ds}")); done + +# --- size the volume to just fit the files (+headroom for the filesystem) ----- +bytes=0 +for f in "${FILES[@]}"; do + if [ "${SRC}" = "s3" ]; then + s=$(curl -fsSI "${BUCKET}/${f}" | awk 'tolower($1)=="content-length:"{print $2}' | tr -d '\r') + else + s=$(stat -c%s "${SRC}/${f}" 2>/dev/null || echo 0) + fi + bytes=$(( bytes + ${s:-0} )) +done +[ "${bytes}" -gt 0 ] || { echo "no source files found for: ${DATASETS}" >&2; exit 1; } +SIZE_GB=$(( bytes / 1000000000 + 3 )) # ~headroom + ext4 overhead +[ "${SIZE_GB}" -lt 8 ] && SIZE_GB=8 +echo "including: ${FILES[*]}" +echo "volume size: ${SIZE_GB} GB" + +# --- this instance / AZ ------------------------------------------------------- +TOKEN=$(curl -sS -X PUT 'http://169.254.169.254/latest/api/token' -H 'X-aws-ec2-metadata-token-ttl-seconds: 600') +md() { curl -sS -H "X-aws-ec2-metadata-token: ${TOKEN}" "http://169.254.169.254/latest/meta-data/$1"; } +IID=$(md instance-id); AZ=$(md placement/availability-zone) + +# --- create + attach a blank volume ------------------------------------------- +VOL=$(AWS_PAGER='' aws ec2 create-volume --availability-zone "${AZ}" --size "${SIZE_GB}" \ + --volume-type gp3 --tag-specifications "ResourceType=volume,Tags=[{Key=Name,Value=${SNAP_NAME}-build}]" \ + --query VolumeId --output text) +echo "created volume ${VOL}; attaching to ${IID} ..." +cleanup() { AWS_PAGER='' aws ec2 detach-volume --volume-id "${VOL}" >/dev/null 2>&1 || true + aws ec2 wait volume-available --volume-ids "${VOL}" 2>/dev/null || true + AWS_PAGER='' aws ec2 delete-volume --volume-id "${VOL}" >/dev/null 2>&1 || true; } +trap cleanup EXIT +aws ec2 wait volume-available --volume-ids "${VOL}" +AWS_PAGER='' aws ec2 attach-volume --volume-id "${VOL}" --instance-id "${IID}" --device /dev/sdf >/dev/null +aws ec2 wait volume-in-use --volume-ids "${VOL}" + +# Find the device (Nitro exposes EBS as NVMe with serial = volume id sans dash). +DEV="" +for _ in $(seq 1 30); do + DEV=$(lsblk -dpno NAME,SERIAL | awk -v s="${VOL//-/}" 'index($2,s){print $1; exit}') + [ -n "${DEV}" ] && break; sleep 2 +done +[ -n "${DEV}" ] || { echo "could not find attached device for ${VOL}" >&2; exit 1; } +echo "device: ${DEV}" + +# --- format, populate, unmount ------------------------------------------------ +sudo mkfs.ext4 -q -L "${LABEL}" "${DEV}" +MNT=$(mktemp -d); sudo mount "${DEV}" "${MNT}"; sudo chown "$(id -u)" "${MNT}" +for f in "${FILES[@]}"; do + if [ "${SRC}" = "s3" ]; then + echo "downloading ${f} ..."; wget --continue --progress=dot:giga -P "${MNT}" "${BUCKET}/${f}" + else + echo "copying ${f} ..."; cp "${SRC}/${f}" "${MNT}/${f}" + fi +done +sync; ls -lh "${MNT}"; sudo umount "${MNT}"; rmdir "${MNT}" + +# --- snapshot, then drop the working volume (trap) ---------------------------- +AWS_PAGER='' aws ec2 detach-volume --volume-id "${VOL}" >/dev/null +aws ec2 wait volume-available --volume-ids "${VOL}" +SNAP=$(AWS_PAGER='' aws ec2 create-snapshot --volume-id "${VOL}" \ + --description "versions-benchmark datasets: ${FILES[*]}" \ + --tag-specifications "ResourceType=snapshot,Tags=[{Key=Name,Value=${SNAP_NAME}},{Key=datasets,Value=${DATASETS// /,}}]" \ + --query SnapshotId --output text) +echo "snapshot ${SNAP} creating; waiting for completion ..." +aws ec2 wait snapshot-completed --snapshot-ids "${SNAP}" +echo "DONE: ${SNAP} (label ${LABEL}, ${SIZE_GB} GB, tag Name=${SNAP_NAME})" From e5b46370b045a3321c295ca4a84ffe2bb4c12524 Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Tue, 30 Jun 2026 23:13:09 +0000 Subject: [PATCH 011/120] versions: drop prepare-ebs-snapshot.sh A snapshot-backed volume lazy-loads from S3, so it isn't faster than the plain S3 download for one-shot VMs; the snapshot approach is not used. Co-Authored-By: Claude Opus 4.8 --- versions/prepare-ebs-snapshot.sh | 99 -------------------------------- 1 file changed, 99 deletions(-) delete mode 100755 versions/prepare-ebs-snapshot.sh diff --git a/versions/prepare-ebs-snapshot.sh b/versions/prepare-ebs-snapshot.sh deleted file mode 100755 index a0336fde1e..0000000000 --- a/versions/prepare-ebs-snapshot.sh +++ /dev/null @@ -1,99 +0,0 @@ -#!/usr/bin/env bash -# Build an EBS snapshot that holds the prepared Native data files, so benchmark -# VMs attach it as a small read-only data volume instead of re-downloading the -# datasets every time. Run on an EC2 instance whose role/creds can manage EBS -# (this prep box works once `aws` is configured — it already has the files). -# -# ./prepare-ebs-snapshot.sh -# DATASETS="hits ssb mgbench" ./prepare-ebs-snapshot.sh # leave out taxi -# SRC=s3 ./prepare-ebs-snapshot.sh # download from the bucket instead of local files -# -# The volume is filesystem-labelled "versions-data"; the snapshot is tagged -# Name=clickbench-versions-data. The working volume is deleted afterwards — only -# the snapshot is kept. -# -# NOTE: a volume restored from a snapshot is lazy-loaded from S3 (blocks fetched -# on first read), so for one-shot VMs that read the data once it is NOT faster -# than downloading from S3 — and gp3's 125 MB/s baseline can be slower than a -# parallel in-region S3 download. It only pays off with Fast Snapshot Restore -# (paid, per AZ) or when the volume is reused across many runs. This script is -# kept as a standalone option; cloud-init.sh.in downloads from S3 by default. - -set -euo pipefail -HERE="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" -SNAP_NAME="${SNAP_NAME:-clickbench-versions-data}" -LABEL="${LABEL:-versions-data}" -DATASETS="${DATASETS:-hits ssb mgbench taxi}" -SRC="${SRC:-${HERE}/prepare-data/data}" # local dir, or "s3" to download -BUCKET='https://clickhouse-public-datasets.s3.amazonaws.com/versions-benchmark' - -files_for() { case "$1" in - hits) echo hits.native.zst;; ssb) echo ssb.native.zst;; taxi) echo taxi.native.zst;; - mgbench) echo mgbench1.native.zst mgbench2.native.zst mgbench3.native.zst;; esac; } -FILES=(); for ds in ${DATASETS}; do FILES+=($(files_for "${ds}")); done - -# --- size the volume to just fit the files (+headroom for the filesystem) ----- -bytes=0 -for f in "${FILES[@]}"; do - if [ "${SRC}" = "s3" ]; then - s=$(curl -fsSI "${BUCKET}/${f}" | awk 'tolower($1)=="content-length:"{print $2}' | tr -d '\r') - else - s=$(stat -c%s "${SRC}/${f}" 2>/dev/null || echo 0) - fi - bytes=$(( bytes + ${s:-0} )) -done -[ "${bytes}" -gt 0 ] || { echo "no source files found for: ${DATASETS}" >&2; exit 1; } -SIZE_GB=$(( bytes / 1000000000 + 3 )) # ~headroom + ext4 overhead -[ "${SIZE_GB}" -lt 8 ] && SIZE_GB=8 -echo "including: ${FILES[*]}" -echo "volume size: ${SIZE_GB} GB" - -# --- this instance / AZ ------------------------------------------------------- -TOKEN=$(curl -sS -X PUT 'http://169.254.169.254/latest/api/token' -H 'X-aws-ec2-metadata-token-ttl-seconds: 600') -md() { curl -sS -H "X-aws-ec2-metadata-token: ${TOKEN}" "http://169.254.169.254/latest/meta-data/$1"; } -IID=$(md instance-id); AZ=$(md placement/availability-zone) - -# --- create + attach a blank volume ------------------------------------------- -VOL=$(AWS_PAGER='' aws ec2 create-volume --availability-zone "${AZ}" --size "${SIZE_GB}" \ - --volume-type gp3 --tag-specifications "ResourceType=volume,Tags=[{Key=Name,Value=${SNAP_NAME}-build}]" \ - --query VolumeId --output text) -echo "created volume ${VOL}; attaching to ${IID} ..." -cleanup() { AWS_PAGER='' aws ec2 detach-volume --volume-id "${VOL}" >/dev/null 2>&1 || true - aws ec2 wait volume-available --volume-ids "${VOL}" 2>/dev/null || true - AWS_PAGER='' aws ec2 delete-volume --volume-id "${VOL}" >/dev/null 2>&1 || true; } -trap cleanup EXIT -aws ec2 wait volume-available --volume-ids "${VOL}" -AWS_PAGER='' aws ec2 attach-volume --volume-id "${VOL}" --instance-id "${IID}" --device /dev/sdf >/dev/null -aws ec2 wait volume-in-use --volume-ids "${VOL}" - -# Find the device (Nitro exposes EBS as NVMe with serial = volume id sans dash). -DEV="" -for _ in $(seq 1 30); do - DEV=$(lsblk -dpno NAME,SERIAL | awk -v s="${VOL//-/}" 'index($2,s){print $1; exit}') - [ -n "${DEV}" ] && break; sleep 2 -done -[ -n "${DEV}" ] || { echo "could not find attached device for ${VOL}" >&2; exit 1; } -echo "device: ${DEV}" - -# --- format, populate, unmount ------------------------------------------------ -sudo mkfs.ext4 -q -L "${LABEL}" "${DEV}" -MNT=$(mktemp -d); sudo mount "${DEV}" "${MNT}"; sudo chown "$(id -u)" "${MNT}" -for f in "${FILES[@]}"; do - if [ "${SRC}" = "s3" ]; then - echo "downloading ${f} ..."; wget --continue --progress=dot:giga -P "${MNT}" "${BUCKET}/${f}" - else - echo "copying ${f} ..."; cp "${SRC}/${f}" "${MNT}/${f}" - fi -done -sync; ls -lh "${MNT}"; sudo umount "${MNT}"; rmdir "${MNT}" - -# --- snapshot, then drop the working volume (trap) ---------------------------- -AWS_PAGER='' aws ec2 detach-volume --volume-id "${VOL}" >/dev/null -aws ec2 wait volume-available --volume-ids "${VOL}" -SNAP=$(AWS_PAGER='' aws ec2 create-snapshot --volume-id "${VOL}" \ - --description "versions-benchmark datasets: ${FILES[*]}" \ - --tag-specifications "ResourceType=snapshot,Tags=[{Key=Name,Value=${SNAP_NAME}},{Key=datasets,Value=${DATASETS// /,}}]" \ - --query SnapshotId --output text) -echo "snapshot ${SNAP} creating; waiting for completion ..." -aws ec2 wait snapshot-completed --snapshot-ids "${SNAP}" -echo "DONE: ${SNAP} (label ${LABEL}, ${SIZE_GB} GB, tag Name=${SNAP_NAME})" From 6fd60342259ac6fbd9148e4e0d80937674ed5f3d Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Tue, 30 Jun 2026 23:33:34 +0000 Subject: [PATCH 012/120] versions: verbose load logging, robust old-version client, fix query-loop stdin MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit - load_data now echoes each CREATE (with DDL), the INSERT ... FORMAT Native and source file, and "loaded
: N rows in Ns" — so the cloud-init log shows what's happening during ingest. - Client invocations set HOME=/tmp (old images' clickhouse user has HOME /nonexistent -> history-file error) and TZ=UTC, and the sidecar client mounts the host /usr/share/zoneinfo (some old client images ship no tzdata and fail at startup with "Could not determine local time zone"). - Fix a stdin-drain regression from the crash-retry: the per-query `docker exec/run -i` client (and the SELECT 1 liveness probe) consumed the query file the benchmark loop reads on stdin, truncating each version to ~60/75 queries. Read queries on FD 3 and give the probe --- versions/run-version.sh | 43 +++++++++++++++++++++++++++++------------ 1 file changed, 31 insertions(+), 12 deletions(-) diff --git a/versions/run-version.sh b/versions/run-version.sh index 43b25cf7cb..523288aac9 100755 --- a/versions/run-version.sh +++ b/versions/run-version.sh @@ -59,8 +59,14 @@ cleanup() { sudo docker rm -f "${CONTAINER}" >/dev/null 2>&1; } # network namespace (`sidecar` mode) — same native protocol, precise --time. CLIENT_IMAGE="${IMAGE/-server/-client}" CLIENT_MODE="" # set by start_server: exec | sidecar -exec_client() { sudo docker exec -i "${CONTAINER}" clickhouse client "$@"; } -sidecar_client() { sudo docker run --rm -i --network "container:${CONTAINER}" "${CLIENT_IMAGE}" "$@"; } +# HOME=/tmp: old images set the clickhouse user's home to /nonexistent, so the +# client can't write its history file. TZ=UTC + the zoneinfo mount: some old +# client images ship no tzdata and otherwise fail at startup with "Could not +# determine local time zone" (before any query runs). +exec_client() { sudo docker exec -i -e HOME=/tmp -e TZ=UTC "${CONTAINER}" clickhouse client "$@"; } +sidecar_client() { sudo docker run --rm -i -e HOME=/tmp -e TZ=UTC \ + -v /usr/share/zoneinfo:/usr/share/zoneinfo:ro \ + --network "container:${CONTAINER}" "${CLIENT_IMAGE}" "$@"; } client() { case "${CLIENT_MODE}" in sidecar) sidecar_client "$@" ;; @@ -113,25 +119,36 @@ start_server() { # Load every dataset; tables that fail to create/load are left absent so their # queries report null. load_data() { - local ds pair table file + local ds pair table file ddl t0 for ds in ${LOAD_DATASETS}; do for pair in ${TABLES[$ds]}; do table="${pair%%:*}"; file="${pair##*:}" - [ -f "${DATA}/${file}" ] || { echo "missing ${file}, skipping ${table}" >&2; continue; } - "${HERE}/create/create.sh" "${VERSION}" "${table}" \ - | client --multiquery >/dev/null 2>&1 \ - || { echo "create ${table} failed on ${VERSION}" >&2; continue; } + [ -f "${DATA}/${file}" ] || { echo "SKIP ${table}: ${file} not present"; continue; } + ddl="$("${HERE}/create/create.sh" "${VERSION}" "${table}")" + echo "=== CREATE ${table} on ${VERSION} ===" + echo "${ddl}" + if ! printf '%s' "${ddl}" | client --multiquery; then + echo "CREATE ${table} FAILED on ${VERSION}"; continue + fi + echo "=== INSERT INTO ${table} FORMAT Native <- ${file} ($(du -h "${DATA}/${file}" | cut -f1)) ===" # Decompress on the host and stream plain Native into the client, so # the (possibly ancient) clickhouse-client never sees compression. - zstd -dc "${DATA}/${file}" | client --query "INSERT INTO ${table} FORMAT Native" >/dev/null 2>&1 \ - || echo "load ${table} failed on ${VERSION}" >&2 + t0=${SECONDS} + if zstd -dc "${DATA}/${file}" | client --query "INSERT INTO ${table} FORMAT Native"; then + echo "loaded ${table}: $(client --query "SELECT count() FROM ${table}" 2>/dev/null) rows in $((SECONDS - t0))s" + else + echo "LOAD ${table} FAILED on ${VERSION}" + fi done done } drop_caches() { sync; echo 3 | sudo tee /proc/sys/vm/drop_caches >/dev/null 2>&1; } -server_alive() { client --query "SELECT 1" >/dev/null 2>&1; } +# /dev/null 2>&1; } # Bring the server back after a crash. An OOM kill takes down clickhouse-server # (PID 1 for image providers), so the container exits — but its data layer @@ -197,14 +214,16 @@ run_benchmark() { echo ' "result":' echo ' [' for ds in ${QUERY_ORDER}; do - while IFS= read -r query; do + # Read queries on FD 3 (not stdin) so the per-query `docker exec/run -i` + # client calls can't consume the query file. + while IFS= read -r query <&3; do [ -z "${query}" ] && continue query="${query%;}" # strip trailing semicolon drop_caches [ "${FIRST}" = 0 ] && echo ',' FIRST=0 printf '%s' "$(run_query "${query}")" - done < "${HERE}/queries/${ds}.sql" + done 3< "${HERE}/queries/${ds}.sql" done echo echo ' ]' From 78758b99f6a8736e4d2e573b9f671a84126dbb58 Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Wed, 1 Jul 2026 00:07:29 +0000 Subject: [PATCH 013/120] versions: stream per-query timings and cat the result JSON at the end Echo 'qN [dataset]: [t1, t2, t3]' to the log as each query finishes, and cat results/.json at the end so the full result is visible in the run output / cloud-init log (and thus received via the sink), not just written to a file. Co-Authored-By: Claude Opus 4.8 --- versions/run-version.sh | 10 +++++++--- 1 file changed, 7 insertions(+), 3 deletions(-) diff --git a/versions/run-version.sh b/versions/run-version.sh index 523288aac9..4d9306fbb6 100755 --- a/versions/run-version.sh +++ b/versions/run-version.sh @@ -204,7 +204,7 @@ detect_client() { # Time every query and write results/.json. run_benchmark() { - local ACTUAL ds query FIRST=1 + local ACTUAL ds query FIRST=1 qnum=0 row ACTUAL=$(client --query "SELECT version()" 2>/dev/null | tr -d '\r') echo "benchmarking ${VERSION} (server reports ${ACTUAL})" >&2 { @@ -220,16 +220,20 @@ run_benchmark() { [ -z "${query}" ] && continue query="${query%;}" # strip trailing semicolon drop_caches + qnum=$((qnum + 1)) + row="$(run_query "${query}")" + echo "q${qnum} [${ds}]: ${row}" >&2 # live timings to the log [ "${FIRST}" = 0 ] && echo ',' FIRST=0 - printf '%s' "$(run_query "${query}")" + printf '%s' "${row}" done 3< "${HERE}/queries/${ds}.sql" done echo echo ' ]' echo '}' } > "${OUT}" - echo "wrote ${OUT}" >&2 + echo "wrote ${OUT}; result:" >&2 + cat "${OUT}" # emit the JSON so it is captured/received } # ---- run ---- From 02b34207eb5d80c884e38d8a5e33388589c68801 Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Wed, 1 Jul 2026 00:22:47 +0000 Subject: [PATCH 014/120] versions: show INSERT progress with pv (once-a-second %/rate/ETA) Pipe the compressed file through pv before zstd -> INSERT, so loads report a periodic progress bar (percentage, rate, ETA) based on the known file size. Falls back to cat when pv is absent; pv added to the cloud-init apt install. Co-Authored-By: Claude Opus 4.8 --- versions/cloud-init.sh.in | 2 +- versions/run-version.sh | 14 ++++++++++---- 2 files changed, 11 insertions(+), 5 deletions(-) diff --git a/versions/cloud-init.sh.in b/versions/cloud-init.sh.in index aeda3511c9..9ab53398b2 100644 --- a/versions/cloud-init.sh.in +++ b/versions/cloud-init.sh.in @@ -12,7 +12,7 @@ export HOME="${HOME:-/root}" export DEBIAN_FRONTEND=noninteractive apt-get update -y -apt-get install -y docker.io git wget curl jq zstd +apt-get install -y docker.io git wget curl jq zstd pv systemctl enable --now docker git clone --depth 1 'https://github.com/@repo@.git' --branch '@branch@' ClickBench diff --git a/versions/run-version.sh b/versions/run-version.sh index 4d9306fbb6..f2e4757cd3 100755 --- a/versions/run-version.sh +++ b/versions/run-version.sh @@ -119,7 +119,7 @@ start_server() { # Load every dataset; tables that fail to create/load are left absent so their # queries report null. load_data() { - local ds pair table file ddl t0 + local ds pair table file ddl t0 reader for ds in ${LOAD_DATASETS}; do for pair in ${TABLES[$ds]}; do table="${pair%%:*}"; file="${pair##*:}" @@ -131,10 +131,16 @@ load_data() { echo "CREATE ${table} FAILED on ${VERSION}"; continue fi echo "=== INSERT INTO ${table} FORMAT Native <- ${file} ($(du -h "${DATA}/${file}" | cut -f1)) ===" - # Decompress on the host and stream plain Native into the client, so - # the (possibly ancient) clickhouse-client never sees compression. + # Stream the compressed file through pv (progress %/rate/ETA once a + # second, based on the known file size) -> zstd -dc -> a plain Native + # INSERT, so the ancient clickhouse-client never sees compression. + if command -v pv >/dev/null 2>&1; then + reader=(pv -f -i 1 -N "${table}" -- "${DATA}/${file}") + else + reader=(cat -- "${DATA}/${file}") + fi t0=${SECONDS} - if zstd -dc "${DATA}/${file}" | client --query "INSERT INTO ${table} FORMAT Native"; then + if "${reader[@]}" | zstd -dc | client --query "INSERT INTO ${table} FORMAT Native"; then echo "loaded ${table}: $(client --query "SELECT count() FROM ${table}" 2>/dev/null) rows in $((SECONDS - t0))s" else echo "LOAD ${table} FAILED on ${VERSION}" From 98f597d75e75e6267e491f5f58cffc25b0c83f0b Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Wed, 1 Jul 2026 00:26:51 +0000 Subject: [PATCH 015/120] versions: use real commit dates for built versions Fetch the actual git commit date for every from-source version (the bare tags 53973..54011 had bogus 2016-01-01 fallbacks from an earlier rate-limited fetch) and record it in versions.txt; list-versions.sh now reports that commit date for built versions instead of the version_date.tsv release date. Co-Authored-By: Claude Opus 4.8 --- versions/build-from-source/versions.txt | 56 ++++++++++++------------- versions/list-versions.sh | 9 +++- 2 files changed, 35 insertions(+), 30 deletions(-) diff --git a/versions/build-from-source/versions.txt b/versions/build-from-source/versions.txt index e79be7d976..262360f1be 100644 --- a/versions/build-from-source/versions.txt +++ b/versions/build-from-source/versions.txt @@ -15,32 +15,32 @@ 53987 53987 2016-06-28 5 53988 53988 2016-06-28 5 53989 53989 2016-07-01 5 -53990 53990 2016-01-01 5 -53991 53991 2016-01-01 5 -53992 53992 2016-01-01 5 -53993 53993 2016-01-01 5 -53994 53994 2016-01-01 5 -53995 53995 2016-01-01 5 -53996 53996 2016-01-01 5 -53997 53997 2016-01-01 5 -53998 53998 2016-01-01 5 -53999 53999 2016-01-01 5 -54000 54000 2016-01-01 5 -54001 54001 2016-01-01 5 -54002 54002 2016-01-01 5 -54003 54003 2016-01-01 5 -54004 54004 2016-01-01 5 -54005 54005 2016-01-01 5 -54006 54006 2016-01-01 5 -54007 54007 2016-01-01 5 -54008 54008 2016-01-01 5 -54009 54009 2016-01-01 5 -54010 54010 2016-01-01 5 -54011 54011 2016-01-01 5 -1.1.54165 v1.1.54165-stable 2017-02-15 5 -1.1.54318 v1.1.54318-stable 2017-12-01 6 -1.1.54335 v1.1.54335-stable 2018-01-17 7 -1.1.54336 v1.1.54336-stable 2018-01-17 7 -1.1.54358 v1.1.54358-stable 2018-03-08 7 -1.1.54362 v1.1.54362-stable 2018-03-11 7 +53990 53990 2016-07-01 5 +53991 53991 2016-07-07 5 +53992 53992 2016-07-14 5 +53993 53993 2016-07-14 5 +53994 53994 2016-07-14 5 +53995 53995 2016-07-14 5 +53996 53996 2016-07-14 5 +53997 53997 2016-07-17 5 +53998 53998 2016-07-21 5 +53999 53999 2016-07-25 5 +54000 54000 2016-07-27 5 +54001 54001 2016-07-28 5 +54002 54002 2016-08-02 5 +54003 54003 2016-08-03 5 +54004 54004 2016-08-03 5 +54005 54005 2016-08-07 5 +54006 54006 2016-08-10 5 +54007 54007 2016-08-10 5 +54008 54008 2016-08-13 5 +54009 54009 2016-08-15 5 +54010 54010 2016-08-15 5 +54011 54011 2016-08-17 5 +1.1.54165 v1.1.54165-stable 2017-02-14 5 +1.1.54318 v1.1.54318-stable 2017-11-30 6 +1.1.54335 v1.1.54335-stable 2018-01-16 7 +1.1.54336 v1.1.54336-stable 2018-01-16 7 +1.1.54358 v1.1.54358-stable 2018-03-07 7 +1.1.54362 v1.1.54362-stable 2018-03-10 7 1.1.54370 v1.1.54370-stable 2018-03-16 7 diff --git a/versions/list-versions.sh b/versions/list-versions.sh index 6313c6d41d..5582a094ac 100755 --- a/versions/list-versions.sh +++ b/versions/list-versions.sh @@ -91,8 +91,13 @@ emit() { # version date -> resolve provider and print the line # No image. packages.clickhouse.com ships .tgz from 21.1 on; older = gone. [ "${v%%.*}" -ge 21 ] 2>/dev/null && image="package" || image="unavailable" fi - # Prefer a from-source build where we have one (resurrects the oldest). - [ "${image}" = "unavailable" ] && [ -n "${BUILT_DATE[$v]:-}" ] && image="clickhouse-built:${v}" + # Prefer a from-source build where we have one (resurrects the oldest), and + # for built versions report the real commit date from versions.txt rather + # than the version_date.tsv release date. + if [ "${image}" = "unavailable" ] && [ -n "${BUILT_DATE[$v]:-}" ]; then + image="clickhouse-built:${v}" + fi + [[ "${image}" == clickhouse-built:* ]] && date="${BUILT_DATE[$v]:-$date}" printf '%s\t%s\t%s\n' "${v}" "${image}" "${date}" } From c19d42f1f207ea05f15c4bfacc51dc5d6645528c Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Wed, 1 Jul 2026 00:55:00 +0000 Subject: [PATCH 016/120] versions: report per-table on-disk sizes at end of run Print 'table bytes' from system.parts (database 'default'), falling back for old versions without it to du -sLb on the data dir (/var/lib/clickhouse or /opt/clickhouse), following symlinks. Co-Authored-By: Claude Opus 4.8 --- versions/run-version.sh | 20 ++++++++++++++++++++ 1 file changed, 20 insertions(+) diff --git a/versions/run-version.sh b/versions/run-version.sh index f2e4757cd3..a5d3b27600 100755 --- a/versions/run-version.sh +++ b/versions/run-version.sh @@ -171,6 +171,25 @@ revive_server() { return 1 } +# Report on-disk size per table: via system.parts, or (for old versions without +# it) by measuring the data directory inside the container, following symlinks. +report_sizes() { + echo "=== table sizes on disk (${VERSION}) ===" + local out + # Only the benchmark tables (database 'default'), not the server's own + # system.* log tables. + out=$(client --query "SELECT table, sum(bytes_on_disk) AS size FROM system.parts WHERE database = 'default' GROUP BY table ORDER BY table FORMAT TabSeparated" /dev/null) + if [ -n "${out}" ]; then + printf '%s\n' "${out}" + else + echo "(system.parts unavailable — measuring the data directory)" + sudo docker exec "${CONTAINER}" sh -c ' + base=/var/lib/clickhouse; [ -d "$base/data" ] || base=/opt/clickhouse + du -sLb "$base"/data/default/* 2>/dev/null | sort -k2' 2>/dev/null \ + || echo "(could not measure data directory)" + fi +} + # Run one query TRIES times, print a JSON array "[t1, t2, t3]" (null on error). # If the server dies mid-query (e.g. OOM-killed), revive it and retry up to # CRASH_RETRIES times so one heavy query doesn't null out the whole version. @@ -240,6 +259,7 @@ run_benchmark() { } > "${OUT}" echo "wrote ${OUT}; result:" >&2 cat "${OUT}" # emit the JSON so it is captured/received + report_sizes } # ---- run ---- From 0aae31aa043a87ddba4d4df52b603c39a8c0eded Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Wed, 1 Jul 2026 00:55:00 +0000 Subject: [PATCH 017/120] versions: gp3 root volume with provisioned throughput/IOPS Cold-cache query reads and ingest are disk-bound, so use gp3 (default 1000 MB/s / 16000 IOPS, both overridable via throughput=/iops=) instead of gp2 whose throughput is tied to size. Co-Authored-By: Claude Opus 4.8 --- versions/run-benchmark.sh | 7 ++++++- 1 file changed, 6 insertions(+), 1 deletion(-) diff --git a/versions/run-benchmark.sh b/versions/run-benchmark.sh index 3cb8cdc8f8..c4fbd5a8e2 100755 --- a/versions/run-benchmark.sh +++ b/versions/run-benchmark.sh @@ -22,6 +22,11 @@ datasets="${datasets:=hits ssb mgbench}" # taxi skipped by default (huge); add tries="${tries:=3}" timeout="${timeout:-18000}" # load + (optional source build) + queries volume="${volume:-500}" # GB; raise well past 1000 if including taxi +# gp3 root volume with provisioned throughput/IOPS (cold-cache query reads and +# the ingest are disk-bound). gp3 maxes at 1000 MB/s / 16000 IOPS per volume; +# the instance's own EBS bandwidth is the real ceiling. +iops="${iops:-16000}" +throughput="${throughput:-1000}" # MB/s # Resolve the version against list-versions.sh: accept an exact version # (26.6.1.1193, 1.1.54378, 53973) or a prefix at a dot boundary, choosing the @@ -61,7 +66,7 @@ awk -v repo="$repo" -v branch="$branch" -v version="$VERSION" -v image="$image" RETRY_RE='InsufficientInstanceCapacity|VcpuLimitExceeded|InstanceLimitExceeded|MaxSpotInstanceCountExceeded' while :; do out=$(AWS_PAGER='' aws ec2 run-instances --image-id "$ami" --instance-type "$machine" \ - --block-device-mappings "DeviceName=/dev/sda1,Ebs={DeleteOnTermination=true,VolumeSize=${volume},VolumeType=gp2}" \ + --block-device-mappings "DeviceName=/dev/sda1,Ebs={DeleteOnTermination=true,VolumeSize=${volume},VolumeType=gp3,Iops=${iops},Throughput=${throughput}}" \ --instance-initiated-shutdown-behavior terminate \ --tag-specifications "ResourceType=instance,Tags=[{Key=Name,Value=clickbench-versions-${VERSION}}]" \ --user-data "file://cloud-init.${VERSION}.sh" 2>&1) && rc=0 || rc=$? From 40e13f34157799343ca13dc9f723973a9c7d1b64 Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Wed, 1 Jul 2026 00:56:40 +0000 Subject: [PATCH 018/120] versions: download datasets in parallel Build the list of dataset files and fetch them concurrently (xargs -P 8 wget --continue --progress=dot:giga) instead of one at a time. Missing files (e.g. ssb/taxi not yet uploaded) fail their own wget and are skipped. Co-Authored-By: Claude Opus 4.8 --- versions/cloud-init.sh.in | 19 +++++++++++-------- 1 file changed, 11 insertions(+), 8 deletions(-) diff --git a/versions/cloud-init.sh.in b/versions/cloud-init.sh.in index 9ab53398b2..62056a1e62 100644 --- a/versions/cloud-init.sh.in +++ b/versions/cloud-init.sh.in @@ -30,18 +30,21 @@ DATADIR=prepare-data/data mkdir -p "${DATADIR}" BUCKET='https://clickhouse-public-datasets.s3.amazonaws.com/versions-benchmark' -# Download only the files for the datasets we will load; -f so a missing file -# (e.g. ssb/taxi not uploaded yet) is skipped and run-version.sh reports its -# queries as null rather than failing. -fetch() { wget --continue --progress=dot:giga -P "${DATADIR}" "${BUCKET}/$1" || echo "skip $1 (not in bucket)"; } +# Download the files for the datasets we will load, in parallel. A missing file +# (e.g. ssb/taxi not uploaded yet) just fails its own wget and is skipped, so +# run-version.sh reports that dataset's queries as null rather than failing. +FILES="" for ds in ${DATASETS}; do case "${ds}" in - hits) fetch hits.native.zst ;; - ssb) fetch ssb.native.zst ;; - mgbench) fetch mgbench1.native.zst; fetch mgbench2.native.zst; fetch mgbench3.native.zst ;; - taxi) fetch taxi.native.zst ;; + hits) FILES="${FILES} hits.native.zst" ;; + ssb) FILES="${FILES} ssb.native.zst" ;; + mgbench) FILES="${FILES} mgbench1.native.zst mgbench2.native.zst mgbench3.native.zst" ;; + taxi) FILES="${FILES} taxi.native.zst" ;; esac done +echo "downloading in parallel:${FILES}" +echo ${FILES} | tr ' ' '\n' | grep . | \ + xargs -P 8 -I{} wget --continue --progress=dot:giga -P "${DATADIR}" "${BUCKET}/{}" # Versions with no published Docker image are built from source on this VM. if [[ "${IMAGE}" == clickhouse-built:* ]]; then From 170be69c1c4af5de33eb9cbde5b10d33bb3fe3f4 Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Wed, 1 Jul 2026 00:58:42 +0000 Subject: [PATCH 019/120] versions: parallelize single-file downloads with aria2c Use aria2c to split each file into parallel byte-range segments (-x16 -s16) and run several files at once (-j4), so the huge taxi file isn't one slow stream and small files don't wait behind it. Falls back to parallel wget if aria2c is absent; aria2 added to the cloud-init install. Co-Authored-By: Claude Opus 4.8 --- versions/cloud-init.sh.in | 16 +++++++++++++--- 1 file changed, 13 insertions(+), 3 deletions(-) diff --git a/versions/cloud-init.sh.in b/versions/cloud-init.sh.in index 62056a1e62..2e40ff0f17 100644 --- a/versions/cloud-init.sh.in +++ b/versions/cloud-init.sh.in @@ -12,7 +12,7 @@ export HOME="${HOME:-/root}" export DEBIAN_FRONTEND=noninteractive apt-get update -y -apt-get install -y docker.io git wget curl jq zstd pv +apt-get install -y docker.io git wget curl jq zstd pv aria2 systemctl enable --now docker git clone --depth 1 'https://github.com/@repo@.git' --branch '@branch@' ClickBench @@ -43,8 +43,18 @@ for ds in ${DATASETS}; do esac done echo "downloading in parallel:${FILES}" -echo ${FILES} | tr ' ' '\n' | grep . | \ - xargs -P 8 -I{} wget --continue --progress=dot:giga -P "${DATADIR}" "${BUCKET}/{}" +if command -v aria2c >/dev/null 2>&1; then + # aria2 splits each file into parallel byte-range segments (-x/-s) and also + # runs several files at once (-j), so the huge taxi file isn't one slow + # stream. S3 supports Range requests. A missing file just errors and is + # skipped (|| true). + urls=""; for f in ${FILES}; do urls="${urls} ${BUCKET}/${f}"; done + aria2c --continue=true --dir="${DATADIR}" -j4 -x16 -s16 --min-split-size=20M \ + --summary-interval=10 --auto-file-renaming=false ${urls} || true +else + echo ${FILES} | tr ' ' '\n' | grep . | \ + xargs -P 8 -I{} wget --continue --progress=dot:giga -P "${DATADIR}" "${BUCKET}/{}" +fi # Versions with no published Docker image are built from source on this VM. if [[ "${IMAGE}" == clickhouse-built:* ]]; then From cb8eeb5bb43c407a7bc46432168169be1411050d Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Wed, 1 Jul 2026 01:04:02 +0000 Subject: [PATCH 020/120] =?UTF-8?q?versions:=20fix=20multi-file=20download?= =?UTF-8?q?=20=E2=80=94=20one=20aria2c=20per=20file?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit aria2 -j (multiple files at once) cross-contaminated per-file sizes (it used hits's length for ssb's byte ranges), so only hits downloaded and ssb/mgbench were aborted -> skipped at load time. Run one aria2c per file via xargs -P instead: each still uses 16 parallel segments, files download concurrently, and --allow-overwrite re-fetches a non-resumable pre-existing file rather than 416. Co-Authored-By: Claude Opus 4.8 --- versions/cloud-init.sh.in | 16 +++++++++------- 1 file changed, 9 insertions(+), 7 deletions(-) diff --git a/versions/cloud-init.sh.in b/versions/cloud-init.sh.in index 2e40ff0f17..46b11f3d91 100644 --- a/versions/cloud-init.sh.in +++ b/versions/cloud-init.sh.in @@ -44,13 +44,15 @@ for ds in ${DATASETS}; do done echo "downloading in parallel:${FILES}" if command -v aria2c >/dev/null 2>&1; then - # aria2 splits each file into parallel byte-range segments (-x/-s) and also - # runs several files at once (-j), so the huge taxi file isn't one slow - # stream. S3 supports Range requests. A missing file just errors and is - # skipped (|| true). - urls=""; for f in ${FILES}; do urls="${urls} ${BUCKET}/${f}"; done - aria2c --continue=true --dir="${DATADIR}" -j4 -x16 -s16 --min-split-size=20M \ - --summary-interval=10 --auto-file-renaming=false ${urls} || true + # One aria2c per file, run several at once with xargs -P. Each splits its + # file into 16 parallel byte-range segments (S3 supports Range), so the huge + # taxi file isn't one slow stream. Per-file invocation avoids aria2's -j + # cross-file size accounting; --allow-overwrite re-fetches a pre-existing + # file it can't resume instead of erroring; a missing file is skipped. + echo ${FILES} | tr ' ' '\n' | grep . | xargs -P 4 -I{} \ + aria2c --continue=true --allow-overwrite=true --auto-file-renaming=false \ + -x16 -s16 --min-split-size=20M --summary-interval=15 \ + -d "${DATADIR}" "${BUCKET}/{}" else echo ${FILES} | tr ' ' '\n' | grep . | \ xargs -P 8 -I{} wget --continue --progress=dot:giga -P "${DATADIR}" "${BUCKET}/{}" From fc3d261119cb7f7225132b280ca8d2b2b0619965 Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Wed, 1 Jul 2026 02:56:55 +0000 Subject: [PATCH 021/120] versions: add TPC-H, TPC-DS, Coffee Shop, ontime, UK, JOB datasets Expand the Versions Benchmark to 9 datasets / 344 queries, each loaded into its own database so same-named tables never collide (e.g. TPC-H and TPC-DS both have `customer`): - TPC-H (SF40) and TPC-DS (SF32): official schemas/queries from the ClickHouse repo, Decimal->Float64, NULL->type defaults, synth_date for the legacy engine. - Coffee Shop (fact_sales_500m, minus the unused order_line_id column) from the published Iceberg tables. - ontime (12 used columns) and UK price-paid, from the docs' saved copies. - Join Order Benchmark (21 IMDB tables, 113 queries) with a CSV re-encoder. - Narrow taxi to the 5 columns its queries use. Also: per-dataset databases in run-version.sh/create.sh; default 6 tries (1 cold + 5 hot); dataset-qualified column schemas. Co-Authored-By: Claude Opus 4.8 --- versions/README.md | 69 ++++-- .../build-from-source/Dockerfile.ubuntu1604 | 11 +- versions/build-from-source/monthly.tsv | 53 +++++ versions/cloud-init.sh.in | 6 + versions/config/listen.xml | 2 +- versions/create/create.sh | 82 ++++++- versions/create/schema/aka_name.columns | 9 + versions/create/schema/aka_title.columns | 13 ++ versions/create/schema/call_center.columns | 32 +++ versions/create/schema/cast_info.columns | 8 + versions/create/schema/catalog_page.columns | 10 + .../create/schema/catalog_returns.columns | 28 +++ versions/create/schema/catalog_sales.columns | 35 +++ versions/create/schema/char_name.columns | 8 + versions/create/schema/comp_cast_type.columns | 3 + versions/create/schema/company_name.columns | 8 + versions/create/schema/company_type.columns | 3 + versions/create/schema/complete_cast.columns | 5 + versions/create/schema/customer.columns | 9 + .../create/schema/customer_address.columns | 14 ++ .../schema/customer_demographics.columns | 10 + versions/create/schema/date_dim.columns | 29 +++ versions/create/schema/dim_locations.columns | 7 + versions/create/schema/dim_products.columns | 10 + versions/create/schema/fact_sales.columns | 12 + .../schema/household_demographics.columns | 6 + versions/create/schema/income_band.columns | 4 + versions/create/schema/info_type.columns | 3 + versions/create/schema/inventory.columns | 5 + versions/create/schema/item.columns | 23 ++ versions/create/schema/keyword.columns | 4 + versions/create/schema/kind_type.columns | 3 + versions/create/schema/lineitem.columns | 16 ++ versions/create/schema/link_type.columns | 3 + .../create/schema/movie_companies.columns | 6 + versions/create/schema/movie_info.columns | 6 + versions/create/schema/movie_info_idx.columns | 6 + versions/create/schema/movie_keyword.columns | 4 + versions/create/schema/movie_link.columns | 5 + versions/create/schema/name.columns | 10 + versions/create/schema/nation.columns | 5 + versions/create/schema/ontime.columns | 12 + versions/create/schema/orders.columns | 9 + versions/create/schema/part.columns | 10 + versions/create/schema/partsupp.columns | 6 + versions/create/schema/person_info.columns | 6 + versions/create/schema/promotion.columns | 20 ++ versions/create/schema/reason.columns | 4 + versions/create/schema/region.columns | 4 + versions/create/schema/role_type.columns | 3 + versions/create/schema/ship_mode.columns | 7 + versions/create/schema/store.columns | 30 +++ versions/create/schema/store_returns.columns | 21 ++ versions/create/schema/store_sales.columns | 24 ++ versions/create/schema/supplier.columns | 8 + versions/create/schema/time_dim.columns | 11 + versions/create/schema/title.columns | 13 ++ versions/create/schema/tpcds_customer.columns | 19 ++ versions/create/schema/trips.columns | 51 +---- versions/create/schema/uk_price_paid.columns | 14 ++ versions/create/schema/warehouse.columns | 15 ++ versions/create/schema/web_page.columns | 15 ++ versions/create/schema/web_returns.columns | 25 +++ versions/create/schema/web_sales.columns | 35 +++ versions/create/schema/web_site.columns | 27 +++ versions/index.html | 209 +++++++++--------- versions/prepare-data/coffeeshop.sh | 44 ++++ versions/prepare-data/job.sh | 67 ++++++ versions/prepare-data/job_convert.py | 115 ++++++++++ versions/prepare-data/ontime.sh | 22 ++ versions/prepare-data/prepare.sh | 6 +- versions/prepare-data/taxi.sh | 63 +----- versions/prepare-data/tpcds.sh | 75 +++++++ versions/prepare-data/tpch.sh | 60 +++++ versions/prepare-data/uk.sh | 30 +++ versions/queries/coffeeshop.sql | 17 ++ versions/queries/job.sql | 113 ++++++++++ versions/queries/ontime.sql | 11 + versions/queries/tpcds.sql | 103 +++++++++ versions/queries/tpch.sql | 22 ++ versions/queries/uk.sql | 3 + versions/results/1.1.54019.json | 82 +++++++ versions/results/1.1.54378.json | 157 ++++++------- versions/results/19.8.3.8.json | 158 ++++++------- versions/results/53974.json | 82 +++++++ versions/results/53975.json | 82 +++++++ versions/results/53976.json | 82 +++++++ versions/results/53977.json | 82 +++++++ versions/results/53978.json | 82 +++++++ versions/results/53979.json | 82 +++++++ versions/results/53980.json | 82 +++++++ versions/results/53981.json | 82 +++++++ versions/results/53982.json | 82 +++++++ versions/results/53990.json | 82 +++++++ versions/results/53991.json | 82 +++++++ versions/results/53992.json | 82 +++++++ versions/results/53993.json | 82 +++++++ versions/results/53994.json | 82 +++++++ versions/results/53995.json | 82 +++++++ versions/results/53996.json | 82 +++++++ versions/results/53997.json | 82 +++++++ versions/results/53998.json | 82 +++++++ versions/results/53999.json | 82 +++++++ versions/results/54000.json | 82 +++++++ versions/results/54001.json | 82 +++++++ versions/results/54002.json | 82 +++++++ versions/results/54003.json | 82 +++++++ versions/results/54004.json | 82 +++++++ versions/results/54005.json | 82 +++++++ versions/results/54006.json | 82 +++++++ versions/results/54007.json | 82 +++++++ versions/results/54008.json | 82 +++++++ versions/results/54009.json | 82 +++++++ versions/results/54010.json | 82 +++++++ versions/results/54011.json | 82 +++++++ versions/run-benchmark.sh | 6 +- versions/run-version.sh | 54 +++-- 117 files changed, 4509 insertions(+), 424 deletions(-) create mode 100644 versions/build-from-source/monthly.tsv create mode 100644 versions/create/schema/aka_name.columns create mode 100644 versions/create/schema/aka_title.columns create mode 100644 versions/create/schema/call_center.columns create mode 100644 versions/create/schema/cast_info.columns create mode 100644 versions/create/schema/catalog_page.columns create mode 100644 versions/create/schema/catalog_returns.columns create mode 100644 versions/create/schema/catalog_sales.columns create mode 100644 versions/create/schema/char_name.columns create mode 100644 versions/create/schema/comp_cast_type.columns create mode 100644 versions/create/schema/company_name.columns create mode 100644 versions/create/schema/company_type.columns create mode 100644 versions/create/schema/complete_cast.columns create mode 100644 versions/create/schema/customer.columns create mode 100644 versions/create/schema/customer_address.columns create mode 100644 versions/create/schema/customer_demographics.columns create mode 100644 versions/create/schema/date_dim.columns create mode 100644 versions/create/schema/dim_locations.columns create mode 100644 versions/create/schema/dim_products.columns create mode 100644 versions/create/schema/fact_sales.columns create mode 100644 versions/create/schema/household_demographics.columns create mode 100644 versions/create/schema/income_band.columns create mode 100644 versions/create/schema/info_type.columns create mode 100644 versions/create/schema/inventory.columns create mode 100644 versions/create/schema/item.columns create mode 100644 versions/create/schema/keyword.columns create mode 100644 versions/create/schema/kind_type.columns create mode 100644 versions/create/schema/lineitem.columns create mode 100644 versions/create/schema/link_type.columns create mode 100644 versions/create/schema/movie_companies.columns create mode 100644 versions/create/schema/movie_info.columns create mode 100644 versions/create/schema/movie_info_idx.columns create mode 100644 versions/create/schema/movie_keyword.columns create mode 100644 versions/create/schema/movie_link.columns create mode 100644 versions/create/schema/name.columns create mode 100644 versions/create/schema/nation.columns create mode 100644 versions/create/schema/ontime.columns create mode 100644 versions/create/schema/orders.columns create mode 100644 versions/create/schema/part.columns create mode 100644 versions/create/schema/partsupp.columns create mode 100644 versions/create/schema/person_info.columns create mode 100644 versions/create/schema/promotion.columns create mode 100644 versions/create/schema/reason.columns create mode 100644 versions/create/schema/region.columns create mode 100644 versions/create/schema/role_type.columns create mode 100644 versions/create/schema/ship_mode.columns create mode 100644 versions/create/schema/store.columns create mode 100644 versions/create/schema/store_returns.columns create mode 100644 versions/create/schema/store_sales.columns create mode 100644 versions/create/schema/supplier.columns create mode 100644 versions/create/schema/time_dim.columns create mode 100644 versions/create/schema/title.columns create mode 100644 versions/create/schema/tpcds_customer.columns create mode 100644 versions/create/schema/uk_price_paid.columns create mode 100644 versions/create/schema/warehouse.columns create mode 100644 versions/create/schema/web_page.columns create mode 100644 versions/create/schema/web_returns.columns create mode 100644 versions/create/schema/web_sales.columns create mode 100644 versions/create/schema/web_site.columns create mode 100644 versions/prepare-data/coffeeshop.sh create mode 100755 versions/prepare-data/job.sh create mode 100644 versions/prepare-data/job_convert.py create mode 100755 versions/prepare-data/ontime.sh create mode 100755 versions/prepare-data/tpcds.sh create mode 100644 versions/prepare-data/tpch.sh create mode 100755 versions/prepare-data/uk.sh create mode 100644 versions/queries/coffeeshop.sql create mode 100644 versions/queries/job.sql create mode 100644 versions/queries/ontime.sql create mode 100644 versions/queries/tpcds.sql create mode 100644 versions/queries/tpch.sql create mode 100644 versions/queries/uk.sql create mode 100644 versions/results/1.1.54019.json create mode 100644 versions/results/53974.json create mode 100644 versions/results/53975.json create mode 100644 versions/results/53976.json create mode 100644 versions/results/53977.json create mode 100644 versions/results/53978.json create mode 100644 versions/results/53979.json create mode 100644 versions/results/53980.json create mode 100644 versions/results/53981.json create mode 100644 versions/results/53982.json create mode 100644 versions/results/53990.json create mode 100644 versions/results/53991.json create mode 100644 versions/results/53992.json create mode 100644 versions/results/53993.json create mode 100644 versions/results/53994.json create mode 100644 versions/results/53995.json create mode 100644 versions/results/53996.json create mode 100644 versions/results/53997.json create mode 100644 versions/results/53998.json create mode 100644 versions/results/53999.json create mode 100644 versions/results/54000.json create mode 100644 versions/results/54001.json create mode 100644 versions/results/54002.json create mode 100644 versions/results/54003.json create mode 100644 versions/results/54004.json create mode 100644 versions/results/54005.json create mode 100644 versions/results/54006.json create mode 100644 versions/results/54007.json create mode 100644 versions/results/54008.json create mode 100644 versions/results/54009.json create mode 100644 versions/results/54010.json create mode 100644 versions/results/54011.json diff --git a/versions/README.md b/versions/README.md index 9243a2baf4..38ff6f6bd6 100644 --- a/versions/README.md +++ b/versions/README.md @@ -27,24 +27,43 @@ in its own container — from `1.1.54xxx` (2018) to today — with no host insta - `hits.native` — ClickBench `hits` (100M rows, 105 columns). - `ssb.native` — Star Schema Benchmark `lineorder_flat` (scale factor 100). - `mgbench{1,2,3}.native` — Brown benchmark `logs1`/`logs2`/`logs3`. - - `taxi.native` — NYC `trips`. + - `tpch_*.native` — TPC-H, 8 tables from the `dbgen` generator at scale + factor 40 (~10 GB compressed). + - `tpcds_*.native` — TPC-DS, 24 tables from the `dsdgen` generator at scale + factor 32 (~10 GB compressed). + - `coffeeshop_*.native` — Coffee Shop benchmark (`fact_sales` + `dim_locations` + + `dim_products`), from the published Iceberg tables; the smallest fact + table (`fact_sales_500m`, 500M rows) is used, minus the unused + high-cardinality `order_line_id` column. + - `ontime.native` — airline on-time performance (single table), from the saved + copy in the public bucket, narrowed to the 12 columns its queries use. + - `uk_price_paid.native` — UK land registry "price paid" (single table, ~28M + rows / ~200 MB), preprocessed per the ClickHouse docs. + - `job_*.native` — Join Order Benchmark, 21 tables (a snapshot of IMDB) from + the canonical CSV dump. + - `taxi.native` — NYC `trips` (narrowed to the 5 columns its queries use). Type downgrades: `LowCardinality`→`String`, `IPv4`→`String`, - `DateTime64`→`DateTime`, enums→`String`; `Nullable` is kept only where the - query set needs `IS NULL` (mgbench `logs1`). Tables without a natural date - carry a synthesised `log_date Date` so the legacy `MergeTree` engine works. - -3. **`create/create.sh
`** — emits version-appropriate DDL. - Modern releases use `ENGINE = MergeTree PARTITION BY … ORDER BY …`; the + `DateTime64`→`DateTime`, enums→`String`, TPC-H/TPC-DS `Decimal`→`Float64` + (TPC-H `CHAR(N)`→`FixedString(N)`; TPC-DS NULLs → type defaults so its + non-Nullable columns load); `Nullable` is kept only where the query set needs + `IS NULL` (mgbench `logs1`). Tables without a natural date carry a synthesised + `Date` column (`log_date` / TPC-H dimensions' constant `synth_date`) so the + legacy `MergeTree` engine works. + +3. **`create/create.sh
`** — emits version-appropriate + DDL. Modern releases use `ENGINE = MergeTree PARTITION BY … ORDER BY …`; the earliest `1.1.x` (before custom partitioning, < `1.1.54310`) use the legacy positional `ENGINE = MergeTree(date, (key), 8192)`. Column lists live in - `create/schema/*.columns`. + `create/schema/*.columns` (dataset-qualified, e.g. `tpcds_customer.columns`, + where a table name is shared across datasets). -4. **`run-version.sh [image]`** — starts the server, creates the - tables, loads each Native file with the simplest possible - `clickhouse-client INSERT … FORMAT Native`, then times every query in - `queries/{mgbench,ssb,hits,taxi}.sql` (`TRIES` runs each, dropping the page - cache between queries) and writes `results/.json`. +4. **`run-version.sh [image]`** — starts the server, creates each + dataset's tables **in its own database** (so same-named tables like TPC-H and + TPC-DS `customer` don't collide), loads each Native file with the simplest + possible `clickhouse-client INSERT … FORMAT Native`, then times every query in + `queries/{mgbench,ssb,hits,tpch,tpcds,coffeeshop,taxi}.sql` (`TRIES` runs each, + dropping the page cache between queries) and writes `results/.json`. 5. **`run-all.sh`** — runs `run-version.sh` for every selected version. @@ -93,7 +112,7 @@ that self-terminates and sends its result to the sink: ```bash ./run-benchmark.sh 1.1.54378 # one version on a c7a.4xlarge machine=c6a.metal ./run-benchmark.sh 24.8.1.1 -datasets="hits ssb mgbench taxi" ./run-benchmark.sh 25.1.1.1 # include taxi +datasets="hits ssb" ./run-benchmark.sh 25.1.1.1 # subset of datasets ./run-all-benchmarks.sh # one VM per runnable version ``` @@ -107,16 +126,24 @@ result JSON (enriched with the machine type, `kind:"versions-benchmark"`) plus the log to `sink.data` on play.clickhouse.com. A server-side materialized view turns those into the published report, exactly as the main benchmark does. -Notes: taxi is skipped by default (`datasets="hits ssb mgbench"`) — include it -only with a much larger `volume=`. While this branch is unmerged, pass -`branch=versions-benchmark-rework`. Only `hits` and `mgbench` are in the bucket -so far; missing dataset files are skipped (their queries report null). +Notes: all datasets run by default (`datasets="hits ssb mgbench tpch tpcds +coffeeshop taxi"`); the taxi table is narrowed to the five columns its queries +use (~15 GB), so it no longer dominates. Pass a subset via `datasets=` to skip +some. While this branch is unmerged, pass `branch=versions-benchmark-rework`. +Missing dataset files in the bucket are skipped (their queries report null). ## Query set -75 queries in a fixed order: mgbench (15) + Star Schema Benchmark (13) + -ClickBench/hits (43) + taxi (4). See `queries/*.sql`. Results are reported one -row per query, with `null` for queries a given version cannot run. +344 queries in a fixed order: mgbench (15) + Star Schema Benchmark (13) + +ClickBench/hits (43) + TPC-H (22) + TPC-DS (103) + Coffee Shop (17) + ontime (11) ++ UK price-paid (3) + Join Order Benchmark (113) + taxi (4). See `queries/*.sql`. +The TPC-H, TPC-DS and JOB queries are the official sets taken +from the ClickHouse repository (`tests/benchmarks/tpc-{h,ds}/queries`), flattened +to one line each (TPC-H Q15 is rewritten from its `CREATE VIEW` form into a single +`WITH` query; TPC-DS two-part queries become two lines, giving 103 statements from +the 99 queries). Their many joins, subqueries and window functions only run on +modern versions — older releases report `null`. Results are reported one row per +query, with `null` for queries a given version cannot run. The previous apt-based scripts are kept under `scripts/` and `unified_scripts/` for reference. diff --git a/versions/build-from-source/Dockerfile.ubuntu1604 b/versions/build-from-source/Dockerfile.ubuntu1604 index afcea42419..7c31351a83 100644 --- a/versions/build-from-source/Dockerfile.ubuntu1604 +++ b/versions/build-from-source/Dockerfile.ubuntu1604 @@ -37,14 +37,19 @@ RUN set -eu; \ && rm -rf /var/lib/apt/lists/* ENV CC=gcc-${GCC} CXX=g++-${GCC} DISABLE_MONGODB=1 +# TAG may be a tag (v1.1.54318-stable), a bare tag (53973) or a raw commit SHA +# (for the untagged monthly snapshots). Fetch it by ref/SHA rather than clone +# --branch, which only accepts named refs. ARG TAG -# The 2016 bare tags vendor contrib (no submodules). The later 1.1.x (>= ~54318, +# The 2016 tree vendors contrib (no submodules). The later 1.1.x (>= ~54318, # Dec 2017) use git submodules, and one of them (contrib/zookeeper at the dead # ClickHouse-Extras/zookeeper.git) 404s today. Init submodules one-by-one and # tolerate the dead one — cmake's find_zookeeper.cmake then falls back to the # system libzookeeper-mt-dev automatically. -RUN git clone --depth 1 --branch "${TAG}" https://github.com/ClickHouse/ClickHouse.git /src \ - && cd /src \ +RUN git init -q /src && cd /src \ + && git remote add origin https://github.com/ClickHouse/ClickHouse.git \ + && git fetch --depth 1 origin "${TAG}" \ + && git checkout -q --detach FETCH_HEAD \ && if [ -f .gitmodules ]; then \ git config -f .gitmodules --get-regexp '\.path$' | awk '{print $2}' | while read -r p; do \ git submodule update --init --recursive "$p" 2>/dev/null || echo "WARN: skipping unavailable submodule $p"; \ diff --git a/versions/build-from-source/monthly.tsv b/versions/build-from-source/monthly.tsv new file mode 100644 index 0000000000..bd52a1d21f --- /dev/null +++ b/versions/build-from-source/monthly.tsv @@ -0,0 +1,53 @@ +2016-05-01 2b1550105cec9ff8192606560931191d69101397 2016-04-28 +2016-04-01 f41bba57a546430ed2c3d3c5e97a599003a6889d 2016-04-01 +2016-03-01 5360c78806e043d0d2bf3de15a363f87fbdaf5f4 2016-03-01 +2016-02-01 21fb1cca7c1342f02cda0b8df08df08a737eb7ee 2016-01-30 +2016-01-01 a6b01ee987c44a8291c616ffdedb63677ef0780a 2015-12-30 +2015-12-01 a7387d9ce431a1f288d1a4898fa0c0c36c765abc 2015-11-30 +2015-11-01 b17cc7181edbb05637b23f2f632d44d092e276e5 2015-10-31 +2015-10-01 c915538fa788697feea7910c7de5339f6b5a2ce2 2015-09-30 +2015-09-01 bc5007fc36ba2a81a6b45b9e9b0b26ff09efa994 2015-08-31 +2015-08-01 3eb7c149aba7bc650e27cc40885cf29e3332c94b 2015-07-31 +2015-07-01 719f0ee89cc560a96bec8d527ff7316f13101b33 2015-06-30 +2015-06-01 d378c76964b58eae67fbe41fa9d54694b5e88f99 2015-05-31 +2015-05-01 9dfd271c684c7f7792751a9ea7c72c11604afda5 2015-05-01 +2015-04-01 54397c6c7a99cfa7cb293651356c8b65143669e1 2015-04-01 +2015-03-01 3e1dafe3cb96b69fc34df13cd10bdc79adfe2818 2015-02-28 +2015-02-01 bd51359819f6ade46cf5de2e22e1fafc1d2080fc 2015-02-01 +2015-01-01 43c75bb37b3b2f27d473296cc12d7e6314520505 2014-12-31 +2014-12-01 da4c4a05663581f9729ad1bd000481fbcd1a0353 2014-11-30 +2014-11-01 ec08b393dec6f513f13bcc8654055dea7069dc8b 2014-11-01 +2014-10-01 4b83a8d3b3af54e7a816330398dfc1b3a37d686b 2014-10-01 +2014-09-01 b5624cd57fdcc354dc31348da0cb1a332fb24345 2014-08-29 +2014-08-01 36b0355c6861d695836e45cec56d7bea7dc444ae 2014-08-01 +2014-07-01 cbab5fb19339775223d43f5c69060096aa03f830 2014-07-01 +2014-06-01 a4fba5c6b19ceddf0340184c9f224b4c08fb80fe 2014-05-30 +2014-05-01 4cee45e004f118bd8cf43f08a6b634021b106825 2014-04-30 +2014-04-01 c12d5231dd48ad2e82d4e5bfa62987b32dae8a51 2014-03-29 +2014-03-01 78e9b847e08b1ad50db5443dd896ad5e7100e01b 2014-03-01 +2014-02-01 82b98ffb6d88b4a30257f623e628ecbe48925436 2014-01-29 +2014-01-01 5d7fb8ecce5987e108afba878e77d5364a93d960 2013-12-30 +2013-12-01 ff7cd145ca21b225b9734e5c08e9984475fb6d68 2013-11-30 +2013-11-01 6a12f5a43a902f1b843922261a6acbed88e25881 2013-10-31 +2013-10-01 c084250925a3fd2e30241f8ee7fb12a40ecc3002 2013-09-30 +2013-09-01 81d9d1deaadc29badf8122b1bd24e7aef9f2192f 2013-08-31 +2013-08-01 0e96233d2b3c643e37fcc6302f090da4a442d3d6 2013-07-31 +2013-07-01 858b2805eb0eaea7efdf4c2409d0ccce9ec3ae1e 2013-06-30 +2013-06-01 9848a42c8241cbd2fb85ffc5fc217f773a63f59d 2013-05-31 +2013-05-01 da4454b46e583da4fa91f973b84cdb79cba2d90e 2013-04-30 +2013-04-01 1f375250d6ca9bf2bcf5c1afbf6c08165e6dd7ce 2013-03-31 +2013-03-01 ea816297c2ae16b50a20ebd684471a535b59e6b0 2013-02-28 +2013-02-01 b5937d0539a16754313c06d54b690d31d3f56561 2013-01-28 +2013-01-01 7b17b8f342adf339210d865f783bae4d1d5f6671 2012-12-29 +2012-12-01 914b41cf2f9bdcd79054d4466f1595a962f97053 2012-11-30 +2012-11-01 02b95a22975bf0d20cee6e6628d3e74aeac41e8d 2012-10-30 +2012-10-01 f86d5d4d7e7e781e86d176e59fb0d669dec2e1fc 2012-09-28 +2012-09-01 0652f9da9685041732d44d120da286a1a58c8ae4 2012-08-31 +2012-08-01 83337ec47416dc3166871561a54e3d52c57f1c52 2012-07-31 +2012-07-01 2c69e7eb4aaf8c82583520976e51cf6cbc7e467e 2012-06-25 +2012-06-01 0b5d5b6a52ab4dd30f2ca6106bb7efdd904f9ddd 2012-05-31 +2012-05-01 8b958c4f698830cbf22c038c9fb44616a331ed44 2012-04-14 +2012-04-01 26096423fe53dccc5559952515fe421563cd23af 2012-03-30 +2012-03-01 c90243f7fe778ce4524341e5daad2a936bb8564f 2012-02-27 +2012-02-01 635f1638e2c6d5d70b3f95042398abdd2798648c 2012-01-31 +2012-01-01 7182920cecd3ec7d1e6fffd64ec52679d4e111ef 2011-12-30 diff --git a/versions/cloud-init.sh.in b/versions/cloud-init.sh.in index 46b11f3d91..591b189467 100644 --- a/versions/cloud-init.sh.in +++ b/versions/cloud-init.sh.in @@ -39,6 +39,12 @@ for ds in ${DATASETS}; do hits) FILES="${FILES} hits.native.zst" ;; ssb) FILES="${FILES} ssb.native.zst" ;; mgbench) FILES="${FILES} mgbench1.native.zst mgbench2.native.zst mgbench3.native.zst" ;; + tpch) FILES="${FILES} tpch_nation.native.zst tpch_region.native.zst tpch_part.native.zst tpch_supplier.native.zst tpch_partsupp.native.zst tpch_customer.native.zst tpch_orders.native.zst tpch_lineitem.native.zst" ;; + tpcds) FILES="${FILES} tpcds_call_center.native.zst tpcds_catalog_page.native.zst tpcds_catalog_returns.native.zst tpcds_catalog_sales.native.zst tpcds_customer_address.native.zst tpcds_customer_demographics.native.zst tpcds_customer.native.zst tpcds_date_dim.native.zst tpcds_household_demographics.native.zst tpcds_income_band.native.zst tpcds_inventory.native.zst tpcds_item.native.zst tpcds_promotion.native.zst tpcds_reason.native.zst tpcds_ship_mode.native.zst tpcds_store_returns.native.zst tpcds_store_sales.native.zst tpcds_store.native.zst tpcds_time_dim.native.zst tpcds_warehouse.native.zst tpcds_web_page.native.zst tpcds_web_returns.native.zst tpcds_web_sales.native.zst tpcds_web_site.native.zst" ;; + coffeeshop) FILES="${FILES} coffeeshop_fact_sales.native.zst coffeeshop_dim_locations.native.zst coffeeshop_dim_products.native.zst" ;; + ontime) FILES="${FILES} ontime.native.zst" ;; + uk) FILES="${FILES} uk_price_paid.native.zst" ;; + job) FILES="${FILES} job_aka_name.native.zst job_aka_title.native.zst job_cast_info.native.zst job_char_name.native.zst job_comp_cast_type.native.zst job_company_name.native.zst job_company_type.native.zst job_complete_cast.native.zst job_info_type.native.zst job_keyword.native.zst job_kind_type.native.zst job_link_type.native.zst job_movie_companies.native.zst job_movie_info.native.zst job_movie_info_idx.native.zst job_movie_keyword.native.zst job_movie_link.native.zst job_name.native.zst job_person_info.native.zst job_role_type.native.zst job_title.native.zst" ;; taxi) FILES="${FILES} taxi.native.zst" ;; esac done diff --git a/versions/config/listen.xml b/versions/config/listen.xml index 78b75a29d4..1f321d1495 100644 --- a/versions/config/listen.xml +++ b/versions/config/listen.xml @@ -1,6 +1,6 @@ diff --git a/versions/create/create.sh b/versions/create/create.sh index 5c2f62ac2f..29dd79ba8f 100755 --- a/versions/create/create.sh +++ b/versions/create/create.sh @@ -1,9 +1,13 @@ #!/usr/bin/env bash -# Emit a CREATE TABLE statement for
tailored to ClickHouse . +# Emit a CREATE TABLE statement for
of , tailored to . # -# ./create.sh
+# ./create.sh
# -# Tables: hits | lineorder_flat | logs1 | logs2 | logs3 | trips +# Datasets: hits | ssb | mgbench | tpch | tpcds | coffeeshop | taxi +# Each dataset is loaded into its own database (named after the dataset), so +# tables with the same name across datasets (e.g. TPC-H and TPC-DS both have a +# `customer`) never collide. The statement here is unqualified; the runner +# creates it with `--database `. # # The same Native data files load into every version, so only the *engine* # clause changes with the version: @@ -12,14 +16,15 @@ # * The earliest 1.1.x releases (before custom partitioning landed) only # understand the legacy positional syntax, which needs a Date column: # ENGINE = MergeTree(, (), 8192) -# Every table therefore carries a Date column (EventDate / LO_ORDERDATE / -# pickup_date / the synthesised log_date) usable by the legacy engine. +# Every table therefore carries a Date column (a natural one where it exists, +# else a synthesised constant synth_date) usable by the legacy engine. set -euo pipefail HERE="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" -VERSION="${1:?usage: create.sh
}" -TABLE="${2:?usage: create.sh
}" +VERSION="${1:?usage: create.sh
}" +DATASET="${2:?usage: create.sh
}" +TABLE="${3:?usage: create.sh
}" # Custom-partitioning (new) syntax landed in 1.1.54310; everything from 18.x # on supports it. Older 1.1.x builds get the legacy positional engine. @@ -37,18 +42,75 @@ new_syntax() { fi } -# Per-table Date column and primary key. +# `customer` exists in both TPC-H and TPC-DS with different schemas, so it is +# disambiguated by dataset (and its columns file is dataset-qualified below). +if [ "$TABLE" = "customer" ]; then + DATE_COL=synth_date + if [ "$DATASET" = "tpcds" ]; then ORDER_KEY="c_customer_sk"; else ORDER_KEY="c_custkey"; fi +else case "$TABLE" in hits) DATE_COL=EventDate; ORDER_KEY="CounterID, EventDate, intHash32(UserID), EventTime" ;; lineorder_flat) DATE_COL=LO_ORDERDATE; ORDER_KEY="LO_ORDERDATE, LO_ORDERKEY" ;; logs1) DATE_COL=log_date; ORDER_KEY="machine_group, machine_name, log_time" ;; logs2) DATE_COL=log_date; ORDER_KEY="log_time" ;; logs3) DATE_COL=log_date; ORDER_KEY="event_type, log_time" ;; - trips) DATE_COL=pickup_date; ORDER_KEY="pickup_datetime" ;; + trips) DATE_COL=pickup_date; ORDER_KEY="cab_type, passenger_count" ;; + ontime) DATE_COL=FlightDate; ORDER_KEY="Year, Month, FlightDate, IATA_CODE_Reporting_Airline" ;; + uk_price_paid) DATE_COL=date; ORDER_KEY="postcode1, postcode2, addr1, addr2" ;; + # TPC-H. Dimension tables have no date, so they carry a synthesised constant + # synth_date usable by the legacy positional engine; the two fact tables use + # their natural date (o_orderdate / l_shipdate). + nation) DATE_COL=synth_date; ORDER_KEY="n_nationkey" ;; + region) DATE_COL=synth_date; ORDER_KEY="r_regionkey" ;; + part) DATE_COL=synth_date; ORDER_KEY="p_partkey" ;; + supplier) DATE_COL=synth_date; ORDER_KEY="s_suppkey" ;; + partsupp) DATE_COL=synth_date; ORDER_KEY="ps_partkey, ps_suppkey" ;; + orders) DATE_COL=o_orderdate; ORDER_KEY="o_orderkey" ;; + lineitem) DATE_COL=l_shipdate; ORDER_KEY="l_orderkey, l_linenumber" ;; + # TPC-DS. Only Decimal was downgraded (-> Float64); all 24 tables carry a + # constant synth_date for the legacy engine, with the spec primary key as + # the sort key. + call_center) DATE_COL=synth_date; ORDER_KEY="cc_call_center_sk" ;; + catalog_page) DATE_COL=synth_date; ORDER_KEY="cp_catalog_page_sk" ;; + catalog_returns) DATE_COL=synth_date; ORDER_KEY="cr_item_sk, cr_order_number" ;; + catalog_sales) DATE_COL=synth_date; ORDER_KEY="cs_item_sk, cs_order_number" ;; + customer_address) DATE_COL=synth_date; ORDER_KEY="ca_address_sk" ;; + customer_demographics) DATE_COL=synth_date; ORDER_KEY="cd_demo_sk" ;; + date_dim) DATE_COL=synth_date; ORDER_KEY="d_date_sk" ;; + household_demographics) DATE_COL=synth_date; ORDER_KEY="hd_demo_sk" ;; + income_band) DATE_COL=synth_date; ORDER_KEY="ib_income_band_sk" ;; + inventory) DATE_COL=synth_date; ORDER_KEY="inv_date_sk, inv_item_sk, inv_warehouse_sk" ;; + item) DATE_COL=synth_date; ORDER_KEY="i_item_sk" ;; + promotion) DATE_COL=synth_date; ORDER_KEY="p_promo_sk" ;; + reason) DATE_COL=synth_date; ORDER_KEY="r_reason_sk" ;; + ship_mode) DATE_COL=synth_date; ORDER_KEY="sm_ship_mode_sk" ;; + store_returns) DATE_COL=synth_date; ORDER_KEY="sr_item_sk, sr_ticket_number" ;; + store_sales) DATE_COL=synth_date; ORDER_KEY="ss_item_sk, ss_ticket_number" ;; + store) DATE_COL=synth_date; ORDER_KEY="s_store_sk" ;; + time_dim) DATE_COL=synth_date; ORDER_KEY="t_time_sk" ;; + warehouse) DATE_COL=synth_date; ORDER_KEY="w_warehouse_sk" ;; + web_page) DATE_COL=synth_date; ORDER_KEY="wp_web_page_sk" ;; + web_returns) DATE_COL=synth_date; ORDER_KEY="wr_item_sk, wr_order_number" ;; + web_sales) DATE_COL=synth_date; ORDER_KEY="ws_item_sk, ws_order_number" ;; + web_site) DATE_COL=synth_date; ORDER_KEY="web_site_sk" ;; + # Coffee Shop benchmark. fact_sales has a natural order_date; the two small + # dimensions carry synth_date. + fact_sales) DATE_COL=order_date; ORDER_KEY="order_id" ;; + dim_locations) DATE_COL=synth_date; ORDER_KEY="record_id" ;; + dim_products) DATE_COL=synth_date; ORDER_KEY="record_id" ;; + # Join Order Benchmark (IMDB). No date columns anywhere, so all 21 tables + # carry a constant synth_date; every table's primary key is `id`. + aka_name|aka_title|cast_info|char_name|comp_cast_type|company_name|company_type|complete_cast|info_type|keyword|kind_type|link_type|movie_companies|movie_info|movie_info_idx|movie_keyword|movie_link|name|person_info|role_type|title) + DATE_COL=synth_date; ORDER_KEY="id" ;; *) echo "unknown table: $TABLE" >&2; exit 1 ;; esac +fi -COLUMNS="$(cat "${HERE}/schema/${TABLE}.columns")" +# Columns file, dataset-qualified where a table name is shared across datasets +# (e.g. schema/tpcds_customer.columns), otherwise the plain schema/
.columns. +COLUMNS_FILE="${HERE}/schema/${DATASET}_${TABLE}.columns" +[ -f "${COLUMNS_FILE}" ] || COLUMNS_FILE="${HERE}/schema/${TABLE}.columns" +COLUMNS="$(cat "${COLUMNS_FILE}")" echo "DROP TABLE IF EXISTS ${TABLE};" if new_syntax; then diff --git a/versions/create/schema/aka_name.columns b/versions/create/schema/aka_name.columns new file mode 100644 index 0000000000..467c082c46 --- /dev/null +++ b/versions/create/schema/aka_name.columns @@ -0,0 +1,9 @@ +synth_date Date, +id Int32, +person_id Int32, +name String, +imdb_index String, +name_pcode_cf String, +name_pcode_nf String, +surname_pcode String, +md5sum String diff --git a/versions/create/schema/aka_title.columns b/versions/create/schema/aka_title.columns new file mode 100644 index 0000000000..3d197dc0be --- /dev/null +++ b/versions/create/schema/aka_title.columns @@ -0,0 +1,13 @@ +synth_date Date, +id Int32, +movie_id Int32, +title String, +imdb_index String, +kind_id Int32, +production_year Int32, +phonetic_code String, +episode_of_id Int32, +season_nr Int32, +episode_nr Int32, +note String, +md5sum String diff --git a/versions/create/schema/call_center.columns b/versions/create/schema/call_center.columns new file mode 100644 index 0000000000..8968f02238 --- /dev/null +++ b/versions/create/schema/call_center.columns @@ -0,0 +1,32 @@ +synth_date Date, +cc_call_center_sk Int64, +cc_call_center_id FixedString(16), +cc_rec_start_date Date, +cc_rec_end_date Date, +cc_closed_date_sk UInt32, +cc_open_date_sk UInt32, +cc_name String, +cc_class String, +cc_employees Int64, +cc_sq_ft Int64, +cc_hours FixedString(20), +cc_manager String, +cc_mkt_id Int64, +cc_mkt_class FixedString(50), +cc_mkt_desc String, +cc_market_manager String, +cc_division Int64, +cc_division_name String, +cc_company Int64, +cc_company_name FixedString(50), +cc_street_number FixedString(10), +cc_street_name String, +cc_street_type FixedString(15), +cc_suite_number FixedString(10), +cc_city String, +cc_county String, +cc_state FixedString(2), +cc_zip FixedString(10), +cc_country String, +cc_gmt_offset Float64, +cc_tax_percentage Float64 diff --git a/versions/create/schema/cast_info.columns b/versions/create/schema/cast_info.columns new file mode 100644 index 0000000000..91c6eda4c7 --- /dev/null +++ b/versions/create/schema/cast_info.columns @@ -0,0 +1,8 @@ +synth_date Date, +id Int32, +person_id Int32, +movie_id Int32, +person_role_id Int32, +note String, +nr_order Int32, +role_id Int32 diff --git a/versions/create/schema/catalog_page.columns b/versions/create/schema/catalog_page.columns new file mode 100644 index 0000000000..a1c7c21b30 --- /dev/null +++ b/versions/create/schema/catalog_page.columns @@ -0,0 +1,10 @@ +synth_date Date, +cp_catalog_page_sk Int64, +cp_catalog_page_id FixedString(16), +cp_start_date_sk UInt32, +cp_end_date_sk UInt32, +cp_department String, +cp_catalog_number Int64, +cp_catalog_page_number Int64, +cp_description String, +cp_type String diff --git a/versions/create/schema/catalog_returns.columns b/versions/create/schema/catalog_returns.columns new file mode 100644 index 0000000000..54ae1a28e0 --- /dev/null +++ b/versions/create/schema/catalog_returns.columns @@ -0,0 +1,28 @@ +synth_date Date, +cr_returned_date_sk UInt32, +cr_returned_time_sk UInt32, +cr_item_sk Int64, +cr_refunded_customer_sk Int64, +cr_refunded_cdemo_sk Int64, +cr_refunded_hdemo_sk Int64, +cr_refunded_addr_sk Int64, +cr_returning_customer_sk Int64, +cr_returning_cdemo_sk Int64, +cr_returning_hdemo_sk Int64, +cr_returning_addr_sk Int64, +cr_call_center_sk Int64, +cr_catalog_page_sk Int64, +cr_ship_mode_sk Int64, +cr_warehouse_sk Int64, +cr_reason_sk Int64, +cr_order_number Int64, +cr_return_quantity Int64, +cr_return_amount Float64, +cr_return_tax Float64, +cr_return_amt_inc_tax Float64, +cr_fee Float64, +cr_return_ship_cost Float64, +cr_refunded_cash Float64, +cr_reversed_charge Float64, +cr_store_credit Float64, +cr_net_loss Float64 diff --git a/versions/create/schema/catalog_sales.columns b/versions/create/schema/catalog_sales.columns new file mode 100644 index 0000000000..499963812d --- /dev/null +++ b/versions/create/schema/catalog_sales.columns @@ -0,0 +1,35 @@ +synth_date Date, +cs_sold_date_sk UInt32, +cs_sold_time_sk UInt32, +cs_ship_date_sk UInt32, +cs_bill_customer_sk Int64, +cs_bill_cdemo_sk Int64, +cs_bill_hdemo_sk Int64, +cs_bill_addr_sk Int64, +cs_ship_customer_sk Int64, +cs_ship_cdemo_sk Int64, +cs_ship_hdemo_sk Int64, +cs_ship_addr_sk Int64, +cs_call_center_sk Int64, +cs_catalog_page_sk Int64, +cs_ship_mode_sk Int64, +cs_warehouse_sk Int64, +cs_item_sk Int64, +cs_promo_sk Int64, +cs_order_number Int64, +cs_quantity Int64, +cs_wholesale_cost Float64, +cs_list_price Float64, +cs_sales_price Float64, +cs_ext_discount_amt Float64, +cs_ext_sales_price Float64, +cs_ext_wholesale_cost Float64, +cs_ext_list_price Float64, +cs_ext_tax Float64, +cs_coupon_amt Float64, +cs_ext_ship_cost Float64, +cs_net_paid Float64, +cs_net_paid_inc_tax Float64, +cs_net_paid_inc_ship Float64, +cs_net_paid_inc_ship_tax Float64, +cs_net_profit Float64 diff --git a/versions/create/schema/char_name.columns b/versions/create/schema/char_name.columns new file mode 100644 index 0000000000..8117f464cd --- /dev/null +++ b/versions/create/schema/char_name.columns @@ -0,0 +1,8 @@ +synth_date Date, +id Int32, +name String, +imdb_index String, +imdb_id Int32, +name_pcode_nf String, +surname_pcode String, +md5sum String diff --git a/versions/create/schema/comp_cast_type.columns b/versions/create/schema/comp_cast_type.columns new file mode 100644 index 0000000000..6cb864ff0e --- /dev/null +++ b/versions/create/schema/comp_cast_type.columns @@ -0,0 +1,3 @@ +synth_date Date, +id Int32, +kind String diff --git a/versions/create/schema/company_name.columns b/versions/create/schema/company_name.columns new file mode 100644 index 0000000000..d4846949e8 --- /dev/null +++ b/versions/create/schema/company_name.columns @@ -0,0 +1,8 @@ +synth_date Date, +id Int32, +name String, +country_code String, +imdb_id Int32, +name_pcode_nf String, +name_pcode_sf String, +md5sum String diff --git a/versions/create/schema/company_type.columns b/versions/create/schema/company_type.columns new file mode 100644 index 0000000000..6cb864ff0e --- /dev/null +++ b/versions/create/schema/company_type.columns @@ -0,0 +1,3 @@ +synth_date Date, +id Int32, +kind String diff --git a/versions/create/schema/complete_cast.columns b/versions/create/schema/complete_cast.columns new file mode 100644 index 0000000000..713b866ccb --- /dev/null +++ b/versions/create/schema/complete_cast.columns @@ -0,0 +1,5 @@ +synth_date Date, +id Int32, +movie_id Int32, +subject_id Int32, +status_id Int32 diff --git a/versions/create/schema/customer.columns b/versions/create/schema/customer.columns new file mode 100644 index 0000000000..6bbf483bb7 --- /dev/null +++ b/versions/create/schema/customer.columns @@ -0,0 +1,9 @@ +synth_date Date, +c_custkey UInt32, +c_name String, +c_address String, +c_nationkey UInt32, +c_phone FixedString(15), +c_acctbal Float64, +c_mktsegment FixedString(10), +c_comment String diff --git a/versions/create/schema/customer_address.columns b/versions/create/schema/customer_address.columns new file mode 100644 index 0000000000..8a0f11af93 --- /dev/null +++ b/versions/create/schema/customer_address.columns @@ -0,0 +1,14 @@ +synth_date Date, +ca_address_sk Int64, +ca_address_id FixedString(16), +ca_street_number FixedString(10), +ca_street_name String, +ca_street_type FixedString(15), +ca_suite_number FixedString(10), +ca_city String, +ca_county String, +ca_state FixedString(2), +ca_zip FixedString(10), +ca_country String, +ca_gmt_offset Float64, +ca_location_type FixedString(20) diff --git a/versions/create/schema/customer_demographics.columns b/versions/create/schema/customer_demographics.columns new file mode 100644 index 0000000000..8ae86e60b7 --- /dev/null +++ b/versions/create/schema/customer_demographics.columns @@ -0,0 +1,10 @@ +synth_date Date, +cd_demo_sk Int64, +cd_gender FixedString(1), +cd_marital_status FixedString(1), +cd_education_status FixedString(20), +cd_purchase_estimate Int64, +cd_credit_rating FixedString(10), +cd_dep_count Int64, +cd_dep_employed_count Int64, +cd_dep_college_count Int64 diff --git a/versions/create/schema/date_dim.columns b/versions/create/schema/date_dim.columns new file mode 100644 index 0000000000..105e757e26 --- /dev/null +++ b/versions/create/schema/date_dim.columns @@ -0,0 +1,29 @@ +synth_date Date, +d_date_sk UInt32, +d_date_id FixedString(16), +d_date Date, +d_month_seq Int64, +d_week_seq Int64, +d_quarter_seq Int64, +d_year Int64, +d_dow Int64, +d_moy Int64, +d_dom Int64, +d_qoy Int64, +d_fy_year Int64, +d_fy_quarter_seq Int64, +d_fy_week_seq Int64, +d_day_name FixedString(9), +d_quarter_name FixedString(6), +d_holiday FixedString(1), +d_weekend FixedString(1), +d_following_holiday FixedString(1), +d_first_dom Int64, +d_last_dom Int64, +d_same_day_ly Int64, +d_same_day_lq Int64, +d_current_day FixedString(1), +d_current_week FixedString(1), +d_current_month FixedString(1), +d_current_quarter FixedString(1), +d_current_year FixedString(1) diff --git a/versions/create/schema/dim_locations.columns b/versions/create/schema/dim_locations.columns new file mode 100644 index 0000000000..21bc10c35e --- /dev/null +++ b/versions/create/schema/dim_locations.columns @@ -0,0 +1,7 @@ +synth_date Date, +record_id String, +location_id String, +city String, +state String, +country String, +region String diff --git a/versions/create/schema/dim_products.columns b/versions/create/schema/dim_products.columns new file mode 100644 index 0000000000..828f4b0496 --- /dev/null +++ b/versions/create/schema/dim_products.columns @@ -0,0 +1,10 @@ +synth_date Date, +record_id String, +product_id String, +name String, +category String, +subcategory String, +standard_cost Float64, +standard_price Float64, +from_date Date, +to_date Date diff --git a/versions/create/schema/fact_sales.columns b/versions/create/schema/fact_sales.columns new file mode 100644 index 0000000000..ad37a0c37b --- /dev/null +++ b/versions/create/schema/fact_sales.columns @@ -0,0 +1,12 @@ +order_id String, +order_date Date, +time_of_day String, +season String, +month Int32, +location_id String, +region String, +product_name String, +quantity Int32, +sales_amount Float64, +discount_percentage Int32, +product_id String diff --git a/versions/create/schema/household_demographics.columns b/versions/create/schema/household_demographics.columns new file mode 100644 index 0000000000..ebaa175cc6 --- /dev/null +++ b/versions/create/schema/household_demographics.columns @@ -0,0 +1,6 @@ +synth_date Date, +hd_demo_sk Int64, +hd_income_band_sk Int64, +hd_buy_potential FixedString(15), +hd_dep_count Int64, +hd_vehicle_count Int64 diff --git a/versions/create/schema/income_band.columns b/versions/create/schema/income_band.columns new file mode 100644 index 0000000000..73bdbcdb9c --- /dev/null +++ b/versions/create/schema/income_band.columns @@ -0,0 +1,4 @@ +synth_date Date, +ib_income_band_sk Int64, +ib_lower_bound Int64, +ib_upper_bound Int64 diff --git a/versions/create/schema/info_type.columns b/versions/create/schema/info_type.columns new file mode 100644 index 0000000000..79a7a29a8a --- /dev/null +++ b/versions/create/schema/info_type.columns @@ -0,0 +1,3 @@ +synth_date Date, +id Int32, +info String diff --git a/versions/create/schema/inventory.columns b/versions/create/schema/inventory.columns new file mode 100644 index 0000000000..9d6208a7ae --- /dev/null +++ b/versions/create/schema/inventory.columns @@ -0,0 +1,5 @@ +synth_date Date, +inv_date_sk UInt32, +inv_item_sk Int64, +inv_warehouse_sk Int64, +inv_quantity_on_hand Int64 diff --git a/versions/create/schema/item.columns b/versions/create/schema/item.columns new file mode 100644 index 0000000000..d6a0c4b6fc --- /dev/null +++ b/versions/create/schema/item.columns @@ -0,0 +1,23 @@ +synth_date Date, +i_item_sk Int64, +i_item_id FixedString(16), +i_rec_start_date Date, +i_rec_end_date Date, +i_item_desc String, +i_current_price Float64, +i_wholesale_cost Float64, +i_brand_id Int64, +i_brand FixedString(50), +i_class_id Int64, +i_class FixedString(50), +i_category_id Int64, +i_category FixedString(50), +i_manufact_id Int64, +i_manufact FixedString(50), +i_size FixedString(20), +i_formulation FixedString(20), +i_color FixedString(20), +i_units FixedString(10), +i_container FixedString(10), +i_manager_id Int64, +i_product_name FixedString(50) diff --git a/versions/create/schema/keyword.columns b/versions/create/schema/keyword.columns new file mode 100644 index 0000000000..deb04c0581 --- /dev/null +++ b/versions/create/schema/keyword.columns @@ -0,0 +1,4 @@ +synth_date Date, +id Int32, +keyword String, +phonetic_code String diff --git a/versions/create/schema/kind_type.columns b/versions/create/schema/kind_type.columns new file mode 100644 index 0000000000..6cb864ff0e --- /dev/null +++ b/versions/create/schema/kind_type.columns @@ -0,0 +1,3 @@ +synth_date Date, +id Int32, +kind String diff --git a/versions/create/schema/lineitem.columns b/versions/create/schema/lineitem.columns new file mode 100644 index 0000000000..5f67a7f9e9 --- /dev/null +++ b/versions/create/schema/lineitem.columns @@ -0,0 +1,16 @@ +l_orderkey UInt32, +l_partkey UInt32, +l_suppkey UInt32, +l_linenumber Int32, +l_quantity Float64, +l_extendedprice Float64, +l_discount Float64, +l_tax Float64, +l_returnflag FixedString(1), +l_linestatus FixedString(1), +l_shipdate Date, +l_commitdate Date, +l_receiptdate Date, +l_shipinstruct FixedString(25), +l_shipmode FixedString(10), +l_comment String diff --git a/versions/create/schema/link_type.columns b/versions/create/schema/link_type.columns new file mode 100644 index 0000000000..53bff558b3 --- /dev/null +++ b/versions/create/schema/link_type.columns @@ -0,0 +1,3 @@ +synth_date Date, +id Int32, +link String diff --git a/versions/create/schema/movie_companies.columns b/versions/create/schema/movie_companies.columns new file mode 100644 index 0000000000..f6de29f7d6 --- /dev/null +++ b/versions/create/schema/movie_companies.columns @@ -0,0 +1,6 @@ +synth_date Date, +id Int32, +movie_id Int32, +company_id Int32, +company_type_id Int32, +note String diff --git a/versions/create/schema/movie_info.columns b/versions/create/schema/movie_info.columns new file mode 100644 index 0000000000..a3fc5fd1c1 --- /dev/null +++ b/versions/create/schema/movie_info.columns @@ -0,0 +1,6 @@ +synth_date Date, +id Int32, +movie_id Int32, +info_type_id Int32, +info String, +note String diff --git a/versions/create/schema/movie_info_idx.columns b/versions/create/schema/movie_info_idx.columns new file mode 100644 index 0000000000..a3fc5fd1c1 --- /dev/null +++ b/versions/create/schema/movie_info_idx.columns @@ -0,0 +1,6 @@ +synth_date Date, +id Int32, +movie_id Int32, +info_type_id Int32, +info String, +note String diff --git a/versions/create/schema/movie_keyword.columns b/versions/create/schema/movie_keyword.columns new file mode 100644 index 0000000000..5c230d6efc --- /dev/null +++ b/versions/create/schema/movie_keyword.columns @@ -0,0 +1,4 @@ +synth_date Date, +id Int32, +movie_id Int32, +keyword_id Int32 diff --git a/versions/create/schema/movie_link.columns b/versions/create/schema/movie_link.columns new file mode 100644 index 0000000000..4292549fac --- /dev/null +++ b/versions/create/schema/movie_link.columns @@ -0,0 +1,5 @@ +synth_date Date, +id Int32, +movie_id Int32, +linked_movie_id Int32, +link_type_id Int32 diff --git a/versions/create/schema/name.columns b/versions/create/schema/name.columns new file mode 100644 index 0000000000..e05d6ace9a --- /dev/null +++ b/versions/create/schema/name.columns @@ -0,0 +1,10 @@ +synth_date Date, +id Int32, +name String, +imdb_index String, +imdb_id Int32, +gender String, +name_pcode_cf String, +name_pcode_nf String, +surname_pcode String, +md5sum String diff --git a/versions/create/schema/nation.columns b/versions/create/schema/nation.columns new file mode 100644 index 0000000000..b7e85c2240 --- /dev/null +++ b/versions/create/schema/nation.columns @@ -0,0 +1,5 @@ +synth_date Date, +n_nationkey UInt32, +n_name FixedString(25), +n_regionkey UInt32, +n_comment String diff --git a/versions/create/schema/ontime.columns b/versions/create/schema/ontime.columns new file mode 100644 index 0000000000..c7f8911d7e --- /dev/null +++ b/versions/create/schema/ontime.columns @@ -0,0 +1,12 @@ +Year UInt16, +Month UInt8, +DayOfWeek UInt8, +FlightDate Date, +IATA_CODE_Reporting_Airline String, +Origin FixedString(5), +OriginCityName String, +OriginState FixedString(2), +DestCityName String, +DestState FixedString(2), +DepDelay Int32, +ArrDelayMinutes Int32 diff --git a/versions/create/schema/orders.columns b/versions/create/schema/orders.columns new file mode 100644 index 0000000000..ebfb6fbc7b --- /dev/null +++ b/versions/create/schema/orders.columns @@ -0,0 +1,9 @@ +o_orderkey UInt32, +o_custkey UInt32, +o_orderstatus FixedString(1), +o_totalprice Float64, +o_orderdate Date, +o_orderpriority FixedString(15), +o_clerk FixedString(15), +o_shippriority Int32, +o_comment String diff --git a/versions/create/schema/part.columns b/versions/create/schema/part.columns new file mode 100644 index 0000000000..3fd02d5cbe --- /dev/null +++ b/versions/create/schema/part.columns @@ -0,0 +1,10 @@ +synth_date Date, +p_partkey UInt32, +p_name String, +p_mfgr FixedString(25), +p_brand FixedString(10), +p_type String, +p_size Int32, +p_container FixedString(10), +p_retailprice Float64, +p_comment String diff --git a/versions/create/schema/partsupp.columns b/versions/create/schema/partsupp.columns new file mode 100644 index 0000000000..a1bb251d62 --- /dev/null +++ b/versions/create/schema/partsupp.columns @@ -0,0 +1,6 @@ +synth_date Date, +ps_partkey UInt32, +ps_suppkey UInt32, +ps_availqty Int32, +ps_supplycost Float64, +ps_comment String diff --git a/versions/create/schema/person_info.columns b/versions/create/schema/person_info.columns new file mode 100644 index 0000000000..aacc51961e --- /dev/null +++ b/versions/create/schema/person_info.columns @@ -0,0 +1,6 @@ +synth_date Date, +id Int32, +person_id Int32, +info_type_id Int32, +info String, +note String diff --git a/versions/create/schema/promotion.columns b/versions/create/schema/promotion.columns new file mode 100644 index 0000000000..8af12edf93 --- /dev/null +++ b/versions/create/schema/promotion.columns @@ -0,0 +1,20 @@ +synth_date Date, +p_promo_sk Int64, +p_promo_id FixedString(16), +p_start_date_sk UInt32, +p_end_date_sk UInt32, +p_item_sk Int64, +p_cost Float64, +p_response_target Int64, +p_promo_name FixedString(50), +p_channel_dmail FixedString(1), +p_channel_email FixedString(1), +p_channel_catalog FixedString(1), +p_channel_tv FixedString(1), +p_channel_radio FixedString(1), +p_channel_press FixedString(1), +p_channel_event FixedString(1), +p_channel_demo FixedString(1), +p_channel_details String, +p_purpose FixedString(15), +p_discount_active FixedString(1) diff --git a/versions/create/schema/reason.columns b/versions/create/schema/reason.columns new file mode 100644 index 0000000000..4f84582620 --- /dev/null +++ b/versions/create/schema/reason.columns @@ -0,0 +1,4 @@ +synth_date Date, +r_reason_sk Int64, +r_reason_id FixedString(16), +r_reason_desc FixedString(100) diff --git a/versions/create/schema/region.columns b/versions/create/schema/region.columns new file mode 100644 index 0000000000..011653dee3 --- /dev/null +++ b/versions/create/schema/region.columns @@ -0,0 +1,4 @@ +synth_date Date, +r_regionkey UInt32, +r_name FixedString(25), +r_comment String diff --git a/versions/create/schema/role_type.columns b/versions/create/schema/role_type.columns new file mode 100644 index 0000000000..215744e024 --- /dev/null +++ b/versions/create/schema/role_type.columns @@ -0,0 +1,3 @@ +synth_date Date, +id Int32, +role String diff --git a/versions/create/schema/ship_mode.columns b/versions/create/schema/ship_mode.columns new file mode 100644 index 0000000000..49168fb54a --- /dev/null +++ b/versions/create/schema/ship_mode.columns @@ -0,0 +1,7 @@ +synth_date Date, +sm_ship_mode_sk Int64, +sm_ship_mode_id FixedString(16), +sm_type FixedString(30), +sm_code FixedString(10), +sm_carrier FixedString(20), +sm_contract FixedString(20) diff --git a/versions/create/schema/store.columns b/versions/create/schema/store.columns new file mode 100644 index 0000000000..d759c41201 --- /dev/null +++ b/versions/create/schema/store.columns @@ -0,0 +1,30 @@ +synth_date Date, +s_store_sk Int64, +s_store_id FixedString(16), +s_rec_start_date Date, +s_rec_end_date Date, +s_closed_date_sk UInt32, +s_store_name String, +s_number_employees Int64, +s_floor_space Int64, +s_hours FixedString(20), +s_manager String, +s_market_id Int64, +s_geography_class String, +s_market_desc String, +s_market_manager String, +s_division_id Int64, +s_division_name String, +s_company_id Int64, +s_company_name String, +s_street_number String, +s_street_name String, +s_street_type FixedString(15), +s_suite_number FixedString(10), +s_city String, +s_county String, +s_state FixedString(2), +s_zip FixedString(10), +s_country String, +s_gmt_offset Float64, +s_tax_percentage Float64 diff --git a/versions/create/schema/store_returns.columns b/versions/create/schema/store_returns.columns new file mode 100644 index 0000000000..ad4ebe5e3f --- /dev/null +++ b/versions/create/schema/store_returns.columns @@ -0,0 +1,21 @@ +synth_date Date, +sr_returned_date_sk UInt32, +sr_return_time_sk UInt32, +sr_item_sk Int64, +sr_customer_sk Int64, +sr_cdemo_sk Int64, +sr_hdemo_sk Int64, +sr_addr_sk Int64, +sr_store_sk Int64, +sr_reason_sk Int64, +sr_ticket_number Int64, +sr_return_quantity Int64, +sr_return_amt Float64, +sr_return_tax Float64, +sr_return_amt_inc_tax Float64, +sr_fee Float64, +sr_return_ship_cost Float64, +sr_refunded_cash Float64, +sr_reversed_charge Float64, +sr_store_credit Float64, +sr_net_loss Float64 diff --git a/versions/create/schema/store_sales.columns b/versions/create/schema/store_sales.columns new file mode 100644 index 0000000000..52f70a0f21 --- /dev/null +++ b/versions/create/schema/store_sales.columns @@ -0,0 +1,24 @@ +synth_date Date, +ss_sold_date_sk UInt32, +ss_sold_time_sk UInt32, +ss_item_sk Int64, +ss_customer_sk Int64, +ss_cdemo_sk Int64, +ss_hdemo_sk Int64, +ss_addr_sk Int64, +ss_store_sk Int64, +ss_promo_sk Int64, +ss_ticket_number Int64, +ss_quantity Int64, +ss_wholesale_cost Float64, +ss_list_price Float64, +ss_sales_price Float64, +ss_ext_discount_amt Float64, +ss_ext_sales_price Float64, +ss_ext_wholesale_cost Float64, +ss_ext_list_price Float64, +ss_ext_tax Float64, +ss_coupon_amt Float64, +ss_net_paid Float64, +ss_net_paid_inc_tax Float64, +ss_net_profit Float64 diff --git a/versions/create/schema/supplier.columns b/versions/create/schema/supplier.columns new file mode 100644 index 0000000000..c4f5928fe9 --- /dev/null +++ b/versions/create/schema/supplier.columns @@ -0,0 +1,8 @@ +synth_date Date, +s_suppkey UInt32, +s_name FixedString(25), +s_address String, +s_nationkey UInt32, +s_phone FixedString(15), +s_acctbal Float64, +s_comment String diff --git a/versions/create/schema/time_dim.columns b/versions/create/schema/time_dim.columns new file mode 100644 index 0000000000..5ccd2e5cdd --- /dev/null +++ b/versions/create/schema/time_dim.columns @@ -0,0 +1,11 @@ +synth_date Date, +t_time_sk UInt32, +t_time_id FixedString(16), +t_time Int64, +t_hour Int64, +t_minute Int64, +t_second Int64, +t_am_pm FixedString(2), +t_shift FixedString(20), +t_sub_shift FixedString(20), +t_meal_time FixedString(20) diff --git a/versions/create/schema/title.columns b/versions/create/schema/title.columns new file mode 100644 index 0000000000..a49ac3dab5 --- /dev/null +++ b/versions/create/schema/title.columns @@ -0,0 +1,13 @@ +synth_date Date, +id Int32, +title String, +imdb_index String, +kind_id Int32, +production_year Int32, +imdb_id Int32, +phonetic_code String, +episode_of_id Int32, +season_nr Int32, +episode_nr Int32, +series_years String, +md5sum String diff --git a/versions/create/schema/tpcds_customer.columns b/versions/create/schema/tpcds_customer.columns new file mode 100644 index 0000000000..ed4d3781cb --- /dev/null +++ b/versions/create/schema/tpcds_customer.columns @@ -0,0 +1,19 @@ +synth_date Date, +c_customer_sk Int64, +c_customer_id FixedString(16), +c_current_cdemo_sk Int64, +c_current_hdemo_sk Int64, +c_current_addr_sk Int64, +c_first_shipto_date_sk UInt32, +c_first_sales_date_sk UInt32, +c_salutation FixedString(10), +c_first_name FixedString(20), +c_last_name FixedString(30), +c_preferred_cust_flag FixedString(1), +c_birth_day Int64, +c_birth_month Int64, +c_birth_year Int64, +c_birth_country String, +c_login FixedString(13), +c_email_address FixedString(50), +c_last_review_date_sk UInt32 diff --git a/versions/create/schema/trips.columns b/versions/create/schema/trips.columns index cf07783142..ef740051ae 100644 --- a/versions/create/schema/trips.columns +++ b/versions/create/schema/trips.columns @@ -1,52 +1,5 @@ pickup_date Date, -trip_id UInt32, -vendor_id String, -pickup_datetime DateTime, -dropoff_datetime DateTime, -store_and_fwd_flag String, -rate_code_id UInt8, -pickup_longitude Float64, -pickup_latitude Float64, -dropoff_longitude Float64, -dropoff_latitude Float64, +cab_type String, passenger_count UInt8, trip_distance Float64, -fare_amount Float32, -extra Float32, -mta_tax Float32, -tip_amount Float32, -tolls_amount Float32, -ehail_fee Float32, -improvement_surcharge Float32, -total_amount Float32, -payment_type String, -trip_type UInt8, -pickup String, -dropoff String, -cab_type String, -precipitation Float32, -snow_depth Float32, -snowfall Float32, -max_temperature Float32, -min_temperature Float32, -average_wind_speed Float32, -pickup_nyct2010_gid Int32, -pickup_ctlabel String, -pickup_borocode Int32, -pickup_boroname String, -pickup_ct2010 String, -pickup_boroct2010 String, -pickup_cdeligibil String, -pickup_ntacode String, -pickup_ntaname String, -pickup_puma Int32, -dropoff_nyct2010_gid Int32, -dropoff_ctlabel String, -dropoff_borocode Int32, -dropoff_boroname String, -dropoff_ct2010 String, -dropoff_boroct2010 String, -dropoff_cdeligibil String, -dropoff_ntacode String, -dropoff_ntaname String, -dropoff_puma Int32 +total_amount Float32 diff --git a/versions/create/schema/uk_price_paid.columns b/versions/create/schema/uk_price_paid.columns new file mode 100644 index 0000000000..177405f50e --- /dev/null +++ b/versions/create/schema/uk_price_paid.columns @@ -0,0 +1,14 @@ +price UInt32, +date Date, +postcode1 String, +postcode2 String, +type String, +is_new UInt8, +duration String, +addr1 String, +addr2 String, +street String, +locality String, +town String, +district String, +county String diff --git a/versions/create/schema/warehouse.columns b/versions/create/schema/warehouse.columns new file mode 100644 index 0000000000..3d9329a618 --- /dev/null +++ b/versions/create/schema/warehouse.columns @@ -0,0 +1,15 @@ +synth_date Date, +w_warehouse_sk Int64, +w_warehouse_id FixedString(16), +w_warehouse_name String, +w_warehouse_sq_ft Int64, +w_street_number FixedString(10), +w_street_name String, +w_street_type FixedString(15), +w_suite_number FixedString(10), +w_city String, +w_county String, +w_state FixedString(2), +w_zip FixedString(10), +w_country String, +w_gmt_offset Float64 diff --git a/versions/create/schema/web_page.columns b/versions/create/schema/web_page.columns new file mode 100644 index 0000000000..0419d35594 --- /dev/null +++ b/versions/create/schema/web_page.columns @@ -0,0 +1,15 @@ +synth_date Date, +wp_web_page_sk Int64, +wp_web_page_id FixedString(16), +wp_rec_start_date Date, +wp_rec_end_date Date, +wp_creation_date_sk UInt32, +wp_access_date_sk UInt32, +wp_autogen_flag FixedString(1), +wp_customer_sk Int64, +wp_url String, +wp_type FixedString(50), +wp_char_count Int64, +wp_link_count Int64, +wp_image_count Int64, +wp_max_ad_count Int64 diff --git a/versions/create/schema/web_returns.columns b/versions/create/schema/web_returns.columns new file mode 100644 index 0000000000..b3f11c78ff --- /dev/null +++ b/versions/create/schema/web_returns.columns @@ -0,0 +1,25 @@ +synth_date Date, +wr_returned_date_sk UInt32, +wr_returned_time_sk UInt32, +wr_item_sk Int64, +wr_refunded_customer_sk Int64, +wr_refunded_cdemo_sk Int64, +wr_refunded_hdemo_sk Int64, +wr_refunded_addr_sk Int64, +wr_returning_customer_sk Int64, +wr_returning_cdemo_sk Int64, +wr_returning_hdemo_sk Int64, +wr_returning_addr_sk Int64, +wr_web_page_sk Int64, +wr_reason_sk Int64, +wr_order_number Int64, +wr_return_quantity Int64, +wr_return_amt Float64, +wr_return_tax Float64, +wr_return_amt_inc_tax Float64, +wr_fee Float64, +wr_return_ship_cost Float64, +wr_refunded_cash Float64, +wr_reversed_charge Float64, +wr_account_credit Float64, +wr_net_loss Float64 diff --git a/versions/create/schema/web_sales.columns b/versions/create/schema/web_sales.columns new file mode 100644 index 0000000000..4acf829601 --- /dev/null +++ b/versions/create/schema/web_sales.columns @@ -0,0 +1,35 @@ +synth_date Date, +ws_sold_date_sk UInt32, +ws_sold_time_sk UInt32, +ws_ship_date_sk UInt32, +ws_item_sk Int64, +ws_bill_customer_sk Int64, +ws_bill_cdemo_sk Int64, +ws_bill_hdemo_sk Int64, +ws_bill_addr_sk Int64, +ws_ship_customer_sk Int64, +ws_ship_cdemo_sk Int64, +ws_ship_hdemo_sk Int64, +ws_ship_addr_sk Int64, +ws_web_page_sk Int64, +ws_web_site_sk Int64, +ws_ship_mode_sk Int64, +ws_warehouse_sk Int64, +ws_promo_sk Int64, +ws_order_number Int64, +ws_quantity Int64, +ws_wholesale_cost Float64, +ws_list_price Float64, +ws_sales_price Float64, +ws_ext_discount_amt Float64, +ws_ext_sales_price Float64, +ws_ext_wholesale_cost Float64, +ws_ext_list_price Float64, +ws_ext_tax Float64, +ws_coupon_amt Float64, +ws_ext_ship_cost Float64, +ws_net_paid Float64, +ws_net_paid_inc_tax Float64, +ws_net_paid_inc_ship Float64, +ws_net_paid_inc_ship_tax Float64, +ws_net_profit Float64 diff --git a/versions/create/schema/web_site.columns b/versions/create/schema/web_site.columns new file mode 100644 index 0000000000..331e115882 --- /dev/null +++ b/versions/create/schema/web_site.columns @@ -0,0 +1,27 @@ +synth_date Date, +web_site_sk Int64, +web_site_id FixedString(16), +web_rec_start_date Date, +web_rec_end_date Date, +web_name String, +web_open_date_sk UInt32, +web_close_date_sk UInt32, +web_class String, +web_manager String, +web_mkt_id Int64, +web_mkt_class String, +web_mkt_desc String, +web_market_manager String, +web_company_id Int64, +web_company_name FixedString(50), +web_street_number FixedString(10), +web_street_name String, +web_street_type FixedString(15), +web_suite_number FixedString(10), +web_city String, +web_county String, +web_state FixedString(2), +web_zip FixedString(10), +web_country String, +web_gmt_offset 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]; // end of data diff --git a/versions/prepare-data/coffeeshop.sh b/versions/prepare-data/coffeeshop.sh new file mode 100644 index 0000000000..4628448828 --- /dev/null +++ b/versions/prepare-data/coffeeshop.sh @@ -0,0 +1,44 @@ +#!/usr/bin/env bash +# Prepare the Coffee Shop benchmark dataset as oldest-ClickHouse-compatible +# Native files, from the published Iceberg tables in the public bucket +# (s3://clickhouse-datasets/coffeeshop/). Table definitions match the +# coffeeshop-benchmark repo (clickhouse-cloud/tables.sql). +# +# COFFEESHOP_SCALE selects the fact table (default 500m, the smallest of +# 500m/1b/5b). All types are already oldest-compatible (String/Int32/Float64/ +# Date); NULLs are replaced with defaults (COALESCE) so the non-Nullable columns +# load, and the two small dimensions carry a constant synth_date for the legacy +# MergeTree engine (fact_sales uses its natural order_date). The unused +# high-cardinality order_line_id column is dropped (no query references it), +# which roughly halves the fact table's size. + +set -euo pipefail +HERE="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" +CLICKHOUSE="${CLICKHOUSE:-$HOME/clickhouse}" +SCALE="${COFFEESHOP_SCALE:-500m}" +BUCKET="https://clickhouse-datasets.s3.amazonaws.com/coffeeshop" +command -v "${CLICKHOUSE}" >/dev/null 2>&1 || CLICKHOUSE=clickhouse + +# Read an Iceberg table from the public bucket and re-emit it as oldest- +# compatible Native, columns/order matching create/schema/
.columns. +emit() { + local out="$1" src="$2" sel="$3" + echo "coffeeshop: building ${out} from ${src}" + "${CLICKHOUSE}" local --max_memory_usage 0 \ + --query "SELECT ${sel} FROM icebergS3('${src}', NOSIGN) FORMAT Native" \ + | zstd -q -6 -T0 -c > "${HERE}/data/${out}" + echo " ${out}: $(du -h "${HERE}/data/${out}" | cut -f1)" +} + +D="CAST('2000-01-01' AS Date) AS synth_date" + +emit coffeeshop_dim_locations.native.zst "${BUCKET}/dim_locations/" \ +"${D}, CAST(ifNull(record_id,'') AS String) AS record_id, CAST(ifNull(location_id,'') AS String) AS location_id, CAST(ifNull(city,'') AS String) AS city, CAST(ifNull(state,'') AS String) AS state, CAST(ifNull(country,'') AS String) AS country, CAST(ifNull(region,'') AS String) AS region" + +emit coffeeshop_dim_products.native.zst "${BUCKET}/dim_products/" \ +"${D}, CAST(ifNull(record_id,'') AS String) AS record_id, CAST(ifNull(product_id,'') AS String) AS product_id, CAST(ifNull(name,'') AS String) AS name, CAST(ifNull(category,'') AS String) AS category, CAST(ifNull(subcategory,'') AS String) AS subcategory, CAST(ifNull(standard_cost,0) AS Float64) AS standard_cost, CAST(ifNull(standard_price,0) AS Float64) AS standard_price, CAST(ifNull(from_date, toDate(0)) AS Date) AS from_date, CAST(ifNull(to_date, toDate(0)) AS Date) AS to_date" + +emit coffeeshop_fact_sales.native.zst "${BUCKET}/fact_sales_${SCALE}/" \ +"CAST(ifNull(order_id,'') AS String) AS order_id, CAST(ifNull(order_date, toDate(0)) AS Date) AS order_date, CAST(ifNull(time_of_day,'') AS String) AS time_of_day, CAST(ifNull(season,'') AS String) AS season, CAST(ifNull(month,0) AS Int32) AS month, CAST(ifNull(location_id,'') AS String) AS location_id, CAST(ifNull(region,'') AS String) AS region, CAST(ifNull(product_name,'') AS String) AS product_name, CAST(ifNull(quantity,0) AS Int32) AS quantity, CAST(ifNull(sales_amount,0) AS Float64) AS sales_amount, CAST(ifNull(discount_percentage,0) AS Int32) AS discount_percentage, CAST(ifNull(product_id,'') AS String) AS product_id" + +echo "coffeeshop: done" diff --git a/versions/prepare-data/job.sh b/versions/prepare-data/job.sh new file mode 100755 index 0000000000..b0adce6b0b --- /dev/null +++ b/versions/prepare-data/job.sh @@ -0,0 +1,67 @@ +#!/usr/bin/env bash +# Prepare the Join Order Benchmark (JOB / IMDB) dataset as oldest-ClickHouse- +# compatible Native files. Schema (21 tables) is from the ClickHouse repository +# (tests/benchmarks/job/init.sql): `integer` -> Int32, `text`/`varchar` -> String +# (the JOB set has no Decimal and no date columns, so every table carries a +# constant synth_date for the legacy MergeTree engine). NULLs load as type +# defaults (empty CSV field + input_format_csv_empty_as_default). +# +# The source is the canonical IMDB snapshot (Postgres-COPY CSV); job_convert.py +# re-encodes it to standard RFC-4180 CSV that ClickHouse parses. + +set -euo pipefail +HERE="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" +CLICKHOUSE="${CLICKHOUSE:-$HOME/clickhouse}" +SRC="${JOB_SRC:-https://event.cwi.nl/da/job/imdb.tgz}" +WORK="${HERE}/data/job-work" +command -v "${CLICKHOUSE}" >/dev/null 2>&1 || CLICKHOUSE=clickhouse +mkdir -p "${WORK}" + +TABLES="aka_name aka_title cast_info char_name comp_cast_type company_name company_type complete_cast info_type keyword kind_type link_type movie_companies movie_info movie_info_idx movie_keyword movie_link name person_info role_type title" + +struct_of() { + case "$1" in + aka_name) echo "id Int32, person_id Int32, name String, imdb_index String, name_pcode_cf String, name_pcode_nf String, surname_pcode String, md5sum String" ;; + aka_title) echo "id Int32, movie_id Int32, title String, imdb_index String, kind_id Int32, production_year Int32, phonetic_code String, episode_of_id Int32, season_nr Int32, episode_nr Int32, note String, md5sum String" ;; + cast_info) echo "id Int32, person_id Int32, movie_id Int32, person_role_id Int32, note String, nr_order Int32, role_id Int32" ;; + char_name) echo "id Int32, name String, imdb_index String, imdb_id Int32, name_pcode_nf String, surname_pcode String, md5sum String" ;; + comp_cast_type) echo "id Int32, kind String" ;; + company_name) echo "id Int32, name String, country_code String, imdb_id Int32, name_pcode_nf String, name_pcode_sf String, md5sum String" ;; + company_type) echo "id Int32, kind String" ;; + complete_cast) echo "id Int32, movie_id Int32, subject_id Int32, status_id Int32" ;; + info_type) echo "id Int32, info String" ;; + keyword) echo "id Int32, keyword String, phonetic_code String" ;; + kind_type) echo "id Int32, kind String" ;; + link_type) echo "id Int32, link String" ;; + movie_companies) echo "id Int32, movie_id Int32, company_id Int32, company_type_id Int32, note String" ;; + movie_info) echo "id Int32, movie_id Int32, info_type_id Int32, info String, note String" ;; + movie_info_idx) echo "id Int32, movie_id Int32, info_type_id Int32, info String, note String" ;; + movie_keyword) echo "id Int32, movie_id Int32, keyword_id Int32" ;; + movie_link) echo "id Int32, movie_id Int32, linked_movie_id Int32, link_type_id Int32" ;; + name) echo "id Int32, name String, imdb_index String, imdb_id Int32, gender String, name_pcode_cf String, name_pcode_nf String, surname_pcode String, md5sum String" ;; + person_info) echo "id Int32, person_id Int32, info_type_id Int32, info String, note String" ;; + role_type) echo "id Int32, role String" ;; + title) echo "id Int32, title String, imdb_index String, kind_id Int32, production_year Int32, imdb_id Int32, phonetic_code String, episode_of_id Int32, season_nr Int32, episode_nr Int32, series_years String, md5sum String" ;; + esac +} + +if [ ! -f "${WORK}/.extracted" ]; then + echo "job: downloading ${SRC}" + curl -fsSL "${SRC}" -o "${WORK}/imdb.tgz" + echo "job: extracting" + tar -xzf "${WORK}/imdb.tgz" -C "${WORK}" + touch "${WORK}/.extracted" +fi + +for t in ${TABLES}; do + csv="$(find "${WORK}" -name "${t}.csv" | head -1)" + [ -n "${csv}" ] || { echo "job: ${t}.csv not found" >&2; exit 1; } + python3 "${HERE}/job_convert.py" < "${csv}" \ + | "${CLICKHOUSE}" local --input_format_csv_empty_as_default 1 \ + --input-format CSV --structure "$(struct_of "$t")" \ + --query "SELECT CAST('2000-01-01' AS Date) AS synth_date, * FROM table FORMAT Native" \ + | zstd -q -6 -T0 -c > "${HERE}/data/job_${t}.native.zst" + echo " job_${t}.native.zst: $(du -h "${HERE}/data/job_${t}.native.zst" | cut -f1)" +done +rm -rf "${WORK}" +echo "job: done" diff --git a/versions/prepare-data/job_convert.py b/versions/prepare-data/job_convert.py new file mode 100644 index 0000000000..a6ce71696a --- /dev/null +++ b/versions/prepare-data/job_convert.py @@ -0,0 +1,115 @@ +#!/usr/bin/env python3 +"""Re-encode IMDB/JOB CSV to RFC 4180 CSV that ClickHouse can parse. + +The JOB dataset is Postgres-COPY CSV with ESCAPE '\\': a backslash escapes the +quote character ONLY inside a quoted field (e.g. "5' 9\\"" -> 5' 9"). Outside +quoted fields a backslash is a literal character (e.g. an unquoted value may end +with `\\` right before the delimiter). Python's csv module applies escapechar +everywhere, which corrupts the latter case, so we parse with a small state +machine that matches Postgres semantics and re-emit standard doubled-quote CSV. + +Empty unquoted fields are preserved as empty, which ClickHouse maps to NULL for +Nullable columns. + +Fast path: any physical line containing neither '"' nor '\\' is already valid +CSV (it cannot hold an open quote or an escape), so it is forwarded verbatim. +""" +import csv +import sys + + +def parse_record(s: str): + """Parse one record from ``s`` (Postgres CSV semantics). + + Returns ``(fields, True)`` when a complete record was parsed, or + ``(None, False)`` when more input is needed (an open quoted field, or a + trailing backslash whose escaped char has not arrived yet). + """ + fields = [] + buf = [] + in_quotes = False + at_field_start = True + i = 0 + n = len(s) + while i < n: + ch = s[i] + if in_quotes: + if ch == "\\": + if i + 1 < n: + nxt = s[i + 1] + if nxt == '"' or nxt == "\\": + buf.append(nxt) + i += 2 + continue + buf.append("\\") + i += 1 + continue + return None, False + if ch == '"': + in_quotes = False + i += 1 + continue + buf.append(ch) + i += 1 + continue + if ch == '"' and at_field_start: + in_quotes = True + at_field_start = False + i += 1 + continue + if ch == ",": + fields.append("".join(buf)) + buf = [] + at_field_start = True + i += 1 + continue + if ch == "\n": + fields.append("".join(buf)) + return fields, True + if ch == "\r": + i += 1 + continue + buf.append(ch) + at_field_start = False + i += 1 + if in_quotes: + return None, False + fields.append("".join(buf)) + return fields, True + + +def main() -> int: + out = sys.stdout + writer = csv.writer( + out, + delimiter=",", + quotechar='"', + doublequote=True, + quoting=csv.QUOTE_MINIMAL, + lineterminator="\n", + ) + pending = None + for line in sys.stdin: + if pending is None and "\\" not in line and '"' not in line: + out.write(line) + continue + pending = line if pending is None else pending + line + fields, complete = parse_record(pending) + if complete: + writer.writerow(fields) + pending = None + if pending is not None: + fields, complete = parse_record(pending) + if not complete: + sys.stderr.write( + "error: incomplete final record at end of input " + "(unterminated quoted field or trailing escape); " + "input is likely truncated or corrupted\n" + ) + return 1 + writer.writerow(fields) + return 0 + + +if __name__ == "__main__": + sys.exit(main()) diff --git a/versions/prepare-data/ontime.sh b/versions/prepare-data/ontime.sh new file mode 100755 index 0000000000..8de1f59984 --- /dev/null +++ b/versions/prepare-data/ontime.sh @@ -0,0 +1,22 @@ +#!/usr/bin/env bash +# Prepare ontime.native - the airline on-time performance dataset (single table), +# from the saved copy in the public bucket (ClickHouse docs "Import from a saved +# copy"). The full CSV has 109 columns but the query set touches only 12, so we +# read the full schema (LowCardinality(String) -> String, the only oldest- +# incompatible type) and project just those. FlightDate (a real Date) serves the +# legacy MergeTree engine, so no synth_date is needed. + +set -euo pipefail +HERE="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" +CLICKHOUSE="${CLICKHOUSE:-$HOME/clickhouse}" +OUT="${HERE}/data/ontime.native.zst" +SRC="https://clickhouse-public-datasets.s3.amazonaws.com/ontime/csv_by_year/*.csv.gz" +command -v "${CLICKHOUSE}" >/dev/null 2>&1 || CLICKHOUSE=clickhouse + +FULL_STRUCT="Year UInt16, Quarter UInt8, Month UInt8, DayofMonth UInt8, DayOfWeek UInt8, FlightDate Date, Reporting_Airline String, DOT_ID_Reporting_Airline Int32, IATA_CODE_Reporting_Airline String, Tail_Number String, Flight_Number_Reporting_Airline String, OriginAirportID Int32, OriginAirportSeqID Int32, OriginCityMarketID Int32, Origin FixedString(5), OriginCityName String, OriginState FixedString(2), OriginStateFips FixedString(2), OriginStateName String, OriginWac Int32, DestAirportID Int32, DestAirportSeqID Int32, DestCityMarketID Int32, Dest FixedString(5), DestCityName String, DestState FixedString(2), DestStateFips FixedString(2), DestStateName String, DestWac Int32, CRSDepTime Int32, DepTime Int32, DepDelay Int32, DepDelayMinutes Int32, DepDel15 Int32, DepartureDelayGroups String, DepTimeBlk String, TaxiOut Int32, WheelsOff String, WheelsOn String, TaxiIn Int32, CRSArrTime Int32, ArrTime Int32, ArrDelay Int32, ArrDelayMinutes Int32, ArrDel15 Int32, ArrivalDelayGroups String, ArrTimeBlk String, Cancelled Int8, CancellationCode FixedString(1), Diverted Int8, CRSElapsedTime Int32, ActualElapsedTime Int32, AirTime Int32, Flights Int32, Distance Int32, DistanceGroup Int8, CarrierDelay Int32, WeatherDelay Int32, NASDelay Int32, SecurityDelay Int32, LateAircraftDelay Int32, FirstDepTime Int16, TotalAddGTime Int16, LongestAddGTime Int16, DivAirportLandings Int8, DivReachedDest Int8, DivActualElapsedTime Int16, DivArrDelay Int16, DivDistance Int16, Div1Airport String, Div1AirportID Int32, Div1AirportSeqID Int32, Div1WheelsOn Int16, Div1TotalGTime Int16, Div1LongestGTime Int16, Div1WheelsOff Int16, Div1TailNum String, Div2Airport String, Div2AirportID Int32, Div2AirportSeqID Int32, Div2WheelsOn Int16, Div2TotalGTime Int16, Div2LongestGTime Int16, Div2WheelsOff Int16, Div2TailNum String, Div3Airport String, Div3AirportID Int32, Div3AirportSeqID Int32, Div3WheelsOn Int16, Div3TotalGTime Int16, Div3LongestGTime Int16, Div3WheelsOff Int16, Div3TailNum String, Div4Airport String, Div4AirportID Int32, Div4AirportSeqID Int32, Div4WheelsOn Int16, Div4TotalGTime Int16, Div4LongestGTime Int16, Div4WheelsOff Int16, Div4TailNum String, Div5Airport String, Div5AirportID Int32, Div5AirportSeqID Int32, Div5WheelsOn Int16, Div5TotalGTime Int16, Div5LongestGTime Int16, Div5WheelsOff Int16, Div5TailNum String" + +echo "ontime: building from ${SRC} -> ${OUT}" +"${CLICKHOUSE}" local --max_memory_usage 0 --input_format_csv_empty_as_default 1 \ + --query "SELECT Year, Month, DayOfWeek, FlightDate, IATA_CODE_Reporting_Airline, Origin, OriginCityName, OriginState, DestCityName, DestState, DepDelay, ArrDelayMinutes FROM s3('${SRC}', 'CSVWithNames', '${FULL_STRUCT}') FORMAT Native" \ + | zstd -q -6 -T0 -c > "${OUT}" +ls -l "${OUT}" diff --git a/versions/prepare-data/prepare.sh b/versions/prepare-data/prepare.sh index b55d69ee58..109f4bf6bc 100755 --- a/versions/prepare-data/prepare.sh +++ b/versions/prepare-data/prepare.sh @@ -2,7 +2,8 @@ # Prepare all Native data files used by the Versions Benchmark. # # Produces, under prepare-data/data/ (zstd-compressed Native, level 6): -# hits.native.zst ssb.native.zst mgbench{1,2,3}.native.zst taxi.native.zst +# hits.native.zst ssb.native.zst mgbench{1,2,3}.native.zst +# tpch_{nation,region,part,supplier,partsupp,customer,orders,lineitem}.native.zst taxi.native.zst # # These files use only the oldest-compatible ClickHouse types and load into # every version (including 1.1.x): the runner streams `zstd -dc file | INSERT`, @@ -11,6 +12,7 @@ # Scale is controlled by env vars (defaults reproduce the original benchmark): # HITS_PARTS=255 # 0..255 -> full 100M rows # SSB_SCALE=100 # lineorder_flat ~600M rows +# TPCH_SCALE=40 # ~10 GB compressed # TAXI_GLOB=trips_*.csv.gz # full ~1.3B trips # For a quick validation slice, e.g.: # HITS_PARTS=0 SSB_SCALE=1 TAXI_GLOB=trips_xaa.csv.gz ./prepare.sh @@ -19,7 +21,7 @@ set -euo pipefail HERE="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" mkdir -p "${HERE}/data" -DATASETS="${*:-hits ssb mgbench taxi}" +DATASETS="${*:-hits ssb mgbench tpch tpcds coffeeshop ontime uk job taxi}" for ds in ${DATASETS}; do echo "================ preparing: ${ds} ================" bash "${HERE}/${ds}.sh" diff --git a/versions/prepare-data/taxi.sh b/versions/prepare-data/taxi.sh index 4ad0ed6335..bb07ba4be4 100755 --- a/versions/prepare-data/taxi.sh +++ b/versions/prepare-data/taxi.sh @@ -1,11 +1,13 @@ #!/usr/bin/env bash # Prepare taxi.native — the NYC taxi "trips" table (classic ClickHouse dataset). # -# The source CSVs have 51 positional columns. We read every field as String -# (so parsing never fails across the whole dump) and cast to the oldest- -# compatible target types, synthesising pickup_date (Date) from the pickup -# timestamp for the legacy MergeTree engine. Enum columns (vendor_id, -# payment_type, cab_type) are downgraded to String. +# The source CSVs have 51 positional columns, but the 4 taxi queries only touch +# five, so we project just those (a ~10x smaller file than the full width): +# pickup_date (synthesised Date, also the legacy MergeTree engine's date), +# cab_type, passenger_count, trip_distance, total_amount. +# Every needed field is read as String (so parsing never fails across the whole +# dump) and cast to the oldest-compatible target type; cab_type (an Enum in +# modern schemas) is downgraded to String. # # TAXI_GLOB selects the source files: a single file for a quick slice, or # trips_*.csv.gz (default) for the full ~1.3B-row dataset. @@ -25,57 +27,10 @@ echo "taxi: building trips from ${GLOB} -> ${OUT}" --query " SELECT toDate(parseDateTimeBestEffortOrZero(c3)) AS pickup_date, - toUInt32OrZero(c1) AS trip_id, - c2 AS vendor_id, - parseDateTimeBestEffortOrZero(c3) AS pickup_datetime, - parseDateTimeBestEffortOrZero(c4) AS dropoff_datetime, - c5 AS store_and_fwd_flag, - toUInt8OrZero(c6) AS rate_code_id, - toFloat64OrZero(c7) AS pickup_longitude, - toFloat64OrZero(c8) AS pickup_latitude, - toFloat64OrZero(c9) AS dropoff_longitude, - toFloat64OrZero(c10) AS dropoff_latitude, + c25 AS cab_type, toUInt8OrZero(c11) AS passenger_count, toFloat64OrZero(c12) AS trip_distance, - toFloat32OrZero(c13) AS fare_amount, - toFloat32OrZero(c14) AS extra, - toFloat32OrZero(c15) AS mta_tax, - toFloat32OrZero(c16) AS tip_amount, - toFloat32OrZero(c17) AS tolls_amount, - toFloat32OrZero(c18) AS ehail_fee, - toFloat32OrZero(c19) AS improvement_surcharge, - toFloat32OrZero(c20) AS total_amount, - c21 AS payment_type, - toUInt8OrZero(c22) AS trip_type, - c23 AS pickup, - c24 AS dropoff, - c25 AS cab_type, - toFloat32OrZero(c26) AS precipitation, - toFloat32OrZero(c27) AS snow_depth, - toFloat32OrZero(c28) AS snowfall, - toFloat32OrZero(c29) AS max_temperature, - toFloat32OrZero(c30) AS min_temperature, - toFloat32OrZero(c31) AS average_wind_speed, - toInt32OrZero(c32) AS pickup_nyct2010_gid, - c33 AS pickup_ctlabel, - toInt32OrZero(c34) AS pickup_borocode, - c35 AS pickup_boroname, - c36 AS pickup_ct2010, - c37 AS pickup_boroct2010, - c38 AS pickup_cdeligibil, - c39 AS pickup_ntacode, - c40 AS pickup_ntaname, - toInt32OrZero(c41) AS pickup_puma, - toInt32OrZero(c42) AS dropoff_nyct2010_gid, - c43 AS dropoff_ctlabel, - toInt32OrZero(c44) AS dropoff_borocode, - c45 AS dropoff_boroname, - c46 AS dropoff_ct2010, - c47 AS dropoff_boroct2010, - c48 AS dropoff_cdeligibil, - c49 AS dropoff_ntacode, - c50 AS dropoff_ntaname, - toInt32OrZero(c51) AS dropoff_puma + toFloat32OrZero(c20) AS total_amount FROM s3('${SRC}', 'CSV', '${STRUCT}') FORMAT Native" | zstd -q -6 -T0 -c > "${OUT}" ls -l "${OUT}" diff --git a/versions/prepare-data/tpcds.sh b/versions/prepare-data/tpcds.sh new file mode 100755 index 0000000000..904633e960 --- /dev/null +++ b/versions/prepare-data/tpcds.sh @@ -0,0 +1,75 @@ +#!/usr/bin/env bash +# Prepare the TPC-DS dataset as oldest-ClickHouse-compatible Native files. +# +# TPC-DS is produced by the standard `dsdgen` data generator at scale +# TPCDS_SCALE (default 32, ~10 GB compressed); GEN points at a generator that +# understands `INSTALL tpcds; CALL dsdgen(sf=N)` SQL. The schema (24 tables) is +# taken from the ClickHouse repository (tests/benchmarks/tpc-ds/init.sql); the +# only type the earliest +# ClickHouse cannot handle is Decimal, which is downgraded to Float64. Every +# table also gets a constant synth_date so the legacy positional MergeTree +# engine works (see create/create.sh); NULLs (TPC-DS has many optional foreign +# keys) are replaced with type defaults so the non-Nullable columns load. +# Column order and names match create/schema/
.columns exactly. + +set -euo pipefail +HERE="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" +CLICKHOUSE="${CLICKHOUSE:-$HOME/clickhouse}" +GEN="${GEN:-generator}" +SCALE="${TPCDS_SCALE:-32}" +WORK="${HERE}/data/tpcds-work" +mkdir -p "${WORK}" + +command -v "${CLICKHOUSE}" >/dev/null 2>&1 || CLICKHOUSE=clickhouse +[ -x "${GEN}" ] || command -v "${GEN}" >/dev/null 2>&1 || { + echo "generator '${GEN}' not found; set GEN to a data generator" >&2; exit 1; } + +echo "tpcds: generating scale factor ${SCALE}" +rm -f "${WORK}/tpcds.db" +"${GEN}" "${WORK}/tpcds.db" <.columns (Decimal -> Float64, NULL -> type default). +conv() { + local t="$1" sel="$2" + "${CLICKHOUSE}" local --max_memory_usage 0 \ + --query "SELECT ${sel} FROM file('${WORK}/${t}.parquet','Parquet') FORMAT Native" \ + | zstd -q -6 -T0 -c > "${HERE}/data/tpcds_${t}.native.zst" + echo " tpcds_${t}.native.zst: $(du -h "${HERE}/data/tpcds_${t}.native.zst" | cut -f1)" +} + +conv call_center "CAST('2000-01-01' AS Date) AS synth_date, CAST(ifNull(cc_call_center_sk, 0) AS Int64) AS cc_call_center_sk, CAST(ifNull(cc_call_center_id, '') AS FixedString(16)) AS cc_call_center_id, CAST(ifNull(cc_rec_start_date, toDate(0)) AS Date) AS cc_rec_start_date, CAST(ifNull(cc_rec_end_date, toDate(0)) AS Date) AS cc_rec_end_date, CAST(ifNull(cc_closed_date_sk, 0) AS UInt32) AS cc_closed_date_sk, CAST(ifNull(cc_open_date_sk, 0) AS UInt32) AS cc_open_date_sk, CAST(ifNull(cc_name, '') AS String) AS cc_name, CAST(ifNull(cc_class, '') AS String) AS cc_class, CAST(ifNull(cc_employees, 0) AS Int64) AS cc_employees, CAST(ifNull(cc_sq_ft, 0) AS Int64) AS cc_sq_ft, CAST(ifNull(cc_hours, '') AS FixedString(20)) AS cc_hours, CAST(ifNull(cc_manager, '') AS String) AS cc_manager, CAST(ifNull(cc_mkt_id, 0) AS Int64) AS cc_mkt_id, CAST(ifNull(cc_mkt_class, '') AS FixedString(50)) AS cc_mkt_class, CAST(ifNull(cc_mkt_desc, '') AS String) AS cc_mkt_desc, CAST(ifNull(cc_market_manager, '') AS String) AS cc_market_manager, CAST(ifNull(cc_division, 0) AS Int64) AS cc_division, CAST(ifNull(cc_division_name, '') AS String) AS cc_division_name, CAST(ifNull(cc_company, 0) AS Int64) AS cc_company, CAST(ifNull(cc_company_name, '') AS FixedString(50)) AS cc_company_name, CAST(ifNull(cc_street_number, '') AS FixedString(10)) AS cc_street_number, CAST(ifNull(cc_street_name, '') AS String) AS cc_street_name, CAST(ifNull(cc_street_type, '') AS FixedString(15)) AS cc_street_type, CAST(ifNull(cc_suite_number, '') AS FixedString(10)) AS cc_suite_number, CAST(ifNull(cc_city, '') AS String) AS cc_city, CAST(ifNull(cc_county, '') AS String) AS cc_county, CAST(ifNull(cc_state, '') AS FixedString(2)) AS cc_state, CAST(ifNull(cc_zip, '') AS FixedString(10)) AS cc_zip, CAST(ifNull(cc_country, '') AS String) AS cc_country, CAST(ifNull(cc_gmt_offset, 0) AS Float64) AS cc_gmt_offset, CAST(ifNull(cc_tax_percentage, 0) AS Float64) AS cc_tax_percentage" +conv catalog_page "CAST('2000-01-01' AS Date) AS synth_date, CAST(ifNull(cp_catalog_page_sk, 0) AS Int64) AS cp_catalog_page_sk, CAST(ifNull(cp_catalog_page_id, '') AS FixedString(16)) AS cp_catalog_page_id, CAST(ifNull(cp_start_date_sk, 0) AS UInt32) AS cp_start_date_sk, CAST(ifNull(cp_end_date_sk, 0) AS UInt32) AS cp_end_date_sk, CAST(ifNull(cp_department, '') AS String) AS cp_department, CAST(ifNull(cp_catalog_number, 0) AS Int64) AS cp_catalog_number, CAST(ifNull(cp_catalog_page_number, 0) AS Int64) AS cp_catalog_page_number, CAST(ifNull(cp_description, '') AS String) AS cp_description, CAST(ifNull(cp_type, '') AS String) AS cp_type" +conv catalog_returns "CAST('2000-01-01' AS Date) AS synth_date, CAST(ifNull(cr_returned_date_sk, 0) AS UInt32) AS cr_returned_date_sk, CAST(ifNull(cr_returned_time_sk, 0) AS UInt32) AS cr_returned_time_sk, CAST(ifNull(cr_item_sk, 0) AS Int64) AS cr_item_sk, CAST(ifNull(cr_refunded_customer_sk, 0) AS Int64) AS cr_refunded_customer_sk, CAST(ifNull(cr_refunded_cdemo_sk, 0) AS Int64) AS cr_refunded_cdemo_sk, CAST(ifNull(cr_refunded_hdemo_sk, 0) AS Int64) AS cr_refunded_hdemo_sk, CAST(ifNull(cr_refunded_addr_sk, 0) AS Int64) AS cr_refunded_addr_sk, CAST(ifNull(cr_returning_customer_sk, 0) AS Int64) AS cr_returning_customer_sk, CAST(ifNull(cr_returning_cdemo_sk, 0) AS Int64) AS cr_returning_cdemo_sk, CAST(ifNull(cr_returning_hdemo_sk, 0) AS Int64) AS cr_returning_hdemo_sk, CAST(ifNull(cr_returning_addr_sk, 0) AS Int64) AS cr_returning_addr_sk, CAST(ifNull(cr_call_center_sk, 0) AS Int64) AS cr_call_center_sk, CAST(ifNull(cr_catalog_page_sk, 0) AS Int64) AS cr_catalog_page_sk, CAST(ifNull(cr_ship_mode_sk, 0) AS Int64) AS cr_ship_mode_sk, CAST(ifNull(cr_warehouse_sk, 0) AS Int64) AS cr_warehouse_sk, CAST(ifNull(cr_reason_sk, 0) AS Int64) AS cr_reason_sk, CAST(ifNull(cr_order_number, 0) AS Int64) AS cr_order_number, CAST(ifNull(cr_return_quantity, 0) AS Int64) AS cr_return_quantity, CAST(ifNull(cr_return_amount, 0) AS Float64) AS cr_return_amount, CAST(ifNull(cr_return_tax, 0) AS Float64) AS cr_return_tax, CAST(ifNull(cr_return_amt_inc_tax, 0) AS Float64) AS cr_return_amt_inc_tax, CAST(ifNull(cr_fee, 0) AS Float64) AS cr_fee, CAST(ifNull(cr_return_ship_cost, 0) AS Float64) AS cr_return_ship_cost, CAST(ifNull(cr_refunded_cash, 0) AS Float64) AS cr_refunded_cash, CAST(ifNull(cr_reversed_charge, 0) AS Float64) AS cr_reversed_charge, CAST(ifNull(cr_store_credit, 0) AS Float64) AS cr_store_credit, CAST(ifNull(cr_net_loss, 0) AS Float64) AS cr_net_loss" +conv catalog_sales "CAST('2000-01-01' AS Date) AS synth_date, CAST(ifNull(cs_sold_date_sk, 0) AS UInt32) AS cs_sold_date_sk, CAST(ifNull(cs_sold_time_sk, 0) AS UInt32) AS cs_sold_time_sk, CAST(ifNull(cs_ship_date_sk, 0) AS UInt32) AS cs_ship_date_sk, CAST(ifNull(cs_bill_customer_sk, 0) AS Int64) AS cs_bill_customer_sk, CAST(ifNull(cs_bill_cdemo_sk, 0) AS Int64) AS cs_bill_cdemo_sk, CAST(ifNull(cs_bill_hdemo_sk, 0) AS Int64) AS cs_bill_hdemo_sk, CAST(ifNull(cs_bill_addr_sk, 0) AS Int64) AS cs_bill_addr_sk, CAST(ifNull(cs_ship_customer_sk, 0) AS Int64) AS cs_ship_customer_sk, CAST(ifNull(cs_ship_cdemo_sk, 0) AS Int64) AS cs_ship_cdemo_sk, CAST(ifNull(cs_ship_hdemo_sk, 0) AS Int64) AS cs_ship_hdemo_sk, CAST(ifNull(cs_ship_addr_sk, 0) AS Int64) AS cs_ship_addr_sk, CAST(ifNull(cs_call_center_sk, 0) AS Int64) AS cs_call_center_sk, CAST(ifNull(cs_catalog_page_sk, 0) AS Int64) AS cs_catalog_page_sk, CAST(ifNull(cs_ship_mode_sk, 0) AS Int64) AS cs_ship_mode_sk, CAST(ifNull(cs_warehouse_sk, 0) AS Int64) AS cs_warehouse_sk, CAST(ifNull(cs_item_sk, 0) AS Int64) AS cs_item_sk, CAST(ifNull(cs_promo_sk, 0) AS Int64) AS cs_promo_sk, CAST(ifNull(cs_order_number, 0) AS Int64) AS cs_order_number, CAST(ifNull(cs_quantity, 0) AS Int64) AS cs_quantity, CAST(ifNull(cs_wholesale_cost, 0) AS Float64) AS cs_wholesale_cost, CAST(ifNull(cs_list_price, 0) AS Float64) AS cs_list_price, CAST(ifNull(cs_sales_price, 0) AS Float64) AS cs_sales_price, CAST(ifNull(cs_ext_discount_amt, 0) AS Float64) AS cs_ext_discount_amt, CAST(ifNull(cs_ext_sales_price, 0) AS Float64) AS cs_ext_sales_price, CAST(ifNull(cs_ext_wholesale_cost, 0) AS Float64) AS cs_ext_wholesale_cost, CAST(ifNull(cs_ext_list_price, 0) AS Float64) AS cs_ext_list_price, CAST(ifNull(cs_ext_tax, 0) AS Float64) AS cs_ext_tax, CAST(ifNull(cs_coupon_amt, 0) AS Float64) AS cs_coupon_amt, CAST(ifNull(cs_ext_ship_cost, 0) AS Float64) AS cs_ext_ship_cost, CAST(ifNull(cs_net_paid, 0) AS Float64) AS cs_net_paid, CAST(ifNull(cs_net_paid_inc_tax, 0) AS Float64) AS cs_net_paid_inc_tax, CAST(ifNull(cs_net_paid_inc_ship, 0) AS Float64) AS cs_net_paid_inc_ship, CAST(ifNull(cs_net_paid_inc_ship_tax, 0) AS Float64) AS cs_net_paid_inc_ship_tax, CAST(ifNull(cs_net_profit, 0) AS Float64) AS cs_net_profit" +conv customer_address "CAST('2000-01-01' AS Date) AS synth_date, CAST(ifNull(ca_address_sk, 0) AS Int64) AS ca_address_sk, CAST(ifNull(ca_address_id, '') AS FixedString(16)) AS ca_address_id, CAST(ifNull(ca_street_number, '') AS FixedString(10)) AS ca_street_number, CAST(ifNull(ca_street_name, '') AS String) AS ca_street_name, CAST(ifNull(ca_street_type, '') AS FixedString(15)) AS ca_street_type, CAST(ifNull(ca_suite_number, '') AS FixedString(10)) AS ca_suite_number, CAST(ifNull(ca_city, '') AS String) AS ca_city, CAST(ifNull(ca_county, '') AS String) AS ca_county, CAST(ifNull(ca_state, '') AS FixedString(2)) AS ca_state, CAST(ifNull(ca_zip, '') AS FixedString(10)) AS ca_zip, CAST(ifNull(ca_country, '') AS String) AS ca_country, CAST(ifNull(ca_gmt_offset, 0) AS Float64) AS ca_gmt_offset, CAST(ifNull(ca_location_type, '') AS FixedString(20)) AS ca_location_type" +conv customer_demographics "CAST('2000-01-01' AS Date) AS synth_date, CAST(ifNull(cd_demo_sk, 0) AS Int64) AS cd_demo_sk, CAST(ifNull(cd_gender, '') AS FixedString(1)) AS cd_gender, CAST(ifNull(cd_marital_status, '') AS FixedString(1)) AS cd_marital_status, CAST(ifNull(cd_education_status, '') AS FixedString(20)) AS cd_education_status, CAST(ifNull(cd_purchase_estimate, 0) AS Int64) AS cd_purchase_estimate, CAST(ifNull(cd_credit_rating, '') AS FixedString(10)) AS cd_credit_rating, CAST(ifNull(cd_dep_count, 0) AS Int64) AS cd_dep_count, CAST(ifNull(cd_dep_employed_count, 0) AS Int64) AS cd_dep_employed_count, CAST(ifNull(cd_dep_college_count, 0) AS Int64) AS cd_dep_college_count" +conv customer "CAST('2000-01-01' AS Date) AS synth_date, CAST(ifNull(c_customer_sk, 0) AS Int64) AS c_customer_sk, CAST(ifNull(c_customer_id, '') AS FixedString(16)) AS c_customer_id, CAST(ifNull(c_current_cdemo_sk, 0) AS Int64) AS c_current_cdemo_sk, CAST(ifNull(c_current_hdemo_sk, 0) AS Int64) AS c_current_hdemo_sk, CAST(ifNull(c_current_addr_sk, 0) AS Int64) AS c_current_addr_sk, CAST(ifNull(c_first_shipto_date_sk, 0) AS UInt32) AS c_first_shipto_date_sk, CAST(ifNull(c_first_sales_date_sk, 0) AS UInt32) AS c_first_sales_date_sk, CAST(ifNull(c_salutation, '') AS FixedString(10)) AS c_salutation, CAST(ifNull(c_first_name, '') AS FixedString(20)) AS c_first_name, CAST(ifNull(c_last_name, '') AS FixedString(30)) AS c_last_name, CAST(ifNull(c_preferred_cust_flag, '') AS FixedString(1)) AS c_preferred_cust_flag, CAST(ifNull(c_birth_day, 0) AS Int64) AS c_birth_day, CAST(ifNull(c_birth_month, 0) AS Int64) AS c_birth_month, CAST(ifNull(c_birth_year, 0) AS Int64) AS c_birth_year, CAST(ifNull(c_birth_country, '') AS String) AS c_birth_country, CAST(ifNull(c_login, '') AS FixedString(13)) AS c_login, CAST(ifNull(c_email_address, '') AS FixedString(50)) AS c_email_address, CAST(ifNull(c_last_review_date_sk, 0) AS UInt32) AS c_last_review_date_sk" +conv date_dim "CAST('2000-01-01' AS Date) AS synth_date, CAST(ifNull(d_date_sk, 0) AS UInt32) AS d_date_sk, CAST(ifNull(d_date_id, '') AS FixedString(16)) AS d_date_id, CAST(ifNull(d_date, toDate(0)) AS Date) AS d_date, CAST(ifNull(d_month_seq, 0) AS Int64) AS d_month_seq, CAST(ifNull(d_week_seq, 0) AS Int64) AS d_week_seq, CAST(ifNull(d_quarter_seq, 0) AS Int64) AS d_quarter_seq, CAST(ifNull(d_year, 0) AS Int64) AS d_year, CAST(ifNull(d_dow, 0) AS Int64) AS d_dow, CAST(ifNull(d_moy, 0) AS Int64) AS d_moy, CAST(ifNull(d_dom, 0) AS Int64) AS d_dom, CAST(ifNull(d_qoy, 0) AS Int64) AS d_qoy, CAST(ifNull(d_fy_year, 0) AS Int64) AS d_fy_year, CAST(ifNull(d_fy_quarter_seq, 0) AS Int64) AS d_fy_quarter_seq, CAST(ifNull(d_fy_week_seq, 0) AS Int64) AS d_fy_week_seq, CAST(ifNull(d_day_name, '') AS FixedString(9)) AS d_day_name, CAST(ifNull(d_quarter_name, '') AS FixedString(6)) AS d_quarter_name, CAST(ifNull(d_holiday, '') AS FixedString(1)) AS d_holiday, CAST(ifNull(d_weekend, '') AS FixedString(1)) AS d_weekend, CAST(ifNull(d_following_holiday, '') AS FixedString(1)) AS d_following_holiday, CAST(ifNull(d_first_dom, 0) AS Int64) AS d_first_dom, CAST(ifNull(d_last_dom, 0) AS Int64) AS d_last_dom, CAST(ifNull(d_same_day_ly, 0) AS Int64) AS d_same_day_ly, CAST(ifNull(d_same_day_lq, 0) AS Int64) AS d_same_day_lq, CAST(ifNull(d_current_day, '') AS FixedString(1)) AS d_current_day, CAST(ifNull(d_current_week, '') AS FixedString(1)) AS d_current_week, CAST(ifNull(d_current_month, '') AS FixedString(1)) AS d_current_month, CAST(ifNull(d_current_quarter, '') AS FixedString(1)) AS d_current_quarter, CAST(ifNull(d_current_year, '') AS FixedString(1)) AS d_current_year" +conv household_demographics "CAST('2000-01-01' AS Date) AS synth_date, CAST(ifNull(hd_demo_sk, 0) AS Int64) AS hd_demo_sk, CAST(ifNull(hd_income_band_sk, 0) AS Int64) AS hd_income_band_sk, CAST(ifNull(hd_buy_potential, '') AS FixedString(15)) AS hd_buy_potential, CAST(ifNull(hd_dep_count, 0) AS Int64) AS hd_dep_count, CAST(ifNull(hd_vehicle_count, 0) AS Int64) AS hd_vehicle_count" +conv income_band "CAST('2000-01-01' AS Date) AS synth_date, CAST(ifNull(ib_income_band_sk, 0) AS Int64) AS ib_income_band_sk, CAST(ifNull(ib_lower_bound, 0) AS Int64) AS ib_lower_bound, CAST(ifNull(ib_upper_bound, 0) AS Int64) AS ib_upper_bound" +conv inventory "CAST('2000-01-01' AS Date) AS synth_date, CAST(ifNull(inv_date_sk, 0) AS UInt32) AS inv_date_sk, CAST(ifNull(inv_item_sk, 0) AS Int64) AS inv_item_sk, CAST(ifNull(inv_warehouse_sk, 0) AS Int64) AS inv_warehouse_sk, CAST(ifNull(inv_quantity_on_hand, 0) AS Int64) AS inv_quantity_on_hand" +conv item "CAST('2000-01-01' AS Date) AS synth_date, CAST(ifNull(i_item_sk, 0) AS Int64) AS i_item_sk, CAST(ifNull(i_item_id, '') AS FixedString(16)) AS i_item_id, CAST(ifNull(i_rec_start_date, toDate(0)) AS Date) AS i_rec_start_date, CAST(ifNull(i_rec_end_date, toDate(0)) AS Date) AS i_rec_end_date, CAST(ifNull(i_item_desc, '') AS String) AS i_item_desc, CAST(ifNull(i_current_price, 0) AS Float64) AS i_current_price, CAST(ifNull(i_wholesale_cost, 0) AS Float64) AS i_wholesale_cost, CAST(ifNull(i_brand_id, 0) AS Int64) AS i_brand_id, CAST(ifNull(i_brand, '') AS FixedString(50)) AS i_brand, CAST(ifNull(i_class_id, 0) AS Int64) AS i_class_id, CAST(ifNull(i_class, '') AS FixedString(50)) AS i_class, CAST(ifNull(i_category_id, 0) AS Int64) AS i_category_id, CAST(ifNull(i_category, '') AS FixedString(50)) AS i_category, CAST(ifNull(i_manufact_id, 0) AS Int64) AS i_manufact_id, CAST(ifNull(i_manufact, '') AS FixedString(50)) AS i_manufact, CAST(ifNull(i_size, '') AS FixedString(20)) AS i_size, CAST(ifNull(i_formulation, '') AS FixedString(20)) AS i_formulation, CAST(ifNull(i_color, '') AS FixedString(20)) AS i_color, CAST(ifNull(i_units, '') AS FixedString(10)) AS i_units, CAST(ifNull(i_container, '') AS FixedString(10)) AS i_container, CAST(ifNull(i_manager_id, 0) AS Int64) AS i_manager_id, CAST(ifNull(i_product_name, '') AS FixedString(50)) AS i_product_name" +conv promotion "CAST('2000-01-01' AS Date) AS synth_date, CAST(ifNull(p_promo_sk, 0) AS Int64) AS p_promo_sk, CAST(ifNull(p_promo_id, '') AS FixedString(16)) AS p_promo_id, CAST(ifNull(p_start_date_sk, 0) AS UInt32) AS p_start_date_sk, CAST(ifNull(p_end_date_sk, 0) AS UInt32) AS p_end_date_sk, CAST(ifNull(p_item_sk, 0) AS Int64) AS p_item_sk, CAST(ifNull(p_cost, 0) AS Float64) AS p_cost, CAST(ifNull(p_response_target, 0) AS Int64) AS p_response_target, CAST(ifNull(p_promo_name, '') AS FixedString(50)) AS p_promo_name, CAST(ifNull(p_channel_dmail, '') AS FixedString(1)) AS p_channel_dmail, CAST(ifNull(p_channel_email, '') AS FixedString(1)) AS p_channel_email, CAST(ifNull(p_channel_catalog, '') AS FixedString(1)) AS p_channel_catalog, CAST(ifNull(p_channel_tv, '') AS FixedString(1)) AS p_channel_tv, CAST(ifNull(p_channel_radio, '') AS FixedString(1)) AS p_channel_radio, CAST(ifNull(p_channel_press, '') AS FixedString(1)) AS p_channel_press, CAST(ifNull(p_channel_event, '') AS FixedString(1)) AS p_channel_event, CAST(ifNull(p_channel_demo, '') AS FixedString(1)) AS p_channel_demo, CAST(ifNull(p_channel_details, '') AS String) AS p_channel_details, CAST(ifNull(p_purpose, '') AS FixedString(15)) AS p_purpose, CAST(ifNull(p_discount_active, '') AS FixedString(1)) AS p_discount_active" +conv reason "CAST('2000-01-01' AS Date) AS synth_date, CAST(ifNull(r_reason_sk, 0) AS Int64) AS r_reason_sk, CAST(ifNull(r_reason_id, '') AS FixedString(16)) AS r_reason_id, CAST(ifNull(r_reason_desc, '') AS FixedString(100)) AS r_reason_desc" +conv ship_mode "CAST('2000-01-01' AS Date) AS synth_date, CAST(ifNull(sm_ship_mode_sk, 0) AS Int64) AS sm_ship_mode_sk, CAST(ifNull(sm_ship_mode_id, '') AS FixedString(16)) AS sm_ship_mode_id, CAST(ifNull(sm_type, '') AS FixedString(30)) AS sm_type, CAST(ifNull(sm_code, '') AS FixedString(10)) AS sm_code, CAST(ifNull(sm_carrier, '') AS FixedString(20)) AS sm_carrier, CAST(ifNull(sm_contract, '') AS FixedString(20)) AS sm_contract" +conv store_returns "CAST('2000-01-01' AS Date) AS synth_date, CAST(ifNull(sr_returned_date_sk, 0) AS UInt32) AS sr_returned_date_sk, CAST(ifNull(sr_return_time_sk, 0) AS UInt32) AS sr_return_time_sk, CAST(ifNull(sr_item_sk, 0) AS Int64) AS sr_item_sk, CAST(ifNull(sr_customer_sk, 0) AS Int64) AS sr_customer_sk, CAST(ifNull(sr_cdemo_sk, 0) AS Int64) AS sr_cdemo_sk, CAST(ifNull(sr_hdemo_sk, 0) AS Int64) AS sr_hdemo_sk, CAST(ifNull(sr_addr_sk, 0) AS Int64) AS sr_addr_sk, CAST(ifNull(sr_store_sk, 0) AS Int64) AS sr_store_sk, CAST(ifNull(sr_reason_sk, 0) AS Int64) AS sr_reason_sk, CAST(ifNull(sr_ticket_number, 0) AS Int64) AS sr_ticket_number, CAST(ifNull(sr_return_quantity, 0) AS Int64) AS sr_return_quantity, CAST(ifNull(sr_return_amt, 0) AS Float64) AS sr_return_amt, CAST(ifNull(sr_return_tax, 0) AS Float64) AS sr_return_tax, CAST(ifNull(sr_return_amt_inc_tax, 0) AS Float64) AS sr_return_amt_inc_tax, CAST(ifNull(sr_fee, 0) AS Float64) AS sr_fee, CAST(ifNull(sr_return_ship_cost, 0) AS Float64) AS sr_return_ship_cost, CAST(ifNull(sr_refunded_cash, 0) AS Float64) AS sr_refunded_cash, CAST(ifNull(sr_reversed_charge, 0) AS Float64) AS sr_reversed_charge, CAST(ifNull(sr_store_credit, 0) AS Float64) AS sr_store_credit, CAST(ifNull(sr_net_loss, 0) AS Float64) AS sr_net_loss" +conv store_sales "CAST('2000-01-01' AS Date) AS synth_date, CAST(ifNull(ss_sold_date_sk, 0) AS UInt32) AS ss_sold_date_sk, CAST(ifNull(ss_sold_time_sk, 0) AS UInt32) AS ss_sold_time_sk, CAST(ifNull(ss_item_sk, 0) AS Int64) AS ss_item_sk, CAST(ifNull(ss_customer_sk, 0) AS Int64) AS ss_customer_sk, CAST(ifNull(ss_cdemo_sk, 0) AS Int64) AS ss_cdemo_sk, CAST(ifNull(ss_hdemo_sk, 0) AS Int64) AS ss_hdemo_sk, CAST(ifNull(ss_addr_sk, 0) AS Int64) AS ss_addr_sk, CAST(ifNull(ss_store_sk, 0) AS Int64) AS ss_store_sk, CAST(ifNull(ss_promo_sk, 0) AS Int64) AS ss_promo_sk, CAST(ifNull(ss_ticket_number, 0) AS Int64) AS ss_ticket_number, CAST(ifNull(ss_quantity, 0) AS Int64) AS ss_quantity, CAST(ifNull(ss_wholesale_cost, 0) AS Float64) AS ss_wholesale_cost, CAST(ifNull(ss_list_price, 0) AS Float64) AS ss_list_price, CAST(ifNull(ss_sales_price, 0) AS Float64) AS ss_sales_price, CAST(ifNull(ss_ext_discount_amt, 0) AS Float64) AS ss_ext_discount_amt, CAST(ifNull(ss_ext_sales_price, 0) AS Float64) AS ss_ext_sales_price, CAST(ifNull(ss_ext_wholesale_cost, 0) AS Float64) AS ss_ext_wholesale_cost, CAST(ifNull(ss_ext_list_price, 0) AS Float64) AS ss_ext_list_price, CAST(ifNull(ss_ext_tax, 0) AS Float64) AS ss_ext_tax, CAST(ifNull(ss_coupon_amt, 0) AS Float64) AS ss_coupon_amt, CAST(ifNull(ss_net_paid, 0) AS Float64) AS ss_net_paid, CAST(ifNull(ss_net_paid_inc_tax, 0) AS Float64) AS ss_net_paid_inc_tax, CAST(ifNull(ss_net_profit, 0) AS Float64) AS ss_net_profit" +conv store "CAST('2000-01-01' AS Date) AS synth_date, CAST(ifNull(s_store_sk, 0) AS Int64) AS s_store_sk, CAST(ifNull(s_store_id, '') AS FixedString(16)) AS s_store_id, CAST(ifNull(s_rec_start_date, toDate(0)) AS Date) AS s_rec_start_date, CAST(ifNull(s_rec_end_date, toDate(0)) AS Date) AS s_rec_end_date, CAST(ifNull(s_closed_date_sk, 0) AS UInt32) AS s_closed_date_sk, CAST(ifNull(s_store_name, '') AS String) AS s_store_name, CAST(ifNull(s_number_employees, 0) AS Int64) AS s_number_employees, CAST(ifNull(s_floor_space, 0) AS Int64) AS s_floor_space, CAST(ifNull(s_hours, '') AS FixedString(20)) AS s_hours, CAST(ifNull(s_manager, '') AS String) AS s_manager, CAST(ifNull(s_market_id, 0) AS Int64) AS s_market_id, CAST(ifNull(s_geography_class, '') AS String) AS s_geography_class, CAST(ifNull(s_market_desc, '') AS String) AS s_market_desc, CAST(ifNull(s_market_manager, '') AS String) AS s_market_manager, CAST(ifNull(s_division_id, 0) AS Int64) AS s_division_id, CAST(ifNull(s_division_name, '') AS String) AS s_division_name, CAST(ifNull(s_company_id, 0) AS Int64) AS s_company_id, CAST(ifNull(s_company_name, '') AS String) AS s_company_name, CAST(ifNull(s_street_number, '') AS String) AS s_street_number, CAST(ifNull(s_street_name, '') AS String) AS s_street_name, CAST(ifNull(s_street_type, '') AS FixedString(15)) AS s_street_type, CAST(ifNull(s_suite_number, '') AS FixedString(10)) AS s_suite_number, CAST(ifNull(s_city, '') AS String) AS s_city, CAST(ifNull(s_county, '') AS String) AS s_county, CAST(ifNull(s_state, '') AS FixedString(2)) AS s_state, CAST(ifNull(s_zip, '') AS FixedString(10)) AS s_zip, CAST(ifNull(s_country, '') AS String) AS s_country, CAST(ifNull(s_gmt_offset, 0) AS Float64) AS s_gmt_offset, CAST(ifNull(s_tax_percentage, 0) AS Float64) AS s_tax_percentage" +conv time_dim "CAST('2000-01-01' AS Date) AS synth_date, CAST(ifNull(t_time_sk, 0) AS UInt32) AS t_time_sk, CAST(ifNull(t_time_id, '') AS FixedString(16)) AS t_time_id, CAST(ifNull(t_time, 0) AS Int64) AS t_time, CAST(ifNull(t_hour, 0) AS Int64) AS t_hour, CAST(ifNull(t_minute, 0) AS Int64) AS t_minute, CAST(ifNull(t_second, 0) AS Int64) AS t_second, CAST(ifNull(t_am_pm, '') AS FixedString(2)) AS t_am_pm, CAST(ifNull(t_shift, '') AS FixedString(20)) AS t_shift, CAST(ifNull(t_sub_shift, '') AS FixedString(20)) AS t_sub_shift, CAST(ifNull(t_meal_time, '') AS FixedString(20)) AS t_meal_time" +conv warehouse "CAST('2000-01-01' AS Date) AS synth_date, CAST(ifNull(w_warehouse_sk, 0) AS Int64) AS w_warehouse_sk, CAST(ifNull(w_warehouse_id, '') AS FixedString(16)) AS w_warehouse_id, CAST(ifNull(w_warehouse_name, '') AS String) AS w_warehouse_name, CAST(ifNull(w_warehouse_sq_ft, 0) AS Int64) AS w_warehouse_sq_ft, CAST(ifNull(w_street_number, '') AS FixedString(10)) AS w_street_number, CAST(ifNull(w_street_name, '') AS String) AS w_street_name, CAST(ifNull(w_street_type, '') AS FixedString(15)) AS w_street_type, CAST(ifNull(w_suite_number, '') AS FixedString(10)) AS w_suite_number, CAST(ifNull(w_city, '') AS String) AS w_city, CAST(ifNull(w_county, '') AS String) AS w_county, CAST(ifNull(w_state, '') AS FixedString(2)) AS w_state, CAST(ifNull(w_zip, '') AS FixedString(10)) AS w_zip, CAST(ifNull(w_country, '') AS String) AS w_country, CAST(ifNull(w_gmt_offset, 0) AS Float64) AS w_gmt_offset" +conv web_page "CAST('2000-01-01' AS Date) AS synth_date, CAST(ifNull(wp_web_page_sk, 0) AS Int64) AS wp_web_page_sk, CAST(ifNull(wp_web_page_id, '') AS FixedString(16)) AS wp_web_page_id, CAST(ifNull(wp_rec_start_date, toDate(0)) AS Date) AS wp_rec_start_date, CAST(ifNull(wp_rec_end_date, toDate(0)) AS Date) AS wp_rec_end_date, CAST(ifNull(wp_creation_date_sk, 0) AS UInt32) AS wp_creation_date_sk, CAST(ifNull(wp_access_date_sk, 0) AS UInt32) AS wp_access_date_sk, CAST(ifNull(wp_autogen_flag, '') AS FixedString(1)) AS wp_autogen_flag, CAST(ifNull(wp_customer_sk, 0) AS Int64) AS wp_customer_sk, CAST(ifNull(wp_url, '') AS String) AS wp_url, CAST(ifNull(wp_type, '') AS FixedString(50)) AS wp_type, CAST(ifNull(wp_char_count, 0) AS Int64) AS wp_char_count, CAST(ifNull(wp_link_count, 0) AS Int64) AS wp_link_count, CAST(ifNull(wp_image_count, 0) AS Int64) AS wp_image_count, CAST(ifNull(wp_max_ad_count, 0) AS Int64) AS wp_max_ad_count" +conv web_returns "CAST('2000-01-01' AS Date) AS synth_date, CAST(ifNull(wr_returned_date_sk, 0) AS UInt32) AS wr_returned_date_sk, CAST(ifNull(wr_returned_time_sk, 0) AS UInt32) AS wr_returned_time_sk, CAST(ifNull(wr_item_sk, 0) AS Int64) AS wr_item_sk, CAST(ifNull(wr_refunded_customer_sk, 0) AS Int64) AS wr_refunded_customer_sk, CAST(ifNull(wr_refunded_cdemo_sk, 0) AS Int64) AS wr_refunded_cdemo_sk, CAST(ifNull(wr_refunded_hdemo_sk, 0) AS Int64) AS wr_refunded_hdemo_sk, CAST(ifNull(wr_refunded_addr_sk, 0) AS Int64) AS wr_refunded_addr_sk, CAST(ifNull(wr_returning_customer_sk, 0) AS Int64) AS wr_returning_customer_sk, CAST(ifNull(wr_returning_cdemo_sk, 0) AS Int64) AS wr_returning_cdemo_sk, CAST(ifNull(wr_returning_hdemo_sk, 0) AS Int64) AS wr_returning_hdemo_sk, CAST(ifNull(wr_returning_addr_sk, 0) AS Int64) AS wr_returning_addr_sk, CAST(ifNull(wr_web_page_sk, 0) AS Int64) AS wr_web_page_sk, CAST(ifNull(wr_reason_sk, 0) AS Int64) AS wr_reason_sk, CAST(ifNull(wr_order_number, 0) AS Int64) AS wr_order_number, CAST(ifNull(wr_return_quantity, 0) AS Int64) AS wr_return_quantity, CAST(ifNull(wr_return_amt, 0) AS Float64) AS wr_return_amt, CAST(ifNull(wr_return_tax, 0) AS Float64) AS wr_return_tax, CAST(ifNull(wr_return_amt_inc_tax, 0) AS Float64) AS wr_return_amt_inc_tax, CAST(ifNull(wr_fee, 0) AS Float64) AS wr_fee, CAST(ifNull(wr_return_ship_cost, 0) AS Float64) AS wr_return_ship_cost, CAST(ifNull(wr_refunded_cash, 0) AS Float64) AS wr_refunded_cash, CAST(ifNull(wr_reversed_charge, 0) AS Float64) AS wr_reversed_charge, CAST(ifNull(wr_account_credit, 0) AS Float64) AS wr_account_credit, CAST(ifNull(wr_net_loss, 0) AS Float64) AS wr_net_loss" +conv web_sales "CAST('2000-01-01' AS Date) AS synth_date, CAST(ifNull(ws_sold_date_sk, 0) AS UInt32) AS ws_sold_date_sk, CAST(ifNull(ws_sold_time_sk, 0) AS UInt32) AS ws_sold_time_sk, CAST(ifNull(ws_ship_date_sk, 0) AS UInt32) AS ws_ship_date_sk, CAST(ifNull(ws_item_sk, 0) AS Int64) AS ws_item_sk, CAST(ifNull(ws_bill_customer_sk, 0) AS Int64) AS ws_bill_customer_sk, CAST(ifNull(ws_bill_cdemo_sk, 0) AS Int64) AS ws_bill_cdemo_sk, CAST(ifNull(ws_bill_hdemo_sk, 0) AS Int64) AS ws_bill_hdemo_sk, CAST(ifNull(ws_bill_addr_sk, 0) AS Int64) AS ws_bill_addr_sk, CAST(ifNull(ws_ship_customer_sk, 0) AS Int64) AS ws_ship_customer_sk, CAST(ifNull(ws_ship_cdemo_sk, 0) AS Int64) AS ws_ship_cdemo_sk, CAST(ifNull(ws_ship_hdemo_sk, 0) AS Int64) AS ws_ship_hdemo_sk, CAST(ifNull(ws_ship_addr_sk, 0) AS Int64) AS ws_ship_addr_sk, CAST(ifNull(ws_web_page_sk, 0) AS Int64) AS ws_web_page_sk, CAST(ifNull(ws_web_site_sk, 0) AS Int64) AS ws_web_site_sk, CAST(ifNull(ws_ship_mode_sk, 0) AS Int64) AS ws_ship_mode_sk, CAST(ifNull(ws_warehouse_sk, 0) AS Int64) AS ws_warehouse_sk, CAST(ifNull(ws_promo_sk, 0) AS Int64) AS ws_promo_sk, CAST(ifNull(ws_order_number, 0) AS Int64) AS ws_order_number, CAST(ifNull(ws_quantity, 0) AS Int64) AS ws_quantity, CAST(ifNull(ws_wholesale_cost, 0) AS Float64) AS ws_wholesale_cost, CAST(ifNull(ws_list_price, 0) AS Float64) AS ws_list_price, CAST(ifNull(ws_sales_price, 0) AS Float64) AS ws_sales_price, CAST(ifNull(ws_ext_discount_amt, 0) AS Float64) AS ws_ext_discount_amt, CAST(ifNull(ws_ext_sales_price, 0) AS Float64) AS ws_ext_sales_price, CAST(ifNull(ws_ext_wholesale_cost, 0) AS Float64) AS ws_ext_wholesale_cost, CAST(ifNull(ws_ext_list_price, 0) AS Float64) AS ws_ext_list_price, CAST(ifNull(ws_ext_tax, 0) AS Float64) AS ws_ext_tax, CAST(ifNull(ws_coupon_amt, 0) AS Float64) AS ws_coupon_amt, CAST(ifNull(ws_ext_ship_cost, 0) AS Float64) AS ws_ext_ship_cost, CAST(ifNull(ws_net_paid, 0) AS Float64) AS ws_net_paid, CAST(ifNull(ws_net_paid_inc_tax, 0) AS Float64) AS ws_net_paid_inc_tax, CAST(ifNull(ws_net_paid_inc_ship, 0) AS Float64) AS ws_net_paid_inc_ship, CAST(ifNull(ws_net_paid_inc_ship_tax, 0) AS Float64) AS ws_net_paid_inc_ship_tax, CAST(ifNull(ws_net_profit, 0) AS Float64) AS ws_net_profit" +conv web_site "CAST('2000-01-01' AS Date) AS synth_date, CAST(ifNull(web_site_sk, 0) AS Int64) AS web_site_sk, CAST(ifNull(web_site_id, '') AS FixedString(16)) AS web_site_id, CAST(ifNull(web_rec_start_date, toDate(0)) AS Date) AS web_rec_start_date, CAST(ifNull(web_rec_end_date, toDate(0)) AS Date) AS web_rec_end_date, CAST(ifNull(web_name, '') AS String) AS web_name, CAST(ifNull(web_open_date_sk, 0) AS UInt32) AS web_open_date_sk, CAST(ifNull(web_close_date_sk, 0) AS UInt32) AS web_close_date_sk, CAST(ifNull(web_class, '') AS String) AS web_class, CAST(ifNull(web_manager, '') AS String) AS web_manager, CAST(ifNull(web_mkt_id, 0) AS Int64) AS web_mkt_id, CAST(ifNull(web_mkt_class, '') AS String) AS web_mkt_class, CAST(ifNull(web_mkt_desc, '') AS String) AS web_mkt_desc, CAST(ifNull(web_market_manager, '') AS String) AS web_market_manager, CAST(ifNull(web_company_id, 0) AS Int64) AS web_company_id, CAST(ifNull(web_company_name, '') AS FixedString(50)) AS web_company_name, CAST(ifNull(web_street_number, '') AS FixedString(10)) AS web_street_number, CAST(ifNull(web_street_name, '') AS String) AS web_street_name, CAST(ifNull(web_street_type, '') AS FixedString(15)) AS web_street_type, CAST(ifNull(web_suite_number, '') AS FixedString(10)) AS web_suite_number, CAST(ifNull(web_city, '') AS String) AS web_city, CAST(ifNull(web_county, '') AS String) AS web_county, CAST(ifNull(web_state, '') AS FixedString(2)) AS web_state, CAST(ifNull(web_zip, '') AS FixedString(10)) AS web_zip, CAST(ifNull(web_country, '') AS String) AS web_country, CAST(ifNull(web_gmt_offset, 0) AS Float64) AS web_gmt_offset, CAST(ifNull(web_tax_percentage, 0) AS Float64) AS web_tax_percentage" +rm -rf "${WORK}" +echo "tpcds: done" diff --git a/versions/prepare-data/tpch.sh b/versions/prepare-data/tpch.sh new file mode 100644 index 0000000000..cae40c9384 --- /dev/null +++ b/versions/prepare-data/tpch.sh @@ -0,0 +1,60 @@ +#!/usr/bin/env bash +# Prepare the TPC-H dataset as oldest-ClickHouse-compatible Native files. +# +# TPC-H is produced by the standard `dbgen` data generator at scale TPCH_SCALE +# (default 40, which yields ~10 GB of compressed Native across the 8 tables); +# GEN points at a generator that understands `INSTALL tpch; CALL dbgen(sf=N)` +# SQL. Each table is re-emitted with only types the earliest ClickHouse +# understands: +# Decimal(12,2) -> Float64 (old ClickHouse has no Decimal) +# CHAR(N) -> FixedString(N) +# the rest (UInt32 / Int32 / Date / String) map unchanged. +# The six dimension tables have no date column, so a constant synth_date is +# prepended for the legacy positional MergeTree engine (see create/create.sh). +# Column order and names match create/schema/
.columns exactly. + +set -euo pipefail +HERE="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" +CLICKHOUSE="${CLICKHOUSE:-$HOME/clickhouse}" +GEN="${GEN:-generator}" +SCALE="${TPCH_SCALE:-40}" +WORK="${HERE}/data/tpch-work" +mkdir -p "${WORK}" + +command -v "${CLICKHOUSE}" >/dev/null 2>&1 || CLICKHOUSE=clickhouse +[ -x "${GEN}" ] || command -v "${GEN}" >/dev/null 2>&1 || { + echo "generator '${GEN}' not found; set GEN to a data generator" >&2; exit 1; } + +echo "tpch: generating scale factor ${SCALE}" +rm -f "${WORK}/tpch.db" +"${GEN}" "${WORK}/tpch.db" <.columns. +conv() { + local t="$1" sel="$2" + "${CLICKHOUSE}" local --max_memory_usage 0 \ + --query "SELECT ${sel} FROM file('${WORK}/${t}.parquet','Parquet') FORMAT Native" \ + | zstd -q -6 -T0 -c > "${HERE}/data/tpch_${t}.native.zst" + echo " tpch_${t}.native.zst: $(du -h "${HERE}/data/tpch_${t}.native.zst" | cut -f1)" +} + +D="CAST('2000-01-01' AS Date) AS synth_date" +conv nation "${D}, CAST(n_nationkey AS UInt32) AS n_nationkey, CAST(n_name AS FixedString(25)) AS n_name, CAST(n_regionkey AS UInt32) AS n_regionkey, CAST(n_comment AS String) AS n_comment" +conv region "${D}, CAST(r_regionkey AS UInt32) AS r_regionkey, CAST(r_name AS FixedString(25)) AS r_name, CAST(r_comment AS String) AS r_comment" +conv part "${D}, CAST(p_partkey AS UInt32) AS p_partkey, CAST(p_name AS String) AS p_name, CAST(p_mfgr AS FixedString(25)) AS p_mfgr, CAST(p_brand AS FixedString(10)) AS p_brand, CAST(p_type AS String) AS p_type, CAST(p_size AS Int32) AS p_size, CAST(p_container AS FixedString(10)) AS p_container, CAST(p_retailprice AS Float64) AS p_retailprice, CAST(p_comment AS String) AS p_comment" +conv supplier "${D}, CAST(s_suppkey AS UInt32) AS s_suppkey, CAST(s_name AS FixedString(25)) AS s_name, CAST(s_address AS String) AS s_address, CAST(s_nationkey AS UInt32) AS s_nationkey, CAST(s_phone AS FixedString(15)) AS s_phone, CAST(s_acctbal AS Float64) AS s_acctbal, CAST(s_comment AS String) AS s_comment" +conv partsupp "${D}, CAST(ps_partkey AS UInt32) AS ps_partkey, CAST(ps_suppkey AS UInt32) AS ps_suppkey, CAST(ps_availqty AS Int32) AS ps_availqty, CAST(ps_supplycost AS Float64) AS ps_supplycost, CAST(ps_comment AS String) AS ps_comment" +conv customer "${D}, CAST(c_custkey AS UInt32) AS c_custkey, CAST(c_name AS String) AS c_name, CAST(c_address AS String) AS c_address, CAST(c_nationkey AS UInt32) AS c_nationkey, CAST(c_phone AS FixedString(15)) AS c_phone, CAST(c_acctbal AS Float64) AS c_acctbal, CAST(c_mktsegment AS FixedString(10)) AS c_mktsegment, CAST(c_comment AS String) AS c_comment" +conv orders "CAST(o_orderkey AS UInt32) AS o_orderkey, CAST(o_custkey AS UInt32) AS o_custkey, CAST(o_orderstatus AS FixedString(1)) AS o_orderstatus, CAST(o_totalprice AS Float64) AS o_totalprice, CAST(o_orderdate AS Date) AS o_orderdate, CAST(o_orderpriority AS FixedString(15)) AS o_orderpriority, CAST(o_clerk AS FixedString(15)) AS o_clerk, CAST(o_shippriority AS Int32) AS o_shippriority, CAST(o_comment AS String) AS o_comment" +conv lineitem "CAST(l_orderkey AS UInt32) AS l_orderkey, CAST(l_partkey AS UInt32) AS l_partkey, CAST(l_suppkey AS UInt32) AS l_suppkey, CAST(l_linenumber AS Int32) AS l_linenumber, CAST(l_quantity AS Float64) AS l_quantity, CAST(l_extendedprice AS Float64) AS l_extendedprice, CAST(l_discount AS Float64) AS l_discount, CAST(l_tax AS Float64) AS l_tax, CAST(l_returnflag AS FixedString(1)) AS l_returnflag, CAST(l_linestatus AS FixedString(1)) AS l_linestatus, CAST(l_shipdate AS Date) AS l_shipdate, CAST(l_commitdate AS Date) AS l_commitdate, CAST(l_receiptdate AS Date) AS l_receiptdate, CAST(l_shipinstruct AS FixedString(25)) AS l_shipinstruct, CAST(l_shipmode AS FixedString(10)) AS l_shipmode, CAST(l_comment AS String) AS l_comment" + +rm -rf "${WORK}" +echo "tpch: done" diff --git a/versions/prepare-data/uk.sh b/versions/prepare-data/uk.sh new file mode 100755 index 0000000000..efa4d0d398 --- /dev/null +++ b/versions/prepare-data/uk.sh @@ -0,0 +1,30 @@ +#!/usr/bin/env bash +# Prepare uk_price_paid.native - the UK land registry "price paid" dataset +# (single table, ~28M rows / ~200 MB), following the ClickHouse docs' preprocessing +# (split postcode, Y/N -> is_new, transform type/duration). Types are already +# oldest-compatible after LowCardinality(String) -> String and Enum8 -> String; +# the natural `date` serves the legacy MergeTree engine. + +set -euo pipefail +HERE="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" +CLICKHOUSE="${CLICKHOUSE:-$HOME/clickhouse}" +OUT="${HERE}/data/uk_price_paid.native.zst" +SRC="http://prod1.publicdata.landregistry.gov.uk.s3-website-eu-west-1.amazonaws.com/pp-complete.csv" +command -v "${CLICKHOUSE}" >/dev/null 2>&1 || CLICKHOUSE=clickhouse + +echo "uk: building from ${SRC} -> ${OUT}" +"${CLICKHOUSE}" local --max_memory_usage 0 --query " +SELECT + toUInt32(price_string) AS price, + toDate(parseDateTimeBestEffortUS(time)) AS date, + splitByChar(' ', postcode)[1] AS postcode1, + splitByChar(' ', postcode)[2] AS postcode2, + transform(a, ['T', 'S', 'D', 'F', 'O'], ['terraced', 'semi-detached', 'detached', 'flat', 'other'], '') AS type, + b = 'Y' AS is_new, + transform(c, ['F', 'L', 'U'], ['freehold', 'leasehold', 'unknown'], '') AS duration, + addr1, addr2, street, locality, town, district, county +FROM url('${SRC}', 'CSV', + 'uuid_string String, price_string String, time String, postcode String, a String, b String, c String, addr1 String, addr2 String, street String, locality String, town String, district String, county String, d String, e String') +SETTINGS max_http_get_redirects=10 +FORMAT Native" | zstd -q -6 -T0 -c > "${OUT}" +ls -l "${OUT}" diff --git a/versions/queries/coffeeshop.sql b/versions/queries/coffeeshop.sql new file mode 100644 index 0000000000..1e1515d7f9 --- /dev/null +++ b/versions/queries/coffeeshop.sql @@ -0,0 +1,17 @@ +SELECT f.order_date, l.city, SUM(f.sales_amount) AS total_sales, AVG(SUM(f.sales_amount)) OVER ( PARTITION BY l.city ORDER BY f.order_date ROWS BETWEEN 6 PRECEDING AND CURRENT ROW ) AS rolling_7day_avg FROM fact_sales f JOIN dim_locations l ON f.location_id = l.location_id GROUP BY f.order_date, l.city ORDER BY l.city, f.order_date +WITH monthly_sales AS ( SELECT DATE_TRUNC('month', f.order_date) AS sales_month, f.product_name, SUM(f.sales_amount) AS total_sales FROM fact_sales f GROUP BY DATE_TRUNC('month', f.order_date), f.product_name ) SELECT sales_month, product_name, total_sales, RANK() OVER (PARTITION BY sales_month ORDER BY total_sales DESC) AS sales_rank FROM monthly_sales ORDER BY sales_month, sales_rank +WITH season_discount AS ( SELECT l.city, l.state, f.season, AVG(f.discount_percentage) AS avg_discount FROM fact_sales f JOIN dim_locations l ON f.location_id = l.location_id GROUP BY l.city, l.state, f.season ) SELECT city, state, season, avg_discount, discount_rank FROM ( SELECT city, state, season, avg_discount, DENSE_RANK() OVER (PARTITION BY season ORDER BY avg_discount DESC) AS discount_rank FROM season_discount ) t WHERE discount_rank <= 3 ORDER BY season, discount_rank +SELECT f.order_date, f.product_name, p.standard_price, p.standard_cost, SUM(f.quantity) AS total_quantity_sold, SUM(f.sales_amount) AS total_sales_amount, (p.standard_price - p.standard_cost) * SUM(f.quantity) AS theoretical_margin FROM fact_sales f JOIN dim_products p ON f.product_name = p.name AND f.order_date BETWEEN p.from_date AND p.to_date GROUP BY f.order_date, f.product_name, p.standard_price, p.standard_cost ORDER BY f.order_date, f.product_name +WITH daily_city_qty AS ( SELECT f.order_date, l.city, SUM(f.quantity) AS daily_qty FROM fact_sales f JOIN dim_locations l ON f.location_id = l.location_id GROUP BY f.order_date, l.city ) SELECT order_date, city, daily_qty, SUM(daily_qty) OVER ( PARTITION BY city ORDER BY order_date ROWS BETWEEN 29 PRECEDING AND CURRENT ROW ) AS rolling_30day_qty FROM daily_city_qty ORDER BY city, order_date +WITH monthly_cat AS ( SELECT DATE_TRUNC('month', f.order_date) AS sales_month, p.category, SUM(f.sales_amount) AS monthly_revenue FROM fact_sales f JOIN dim_products p ON f.product_name = p.name AND f.order_date BETWEEN p.from_date AND p.to_date GROUP BY DATE_TRUNC('month', f.order_date), p.category ) SELECT coalesce(sales_month, DATE('1970-01-01')) AS sales_month, category, monthly_revenue FROM monthly_cat +WITH yearly_sales AS ( SELECT l.location_id, l.city, l.state, YEAR(f.order_date) AS sales_year, SUM(f.sales_amount) AS total_sales_year FROM fact_sales f JOIN dim_locations l ON f.location_id = l.location_id GROUP BY l.location_id, l.city, l.state, YEAR(f.order_date) ) SELECT city, state, SUM(CASE WHEN sales_year = 2023 THEN total_sales_year ELSE 0 END) AS sales_2023, SUM(CASE WHEN sales_year = 2024 THEN total_sales_year ELSE 0 END) AS sales_2024, (SUM(CASE WHEN sales_year = 2024 THEN total_sales_year ELSE 0 END) - SUM(CASE WHEN sales_year = 2023 THEN total_sales_year ELSE 0 END)) AS yoy_diff FROM yearly_sales GROUP BY city, state ORDER BY city, state +WITH city_quarter_subcat AS ( SELECT l.city, DATE_TRUNC('quarter', f.order_date) AS sales_quarter, p.subcategory, SUM(f.sales_amount) AS total_sales FROM fact_sales f JOIN dim_locations l ON f.location_id = l.location_id JOIN dim_products p ON f.product_name = p.name AND f.order_date BETWEEN p.from_date AND p.to_date GROUP BY l.city, DATE_TRUNC('quarter', f.order_date), p.subcategory ) SELECT city, sales_quarter, subcategory, total_sales, RANK() OVER (PARTITION BY city, sales_quarter ORDER BY total_sales DESC) AS subcat_rank FROM city_quarter_subcat ORDER BY city, sales_quarter, subcat_rank +WITH daily_discount AS ( SELECT l.city, f.order_date, AVG(f.discount_percentage) AS avg_discount FROM fact_sales f JOIN dim_locations l ON f.location_id = l.location_id GROUP BY l.city, f.order_date ) SELECT city, order_date, avg_discount, AVG(avg_discount) OVER ( PARTITION BY city ORDER BY order_date ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW ) AS cumulative_avg_discount FROM daily_discount ORDER BY city, order_date +WITH daily_orders AS ( SELECT f.order_date, l.city, COUNT(DISTINCT f.order_id) AS daily_distinct_orders FROM fact_sales f JOIN dim_locations l ON f.location_id = l.location_id GROUP BY l.city, f.order_date ) SELECT coalesce(order_date, DATE('1970-01-01')) AS order_date, coalesce(city, '') AS city, daily_distinct_orders, SUM(daily_distinct_orders) OVER ( PARTITION BY city ORDER BY order_date ROWS BETWEEN 89 PRECEDING AND CURRENT ROW ) AS rolling_90d_distinct_orders FROM daily_orders ORDER BY city, order_date +WITH city_quarter_subcat AS ( SELECT l.city, DATE_TRUNC('quarter', f.order_date) AS sales_quarter, p.subcategory, SUM(f.sales_amount) AS total_sales FROM fact_sales f JOIN dim_locations l ON f.location_id = l.location_id JOIN dim_products p ON f.product_name = p.name AND f.order_date BETWEEN p.from_date AND p.to_date WHERE l.city IN ('Charlotte', 'Houston') GROUP BY l.city, DATE_TRUNC('quarter', f.order_date), p.subcategory ) SELECT city, sales_quarter, subcategory, total_sales, RANK() OVER (PARTITION BY city, sales_quarter ORDER BY total_sales DESC) AS subcat_rank FROM city_quarter_subcat ORDER BY city, sales_quarter, subcat_rank +WITH city_quarter_subcat AS ( SELECT l.city, DATE_TRUNC('quarter', f.order_date) AS sales_quarter, p.subcategory, SUM(f.sales_amount) AS total_sales FROM fact_sales f JOIN dim_locations l ON f.location_id = l.location_id JOIN dim_products p ON f.product_name = p.name AND f.order_date BETWEEN p.from_date AND p.to_date WHERE l.city IN ('Charlotte', 'Houston') AND DATE_TRUNC('quarter', f.order_date) IN ( DATE('2023-01-01'), DATE('2023-04-01'), DATE('2024-01-01'), DATE('2024-04-01') ) GROUP BY l.city, DATE_TRUNC('quarter', f.order_date), p.subcategory ) SELECT city, sales_quarter, subcategory, total_sales, RANK() OVER (PARTITION BY city, sales_quarter ORDER BY total_sales DESC) AS subcat_rank FROM city_quarter_subcat ORDER BY city, sales_quarter, subcat_rank +WITH city_quarter_subcat AS ( SELECT l.city, DATE_TRUNC('quarter', f.order_date) AS sales_quarter, p.subcategory, SUM(f.sales_amount) AS total_sales FROM fact_sales f JOIN dim_locations l ON f.location_id = l.location_id JOIN dim_products p ON f.product_name = p.name AND f.order_date BETWEEN p.from_date AND p.to_date WHERE l.city = 'Austin' AND DATE_TRUNC('quarter', f.order_date) IN ( DATE('2023-01-01'), DATE('2023-04-01'), DATE('2024-01-01'), DATE('2024-04-01') ) GROUP BY l.city, DATE_TRUNC('quarter', f.order_date), p.subcategory ) SELECT city, sales_quarter, subcategory, total_sales, RANK() OVER (PARTITION BY city, sales_quarter ORDER BY total_sales DESC) AS subcat_rank FROM city_quarter_subcat ORDER BY city, sales_quarter, subcat_rank +WITH city_quarter_subcat AS ( SELECT l.city, DATE_TRUNC('quarter', f.order_date) AS sales_quarter, p.subcategory, SUM(f.sales_amount) AS total_sales FROM fact_sales f JOIN dim_locations l ON f.location_id = l.location_id JOIN dim_products p ON f.product_name = p.name AND f.order_date BETWEEN p.from_date AND p.to_date WHERE DATE_TRUNC('quarter', f.order_date) IN ( DATE('2023-01-01'), DATE('2023-04-01'), DATE('2024-01-01'), DATE('2024-04-01') ) GROUP BY l.city, DATE_TRUNC('quarter', f.order_date), p.subcategory ) SELECT city, sales_quarter, subcategory, total_sales, RANK() OVER (PARTITION BY city, sales_quarter ORDER BY total_sales DESC) AS subcat_rank FROM city_quarter_subcat ORDER BY city, sales_quarter, subcat_rank +WITH base_data AS ( SELECT f.location_id as location_id, l.city, f.product_name, toStartOfQuarter(f.order_date) AS sales_quarter, sum(f.sales_amount) AS total_sales, sum(f.sales_amount * (f.discount_percentage / 100.0)) AS total_discount, sum(f.quantity * p.standard_cost) AS total_cogs FROM fact_sales AS f INNER JOIN dim_products AS p ON f.product_name = p.name AND f.order_date BETWEEN p.from_date AND p.to_date INNER JOIN dim_locations AS l ON f.location_id = l.location_id WHERE f.order_date BETWEEN toDate('2022-01-01') AND toDate('2024-12-31') GROUP BY f.location_id, l.city, f.product_name, sales_quarter ), with_profit AS ( SELECT *, total_sales - total_discount - total_cogs AS profit FROM base_data ) SELECT city, product_name, sales_quarter, profit, lagInFrame(profit) OVER w AS prev_profit, round( if(prev_profit = 0 OR prev_profit IS NULL, NULL, 100.0 * (profit - prev_profit) / prev_profit), 2 ) AS yoy_profit_pct FROM with_profit WINDOW w AS ( PARTITION BY location_id, product_name ORDER BY sales_quarter ) +WITH seasonal_data AS ( SELECT l.state, f.season, p.category, SUM(f.sales_amount) AS total_sales, SUM(f.quantity) AS total_units, COUNT(DISTINCT f.order_id) AS order_count FROM fact_sales f JOIN dim_products p ON f.product_name = p.name AND DATE(f.order_date) BETWEEN DATE(p.from_date) AND DATE(p.to_date) JOIN dim_locations l ON f.location_id = l.location_id WHERE DATE(f.order_date) BETWEEN DATE('2023-01-01') AND DATE('2024-06-30') GROUP BY l.state, f.season, p.category ), ranked AS ( SELECT *, DENSE_RANK() OVER (PARTITION BY state, season ORDER BY total_sales DESC) AS category_rank FROM seasonal_data ) SELECT * FROM ranked WHERE category_rank <= 3 ORDER BY state, season, category_rank +WITH raw_agg AS ( SELECT l.state, f.season, p.category, SUM(f.sales_amount) AS total_sales, SUM(f.quantity) AS total_units, COUNT(DISTINCT f.order_id) AS order_count FROM fact_sales AS f JOIN dim_products AS p ON f.product_id = p.product_id AND DATE(f.order_date) BETWEEN DATE(p.from_date) AND DATE(p.to_date) JOIN dim_locations AS l ON f.location_id = l.location_id WHERE l.region = 'West' AND f.time_of_day = 'Morning' AND p.name = 'Frappe' AND DATE(f.order_date) BETWEEN DATE('2023-01-01') AND DATE('2024-06-30') GROUP BY l.state, f.season, p.category ), seasonal_data AS ( SELECT state, season, category, total_sales, total_units, order_count, SUM(total_sales) OVER (PARTITION BY state, season) AS season_total_sales FROM raw_agg ), ranked AS ( SELECT state, season, category, total_sales, total_units, order_count, season_total_sales, ROUND(100.0 * total_sales / season_total_sales, 2) AS pct_of_season, DENSE_RANK() OVER ( PARTITION BY state, season ORDER BY total_sales DESC ) AS category_rank FROM seasonal_data ) SELECT state, season, category, total_sales, total_units, order_count, pct_of_season, category_rank FROM ranked WHERE category_rank <= 3 ORDER BY state, season, category_rank diff --git a/versions/queries/job.sql b/versions/queries/job.sql new file mode 100644 index 0000000000..784d5fda5b --- /dev/null +++ b/versions/queries/job.sql @@ -0,0 +1,113 @@ +SELECT MIN(mc.note) AS production_note, MIN(t.title) AS movie_title, MIN(t.production_year) AS movie_year FROM company_type AS ct, info_type AS it, movie_companies AS mc, movie_info_idx AS mi_idx, title AS t WHERE ct.kind = 'production companies' AND it.info = 'top 250 rank' AND mc.note NOT LIKE '%(as Metro-Goldwyn-Mayer Pictures)%' AND (mc.note LIKE '%(co-production)%' OR mc.note LIKE '%(presents)%') AND ct.id = mc.company_type_id AND t.id = mc.movie_id AND t.id = mi_idx.movie_id AND mc.movie_id = mi_idx.movie_id AND it.id = mi_idx.info_type_id +SELECT MIN(mc.note) AS production_note, MIN(t.title) AS movie_title, MIN(t.production_year) AS movie_year FROM company_type AS ct, info_type AS it, movie_companies AS mc, movie_info_idx AS mi_idx, title AS t WHERE ct.kind = 'production companies' AND it.info = 'bottom 10 rank' AND mc.note NOT LIKE '%(as Metro-Goldwyn-Mayer Pictures)%' AND t.production_year BETWEEN 2005 AND 2010 AND ct.id = mc.company_type_id AND t.id = mc.movie_id AND t.id = mi_idx.movie_id AND mc.movie_id = mi_idx.movie_id AND it.id = mi_idx.info_type_id +SELECT MIN(mc.note) AS production_note, MIN(t.title) AS movie_title, MIN(t.production_year) AS movie_year FROM company_type AS ct, info_type AS it, movie_companies AS mc, movie_info_idx AS mi_idx, title AS t WHERE ct.kind = 'production companies' AND it.info = 'top 250 rank' AND mc.note NOT LIKE '%(as Metro-Goldwyn-Mayer Pictures)%' AND (mc.note LIKE '%(co-production)%') AND t.production_year >2010 AND ct.id = mc.company_type_id AND t.id = mc.movie_id AND t.id = mi_idx.movie_id AND mc.movie_id = mi_idx.movie_id AND it.id = mi_idx.info_type_id +SELECT MIN(mc.note) AS production_note, MIN(t.title) AS movie_title, MIN(t.production_year) AS movie_year FROM company_type AS ct, info_type AS it, movie_companies AS mc, movie_info_idx AS mi_idx, title AS t WHERE ct.kind = 'production companies' AND it.info = 'bottom 10 rank' AND mc.note NOT LIKE '%(as Metro-Goldwyn-Mayer Pictures)%' AND t.production_year >2000 AND ct.id = mc.company_type_id AND t.id = mc.movie_id AND t.id = mi_idx.movie_id AND mc.movie_id = mi_idx.movie_id AND it.id = mi_idx.info_type_id +SELECT MIN(t.title) AS movie_title FROM company_name AS cn, keyword AS k, movie_companies AS mc, movie_keyword AS mk, title AS t WHERE cn.country_code ='[de]' AND k.keyword ='character-name-in-title' AND cn.id = mc.company_id AND mc.movie_id = t.id AND t.id = mk.movie_id AND mk.keyword_id = k.id AND mc.movie_id = mk.movie_id +SELECT MIN(t.title) AS movie_title FROM company_name AS cn, keyword AS k, movie_companies AS mc, movie_keyword AS mk, title AS t WHERE cn.country_code ='[nl]' AND k.keyword ='character-name-in-title' AND cn.id = mc.company_id AND mc.movie_id = t.id AND t.id = mk.movie_id AND mk.keyword_id = k.id AND mc.movie_id = mk.movie_id +SELECT MIN(t.title) AS movie_title FROM company_name AS cn, keyword AS k, movie_companies AS mc, movie_keyword AS mk, title AS t WHERE cn.country_code ='[sm]' AND k.keyword ='character-name-in-title' AND cn.id = mc.company_id AND mc.movie_id = t.id AND t.id = mk.movie_id AND mk.keyword_id = k.id AND mc.movie_id = mk.movie_id +SELECT MIN(t.title) AS movie_title FROM company_name AS cn, keyword AS k, movie_companies AS mc, movie_keyword AS mk, title AS t WHERE cn.country_code ='[us]' AND k.keyword ='character-name-in-title' AND cn.id = mc.company_id AND mc.movie_id = t.id AND t.id = mk.movie_id AND mk.keyword_id = k.id AND mc.movie_id = mk.movie_id +SELECT MIN(t.title) AS movie_title FROM keyword AS k, movie_info AS mi, movie_keyword AS mk, title AS t WHERE k.keyword LIKE '%sequel%' AND mi.info IN ('Sweden', 'Norway', 'Germany', 'Denmark', 'Swedish', 'Denish', 'Norwegian', 'German') AND t.production_year > 2005 AND t.id = mi.movie_id AND t.id = mk.movie_id AND mk.movie_id = mi.movie_id AND k.id = mk.keyword_id +SELECT MIN(t.title) AS movie_title FROM keyword AS k, movie_info AS mi, movie_keyword AS mk, title AS t WHERE k.keyword LIKE '%sequel%' AND mi.info IN ('Bulgaria') AND t.production_year > 2010 AND t.id = mi.movie_id AND t.id = mk.movie_id AND mk.movie_id = mi.movie_id AND k.id = mk.keyword_id +SELECT MIN(t.title) AS movie_title FROM keyword AS k, movie_info AS mi, movie_keyword AS mk, title AS t WHERE k.keyword LIKE '%sequel%' AND mi.info IN ('Sweden', 'Norway', 'Germany', 'Denmark', 'Swedish', 'Denish', 'Norwegian', 'German', 'USA', 'American') AND t.production_year > 1990 AND t.id = mi.movie_id AND t.id = mk.movie_id AND mk.movie_id = mi.movie_id AND k.id = mk.keyword_id +SELECT MIN(mi_idx.info) AS rating, MIN(t.title) AS movie_title FROM info_type AS it, keyword AS k, movie_info_idx AS mi_idx, movie_keyword AS mk, title AS t WHERE it.info ='rating' AND k.keyword LIKE '%sequel%' AND mi_idx.info > '5.0' AND t.production_year > 2005 AND t.id = mi_idx.movie_id AND t.id = mk.movie_id AND mk.movie_id = mi_idx.movie_id AND k.id = mk.keyword_id AND it.id = mi_idx.info_type_id +SELECT MIN(mi_idx.info) AS rating, MIN(t.title) AS movie_title FROM info_type AS it, keyword AS k, movie_info_idx AS mi_idx, movie_keyword AS mk, title AS t WHERE it.info ='rating' AND k.keyword LIKE '%sequel%' AND mi_idx.info > '9.0' AND t.production_year > 2010 AND t.id = mi_idx.movie_id AND t.id = mk.movie_id AND mk.movie_id = mi_idx.movie_id AND k.id = mk.keyword_id AND it.id = mi_idx.info_type_id +SELECT MIN(mi_idx.info) AS rating, MIN(t.title) AS movie_title FROM info_type AS it, keyword AS k, movie_info_idx AS mi_idx, movie_keyword AS mk, title AS t WHERE it.info ='rating' AND k.keyword LIKE '%sequel%' AND mi_idx.info > '2.0' AND t.production_year > 1990 AND t.id = mi_idx.movie_id AND t.id = mk.movie_id AND mk.movie_id = mi_idx.movie_id AND k.id = mk.keyword_id AND it.id = mi_idx.info_type_id +SELECT MIN(t.title) AS typical_european_movie FROM company_type AS ct, info_type AS it, movie_companies AS mc, movie_info AS mi, title AS t WHERE ct.kind = 'production companies' AND mc.note LIKE '%(theatrical)%' AND mc.note LIKE '%(France)%' AND mi.info IN ('Sweden', 'Norway', 'Germany', 'Denmark', 'Swedish', 'Denish', 'Norwegian', 'German') AND t.production_year > 2005 AND t.id = mi.movie_id AND t.id = mc.movie_id AND mc.movie_id = mi.movie_id AND ct.id = mc.company_type_id AND it.id = mi.info_type_id +SELECT MIN(t.title) AS american_vhs_movie FROM company_type AS ct, info_type AS it, movie_companies AS mc, movie_info AS mi, title AS t WHERE ct.kind = 'production companies' AND mc.note LIKE '%(VHS)%' AND mc.note LIKE '%(USA)%' AND mc.note LIKE '%(1994)%' AND mi.info IN ('USA', 'America') AND t.production_year > 2010 AND t.id = mi.movie_id AND t.id = mc.movie_id AND mc.movie_id = mi.movie_id AND ct.id = mc.company_type_id AND it.id = mi.info_type_id +SELECT MIN(t.title) AS american_movie FROM company_type AS ct, info_type AS it, movie_companies AS mc, movie_info AS mi, title AS t WHERE ct.kind = 'production companies' AND mc.note NOT LIKE '%(TV)%' AND mc.note LIKE '%(USA)%' AND mi.info IN ('Sweden', 'Norway', 'Germany', 'Denmark', 'Swedish', 'Denish', 'Norwegian', 'German', 'USA', 'American') AND t.production_year > 1990 AND t.id = mi.movie_id AND t.id = mc.movie_id AND mc.movie_id = mi.movie_id AND ct.id = mc.company_type_id AND it.id = mi.info_type_id +SELECT MIN(k.keyword) AS movie_keyword, MIN(n.name) AS actor_name, MIN(t.title) AS marvel_movie FROM cast_info AS ci, keyword AS k, movie_keyword AS mk, name AS n, title AS t WHERE k.keyword = 'marvel-cinematic-universe' AND n.name LIKE '%Downey%Robert%' AND t.production_year > 2010 AND k.id = mk.keyword_id AND t.id = mk.movie_id AND t.id = ci.movie_id AND ci.movie_id = mk.movie_id AND n.id = ci.person_id +SELECT MIN(k.keyword) AS movie_keyword, MIN(n.name) AS actor_name, MIN(t.title) AS hero_movie FROM cast_info AS ci, keyword AS k, movie_keyword AS mk, name AS n, title AS t WHERE k.keyword IN ('superhero', 'sequel', 'second-part', 'marvel-comics', 'based-on-comic', 'tv-special', 'fight', 'violence') AND n.name LIKE '%Downey%Robert%' AND t.production_year > 2014 AND k.id = mk.keyword_id AND t.id = mk.movie_id AND t.id = ci.movie_id AND ci.movie_id = mk.movie_id AND n.id = ci.person_id +SELECT MIN(k.keyword) AS movie_keyword, MIN(n.name) AS actor_name, MIN(t.title) AS marvel_movie FROM cast_info AS ci, keyword AS k, movie_keyword AS mk, name AS n, title AS t WHERE k.keyword = 'marvel-cinematic-universe' AND n.name LIKE '%Downey%Robert%' AND t.production_year > 2014 AND k.id = mk.keyword_id AND t.id = mk.movie_id AND t.id = ci.movie_id AND ci.movie_id = mk.movie_id AND n.id = ci.person_id +SELECT MIN(k.keyword) AS movie_keyword, MIN(n.name) AS actor_name, MIN(t.title) AS hero_movie FROM cast_info AS ci, keyword AS k, movie_keyword AS mk, name AS n, title AS t WHERE k.keyword IN ('superhero', 'sequel', 'second-part', 'marvel-comics', 'based-on-comic', 'tv-special', 'fight', 'violence') AND n.name LIKE '%Downey%Robert%' AND t.production_year > 2000 AND k.id = mk.keyword_id AND t.id = mk.movie_id AND t.id = ci.movie_id AND ci.movie_id = mk.movie_id AND n.id = ci.person_id +SELECT MIN(k.keyword) AS movie_keyword, MIN(n.name) AS actor_name, MIN(t.title) AS marvel_movie FROM cast_info AS ci, keyword AS k, movie_keyword AS mk, name AS n, title AS t WHERE k.keyword = 'marvel-cinematic-universe' AND n.name LIKE '%Downey%Robert%' AND t.production_year > 2000 AND k.id = mk.keyword_id AND t.id = mk.movie_id AND t.id = ci.movie_id AND ci.movie_id = mk.movie_id AND n.id = ci.person_id +SELECT MIN(k.keyword) AS movie_keyword, MIN(n.name) AS actor_name, MIN(t.title) AS hero_movie FROM cast_info AS ci, keyword AS k, movie_keyword AS mk, name AS n, title AS t WHERE k.keyword IN ('superhero', 'sequel', 'second-part', 'marvel-comics', 'based-on-comic', 'tv-special', 'fight', 'violence') AND t.production_year > 2000 AND k.id = mk.keyword_id AND t.id = mk.movie_id AND t.id = ci.movie_id AND ci.movie_id = mk.movie_id AND n.id = ci.person_id +SELECT MIN(n.name) AS of_person, MIN(t.title) AS biography_movie FROM aka_name AS an, cast_info AS ci, info_type AS it, link_type AS lt, movie_link AS ml, name AS n, person_info AS pi, title AS t WHERE an.name LIKE '%a%' AND it.info ='mini biography' AND lt.link ='features' AND n.name_pcode_cf BETWEEN 'A' AND 'F' AND (n.gender='m' OR (n.gender = 'f' AND n.name LIKE 'B%')) AND pi.note ='Volker Boehm' AND t.production_year BETWEEN 1980 AND 1995 AND n.id = an.person_id AND n.id = pi.person_id AND ci.person_id = n.id AND t.id = ci.movie_id AND ml.linked_movie_id = t.id AND lt.id = ml.link_type_id AND it.id = pi.info_type_id AND pi.person_id = an.person_id AND pi.person_id = ci.person_id AND an.person_id = ci.person_id AND ci.movie_id = ml.linked_movie_id +SELECT MIN(n.name) AS of_person, MIN(t.title) AS biography_movie FROM aka_name AS an, cast_info AS ci, info_type AS it, link_type AS lt, movie_link AS ml, name AS n, person_info AS pi, title AS t WHERE an.name LIKE '%a%' AND it.info ='mini biography' AND lt.link ='features' AND n.name_pcode_cf LIKE 'D%' AND n.gender='m' AND pi.note ='Volker Boehm' AND t.production_year BETWEEN 1980 AND 1984 AND n.id = an.person_id AND n.id = pi.person_id AND ci.person_id = n.id AND t.id = ci.movie_id AND ml.linked_movie_id = t.id AND lt.id = ml.link_type_id AND it.id = pi.info_type_id AND pi.person_id = an.person_id AND pi.person_id = ci.person_id AND an.person_id = ci.person_id AND ci.movie_id = ml.linked_movie_id +SELECT MIN(n.name) AS cast_member_name, MIN(pi.info) AS cast_member_info FROM aka_name AS an, cast_info AS ci, info_type AS it, link_type AS lt, movie_link AS ml, name AS n, person_info AS pi, title AS t WHERE an.name IS NOT NULL AND (an.name LIKE '%a%' OR an.name LIKE 'A%') AND it.info ='mini biography' AND lt.link IN ('references', 'referenced in', 'features', 'featured in') AND n.name_pcode_cf BETWEEN 'A' AND 'F' AND (n.gender='m' OR (n.gender = 'f' AND n.name LIKE 'A%')) AND pi.note IS NOT NULL AND t.production_year BETWEEN 1980 AND 2010 AND n.id = an.person_id AND n.id = pi.person_id AND ci.person_id = n.id AND t.id = ci.movie_id AND ml.linked_movie_id = t.id AND lt.id = ml.link_type_id AND it.id = pi.info_type_id AND pi.person_id = an.person_id AND pi.person_id = ci.person_id AND an.person_id = ci.person_id AND ci.movie_id = ml.linked_movie_id +SELECT MIN(an1.name) AS actress_pseudonym, MIN(t.title) AS japanese_movie_dubbed FROM aka_name AS an1, cast_info AS ci, company_name AS cn, movie_companies AS mc, name AS n1, role_type AS rt, title AS t WHERE ci.note ='(voice: English version)' AND cn.country_code ='[jp]' AND mc.note LIKE '%(Japan)%' AND mc.note NOT LIKE '%(USA)%' AND n1.name LIKE '%Yo%' AND n1.name NOT LIKE '%Yu%' AND rt.role ='actress' AND an1.person_id = n1.id AND n1.id = ci.person_id AND ci.movie_id = t.id AND t.id = mc.movie_id AND mc.company_id = cn.id AND ci.role_id = rt.id AND an1.person_id = ci.person_id AND ci.movie_id = mc.movie_id +SELECT MIN(an.name) AS acress_pseudonym, MIN(t.title) AS japanese_anime_movie FROM aka_name AS an, cast_info AS ci, company_name AS cn, movie_companies AS mc, name AS n, role_type AS rt, title AS t WHERE ci.note ='(voice: English version)' AND cn.country_code ='[jp]' AND mc.note LIKE '%(Japan)%' AND mc.note NOT LIKE '%(USA)%' AND (mc.note LIKE '%(2006)%' OR mc.note LIKE '%(2007)%') AND n.name LIKE '%Yo%' AND n.name NOT LIKE '%Yu%' AND rt.role ='actress' AND t.production_year BETWEEN 2006 AND 2007 AND (t.title LIKE 'One Piece%' OR t.title LIKE 'Dragon Ball Z%') AND an.person_id = n.id AND n.id = ci.person_id AND ci.movie_id = t.id AND t.id = mc.movie_id AND mc.company_id = cn.id AND ci.role_id = rt.id AND an.person_id = ci.person_id AND ci.movie_id = mc.movie_id +SELECT MIN(a1.name) AS writer_pseudo_name, MIN(t.title) AS movie_title FROM aka_name AS a1, cast_info AS ci, company_name AS cn, movie_companies AS mc, name AS n1, role_type AS rt, title AS t WHERE cn.country_code ='[us]' AND rt.role ='writer' AND a1.person_id = n1.id AND n1.id = ci.person_id AND ci.movie_id = t.id AND t.id = mc.movie_id AND mc.company_id = cn.id AND ci.role_id = rt.id AND a1.person_id = ci.person_id AND ci.movie_id = mc.movie_id +SELECT MIN(an1.name) AS costume_designer_pseudo, MIN(t.title) AS movie_with_costumes FROM aka_name AS an1, cast_info AS ci, company_name AS cn, movie_companies AS mc, name AS n1, role_type AS rt, title AS t WHERE cn.country_code ='[us]' AND rt.role ='costume designer' AND an1.person_id = n1.id AND n1.id = ci.person_id AND ci.movie_id = t.id AND t.id = mc.movie_id AND mc.company_id = cn.id AND ci.role_id = rt.id AND an1.person_id = ci.person_id AND ci.movie_id = mc.movie_id +SELECT MIN(an.name) AS alternative_name, MIN(chn.name) AS character_name, MIN(t.title) AS movie FROM aka_name AS an, char_name AS chn, cast_info AS ci, company_name AS cn, movie_companies AS mc, name AS n, role_type AS rt, title AS t WHERE ci.note IN ('(voice)', '(voice: Japanese version)', '(voice) (uncredited)', '(voice: English version)') AND cn.country_code ='[us]' AND mc.note IS NOT NULL AND (mc.note LIKE '%(USA)%' OR mc.note LIKE '%(worldwide)%') AND n.gender ='f' AND n.name LIKE '%Ang%' AND rt.role ='actress' AND t.production_year BETWEEN 2005 AND 2015 AND ci.movie_id = t.id AND t.id = mc.movie_id AND ci.movie_id = mc.movie_id AND mc.company_id = cn.id AND ci.role_id = rt.id AND n.id = ci.person_id AND chn.id = ci.person_role_id AND an.person_id = n.id AND an.person_id = ci.person_id +SELECT MIN(an.name) AS alternative_name, MIN(chn.name) AS voiced_character, MIN(n.name) AS voicing_actress, MIN(t.title) AS american_movie FROM aka_name AS an, char_name AS chn, cast_info AS ci, company_name AS cn, movie_companies AS mc, name AS n, role_type AS rt, title AS t WHERE ci.note = '(voice)' AND cn.country_code ='[us]' AND mc.note LIKE '%(200%)%' AND (mc.note LIKE '%(USA)%' OR mc.note LIKE '%(worldwide)%') AND n.gender ='f' AND n.name LIKE '%Angel%' AND rt.role ='actress' AND t.production_year BETWEEN 2007 AND 2010 AND ci.movie_id = t.id AND t.id = mc.movie_id AND ci.movie_id = mc.movie_id AND mc.company_id = cn.id AND ci.role_id = rt.id AND n.id = ci.person_id AND chn.id = ci.person_role_id AND an.person_id = n.id AND an.person_id = ci.person_id +SELECT MIN(an.name) AS alternative_name, MIN(chn.name) AS voiced_character_name, MIN(n.name) AS voicing_actress, MIN(t.title) AS american_movie FROM aka_name AS an, char_name AS chn, cast_info AS ci, company_name AS cn, movie_companies AS mc, name AS n, role_type AS rt, title AS t WHERE ci.note IN ('(voice)', '(voice: Japanese version)', '(voice) (uncredited)', '(voice: English version)') AND cn.country_code ='[us]' AND n.gender ='f' AND n.name LIKE '%An%' AND rt.role ='actress' AND ci.movie_id = t.id AND t.id = mc.movie_id AND ci.movie_id = mc.movie_id AND mc.company_id = cn.id AND ci.role_id = rt.id AND n.id = ci.person_id AND chn.id = ci.person_role_id AND an.person_id = n.id AND an.person_id = ci.person_id +SELECT MIN(an.name) AS alternative_name, MIN(chn.name) AS voiced_char_name, MIN(n.name) AS voicing_actress, MIN(t.title) AS american_movie FROM aka_name AS an, char_name AS chn, cast_info AS ci, company_name AS cn, movie_companies AS mc, name AS n, role_type AS rt, title AS t WHERE ci.note IN ('(voice)', '(voice: Japanese version)', '(voice) (uncredited)', '(voice: English version)') AND cn.country_code ='[us]' AND n.gender ='f' AND rt.role ='actress' AND ci.movie_id = t.id AND t.id = mc.movie_id AND ci.movie_id = mc.movie_id AND mc.company_id = cn.id AND ci.role_id = rt.id AND n.id = ci.person_id AND chn.id = ci.person_role_id AND an.person_id = n.id AND an.person_id = ci.person_id +SELECT MIN(chn.name) AS uncredited_voiced_character, MIN(t.title) AS russian_movie FROM char_name AS chn, cast_info AS ci, company_name AS cn, company_type AS ct, movie_companies AS mc, role_type AS rt, title AS t WHERE ci.note LIKE '%(voice)%' AND ci.note LIKE '%(uncredited)%' AND cn.country_code = '[ru]' AND rt.role = 'actor' AND t.production_year > 2005 AND t.id = mc.movie_id AND t.id = ci.movie_id AND ci.movie_id = mc.movie_id AND chn.id = ci.person_role_id AND rt.id = ci.role_id AND cn.id = mc.company_id AND ct.id = mc.company_type_id +SELECT MIN(chn.name) AS character, MIN(t.title) AS russian_mov_with_actor_producer FROM char_name AS chn, cast_info AS ci, company_name AS cn, company_type AS ct, movie_companies AS mc, role_type AS rt, title AS t WHERE ci.note LIKE '%(producer)%' AND cn.country_code = '[ru]' AND rt.role = 'actor' AND t.production_year > 2010 AND t.id = mc.movie_id AND t.id = ci.movie_id AND ci.movie_id = mc.movie_id AND chn.id = ci.person_role_id AND rt.id = ci.role_id AND cn.id = mc.company_id AND ct.id = mc.company_type_id +SELECT MIN(chn.name) AS character, MIN(t.title) AS movie_with_american_producer FROM char_name AS chn, cast_info AS ci, company_name AS cn, company_type AS ct, movie_companies AS mc, role_type AS rt, title AS t WHERE ci.note LIKE '%(producer)%' AND cn.country_code = '[us]' AND t.production_year > 1990 AND t.id = mc.movie_id AND t.id = ci.movie_id AND ci.movie_id = mc.movie_id AND chn.id = ci.person_role_id AND rt.id = ci.role_id AND cn.id = mc.company_id AND ct.id = mc.company_type_id +SELECT MIN(cn.name) AS from_company, MIN(lt.link) AS movie_link_type, MIN(t.title) AS non_polish_sequel_movie FROM company_name AS cn, company_type AS ct, keyword AS k, link_type AS lt, movie_companies AS mc, movie_keyword AS mk, movie_link AS ml, title AS t WHERE cn.country_code !='[pl]' AND (cn.name LIKE '%Film%' OR cn.name LIKE '%Warner%') AND ct.kind ='production companies' AND k.keyword ='sequel' AND lt.link LIKE '%follow%' AND mc.note IS NULL AND t.production_year BETWEEN 1950 AND 2000 AND lt.id = ml.link_type_id AND ml.movie_id = t.id AND t.id = mk.movie_id AND mk.keyword_id = k.id AND t.id = mc.movie_id AND mc.company_type_id = ct.id AND mc.company_id = cn.id AND ml.movie_id = mk.movie_id AND ml.movie_id = mc.movie_id AND mk.movie_id = mc.movie_id +SELECT MIN(cn.name) AS from_company, MIN(lt.link) AS movie_link_type, MIN(t.title) AS sequel_movie FROM company_name AS cn, company_type AS ct, keyword AS k, link_type AS lt, movie_companies AS mc, movie_keyword AS mk, movie_link AS ml, title AS t WHERE cn.country_code !='[pl]' AND (cn.name LIKE '%Film%' OR cn.name LIKE '%Warner%') AND ct.kind ='production companies' AND k.keyword ='sequel' AND lt.link LIKE '%follows%' AND mc.note IS NULL AND t.production_year = 1998 AND t.title LIKE '%Money%' AND lt.id = ml.link_type_id AND ml.movie_id = t.id AND t.id = mk.movie_id AND mk.keyword_id = k.id AND t.id = mc.movie_id AND mc.company_type_id = ct.id AND mc.company_id = cn.id AND ml.movie_id = mk.movie_id AND ml.movie_id = mc.movie_id AND mk.movie_id = mc.movie_id +SELECT MIN(cn.name) AS from_company, MIN(mc.note) AS production_note, MIN(t.title) AS movie_based_on_book FROM company_name AS cn, company_type AS ct, keyword AS k, link_type AS lt, movie_companies AS mc, movie_keyword AS mk, movie_link AS ml, title AS t WHERE cn.country_code !='[pl]' AND (cn.name LIKE '20th Century Fox%' OR cn.name LIKE 'Twentieth Century Fox%') AND ct.kind != 'production companies' AND ct.kind IS NOT NULL AND k.keyword IN ('sequel', 'revenge', 'based-on-novel') AND mc.note IS NOT NULL AND t.production_year > 1950 AND lt.id = ml.link_type_id AND ml.movie_id = t.id AND t.id = mk.movie_id AND mk.keyword_id = k.id AND t.id = mc.movie_id AND mc.company_type_id = ct.id AND mc.company_id = cn.id AND ml.movie_id = mk.movie_id AND ml.movie_id = mc.movie_id AND mk.movie_id = mc.movie_id +SELECT MIN(cn.name) AS from_company, MIN(mc.note) AS production_note, MIN(t.title) AS movie_based_on_book FROM company_name AS cn, company_type AS ct, keyword AS k, link_type AS lt, movie_companies AS mc, movie_keyword AS mk, movie_link AS ml, title AS t WHERE cn.country_code !='[pl]' AND ct.kind != 'production companies' AND ct.kind IS NOT NULL AND k.keyword IN ('sequel', 'revenge', 'based-on-novel') AND mc.note IS NOT NULL AND t.production_year > 1950 AND lt.id = ml.link_type_id AND ml.movie_id = t.id AND t.id = mk.movie_id AND mk.keyword_id = k.id AND t.id = mc.movie_id AND mc.company_type_id = ct.id AND mc.company_id = cn.id AND ml.movie_id = mk.movie_id AND ml.movie_id = mc.movie_id AND mk.movie_id = mc.movie_id +SELECT MIN(cn.name) AS movie_company, MIN(mi_idx.info) AS rating, MIN(t.title) AS drama_horror_movie FROM company_name AS cn, company_type AS ct, info_type AS it1, info_type AS it2, movie_companies AS mc, movie_info AS mi, movie_info_idx AS mi_idx, title AS t WHERE cn.country_code = '[us]' AND ct.kind = 'production companies' AND it1.info = 'genres' AND it2.info = 'rating' AND mi.info IN ('Drama', 'Horror') AND mi_idx.info > '8.0' AND t.production_year BETWEEN 2005 AND 2008 AND t.id = mi.movie_id AND t.id = mi_idx.movie_id AND mi.info_type_id = it1.id AND mi_idx.info_type_id = it2.id AND t.id = mc.movie_id AND ct.id = mc.company_type_id AND cn.id = mc.company_id AND mc.movie_id = mi.movie_id AND mc.movie_id = mi_idx.movie_id AND mi.movie_id = mi_idx.movie_id +SELECT MIN(mi.info) AS budget, MIN(t.title) AS unsuccsessful_movie FROM company_name AS cn, company_type AS ct, info_type AS it1, info_type AS it2, movie_companies AS mc, movie_info AS mi, movie_info_idx AS mi_idx, title AS t WHERE cn.country_code ='[us]' AND ct.kind IS NOT NULL AND (ct.kind ='production companies' OR ct.kind = 'distributors') AND it1.info ='budget' AND it2.info ='bottom 10 rank' AND t.production_year >2000 AND (t.title LIKE 'Birdemic%' OR t.title LIKE '%Movie%') AND t.id = mi.movie_id AND t.id = mi_idx.movie_id AND mi.info_type_id = it1.id AND mi_idx.info_type_id = it2.id AND t.id = mc.movie_id AND ct.id = mc.company_type_id AND cn.id = mc.company_id AND mc.movie_id = mi.movie_id AND mc.movie_id = mi_idx.movie_id AND mi.movie_id = mi_idx.movie_id +SELECT MIN(cn.name) AS movie_company, MIN(mi_idx.info) AS rating, MIN(t.title) AS mainstream_movie FROM company_name AS cn, company_type AS ct, info_type AS it1, info_type AS it2, movie_companies AS mc, movie_info AS mi, movie_info_idx AS mi_idx, title AS t WHERE cn.country_code = '[us]' AND ct.kind = 'production companies' AND it1.info = 'genres' AND it2.info = 'rating' AND mi.info IN ('Drama', 'Horror', 'Western', 'Family') AND mi_idx.info > '7.0' AND t.production_year BETWEEN 2000 AND 2010 AND t.id = mi.movie_id AND t.id = mi_idx.movie_id AND mi.info_type_id = it1.id AND mi_idx.info_type_id = it2.id AND t.id = mc.movie_id AND ct.id = mc.company_type_id AND cn.id = mc.company_id AND mc.movie_id = mi.movie_id AND mc.movie_id = mi_idx.movie_id AND mi.movie_id = mi_idx.movie_id +SELECT MIN(mi.info) AS release_date, MIN(miidx.info) AS rating, MIN(t.title) AS german_movie FROM company_name AS cn, company_type AS ct, info_type AS it, info_type AS it2, kind_type AS kt, movie_companies AS mc, movie_info AS mi, movie_info_idx AS miidx, title AS t WHERE cn.country_code ='[de]' AND ct.kind ='production companies' AND it.info ='rating' AND it2.info ='release dates' AND kt.kind ='movie' AND mi.movie_id = t.id AND it2.id = mi.info_type_id AND kt.id = t.kind_id AND mc.movie_id = t.id AND cn.id = mc.company_id AND ct.id = mc.company_type_id AND miidx.movie_id = t.id AND it.id = miidx.info_type_id AND mi.movie_id = miidx.movie_id AND mi.movie_id = mc.movie_id AND miidx.movie_id = mc.movie_id +SELECT MIN(cn.name) AS producing_company, MIN(miidx.info) AS rating, MIN(t.title) AS movie_about_winning FROM company_name AS cn, company_type AS ct, info_type AS it, info_type AS it2, kind_type AS kt, movie_companies AS mc, movie_info AS mi, movie_info_idx AS miidx, title AS t WHERE cn.country_code ='[us]' AND ct.kind ='production companies' AND it.info ='rating' AND it2.info ='release dates' AND kt.kind ='movie' AND t.title != '' AND (t.title LIKE '%Champion%' OR t.title LIKE '%Loser%') AND mi.movie_id = t.id AND it2.id = mi.info_type_id AND kt.id = t.kind_id AND mc.movie_id = t.id AND cn.id = mc.company_id AND ct.id = mc.company_type_id AND miidx.movie_id = t.id AND it.id = miidx.info_type_id AND mi.movie_id = miidx.movie_id AND mi.movie_id = mc.movie_id AND miidx.movie_id = mc.movie_id +SELECT MIN(cn.name) AS producing_company, MIN(miidx.info) AS rating, MIN(t.title) AS movie_about_winning FROM company_name AS cn, company_type AS ct, info_type AS it, info_type AS it2, kind_type AS kt, movie_companies AS mc, movie_info AS mi, movie_info_idx AS miidx, title AS t WHERE cn.country_code ='[us]' AND ct.kind ='production companies' AND it.info ='rating' AND it2.info ='release dates' AND kt.kind ='movie' AND t.title != '' AND (t.title LIKE 'Champion%' OR t.title LIKE 'Loser%') AND mi.movie_id = t.id AND it2.id = mi.info_type_id AND kt.id = t.kind_id AND mc.movie_id = t.id AND cn.id = mc.company_id AND ct.id = mc.company_type_id AND miidx.movie_id = t.id AND it.id = miidx.info_type_id AND mi.movie_id = miidx.movie_id AND mi.movie_id = mc.movie_id AND miidx.movie_id = mc.movie_id +SELECT MIN(cn.name) AS producing_company, MIN(miidx.info) AS rating, MIN(t.title) AS movie FROM company_name AS cn, company_type AS ct, info_type AS it, info_type AS it2, kind_type AS kt, movie_companies AS mc, movie_info AS mi, movie_info_idx AS miidx, title AS t WHERE cn.country_code ='[us]' AND ct.kind ='production companies' AND it.info ='rating' AND it2.info ='release dates' AND kt.kind ='movie' AND mi.movie_id = t.id AND it2.id = mi.info_type_id AND kt.id = t.kind_id AND mc.movie_id = t.id AND cn.id = mc.company_id AND ct.id = mc.company_type_id AND miidx.movie_id = t.id AND it.id = miidx.info_type_id AND mi.movie_id = miidx.movie_id AND mi.movie_id = mc.movie_id AND miidx.movie_id = mc.movie_id +SELECT MIN(mi_idx.info) AS rating, MIN(t.title) AS northern_dark_movie FROM info_type AS it1, info_type AS it2, keyword AS k, kind_type AS kt, movie_info AS mi, movie_info_idx AS mi_idx, movie_keyword AS mk, title AS t WHERE it1.info = 'countries' AND it2.info = 'rating' AND k.keyword IN ('murder', 'murder-in-title', 'blood', 'violence') AND kt.kind = 'movie' AND mi.info IN ('Sweden', 'Norway', 'Germany', 'Denmark', 'Swedish', 'Denish', 'Norwegian', 'German', 'USA', 'American') AND mi_idx.info < '8.5' AND t.production_year > 2010 AND kt.id = t.kind_id AND t.id = mi.movie_id AND t.id = mk.movie_id AND t.id = mi_idx.movie_id AND mk.movie_id = mi.movie_id AND mk.movie_id = mi_idx.movie_id AND mi.movie_id = mi_idx.movie_id AND k.id = mk.keyword_id AND it1.id = mi.info_type_id AND it2.id = mi_idx.info_type_id +SELECT MIN(mi_idx.info) AS rating, MIN(t.title) AS western_dark_production FROM info_type AS it1, info_type AS it2, keyword AS k, kind_type AS kt, movie_info AS mi, movie_info_idx AS mi_idx, movie_keyword AS mk, title AS t WHERE it1.info = 'countries' AND it2.info = 'rating' AND k.keyword IN ('murder', 'murder-in-title') AND kt.kind = 'movie' AND mi.info IN ('Sweden', 'Norway', 'Germany', 'Denmark', 'Swedish', 'Denish', 'Norwegian', 'German', 'USA', 'American') AND mi_idx.info > '6.0' AND t.production_year > 2010 AND (t.title LIKE '%murder%' OR t.title LIKE '%Murder%' OR t.title LIKE '%Mord%') AND kt.id = t.kind_id AND t.id = mi.movie_id AND t.id = mk.movie_id AND t.id = mi_idx.movie_id AND mk.movie_id = mi.movie_id AND mk.movie_id = mi_idx.movie_id AND mi.movie_id = mi_idx.movie_id AND k.id = mk.keyword_id AND it1.id = mi.info_type_id AND it2.id = mi_idx.info_type_id +SELECT MIN(mi_idx.info) AS rating, MIN(t.title) AS north_european_dark_production FROM info_type AS it1, info_type AS it2, keyword AS k, kind_type AS kt, movie_info AS mi, movie_info_idx AS mi_idx, movie_keyword AS mk, title AS t WHERE it1.info = 'countries' AND it2.info = 'rating' AND k.keyword IS NOT NULL AND k.keyword IN ('murder', 'murder-in-title', 'blood', 'violence') AND kt.kind IN ('movie', 'episode') AND mi.info IN ('Sweden', 'Norway', 'Germany', 'Denmark', 'Swedish', 'Danish', 'Norwegian', 'German', 'USA', 'American') AND mi_idx.info < '8.5' AND t.production_year > 2005 AND kt.id = t.kind_id AND t.id = mi.movie_id AND t.id = mk.movie_id AND t.id = mi_idx.movie_id AND mk.movie_id = mi.movie_id AND mk.movie_id = mi_idx.movie_id AND mi.movie_id = mi_idx.movie_id AND k.id = mk.keyword_id AND it1.id = mi.info_type_id AND it2.id = mi_idx.info_type_id +SELECT MIN(mi.info) AS release_date, MIN(t.title) AS internet_movie FROM aka_title AS at, company_name AS cn, company_type AS ct, info_type AS it1, keyword AS k, movie_companies AS mc, movie_info AS mi, movie_keyword AS mk, title AS t WHERE cn.country_code = '[us]' AND it1.info = 'release dates' AND mc.note LIKE '%(200%)%' AND mc.note LIKE '%(worldwide)%' AND mi.note LIKE '%internet%' AND mi.info LIKE 'USA:% 200%' AND t.production_year > 2000 AND t.id = at.movie_id AND t.id = mi.movie_id AND t.id = mk.movie_id AND t.id = mc.movie_id AND mk.movie_id = mi.movie_id AND mk.movie_id = mc.movie_id AND mk.movie_id = at.movie_id AND mi.movie_id = mc.movie_id AND mi.movie_id = at.movie_id AND mc.movie_id = at.movie_id AND k.id = mk.keyword_id AND it1.id = mi.info_type_id AND cn.id = mc.company_id AND ct.id = mc.company_type_id +SELECT MIN(mi.info) AS release_date, MIN(t.title) AS youtube_movie FROM aka_title AS at, company_name AS cn, company_type AS ct, info_type AS it1, keyword AS k, movie_companies AS mc, movie_info AS mi, movie_keyword AS mk, title AS t WHERE cn.country_code = '[us]' AND cn.name = 'YouTube' AND it1.info = 'release dates' AND mc.note LIKE '%(200%)%' AND mc.note LIKE '%(worldwide)%' AND mi.note LIKE '%internet%' AND mi.info LIKE 'USA:% 200%' AND t.production_year BETWEEN 2005 AND 2010 AND t.id = at.movie_id AND t.id = mi.movie_id AND t.id = mk.movie_id AND t.id = mc.movie_id AND mk.movie_id = mi.movie_id AND mk.movie_id = mc.movie_id AND mk.movie_id = at.movie_id AND mi.movie_id = mc.movie_id AND mi.movie_id = at.movie_id AND mc.movie_id = at.movie_id AND k.id = mk.keyword_id AND it1.id = mi.info_type_id AND cn.id = mc.company_id AND ct.id = mc.company_type_id +SELECT MIN(mi.info) AS release_date, MIN(t.title) AS modern_american_internet_movie FROM aka_title AS at, company_name AS cn, company_type AS ct, info_type AS it1, keyword AS k, movie_companies AS mc, movie_info AS mi, movie_keyword AS mk, title AS t WHERE cn.country_code = '[us]' AND it1.info = 'release dates' AND mi.note LIKE '%internet%' AND mi.info IS NOT NULL AND (mi.info LIKE 'USA:% 199%' OR mi.info LIKE 'USA:% 200%') AND t.production_year > 1990 AND t.id = at.movie_id AND t.id = mi.movie_id AND t.id = mk.movie_id AND t.id = mc.movie_id AND mk.movie_id = mi.movie_id AND mk.movie_id = mc.movie_id AND mk.movie_id = at.movie_id AND mi.movie_id = mc.movie_id AND mi.movie_id = at.movie_id AND mc.movie_id = at.movie_id AND k.id = mk.keyword_id AND it1.id = mi.info_type_id AND cn.id = mc.company_id AND ct.id = mc.company_type_id +SELECT MIN(at.title) AS aka_title, MIN(t.title) AS internet_movie_title FROM aka_title AS at, company_name AS cn, company_type AS ct, info_type AS it1, keyword AS k, movie_companies AS mc, movie_info AS mi, movie_keyword AS mk, title AS t WHERE cn.country_code = '[us]' AND it1.info = 'release dates' AND mi.note LIKE '%internet%' AND t.production_year > 1990 AND t.id = at.movie_id AND t.id = mi.movie_id AND t.id = mk.movie_id AND t.id = mc.movie_id AND mk.movie_id = mi.movie_id AND mk.movie_id = mc.movie_id AND mk.movie_id = at.movie_id AND mi.movie_id = mc.movie_id AND mi.movie_id = at.movie_id AND mc.movie_id = at.movie_id AND k.id = mk.keyword_id AND it1.id = mi.info_type_id AND cn.id = mc.company_id AND ct.id = mc.company_type_id +SELECT MIN(an.name) AS cool_actor_pseudonym, MIN(t.title) AS series_named_after_char FROM aka_name AS an, cast_info AS ci, company_name AS cn, keyword AS k, movie_companies AS mc, movie_keyword AS mk, name AS n, title AS t WHERE cn.country_code ='[us]' AND k.keyword ='character-name-in-title' AND t.episode_nr >= 50 AND t.episode_nr < 100 AND an.person_id = n.id AND n.id = ci.person_id AND ci.movie_id = t.id AND t.id = mk.movie_id AND mk.keyword_id = k.id AND t.id = mc.movie_id AND mc.company_id = cn.id AND an.person_id = ci.person_id AND ci.movie_id = mc.movie_id AND ci.movie_id = mk.movie_id AND mc.movie_id = mk.movie_id +SELECT MIN(an.name) AS cool_actor_pseudonym, MIN(t.title) AS series_named_after_char FROM aka_name AS an, cast_info AS ci, company_name AS cn, keyword AS k, movie_companies AS mc, movie_keyword AS mk, name AS n, title AS t WHERE cn.country_code ='[us]' AND k.keyword ='character-name-in-title' AND an.person_id = n.id AND n.id = ci.person_id AND ci.movie_id = t.id AND t.id = mk.movie_id AND mk.keyword_id = k.id AND t.id = mc.movie_id AND mc.company_id = cn.id AND an.person_id = ci.person_id AND ci.movie_id = mc.movie_id AND ci.movie_id = mk.movie_id AND mc.movie_id = mk.movie_id +SELECT MIN(an.name) AS cool_actor_pseudonym, MIN(t.title) AS series_named_after_char FROM aka_name AS an, cast_info AS ci, company_name AS cn, keyword AS k, movie_companies AS mc, movie_keyword AS mk, name AS n, title AS t WHERE cn.country_code ='[us]' AND k.keyword ='character-name-in-title' AND t.episode_nr < 100 AND an.person_id = n.id AND n.id = ci.person_id AND ci.movie_id = t.id AND t.id = mk.movie_id AND mk.keyword_id = k.id AND t.id = mc.movie_id AND mc.company_id = cn.id AND an.person_id = ci.person_id AND ci.movie_id = mc.movie_id AND ci.movie_id = mk.movie_id AND mc.movie_id = mk.movie_id +SELECT MIN(an.name) AS cool_actor_pseudonym, MIN(t.title) AS series_named_after_char FROM aka_name AS an, cast_info AS ci, company_name AS cn, keyword AS k, movie_companies AS mc, movie_keyword AS mk, name AS n, title AS t WHERE cn.country_code ='[us]' AND k.keyword ='character-name-in-title' AND t.episode_nr >= 5 AND t.episode_nr < 100 AND an.person_id = n.id AND n.id = ci.person_id AND ci.movie_id = t.id AND t.id = mk.movie_id AND mk.keyword_id = k.id AND t.id = mc.movie_id AND mc.company_id = cn.id AND an.person_id = ci.person_id AND ci.movie_id = mc.movie_id AND ci.movie_id = mk.movie_id AND mc.movie_id = mk.movie_id +SELECT MIN(n.name) AS member_in_charnamed_american_movie, MIN(n.name) AS a1 FROM cast_info AS ci, company_name AS cn, keyword AS k, movie_companies AS mc, movie_keyword AS mk, name AS n, title AS t WHERE cn.country_code ='[us]' AND k.keyword ='character-name-in-title' AND n.name LIKE 'B%' AND n.id = ci.person_id AND ci.movie_id = t.id AND t.id = mk.movie_id AND mk.keyword_id = k.id AND t.id = mc.movie_id AND mc.company_id = cn.id AND ci.movie_id = mc.movie_id AND ci.movie_id = mk.movie_id AND mc.movie_id = mk.movie_id +SELECT MIN(n.name) AS member_in_charnamed_movie, MIN(n.name) AS a1 FROM cast_info AS ci, company_name AS cn, keyword AS k, movie_companies AS mc, movie_keyword AS mk, name AS n, title AS t WHERE k.keyword ='character-name-in-title' AND n.name LIKE 'Z%' AND n.id = ci.person_id AND ci.movie_id = t.id AND t.id = mk.movie_id AND mk.keyword_id = k.id AND t.id = mc.movie_id AND mc.company_id = cn.id AND ci.movie_id = mc.movie_id AND ci.movie_id = mk.movie_id AND mc.movie_id = mk.movie_id +SELECT MIN(n.name) AS member_in_charnamed_movie, MIN(n.name) AS a1 FROM cast_info AS ci, company_name AS cn, keyword AS k, movie_companies AS mc, movie_keyword AS mk, name AS n, title AS t WHERE k.keyword ='character-name-in-title' AND n.name LIKE 'X%' AND n.id = ci.person_id AND ci.movie_id = t.id AND t.id = mk.movie_id AND mk.keyword_id = k.id AND t.id = mc.movie_id AND mc.company_id = cn.id AND ci.movie_id = mc.movie_id AND ci.movie_id = mk.movie_id AND mc.movie_id = mk.movie_id +SELECT MIN(n.name) AS member_in_charnamed_movie FROM cast_info AS ci, company_name AS cn, keyword AS k, movie_companies AS mc, movie_keyword AS mk, name AS n, title AS t WHERE k.keyword ='character-name-in-title' AND n.name LIKE '%Bert%' AND n.id = ci.person_id AND ci.movie_id = t.id AND t.id = mk.movie_id AND mk.keyword_id = k.id AND t.id = mc.movie_id AND mc.company_id = cn.id AND ci.movie_id = mc.movie_id AND ci.movie_id = mk.movie_id AND mc.movie_id = mk.movie_id +SELECT MIN(n.name) AS member_in_charnamed_movie FROM cast_info AS ci, company_name AS cn, keyword AS k, movie_companies AS mc, movie_keyword AS mk, name AS n, title AS t WHERE cn.country_code ='[us]' AND k.keyword ='character-name-in-title' AND n.id = ci.person_id AND ci.movie_id = t.id AND t.id = mk.movie_id AND mk.keyword_id = k.id AND t.id = mc.movie_id AND mc.company_id = cn.id AND ci.movie_id = mc.movie_id AND ci.movie_id = mk.movie_id AND mc.movie_id = mk.movie_id +SELECT MIN(n.name) AS member_in_charnamed_movie FROM cast_info AS ci, company_name AS cn, keyword AS k, movie_companies AS mc, movie_keyword AS mk, name AS n, title AS t WHERE k.keyword ='character-name-in-title' AND n.name LIKE '%B%' AND n.id = ci.person_id AND ci.movie_id = t.id AND t.id = mk.movie_id AND mk.keyword_id = k.id AND t.id = mc.movie_id AND mc.company_id = cn.id AND ci.movie_id = mc.movie_id AND ci.movie_id = mk.movie_id AND mc.movie_id = mk.movie_id +SELECT MIN(mi.info) AS movie_budget, MIN(mi_idx.info) AS movie_votes, MIN(t.title) AS movie_title FROM cast_info AS ci, info_type AS it1, info_type AS it2, movie_info AS mi, movie_info_idx AS mi_idx, name AS n, title AS t WHERE ci.note IN ('(producer)', '(executive producer)') AND it1.info = 'budget' AND it2.info = 'votes' AND n.gender = 'm' AND n.name LIKE '%Tim%' AND t.id = mi.movie_id AND t.id = mi_idx.movie_id AND t.id = ci.movie_id AND ci.movie_id = mi.movie_id AND ci.movie_id = mi_idx.movie_id AND mi.movie_id = mi_idx.movie_id AND n.id = ci.person_id AND it1.id = mi.info_type_id AND it2.id = mi_idx.info_type_id +SELECT MIN(mi.info) AS movie_budget, MIN(mi_idx.info) AS movie_votes, MIN(t.title) AS movie_title FROM cast_info AS ci, info_type AS it1, info_type AS it2, movie_info AS mi, movie_info_idx AS mi_idx, name AS n, title AS t WHERE ci.note IN ('(writer)', '(head writer)', '(written by)', '(story)', '(story editor)') AND it1.info = 'genres' AND it2.info = 'rating' AND mi.info IN ('Horror', 'Thriller') AND mi.note IS NULL AND mi_idx.info > '8.0' AND n.gender IS NOT NULL AND n.gender = 'f' AND t.production_year BETWEEN 2008 AND 2014 AND t.id = mi.movie_id AND t.id = mi_idx.movie_id AND t.id = ci.movie_id AND ci.movie_id = mi.movie_id AND ci.movie_id = mi_idx.movie_id AND mi.movie_id = mi_idx.movie_id AND n.id = ci.person_id AND it1.id = mi.info_type_id AND it2.id = mi_idx.info_type_id +SELECT MIN(mi.info) AS movie_budget, MIN(mi_idx.info) AS movie_votes, MIN(t.title) AS movie_title FROM cast_info AS ci, info_type AS it1, info_type AS it2, movie_info AS mi, movie_info_idx AS mi_idx, name AS n, title AS t WHERE ci.note IN ('(writer)', '(head writer)', '(written by)', '(story)', '(story editor)') AND it1.info = 'genres' AND it2.info = 'votes' AND mi.info IN ('Horror', 'Action', 'Sci-Fi', 'Thriller', 'Crime', 'War') AND n.gender = 'm' AND t.id = mi.movie_id AND t.id = mi_idx.movie_id AND t.id = ci.movie_id AND ci.movie_id = mi.movie_id AND ci.movie_id = mi_idx.movie_id AND mi.movie_id = mi_idx.movie_id AND n.id = ci.person_id AND it1.id = mi.info_type_id AND it2.id = mi_idx.info_type_id +SELECT MIN(n.name) AS voicing_actress, MIN(t.title) AS voiced_movie FROM aka_name AS an, char_name AS chn, cast_info AS ci, company_name AS cn, info_type AS it, movie_companies AS mc, movie_info AS mi, name AS n, role_type AS rt, title AS t WHERE ci.note IN ('(voice)', '(voice: Japanese version)', '(voice) (uncredited)', '(voice: English version)') AND cn.country_code ='[us]' AND it.info = 'release dates' AND mc.note IS NOT NULL AND (mc.note LIKE '%(USA)%' OR mc.note LIKE '%(worldwide)%') AND mi.info IS NOT NULL AND (mi.info LIKE 'Japan:%200%' OR mi.info LIKE 'USA:%200%') AND n.gender ='f' AND n.name LIKE '%Ang%' AND rt.role ='actress' AND t.production_year BETWEEN 2005 AND 2009 AND t.id = mi.movie_id AND t.id = mc.movie_id AND t.id = ci.movie_id AND mc.movie_id = ci.movie_id AND mc.movie_id = mi.movie_id AND mi.movie_id = ci.movie_id AND cn.id = mc.company_id AND it.id = mi.info_type_id AND n.id = ci.person_id AND rt.id = ci.role_id AND n.id = an.person_id AND ci.person_id = an.person_id AND chn.id = ci.person_role_id +SELECT MIN(n.name) AS voicing_actress, MIN(t.title) AS kung_fu_panda FROM aka_name AS an, char_name AS chn, cast_info AS ci, company_name AS cn, info_type AS it, movie_companies AS mc, movie_info AS mi, name AS n, role_type AS rt, title AS t WHERE ci.note = '(voice)' AND cn.country_code ='[us]' AND it.info = 'release dates' AND mc.note LIKE '%(200%)%' AND (mc.note LIKE '%(USA)%' OR mc.note LIKE '%(worldwide)%') AND mi.info IS NOT NULL AND (mi.info LIKE 'Japan:%2007%' OR mi.info LIKE 'USA:%2008%') AND n.gender ='f' AND n.name LIKE '%Angel%' AND rt.role ='actress' AND t.production_year BETWEEN 2007 AND 2008 AND t.title LIKE '%Kung%Fu%Panda%' AND t.id = mi.movie_id AND t.id = mc.movie_id AND t.id = ci.movie_id AND mc.movie_id = ci.movie_id AND mc.movie_id = mi.movie_id AND mi.movie_id = ci.movie_id AND cn.id = mc.company_id AND it.id = mi.info_type_id AND n.id = ci.person_id AND rt.id = ci.role_id AND n.id = an.person_id AND ci.person_id = an.person_id AND chn.id = ci.person_role_id +SELECT MIN(n.name) AS voicing_actress, MIN(t.title) AS jap_engl_voiced_movie FROM aka_name AS an, char_name AS chn, cast_info AS ci, company_name AS cn, info_type AS it, movie_companies AS mc, movie_info AS mi, name AS n, role_type AS rt, title AS t WHERE ci.note IN ('(voice)', '(voice: Japanese version)', '(voice) (uncredited)', '(voice: English version)') AND cn.country_code ='[us]' AND it.info = 'release dates' AND mi.info IS NOT NULL AND (mi.info LIKE 'Japan:%200%' OR mi.info LIKE 'USA:%200%') AND n.gender ='f' AND n.name LIKE '%An%' AND rt.role ='actress' AND t.production_year > 2000 AND t.id = mi.movie_id AND t.id = mc.movie_id AND t.id = ci.movie_id AND mc.movie_id = ci.movie_id AND mc.movie_id = mi.movie_id AND mi.movie_id = ci.movie_id AND cn.id = mc.company_id AND it.id = mi.info_type_id AND n.id = ci.person_id AND rt.id = ci.role_id AND n.id = an.person_id AND ci.person_id = an.person_id AND chn.id = ci.person_role_id +SELECT MIN(n.name) AS voicing_actress, MIN(t.title) AS jap_engl_voiced_movie FROM aka_name AS an, char_name AS chn, cast_info AS ci, company_name AS cn, info_type AS it, movie_companies AS mc, movie_info AS mi, name AS n, role_type AS rt, title AS t WHERE ci.note IN ('(voice)', '(voice: Japanese version)', '(voice) (uncredited)', '(voice: English version)') AND cn.country_code ='[us]' AND it.info = 'release dates' AND n.gender ='f' AND rt.role ='actress' AND t.production_year > 2000 AND t.id = mi.movie_id AND t.id = mc.movie_id AND t.id = ci.movie_id AND mc.movie_id = ci.movie_id AND mc.movie_id = mi.movie_id AND mi.movie_id = ci.movie_id AND cn.id = mc.company_id AND it.id = mi.info_type_id AND n.id = ci.person_id AND rt.id = ci.role_id AND n.id = an.person_id AND ci.person_id = an.person_id AND chn.id = ci.person_role_id +SELECT MIN(t.title) AS complete_downey_ironman_movie FROM complete_cast AS cc, comp_cast_type AS cct1, comp_cast_type AS cct2, char_name AS chn, cast_info AS ci, keyword AS k, kind_type AS kt, movie_keyword AS mk, name AS n, title AS t WHERE cct1.kind = 'cast' AND cct2.kind LIKE '%complete%' AND chn.name NOT LIKE '%Sherlock%' AND (chn.name LIKE '%Tony%Stark%' OR chn.name LIKE '%Iron%Man%') AND k.keyword IN ('superhero', 'sequel', 'second-part', 'marvel-comics', 'based-on-comic', 'tv-special', 'fight', 'violence') AND kt.kind = 'movie' AND t.production_year > 1950 AND kt.id = t.kind_id AND t.id = mk.movie_id AND t.id = ci.movie_id AND t.id = cc.movie_id AND mk.movie_id = ci.movie_id AND mk.movie_id = cc.movie_id AND ci.movie_id = cc.movie_id AND chn.id = ci.person_role_id AND n.id = ci.person_id AND k.id = mk.keyword_id AND cct1.id = cc.subject_id AND cct2.id = cc.status_id +SELECT MIN(t.title) AS complete_downey_ironman_movie FROM complete_cast AS cc, comp_cast_type AS cct1, comp_cast_type AS cct2, char_name AS chn, cast_info AS ci, keyword AS k, kind_type AS kt, movie_keyword AS mk, name AS n, title AS t WHERE cct1.kind = 'cast' AND cct2.kind LIKE '%complete%' AND chn.name NOT LIKE '%Sherlock%' AND (chn.name LIKE '%Tony%Stark%' OR chn.name LIKE '%Iron%Man%') AND k.keyword IN ('superhero', 'sequel', 'second-part', 'marvel-comics', 'based-on-comic', 'tv-special', 'fight', 'violence') AND kt.kind = 'movie' AND n.name LIKE '%Downey%Robert%' AND t.production_year > 2000 AND kt.id = t.kind_id AND t.id = mk.movie_id AND t.id = ci.movie_id AND t.id = cc.movie_id AND mk.movie_id = ci.movie_id AND mk.movie_id = cc.movie_id AND ci.movie_id = cc.movie_id AND chn.id = ci.person_role_id AND n.id = ci.person_id AND k.id = mk.keyword_id AND cct1.id = cc.subject_id AND cct2.id = cc.status_id +SELECT MIN(n.name) AS cast_member, MIN(t.title) AS complete_dynamic_hero_movie FROM complete_cast AS cc, comp_cast_type AS cct1, comp_cast_type AS cct2, char_name AS chn, cast_info AS ci, keyword AS k, kind_type AS kt, movie_keyword AS mk, name AS n, title AS t WHERE cct1.kind = 'cast' AND cct2.kind LIKE '%complete%' AND chn.name IS NOT NULL AND (chn.name LIKE '%man%' OR chn.name LIKE '%Man%') AND k.keyword IN ('superhero', 'marvel-comics', 'based-on-comic', 'tv-special', 'fight', 'violence', 'magnet', 'web', 'claw', 'laser') AND kt.kind = 'movie' AND t.production_year > 2000 AND kt.id = t.kind_id AND t.id = mk.movie_id AND t.id = ci.movie_id AND t.id = cc.movie_id AND mk.movie_id = ci.movie_id AND mk.movie_id = cc.movie_id AND ci.movie_id = cc.movie_id AND chn.id = ci.person_role_id AND n.id = ci.person_id AND k.id = mk.keyword_id AND cct1.id = cc.subject_id AND cct2.id = cc.status_id +SELECT MIN(cn.name) AS company_name, MIN(lt.link) AS link_type, MIN(t.title) AS western_follow_up FROM company_name AS cn, company_type AS ct, keyword AS k, link_type AS lt, movie_companies AS mc, movie_info AS mi, movie_keyword AS mk, movie_link AS ml, title AS t WHERE cn.country_code !='[pl]' AND (cn.name LIKE '%Film%' OR cn.name LIKE '%Warner%') AND ct.kind ='production companies' AND k.keyword ='sequel' AND lt.link LIKE '%follow%' AND mc.note IS NULL AND mi.info IN ('Sweden', 'Norway', 'Germany', 'Denmark', 'Swedish', 'Denish', 'Norwegian', 'German') AND t.production_year BETWEEN 1950 AND 2000 AND lt.id = ml.link_type_id AND ml.movie_id = t.id AND t.id = mk.movie_id AND mk.keyword_id = k.id AND t.id = mc.movie_id AND mc.company_type_id = ct.id AND mc.company_id = cn.id AND mi.movie_id = t.id AND ml.movie_id = mk.movie_id AND ml.movie_id = mc.movie_id AND mk.movie_id = mc.movie_id AND ml.movie_id = mi.movie_id AND mk.movie_id = mi.movie_id AND mc.movie_id = mi.movie_id +SELECT MIN(cn.name) AS company_name, MIN(lt.link) AS link_type, MIN(t.title) AS german_follow_up FROM company_name AS cn, company_type AS ct, keyword AS k, link_type AS lt, movie_companies AS mc, movie_info AS mi, movie_keyword AS mk, movie_link AS ml, title AS t WHERE cn.country_code !='[pl]' AND (cn.name LIKE '%Film%' OR cn.name LIKE '%Warner%') AND ct.kind ='production companies' AND k.keyword ='sequel' AND lt.link LIKE '%follow%' AND mc.note IS NULL AND mi.info IN ('Germany', 'German') AND t.production_year BETWEEN 2000 AND 2010 AND lt.id = ml.link_type_id AND ml.movie_id = t.id AND t.id = mk.movie_id AND mk.keyword_id = k.id AND t.id = mc.movie_id AND mc.company_type_id = ct.id AND mc.company_id = cn.id AND mi.movie_id = t.id AND ml.movie_id = mk.movie_id AND ml.movie_id = mc.movie_id AND mk.movie_id = mc.movie_id AND ml.movie_id = mi.movie_id AND mk.movie_id = mi.movie_id AND mc.movie_id = mi.movie_id +SELECT MIN(cn.name) AS company_name, MIN(lt.link) AS link_type, MIN(t.title) AS western_follow_up FROM company_name AS cn, company_type AS ct, keyword AS k, link_type AS lt, movie_companies AS mc, movie_info AS mi, movie_keyword AS mk, movie_link AS ml, title AS t WHERE cn.country_code !='[pl]' AND (cn.name LIKE '%Film%' OR cn.name LIKE '%Warner%') AND ct.kind ='production companies' AND k.keyword ='sequel' AND lt.link LIKE '%follow%' AND mc.note IS NULL AND mi.info IN ('Sweden', 'Norway', 'Germany', 'Denmark', 'Swedish', 'Denish', 'Norwegian', 'German', 'English') AND t.production_year BETWEEN 1950 AND 2010 AND lt.id = ml.link_type_id AND ml.movie_id = t.id AND t.id = mk.movie_id AND mk.keyword_id = k.id AND t.id = mc.movie_id AND mc.company_type_id = ct.id AND mc.company_id = cn.id AND mi.movie_id = t.id AND ml.movie_id = mk.movie_id AND ml.movie_id = mc.movie_id AND mk.movie_id = mc.movie_id AND ml.movie_id = mi.movie_id AND mk.movie_id = mi.movie_id AND mc.movie_id = mi.movie_id +SELECT MIN(cn.name) AS movie_company, MIN(mi_idx.info) AS rating, MIN(t.title) AS western_violent_movie FROM company_name AS cn, company_type AS ct, info_type AS it1, info_type AS it2, keyword AS k, kind_type AS kt, movie_companies AS mc, movie_info AS mi, movie_info_idx AS mi_idx, movie_keyword AS mk, title AS t WHERE cn.country_code != '[us]' AND it1.info = 'countries' AND it2.info = 'rating' AND k.keyword IN ('murder', 'murder-in-title', 'blood', 'violence') AND kt.kind IN ('movie', 'episode') AND mc.note NOT LIKE '%(USA)%' AND mc.note LIKE '%(200%)%' AND mi.info IN ('Germany', 'German', 'USA', 'American') AND mi_idx.info < '7.0' AND t.production_year > 2008 AND kt.id = t.kind_id AND t.id = mi.movie_id AND t.id = mk.movie_id AND t.id = mi_idx.movie_id AND t.id = mc.movie_id AND mk.movie_id = mi.movie_id AND mk.movie_id = mi_idx.movie_id AND mk.movie_id = mc.movie_id AND mi.movie_id = mi_idx.movie_id AND mi.movie_id = mc.movie_id AND mc.movie_id = mi_idx.movie_id AND k.id = mk.keyword_id AND it1.id = mi.info_type_id AND it2.id = mi_idx.info_type_id AND ct.id = mc.company_type_id AND cn.id = mc.company_id +SELECT MIN(cn.name) AS movie_company, MIN(mi_idx.info) AS rating, MIN(t.title) AS western_violent_movie FROM company_name AS cn, company_type AS ct, info_type AS it1, info_type AS it2, keyword AS k, kind_type AS kt, movie_companies AS mc, movie_info AS mi, movie_info_idx AS mi_idx, movie_keyword AS mk, title AS t WHERE cn.country_code != '[us]' AND it1.info = 'countries' AND it2.info = 'rating' AND k.keyword IN ('murder', 'murder-in-title', 'blood', 'violence') AND kt.kind IN ('movie', 'episode') AND mc.note NOT LIKE '%(USA)%' AND mc.note LIKE '%(200%)%' AND mi.info IN ('Germany', 'German', 'USA', 'American') AND mi_idx.info < '7.0' AND t.production_year > 2009 AND kt.id = t.kind_id AND t.id = mi.movie_id AND t.id = mk.movie_id AND t.id = mi_idx.movie_id AND t.id = mc.movie_id AND mk.movie_id = mi.movie_id AND mk.movie_id = mi_idx.movie_id AND mk.movie_id = mc.movie_id AND mi.movie_id = mi_idx.movie_id AND mi.movie_id = mc.movie_id AND mc.movie_id = mi_idx.movie_id AND k.id = mk.keyword_id AND it1.id = mi.info_type_id AND it2.id = mi_idx.info_type_id AND ct.id = mc.company_type_id AND cn.id = mc.company_id +SELECT MIN(cn.name) AS movie_company, MIN(mi_idx.info) AS rating, MIN(t.title) AS western_violent_movie FROM company_name AS cn, company_type AS ct, info_type AS it1, info_type AS it2, keyword AS k, kind_type AS kt, movie_companies AS mc, movie_info AS mi, movie_info_idx AS mi_idx, movie_keyword AS mk, title AS t WHERE cn.country_code != '[us]' AND it1.info = 'countries' AND it2.info = 'rating' AND k.keyword IN ('murder', 'murder-in-title', 'blood', 'violence') AND kt.kind IN ('movie', 'episode') AND mc.note NOT LIKE '%(USA)%' AND mc.note LIKE '%(200%)%' AND mi.info IN ('Sweden', 'Norway', 'Germany', 'Denmark', 'Swedish', 'Danish', 'Norwegian', 'German', 'USA', 'American') AND mi_idx.info < '8.5' AND t.production_year > 2005 AND kt.id = t.kind_id AND t.id = mi.movie_id AND t.id = mk.movie_id AND t.id = mi_idx.movie_id AND t.id = mc.movie_id AND mk.movie_id = mi.movie_id AND mk.movie_id = mi_idx.movie_id AND mk.movie_id = mc.movie_id AND mi.movie_id = mi_idx.movie_id AND mi.movie_id = mc.movie_id AND mc.movie_id = mi_idx.movie_id AND k.id = mk.keyword_id AND it1.id = mi.info_type_id AND it2.id = mi_idx.info_type_id AND ct.id = mc.company_type_id AND cn.id = mc.company_id +SELECT MIN(cn.name) AS movie_company, MIN(mi_idx.info) AS rating, MIN(t.title) AS western_violent_movie FROM company_name AS cn, company_type AS ct, info_type AS it1, info_type AS it2, keyword AS k, kind_type AS kt, movie_companies AS mc, movie_info AS mi, movie_info_idx AS mi_idx, movie_keyword AS mk, title AS t WHERE cn.country_code != '[us]' AND it1.info = 'countries' AND it2.info = 'rating' AND k.keyword IN ('murder', 'murder-in-title', 'blood', 'violence') AND kt.kind IN ('movie', 'episode') AND mi.info IN ('Sweden', 'Norway', 'Germany', 'Denmark', 'Swedish', 'Danish', 'Norwegian', 'German', 'USA', 'American') AND mi_idx.info < '8.5' AND t.production_year > 2005 AND kt.id = t.kind_id AND t.id = mi.movie_id AND t.id = mk.movie_id AND t.id = mi_idx.movie_id AND t.id = mc.movie_id AND mk.movie_id = mi.movie_id AND mk.movie_id = mi_idx.movie_id AND mk.movie_id = mc.movie_id AND mi.movie_id = mi_idx.movie_id AND mi.movie_id = mc.movie_id AND mc.movie_id = mi_idx.movie_id AND k.id = mk.keyword_id AND it1.id = mi.info_type_id AND it2.id = mi_idx.info_type_id AND ct.id = mc.company_type_id AND cn.id = mc.company_id +SELECT MIN(kt.kind) AS movie_kind, MIN(t.title) AS complete_us_internet_movie FROM complete_cast AS cc, comp_cast_type AS cct1, company_name AS cn, company_type AS ct, info_type AS it1, keyword AS k, kind_type AS kt, movie_companies AS mc, movie_info AS mi, movie_keyword AS mk, title AS t WHERE cct1.kind = 'complete+verified' AND cn.country_code = '[us]' AND it1.info = 'release dates' AND kt.kind IN ('movie') AND mi.note LIKE '%internet%' AND mi.info IS NOT NULL AND (mi.info LIKE 'USA:% 199%' OR mi.info LIKE 'USA:% 200%') AND t.production_year > 2000 AND kt.id = t.kind_id AND t.id = mi.movie_id AND t.id = mk.movie_id AND t.id = mc.movie_id AND t.id = cc.movie_id AND mk.movie_id = mi.movie_id AND mk.movie_id = mc.movie_id AND mk.movie_id = cc.movie_id AND mi.movie_id = mc.movie_id AND mi.movie_id = cc.movie_id AND mc.movie_id = cc.movie_id AND k.id = mk.keyword_id AND it1.id = mi.info_type_id AND cn.id = mc.company_id AND ct.id = mc.company_type_id AND cct1.id = cc.status_id +SELECT MIN(kt.kind) AS movie_kind, MIN(t.title) AS complete_nerdy_internet_movie FROM complete_cast AS cc, comp_cast_type AS cct1, company_name AS cn, company_type AS ct, info_type AS it1, keyword AS k, kind_type AS kt, movie_companies AS mc, movie_info AS mi, movie_keyword AS mk, title AS t WHERE cct1.kind = 'complete+verified' AND cn.country_code = '[us]' AND it1.info = 'release dates' AND k.keyword IN ('nerd', 'loner', 'alienation', 'dignity') AND kt.kind IN ('movie') AND mi.note LIKE '%internet%' AND mi.info LIKE 'USA:% 200%' AND t.production_year > 2000 AND kt.id = t.kind_id AND t.id = mi.movie_id AND t.id = mk.movie_id AND t.id = mc.movie_id AND t.id = cc.movie_id AND mk.movie_id = mi.movie_id AND mk.movie_id = mc.movie_id AND mk.movie_id = cc.movie_id AND mi.movie_id = mc.movie_id AND mi.movie_id = cc.movie_id AND mc.movie_id = cc.movie_id AND k.id = mk.keyword_id AND it1.id = mi.info_type_id AND cn.id = mc.company_id AND ct.id = mc.company_type_id AND cct1.id = cc.status_id +SELECT MIN(kt.kind) AS movie_kind, MIN(t.title) AS complete_us_internet_movie FROM complete_cast AS cc, comp_cast_type AS cct1, company_name AS cn, company_type AS ct, info_type AS it1, keyword AS k, kind_type AS kt, movie_companies AS mc, movie_info AS mi, movie_keyword AS mk, title AS t WHERE cct1.kind = 'complete+verified' AND cn.country_code = '[us]' AND it1.info = 'release dates' AND kt.kind IN ('movie', 'tv movie', 'video movie', 'video game') AND mi.note LIKE '%internet%' AND mi.info IS NOT NULL AND (mi.info LIKE 'USA:% 199%' OR mi.info LIKE 'USA:% 200%') AND t.production_year > 1990 AND kt.id = t.kind_id AND t.id = mi.movie_id AND t.id = mk.movie_id AND t.id = mc.movie_id AND t.id = cc.movie_id AND mk.movie_id = mi.movie_id AND mk.movie_id = mc.movie_id AND mk.movie_id = cc.movie_id AND mi.movie_id = mc.movie_id AND mi.movie_id = cc.movie_id AND mc.movie_id = cc.movie_id AND k.id = mk.keyword_id AND it1.id = mi.info_type_id AND cn.id = mc.company_id AND ct.id = mc.company_type_id AND cct1.id = cc.status_id +SELECT MIN(chn.name) AS voiced_char_name, MIN(n.name) AS voicing_actress_name, MIN(t.title) AS voiced_action_movie_jap_eng FROM aka_name AS an, char_name AS chn, cast_info AS ci, company_name AS cn, info_type AS it, keyword AS k, movie_companies AS mc, movie_info AS mi, movie_keyword AS mk, name AS n, role_type AS rt, title AS t WHERE ci.note IN ('(voice)', '(voice: Japanese version)', '(voice) (uncredited)', '(voice: English version)') AND cn.country_code ='[us]' AND it.info = 'release dates' AND k.keyword IN ('hero', 'martial-arts', 'hand-to-hand-combat') AND mi.info IS NOT NULL AND (mi.info LIKE 'Japan:%201%' OR mi.info LIKE 'USA:%201%') AND n.gender ='f' AND n.name LIKE '%An%' AND rt.role ='actress' AND t.production_year > 2010 AND t.id = mi.movie_id AND t.id = mc.movie_id AND t.id = ci.movie_id AND t.id = mk.movie_id AND mc.movie_id = ci.movie_id AND mc.movie_id = mi.movie_id AND mc.movie_id = mk.movie_id AND mi.movie_id = ci.movie_id AND mi.movie_id = mk.movie_id AND ci.movie_id = mk.movie_id AND cn.id = mc.company_id AND it.id = mi.info_type_id AND n.id = ci.person_id AND rt.id = ci.role_id AND n.id = an.person_id AND ci.person_id = an.person_id AND chn.id = ci.person_role_id AND k.id = mk.keyword_id +SELECT MIN(chn.name) AS voiced_char_name, MIN(n.name) AS voicing_actress_name, MIN(t.title) AS kung_fu_panda FROM aka_name AS an, char_name AS chn, cast_info AS ci, company_name AS cn, info_type AS it, keyword AS k, movie_companies AS mc, movie_info AS mi, movie_keyword AS mk, name AS n, role_type AS rt, title AS t WHERE ci.note IN ('(voice)', '(voice: Japanese version)', '(voice) (uncredited)', '(voice: English version)') AND cn.country_code ='[us]' AND cn.name = 'DreamWorks Animation' AND it.info = 'release dates' AND k.keyword IN ('hero', 'martial-arts', 'hand-to-hand-combat', 'computer-animated-movie') AND mi.info IS NOT NULL AND (mi.info LIKE 'Japan:%201%' OR mi.info LIKE 'USA:%201%') AND n.gender ='f' AND n.name LIKE '%An%' AND rt.role ='actress' AND t.production_year > 2010 AND t.title LIKE 'Kung Fu Panda%' AND t.id = mi.movie_id AND t.id = mc.movie_id AND t.id = ci.movie_id AND t.id = mk.movie_id AND mc.movie_id = ci.movie_id AND mc.movie_id = mi.movie_id AND mc.movie_id = mk.movie_id AND mi.movie_id = ci.movie_id AND mi.movie_id = mk.movie_id AND ci.movie_id = mk.movie_id AND cn.id = mc.company_id AND it.id = mi.info_type_id AND n.id = ci.person_id AND rt.id = ci.role_id AND n.id = an.person_id AND ci.person_id = an.person_id AND chn.id = ci.person_role_id AND k.id = mk.keyword_id +SELECT MIN(mi.info) AS movie_budget, MIN(mi_idx.info) AS movie_votes, MIN(n.name) AS male_writer, MIN(t.title) AS violent_movie_title FROM cast_info AS ci, info_type AS it1, info_type AS it2, keyword AS k, movie_info AS mi, movie_info_idx AS mi_idx, movie_keyword AS mk, name AS n, title AS t WHERE ci.note IN ('(writer)', '(head writer)', '(written by)', '(story)', '(story editor)') AND it1.info = 'genres' AND it2.info = 'votes' AND k.keyword IN ('murder', 'blood', 'gore', 'death', 'female-nudity') AND mi.info = 'Horror' AND n.gender = 'm' AND t.id = mi.movie_id AND t.id = mi_idx.movie_id AND t.id = ci.movie_id AND t.id = mk.movie_id AND ci.movie_id = mi.movie_id AND ci.movie_id = mi_idx.movie_id AND ci.movie_id = mk.movie_id AND mi.movie_id = mi_idx.movie_id AND mi.movie_id = mk.movie_id AND mi_idx.movie_id = mk.movie_id AND n.id = ci.person_id AND it1.id = mi.info_type_id AND it2.id = mi_idx.info_type_id AND k.id = mk.keyword_id +SELECT MIN(mi.info) AS movie_budget, MIN(mi_idx.info) AS movie_votes, MIN(n.name) AS male_writer, MIN(t.title) AS violent_movie_title FROM cast_info AS ci, info_type AS it1, info_type AS it2, keyword AS k, movie_info AS mi, movie_info_idx AS mi_idx, movie_keyword AS mk, name AS n, title AS t WHERE ci.note IN ('(writer)', '(head writer)', '(written by)', '(story)', '(story editor)') AND it1.info = 'genres' AND it2.info = 'votes' AND k.keyword IN ('murder', 'blood', 'gore', 'death', 'female-nudity') AND mi.info = 'Horror' AND n.gender = 'm' AND t.production_year > 2010 AND t.title LIKE 'Vampire%' AND t.id = mi.movie_id AND t.id = mi_idx.movie_id AND t.id = ci.movie_id AND t.id = mk.movie_id AND ci.movie_id = mi.movie_id AND ci.movie_id = mi_idx.movie_id AND ci.movie_id = mk.movie_id AND mi.movie_id = mi_idx.movie_id AND mi.movie_id = mk.movie_id AND mi_idx.movie_id = mk.movie_id AND n.id = ci.person_id AND it1.id = mi.info_type_id AND it2.id = mi_idx.info_type_id AND k.id = mk.keyword_id +SELECT MIN(mi.info) AS movie_budget, MIN(mi_idx.info) AS movie_votes, MIN(n.name) AS male_writer, MIN(t.title) AS violent_movie_title FROM cast_info AS ci, info_type AS it1, info_type AS it2, keyword AS k, movie_info AS mi, movie_info_idx AS mi_idx, movie_keyword AS mk, name AS n, title AS t WHERE ci.note IN ('(writer)', '(head writer)', '(written by)', '(story)', '(story editor)') AND it1.info = 'genres' AND it2.info = 'votes' AND k.keyword IN ('murder', 'violence', 'blood', 'gore', 'death', 'female-nudity', 'hospital') AND mi.info IN ('Horror', 'Action', 'Sci-Fi', 'Thriller', 'Crime', 'War') AND n.gender = 'm' AND t.id = mi.movie_id AND t.id = mi_idx.movie_id AND t.id = ci.movie_id AND t.id = mk.movie_id AND ci.movie_id = mi.movie_id AND ci.movie_id = mi_idx.movie_id AND ci.movie_id = mk.movie_id AND mi.movie_id = mi_idx.movie_id AND mi.movie_id = mk.movie_id AND mi_idx.movie_id = mk.movie_id AND n.id = ci.person_id AND it1.id = mi.info_type_id AND it2.id = mi_idx.info_type_id AND k.id = mk.keyword_id +SELECT MIN(chn.name) AS character_name, MIN(mi_idx.info) AS rating, MIN(n.name) AS playing_actor, MIN(t.title) AS complete_hero_movie FROM complete_cast AS cc, comp_cast_type AS cct1, comp_cast_type AS cct2, char_name AS chn, cast_info AS ci, info_type AS it2, keyword AS k, kind_type AS kt, movie_info_idx AS mi_idx, movie_keyword AS mk, name AS n, title AS t WHERE cct1.kind = 'cast' AND cct2.kind LIKE '%complete%' AND chn.name IS NOT NULL AND (chn.name LIKE '%man%' OR chn.name LIKE '%Man%') AND it2.info = 'rating' AND k.keyword IN ('superhero', 'marvel-comics', 'based-on-comic', 'tv-special', 'fight', 'violence', 'magnet', 'web', 'claw', 'laser') AND kt.kind = 'movie' AND mi_idx.info > '7.0' AND t.production_year > 2000 AND kt.id = t.kind_id AND t.id = mk.movie_id AND t.id = ci.movie_id AND t.id = cc.movie_id AND t.id = mi_idx.movie_id AND mk.movie_id = ci.movie_id AND mk.movie_id = cc.movie_id AND mk.movie_id = mi_idx.movie_id AND ci.movie_id = cc.movie_id AND ci.movie_id = mi_idx.movie_id AND cc.movie_id = mi_idx.movie_id AND chn.id = ci.person_role_id AND n.id = ci.person_id AND k.id = mk.keyword_id AND cct1.id = cc.subject_id AND cct2.id = cc.status_id AND it2.id = mi_idx.info_type_id +SELECT MIN(chn.name) AS character_name, MIN(mi_idx.info) AS rating, MIN(t.title) AS complete_hero_movie FROM complete_cast AS cc, comp_cast_type AS cct1, comp_cast_type AS cct2, char_name AS chn, cast_info AS ci, info_type AS it2, keyword AS k, kind_type AS kt, movie_info_idx AS mi_idx, movie_keyword AS mk, name AS n, title AS t WHERE cct1.kind = 'cast' AND cct2.kind LIKE '%complete%' AND chn.name IS NOT NULL AND (chn.name LIKE '%man%' OR chn.name LIKE '%Man%') AND it2.info = 'rating' AND k.keyword IN ('superhero', 'marvel-comics', 'based-on-comic', 'fight') AND kt.kind = 'movie' AND mi_idx.info > '8.0' AND t.production_year > 2005 AND kt.id = t.kind_id AND t.id = mk.movie_id AND t.id = ci.movie_id AND t.id = cc.movie_id AND t.id = mi_idx.movie_id AND mk.movie_id = ci.movie_id AND mk.movie_id = cc.movie_id AND mk.movie_id = mi_idx.movie_id AND ci.movie_id = cc.movie_id AND ci.movie_id = mi_idx.movie_id AND cc.movie_id = mi_idx.movie_id AND chn.id = ci.person_role_id AND n.id = ci.person_id AND k.id = mk.keyword_id AND cct1.id = cc.subject_id AND cct2.id = cc.status_id AND it2.id = mi_idx.info_type_id +SELECT MIN(chn.name) AS character_name, MIN(mi_idx.info) AS rating, MIN(t.title) AS complete_hero_movie FROM complete_cast AS cc, comp_cast_type AS cct1, comp_cast_type AS cct2, char_name AS chn, cast_info AS ci, info_type AS it2, keyword AS k, kind_type AS kt, movie_info_idx AS mi_idx, movie_keyword AS mk, name AS n, title AS t WHERE cct1.kind = 'cast' AND cct2.kind LIKE '%complete%' AND chn.name IS NOT NULL AND (chn.name LIKE '%man%' OR chn.name LIKE '%Man%') AND it2.info = 'rating' AND k.keyword IN ('superhero', 'marvel-comics', 'based-on-comic', 'tv-special', 'fight', 'violence', 'magnet', 'web', 'claw', 'laser') AND kt.kind = 'movie' AND t.production_year > 2000 AND kt.id = t.kind_id AND t.id = mk.movie_id AND t.id = ci.movie_id AND t.id = cc.movie_id AND t.id = mi_idx.movie_id AND mk.movie_id = ci.movie_id AND mk.movie_id = cc.movie_id AND mk.movie_id = mi_idx.movie_id AND ci.movie_id = cc.movie_id AND ci.movie_id = mi_idx.movie_id AND cc.movie_id = mi_idx.movie_id AND chn.id = ci.person_role_id AND n.id = ci.person_id AND k.id = mk.keyword_id AND cct1.id = cc.subject_id AND cct2.id = cc.status_id AND it2.id = mi_idx.info_type_id +SELECT MIN(cn.name) AS producing_company, MIN(lt.link) AS link_type, MIN(t.title) AS complete_western_sequel FROM complete_cast AS cc, comp_cast_type AS cct1, comp_cast_type AS cct2, company_name AS cn, company_type AS ct, keyword AS k, link_type AS lt, movie_companies AS mc, movie_info AS mi, movie_keyword AS mk, movie_link AS ml, title AS t WHERE cct1.kind IN ('cast', 'crew') AND cct2.kind = 'complete' AND cn.country_code !='[pl]' AND (cn.name LIKE '%Film%' OR cn.name LIKE '%Warner%') AND ct.kind ='production companies' AND k.keyword ='sequel' AND lt.link LIKE '%follow%' AND mc.note IS NULL AND mi.info IN ('Sweden', 'Germany', 'Swedish', 'German') AND t.production_year BETWEEN 1950 AND 2000 AND lt.id = ml.link_type_id AND ml.movie_id = t.id AND t.id = mk.movie_id AND mk.keyword_id = k.id AND t.id = mc.movie_id AND mc.company_type_id = ct.id AND mc.company_id = cn.id AND mi.movie_id = t.id AND t.id = cc.movie_id AND cct1.id = cc.subject_id AND cct2.id = cc.status_id AND ml.movie_id = mk.movie_id AND ml.movie_id = mc.movie_id AND mk.movie_id = mc.movie_id AND ml.movie_id = mi.movie_id AND mk.movie_id = mi.movie_id AND mc.movie_id = mi.movie_id AND ml.movie_id = cc.movie_id AND mk.movie_id = cc.movie_id AND mc.movie_id = cc.movie_id AND mi.movie_id = cc.movie_id +SELECT MIN(cn.name) AS producing_company, MIN(lt.link) AS link_type, MIN(t.title) AS complete_western_sequel FROM complete_cast AS cc, comp_cast_type AS cct1, comp_cast_type AS cct2, company_name AS cn, company_type AS ct, keyword AS k, link_type AS lt, movie_companies AS mc, movie_info AS mi, movie_keyword AS mk, movie_link AS ml, title AS t WHERE cct1.kind IN ('cast', 'crew') AND cct2.kind = 'complete' AND cn.country_code !='[pl]' AND (cn.name LIKE '%Film%' OR cn.name LIKE '%Warner%') AND ct.kind ='production companies' AND k.keyword ='sequel' AND lt.link LIKE '%follow%' AND mc.note IS NULL AND mi.info IN ('Sweden', 'Germany', 'Swedish', 'German') AND t.production_year = 1998 AND lt.id = ml.link_type_id AND ml.movie_id = t.id AND t.id = mk.movie_id AND mk.keyword_id = k.id AND t.id = mc.movie_id AND mc.company_type_id = ct.id AND mc.company_id = cn.id AND mi.movie_id = t.id AND t.id = cc.movie_id AND cct1.id = cc.subject_id AND cct2.id = cc.status_id AND ml.movie_id = mk.movie_id AND ml.movie_id = mc.movie_id AND mk.movie_id = mc.movie_id AND ml.movie_id = mi.movie_id AND mk.movie_id = mi.movie_id AND mc.movie_id = mi.movie_id AND ml.movie_id = cc.movie_id AND mk.movie_id = cc.movie_id AND mc.movie_id = cc.movie_id AND mi.movie_id = cc.movie_id +SELECT MIN(cn.name) AS producing_company, MIN(lt.link) AS link_type, MIN(t.title) AS complete_western_sequel FROM complete_cast AS cc, comp_cast_type AS cct1, comp_cast_type AS cct2, company_name AS cn, company_type AS ct, keyword AS k, link_type AS lt, movie_companies AS mc, movie_info AS mi, movie_keyword AS mk, movie_link AS ml, title AS t WHERE cct1.kind = 'cast' AND cct2.kind LIKE 'complete%' AND cn.country_code !='[pl]' AND (cn.name LIKE '%Film%' OR cn.name LIKE '%Warner%') AND ct.kind ='production companies' AND k.keyword ='sequel' AND lt.link LIKE '%follow%' AND mc.note IS NULL AND mi.info IN ('Sweden', 'Norway', 'Germany', 'Denmark', 'Swedish', 'Denish', 'Norwegian', 'German', 'English') AND t.production_year BETWEEN 1950 AND 2010 AND lt.id = ml.link_type_id AND ml.movie_id = t.id AND t.id = mk.movie_id AND mk.keyword_id = k.id AND t.id = mc.movie_id AND mc.company_type_id = ct.id AND mc.company_id = cn.id AND mi.movie_id = t.id AND t.id = cc.movie_id AND cct1.id = cc.subject_id AND cct2.id = cc.status_id AND ml.movie_id = mk.movie_id AND ml.movie_id = mc.movie_id AND mk.movie_id = mc.movie_id AND ml.movie_id = mi.movie_id AND mk.movie_id = mi.movie_id AND mc.movie_id = mi.movie_id AND ml.movie_id = cc.movie_id AND mk.movie_id = cc.movie_id AND mc.movie_id = cc.movie_id AND mi.movie_id = cc.movie_id +SELECT MIN(cn.name) AS movie_company, MIN(mi_idx.info) AS rating, MIN(t.title) AS complete_euro_dark_movie FROM complete_cast AS cc, comp_cast_type AS cct1, comp_cast_type AS cct2, company_name AS cn, company_type AS ct, info_type AS it1, info_type AS it2, keyword AS k, kind_type AS kt, movie_companies AS mc, movie_info AS mi, movie_info_idx AS mi_idx, movie_keyword AS mk, title AS t WHERE cct1.kind = 'crew' AND cct2.kind != 'complete+verified' AND cn.country_code != '[us]' AND it1.info = 'countries' AND it2.info = 'rating' AND k.keyword IN ('murder', 'murder-in-title', 'blood', 'violence') AND kt.kind IN ('movie', 'episode') AND mc.note NOT LIKE '%(USA)%' AND mc.note LIKE '%(200%)%' AND mi.info IN ('Sweden', 'Norway', 'Germany', 'Denmark', 'Swedish', 'Danish', 'Norwegian', 'German', 'USA', 'American') AND mi_idx.info < '8.5' AND t.production_year > 2000 AND kt.id = t.kind_id AND t.id = mi.movie_id AND t.id = mk.movie_id AND t.id = mi_idx.movie_id AND t.id = mc.movie_id AND t.id = cc.movie_id AND mk.movie_id = mi.movie_id AND mk.movie_id = mi_idx.movie_id AND mk.movie_id = mc.movie_id AND mk.movie_id = cc.movie_id AND mi.movie_id = mi_idx.movie_id AND mi.movie_id = mc.movie_id AND mi.movie_id = cc.movie_id AND mc.movie_id = mi_idx.movie_id AND mc.movie_id = cc.movie_id AND mi_idx.movie_id = cc.movie_id AND k.id = mk.keyword_id AND it1.id = mi.info_type_id AND it2.id = mi_idx.info_type_id AND ct.id = mc.company_type_id AND cn.id = mc.company_id AND cct1.id = cc.subject_id AND cct2.id = cc.status_id +SELECT MIN(cn.name) AS movie_company, MIN(mi_idx.info) AS rating, MIN(t.title) AS complete_euro_dark_movie FROM complete_cast AS cc, comp_cast_type AS cct1, comp_cast_type AS cct2, company_name AS cn, company_type AS ct, info_type AS it1, info_type AS it2, keyword AS k, kind_type AS kt, movie_companies AS mc, movie_info AS mi, movie_info_idx AS mi_idx, movie_keyword AS mk, title AS t WHERE cct1.kind = 'crew' AND cct2.kind != 'complete+verified' AND cn.country_code != '[us]' AND it1.info = 'countries' AND it2.info = 'rating' AND k.keyword IN ('murder', 'murder-in-title', 'blood', 'violence') AND kt.kind IN ('movie', 'episode') AND mc.note NOT LIKE '%(USA)%' AND mc.note LIKE '%(200%)%' AND mi.info IN ('Sweden', 'Germany', 'Swedish', 'German') AND mi_idx.info > '6.5' AND t.production_year > 2005 AND kt.id = t.kind_id AND t.id = mi.movie_id AND t.id = mk.movie_id AND t.id = mi_idx.movie_id AND t.id = mc.movie_id AND t.id = cc.movie_id AND mk.movie_id = mi.movie_id AND mk.movie_id = mi_idx.movie_id AND mk.movie_id = mc.movie_id AND mk.movie_id = cc.movie_id AND mi.movie_id = mi_idx.movie_id AND mi.movie_id = mc.movie_id AND mi.movie_id = cc.movie_id AND mc.movie_id = mi_idx.movie_id AND mc.movie_id = cc.movie_id AND mi_idx.movie_id = cc.movie_id AND k.id = mk.keyword_id AND it1.id = mi.info_type_id AND it2.id = mi_idx.info_type_id AND ct.id = mc.company_type_id AND cn.id = mc.company_id AND cct1.id = cc.subject_id AND cct2.id = cc.status_id +SELECT MIN(cn.name) AS movie_company, MIN(mi_idx.info) AS rating, MIN(t.title) AS complete_euro_dark_movie FROM complete_cast AS cc, comp_cast_type AS cct1, comp_cast_type AS cct2, company_name AS cn, company_type AS ct, info_type AS it1, info_type AS it2, keyword AS k, kind_type AS kt, movie_companies AS mc, movie_info AS mi, movie_info_idx AS mi_idx, movie_keyword AS mk, title AS t WHERE cct1.kind = 'cast' AND cct2.kind = 'complete' AND cn.country_code != '[us]' AND it1.info = 'countries' AND it2.info = 'rating' AND k.keyword IN ('murder', 'murder-in-title', 'blood', 'violence') AND kt.kind IN ('movie', 'episode') AND mc.note NOT LIKE '%(USA)%' AND mc.note LIKE '%(200%)%' AND mi.info IN ('Sweden', 'Norway', 'Germany', 'Denmark', 'Swedish', 'Danish', 'Norwegian', 'German', 'USA', 'American') AND mi_idx.info < '8.5' AND t.production_year > 2005 AND kt.id = t.kind_id AND t.id = mi.movie_id AND t.id = mk.movie_id AND t.id = mi_idx.movie_id AND t.id = mc.movie_id AND t.id = cc.movie_id AND mk.movie_id = mi.movie_id AND mk.movie_id = mi_idx.movie_id AND mk.movie_id = mc.movie_id AND mk.movie_id = cc.movie_id AND mi.movie_id = mi_idx.movie_id AND mi.movie_id = mc.movie_id AND mi.movie_id = cc.movie_id AND mc.movie_id = mi_idx.movie_id AND mc.movie_id = cc.movie_id AND mi_idx.movie_id = cc.movie_id AND k.id = mk.keyword_id AND it1.id = mi.info_type_id AND it2.id = mi_idx.info_type_id AND ct.id = mc.company_type_id AND cn.id = mc.company_id AND cct1.id = cc.subject_id AND cct2.id = cc.status_id +SELECT MIN(chn.name) AS voiced_char, MIN(n.name) AS voicing_actress, MIN(t.title) AS voiced_animation FROM aka_name AS an, complete_cast AS cc, comp_cast_type AS cct1, comp_cast_type AS cct2, char_name AS chn, cast_info AS ci, company_name AS cn, info_type AS it, info_type AS it3, keyword AS k, movie_companies AS mc, movie_info AS mi, movie_keyword AS mk, name AS n, person_info AS pi, role_type AS rt, title AS t WHERE cct1.kind ='cast' AND cct2.kind ='complete+verified' AND chn.name = 'Queen' AND ci.note IN ('(voice)', '(voice) (uncredited)', '(voice: English version)') AND cn.country_code ='[us]' AND it.info = 'release dates' AND it3.info = 'trivia' AND k.keyword = 'computer-animation' AND mi.info IS NOT NULL AND (mi.info LIKE 'Japan:%200%' OR mi.info LIKE 'USA:%200%') AND n.gender ='f' AND n.name LIKE '%An%' AND rt.role ='actress' AND t.title = 'Shrek 2' AND t.production_year BETWEEN 2000 AND 2010 AND t.id = mi.movie_id AND t.id = mc.movie_id AND t.id = ci.movie_id AND t.id = mk.movie_id AND t.id = cc.movie_id AND mc.movie_id = ci.movie_id AND mc.movie_id = mi.movie_id AND mc.movie_id = mk.movie_id AND mc.movie_id = cc.movie_id AND mi.movie_id = ci.movie_id AND mi.movie_id = mk.movie_id AND mi.movie_id = cc.movie_id AND ci.movie_id = mk.movie_id AND ci.movie_id = cc.movie_id AND mk.movie_id = cc.movie_id AND cn.id = mc.company_id AND it.id = mi.info_type_id AND n.id = ci.person_id AND rt.id = ci.role_id AND n.id = an.person_id AND ci.person_id = an.person_id AND chn.id = ci.person_role_id AND n.id = pi.person_id AND ci.person_id = pi.person_id AND it3.id = pi.info_type_id AND k.id = mk.keyword_id AND cct1.id = cc.subject_id AND cct2.id = cc.status_id +SELECT MIN(chn.name) AS voiced_char, MIN(n.name) AS voicing_actress, MIN(t.title) AS voiced_animation FROM aka_name AS an, complete_cast AS cc, comp_cast_type AS cct1, comp_cast_type AS cct2, char_name AS chn, cast_info AS ci, company_name AS cn, info_type AS it, info_type AS it3, keyword AS k, movie_companies AS mc, movie_info AS mi, movie_keyword AS mk, name AS n, person_info AS pi, role_type AS rt, title AS t WHERE cct1.kind ='cast' AND cct2.kind ='complete+verified' AND chn.name = 'Queen' AND ci.note IN ('(voice)', '(voice) (uncredited)', '(voice: English version)') AND cn.country_code ='[us]' AND it.info = 'release dates' AND it3.info = 'height' AND k.keyword = 'computer-animation' AND mi.info LIKE 'USA:%200%' AND n.gender ='f' AND n.name LIKE '%An%' AND rt.role ='actress' AND t.title = 'Shrek 2' AND t.production_year BETWEEN 2000 AND 2005 AND t.id = mi.movie_id AND t.id = mc.movie_id AND t.id = ci.movie_id AND t.id = mk.movie_id AND t.id = cc.movie_id AND mc.movie_id = ci.movie_id AND mc.movie_id = mi.movie_id AND mc.movie_id = mk.movie_id AND mc.movie_id = cc.movie_id AND mi.movie_id = ci.movie_id AND mi.movie_id = mk.movie_id AND mi.movie_id = cc.movie_id AND ci.movie_id = mk.movie_id AND ci.movie_id = cc.movie_id AND mk.movie_id = cc.movie_id AND cn.id = mc.company_id AND it.id = mi.info_type_id AND n.id = ci.person_id AND rt.id = ci.role_id AND n.id = an.person_id AND ci.person_id = an.person_id AND chn.id = ci.person_role_id AND n.id = pi.person_id AND ci.person_id = pi.person_id AND it3.id = pi.info_type_id AND k.id = mk.keyword_id AND cct1.id = cc.subject_id AND cct2.id = cc.status_id +SELECT MIN(chn.name) AS voiced_char, MIN(n.name) AS voicing_actress, MIN(t.title) AS voiced_animation FROM aka_name AS an, complete_cast AS cc, comp_cast_type AS cct1, comp_cast_type AS cct2, char_name AS chn, cast_info AS ci, company_name AS cn, info_type AS it, info_type AS it3, keyword AS k, movie_companies AS mc, movie_info AS mi, movie_keyword AS mk, name AS n, person_info AS pi, role_type AS rt, title AS t WHERE cct1.kind ='cast' AND cct2.kind ='complete+verified' AND ci.note IN ('(voice)', '(voice: Japanese version)', '(voice) (uncredited)', '(voice: English version)') AND cn.country_code ='[us]' AND it.info = 'release dates' AND it3.info = 'trivia' AND k.keyword = 'computer-animation' AND mi.info IS NOT NULL AND (mi.info LIKE 'Japan:%200%' OR mi.info LIKE 'USA:%200%') AND n.gender ='f' AND n.name LIKE '%An%' AND rt.role ='actress' AND t.production_year BETWEEN 2000 AND 2010 AND t.id = mi.movie_id AND t.id = mc.movie_id AND t.id = ci.movie_id AND t.id = mk.movie_id AND t.id = cc.movie_id AND mc.movie_id = ci.movie_id AND mc.movie_id = mi.movie_id AND mc.movie_id = mk.movie_id AND mc.movie_id = cc.movie_id AND mi.movie_id = ci.movie_id AND mi.movie_id = mk.movie_id AND mi.movie_id = cc.movie_id AND ci.movie_id = mk.movie_id AND ci.movie_id = cc.movie_id AND mk.movie_id = cc.movie_id AND cn.id = mc.company_id AND it.id = mi.info_type_id AND n.id = ci.person_id AND rt.id = ci.role_id AND n.id = an.person_id AND ci.person_id = an.person_id AND chn.id = ci.person_role_id AND n.id = pi.person_id AND ci.person_id = pi.person_id AND it3.id = pi.info_type_id AND k.id = mk.keyword_id AND cct1.id = cc.subject_id AND cct2.id = cc.status_id +SELECT MIN(mi.info) AS movie_budget, MIN(mi_idx.info) AS movie_votes, MIN(n.name) AS writer, MIN(t.title) AS complete_violent_movie FROM complete_cast AS cc, comp_cast_type AS cct1, comp_cast_type AS cct2, cast_info AS ci, info_type AS it1, info_type AS it2, keyword AS k, movie_info AS mi, movie_info_idx AS mi_idx, movie_keyword AS mk, name AS n, title AS t WHERE cct1.kind IN ('cast', 'crew') AND cct2.kind ='complete+verified' AND ci.note IN ('(writer)', '(head writer)', '(written by)', '(story)', '(story editor)') AND it1.info = 'genres' AND it2.info = 'votes' AND k.keyword IN ('murder', 'violence', 'blood', 'gore', 'death', 'female-nudity', 'hospital') AND mi.info IN ('Horror', 'Thriller') AND n.gender = 'm' AND t.production_year > 2000 AND t.id = mi.movie_id AND t.id = mi_idx.movie_id AND t.id = ci.movie_id AND t.id = mk.movie_id AND t.id = cc.movie_id AND ci.movie_id = mi.movie_id AND ci.movie_id = mi_idx.movie_id AND ci.movie_id = mk.movie_id AND ci.movie_id = cc.movie_id AND mi.movie_id = mi_idx.movie_id AND mi.movie_id = mk.movie_id AND mi.movie_id = cc.movie_id AND mi_idx.movie_id = mk.movie_id AND mi_idx.movie_id = cc.movie_id AND mk.movie_id = cc.movie_id AND n.id = ci.person_id AND it1.id = mi.info_type_id AND it2.id = mi_idx.info_type_id AND k.id = mk.keyword_id AND cct1.id = cc.subject_id AND cct2.id = cc.status_id +SELECT MIN(mi.info) AS movie_budget, MIN(mi_idx.info) AS movie_votes, MIN(n.name) AS writer, MIN(t.title) AS complete_gore_movie FROM complete_cast AS cc, comp_cast_type AS cct1, comp_cast_type AS cct2, cast_info AS ci, info_type AS it1, info_type AS it2, keyword AS k, movie_info AS mi, movie_info_idx AS mi_idx, movie_keyword AS mk, name AS n, title AS t WHERE cct1.kind IN ('cast', 'crew') AND cct2.kind ='complete+verified' AND ci.note IN ('(writer)', '(head writer)', '(written by)', '(story)', '(story editor)') AND it1.info = 'genres' AND it2.info = 'votes' AND k.keyword IN ('murder', 'violence', 'blood', 'gore', 'death', 'female-nudity', 'hospital') AND mi.info IN ('Horror', 'Thriller') AND n.gender = 'm' AND t.production_year > 2000 AND (t.title LIKE '%Freddy%' OR t.title LIKE '%Jason%' OR t.title LIKE 'Saw%') AND t.id = mi.movie_id AND t.id = mi_idx.movie_id AND t.id = ci.movie_id AND t.id = mk.movie_id AND t.id = cc.movie_id AND ci.movie_id = mi.movie_id AND ci.movie_id = mi_idx.movie_id AND ci.movie_id = mk.movie_id AND ci.movie_id = cc.movie_id AND mi.movie_id = mi_idx.movie_id AND mi.movie_id = mk.movie_id AND mi.movie_id = cc.movie_id AND mi_idx.movie_id = mk.movie_id AND mi_idx.movie_id = cc.movie_id AND mk.movie_id = cc.movie_id AND n.id = ci.person_id AND it1.id = mi.info_type_id AND it2.id = mi_idx.info_type_id AND k.id = mk.keyword_id AND cct1.id = cc.subject_id AND cct2.id = cc.status_id +SELECT MIN(mi.info) AS movie_budget, MIN(mi_idx.info) AS movie_votes, MIN(n.name) AS writer, MIN(t.title) AS complete_violent_movie FROM complete_cast AS cc, comp_cast_type AS cct1, comp_cast_type AS cct2, cast_info AS ci, info_type AS it1, info_type AS it2, keyword AS k, movie_info AS mi, movie_info_idx AS mi_idx, movie_keyword AS mk, name AS n, title AS t WHERE cct1.kind = 'cast' AND cct2.kind ='complete+verified' AND ci.note IN ('(writer)', '(head writer)', '(written by)', '(story)', '(story editor)') AND it1.info = 'genres' AND it2.info = 'votes' AND k.keyword IN ('murder', 'violence', 'blood', 'gore', 'death', 'female-nudity', 'hospital') AND mi.info IN ('Horror', 'Action', 'Sci-Fi', 'Thriller', 'Crime', 'War') AND n.gender = 'm' AND t.id = mi.movie_id AND t.id = mi_idx.movie_id AND t.id = ci.movie_id AND t.id = mk.movie_id AND t.id = cc.movie_id AND ci.movie_id = mi.movie_id AND ci.movie_id = mi_idx.movie_id AND ci.movie_id = mk.movie_id AND ci.movie_id = cc.movie_id AND mi.movie_id = mi_idx.movie_id AND mi.movie_id = mk.movie_id AND mi.movie_id = cc.movie_id AND mi_idx.movie_id = mk.movie_id AND mi_idx.movie_id = cc.movie_id AND mk.movie_id = cc.movie_id AND n.id = ci.person_id AND it1.id = mi.info_type_id AND it2.id = mi_idx.info_type_id AND k.id = mk.keyword_id AND cct1.id = cc.subject_id AND cct2.id = cc.status_id +SELECT MIN(mi.info) AS movie_budget, MIN(mi_idx.info) AS movie_votes, MIN(n.name) AS writer, MIN(t.title) AS violent_liongate_movie FROM cast_info AS ci, company_name AS cn, info_type AS it1, info_type AS it2, keyword AS k, movie_companies AS mc, movie_info AS mi, movie_info_idx AS mi_idx, movie_keyword AS mk, name AS n, title AS t WHERE ci.note IN ('(writer)', '(head writer)', '(written by)', '(story)', '(story editor)') AND cn.name LIKE 'Lionsgate%' AND it1.info = 'genres' AND it2.info = 'votes' AND k.keyword IN ('murder', 'violence', 'blood', 'gore', 'death', 'female-nudity', 'hospital') AND mi.info IN ('Horror', 'Thriller') AND n.gender = 'm' AND t.id = mi.movie_id AND t.id = mi_idx.movie_id AND t.id = ci.movie_id AND t.id = mk.movie_id AND t.id = mc.movie_id AND ci.movie_id = mi.movie_id AND ci.movie_id = mi_idx.movie_id AND ci.movie_id = mk.movie_id AND ci.movie_id = mc.movie_id AND mi.movie_id = mi_idx.movie_id AND mi.movie_id = mk.movie_id AND mi.movie_id = mc.movie_id AND mi_idx.movie_id = mk.movie_id AND mi_idx.movie_id = mc.movie_id AND mk.movie_id = mc.movie_id AND n.id = ci.person_id AND it1.id = mi.info_type_id AND it2.id = mi_idx.info_type_id AND k.id = mk.keyword_id AND cn.id = mc.company_id +SELECT MIN(mi.info) AS movie_budget, MIN(mi_idx.info) AS movie_votes, MIN(n.name) AS writer, MIN(t.title) AS violent_liongate_movie FROM cast_info AS ci, company_name AS cn, info_type AS it1, info_type AS it2, keyword AS k, movie_companies AS mc, movie_info AS mi, movie_info_idx AS mi_idx, movie_keyword AS mk, name AS n, title AS t WHERE ci.note IN ('(writer)', '(head writer)', '(written by)', '(story)', '(story editor)') AND cn.name LIKE 'Lionsgate%' AND it1.info = 'genres' AND it2.info = 'votes' AND k.keyword IN ('murder', 'violence', 'blood', 'gore', 'death', 'female-nudity', 'hospital') AND mc.note LIKE '%(Blu-ray)%' AND mi.info IN ('Horror', 'Thriller') AND n.gender = 'm' AND t.production_year > 2000 AND (t.title LIKE '%Freddy%' OR t.title LIKE '%Jason%' OR t.title LIKE 'Saw%') AND t.id = mi.movie_id AND t.id = mi_idx.movie_id AND t.id = ci.movie_id AND t.id = mk.movie_id AND t.id = mc.movie_id AND ci.movie_id = mi.movie_id AND ci.movie_id = mi_idx.movie_id AND ci.movie_id = mk.movie_id AND ci.movie_id = mc.movie_id AND mi.movie_id = mi_idx.movie_id AND mi.movie_id = mk.movie_id AND mi.movie_id = mc.movie_id AND mi_idx.movie_id = mk.movie_id AND mi_idx.movie_id = mc.movie_id AND mk.movie_id = mc.movie_id AND n.id = ci.person_id AND it1.id = mi.info_type_id AND it2.id = mi_idx.info_type_id AND k.id = mk.keyword_id AND cn.id = mc.company_id +SELECT MIN(mi.info) AS movie_budget, MIN(mi_idx.info) AS movie_votes, MIN(n.name) AS writer, MIN(t.title) AS violent_liongate_movie FROM cast_info AS ci, company_name AS cn, info_type AS it1, info_type AS it2, keyword AS k, movie_companies AS mc, movie_info AS mi, movie_info_idx AS mi_idx, movie_keyword AS mk, name AS n, title AS t WHERE ci.note IN ('(writer)', '(head writer)', '(written by)', '(story)', '(story editor)') AND cn.name LIKE 'Lionsgate%' AND it1.info = 'genres' AND it2.info = 'votes' AND k.keyword IN ('murder', 'violence', 'blood', 'gore', 'death', 'female-nudity', 'hospital') AND mi.info IN ('Horror', 'Action', 'Sci-Fi', 'Thriller', 'Crime', 'War') AND t.id = mi.movie_id AND t.id = mi_idx.movie_id AND t.id = ci.movie_id AND t.id = mk.movie_id AND t.id = mc.movie_id AND ci.movie_id = mi.movie_id AND ci.movie_id = mi_idx.movie_id AND ci.movie_id = mk.movie_id AND ci.movie_id = mc.movie_id AND mi.movie_id = mi_idx.movie_id AND mi.movie_id = mk.movie_id AND mi.movie_id = mc.movie_id AND mi_idx.movie_id = mk.movie_id AND mi_idx.movie_id = mc.movie_id AND mk.movie_id = mc.movie_id AND n.id = ci.person_id AND it1.id = mi.info_type_id AND it2.id = mi_idx.info_type_id AND k.id = mk.keyword_id AND cn.id = mc.company_id +SELECT MIN(lt.link) AS link_type, MIN(t1.title) AS first_movie, MIN(t2.title) AS second_movie FROM keyword AS k, link_type AS lt, movie_keyword AS mk, movie_link AS ml, title AS t1, title AS t2 WHERE k.keyword ='10,000-mile-club' AND mk.keyword_id = k.id AND t1.id = mk.movie_id AND ml.movie_id = t1.id AND ml.linked_movie_id = t2.id AND lt.id = ml.link_type_id AND mk.movie_id = t1.id +SELECT MIN(lt.link) AS link_type, MIN(t1.title) AS first_movie, MIN(t2.title) AS second_movie FROM keyword AS k, link_type AS lt, movie_keyword AS mk, movie_link AS ml, title AS t1, title AS t2 WHERE k.keyword ='character-name-in-title' AND mk.keyword_id = k.id AND t1.id = mk.movie_id AND ml.movie_id = t1.id AND ml.linked_movie_id = t2.id AND lt.id = ml.link_type_id AND mk.movie_id = t1.id +SELECT MIN(cn1.name) AS first_company, MIN(cn2.name) AS second_company, MIN(mi_idx1.info) AS first_rating, MIN(mi_idx2.info) AS second_rating, MIN(t1.title) AS first_movie, MIN(t2.title) AS second_movie FROM company_name AS cn1, company_name AS cn2, info_type AS it1, info_type AS it2, kind_type AS kt1, kind_type AS kt2, link_type AS lt, movie_companies AS mc1, movie_companies AS mc2, movie_info_idx AS mi_idx1, movie_info_idx AS mi_idx2, movie_link AS ml, title AS t1, title AS t2 WHERE cn1.country_code = '[us]' AND it1.info = 'rating' AND it2.info = 'rating' AND kt1.kind IN ('tv series') AND kt2.kind IN ('tv series') AND lt.link IN ('sequel', 'follows', 'followed by') AND mi_idx2.info < '3.0' AND t2.production_year BETWEEN 2005 AND 2008 AND lt.id = ml.link_type_id AND t1.id = ml.movie_id AND t2.id = ml.linked_movie_id AND it1.id = mi_idx1.info_type_id AND t1.id = mi_idx1.movie_id AND kt1.id = t1.kind_id AND cn1.id = mc1.company_id AND t1.id = mc1.movie_id AND ml.movie_id = mi_idx1.movie_id AND ml.movie_id = mc1.movie_id AND mi_idx1.movie_id = mc1.movie_id AND it2.id = mi_idx2.info_type_id AND t2.id = mi_idx2.movie_id AND kt2.id = t2.kind_id AND cn2.id = mc2.company_id AND t2.id = mc2.movie_id AND ml.linked_movie_id = mi_idx2.movie_id AND ml.linked_movie_id = mc2.movie_id AND mi_idx2.movie_id = mc2.movie_id +SELECT MIN(cn1.name) AS first_company, MIN(cn2.name) AS second_company, MIN(mi_idx1.info) AS first_rating, MIN(mi_idx2.info) AS second_rating, MIN(t1.title) AS first_movie, MIN(t2.title) AS second_movie FROM company_name AS cn1, company_name AS cn2, info_type AS it1, info_type AS it2, kind_type AS kt1, kind_type AS kt2, link_type AS lt, movie_companies AS mc1, movie_companies AS mc2, movie_info_idx AS mi_idx1, movie_info_idx AS mi_idx2, movie_link AS ml, title AS t1, title AS t2 WHERE cn1.country_code = '[nl]' AND it1.info = 'rating' AND it2.info = 'rating' AND kt1.kind IN ('tv series') AND kt2.kind IN ('tv series') AND lt.link LIKE '%follow%' AND mi_idx2.info < '3.0' AND t2.production_year = 2007 AND lt.id = ml.link_type_id AND t1.id = ml.movie_id AND t2.id = ml.linked_movie_id AND it1.id = mi_idx1.info_type_id AND t1.id = mi_idx1.movie_id AND kt1.id = t1.kind_id AND cn1.id = mc1.company_id AND t1.id = mc1.movie_id AND ml.movie_id = mi_idx1.movie_id AND ml.movie_id = mc1.movie_id AND mi_idx1.movie_id = mc1.movie_id AND it2.id = mi_idx2.info_type_id AND t2.id = mi_idx2.movie_id AND kt2.id = t2.kind_id AND cn2.id = mc2.company_id AND t2.id = mc2.movie_id AND ml.linked_movie_id = mi_idx2.movie_id AND ml.linked_movie_id = mc2.movie_id AND mi_idx2.movie_id = mc2.movie_id +SELECT MIN(cn1.name) AS first_company, MIN(cn2.name) AS second_company, MIN(mi_idx1.info) AS first_rating, MIN(mi_idx2.info) AS second_rating, MIN(t1.title) AS first_movie, MIN(t2.title) AS second_movie FROM company_name AS cn1, company_name AS cn2, info_type AS it1, info_type AS it2, kind_type AS kt1, kind_type AS kt2, link_type AS lt, movie_companies AS mc1, movie_companies AS mc2, movie_info_idx AS mi_idx1, movie_info_idx AS mi_idx2, movie_link AS ml, title AS t1, title AS t2 WHERE cn1.country_code != '[us]' AND it1.info = 'rating' AND it2.info = 'rating' AND kt1.kind IN ('tv series', 'episode') AND kt2.kind IN ('tv series', 'episode') AND lt.link IN ('sequel', 'follows', 'followed by') AND mi_idx2.info < '3.5' AND t2.production_year BETWEEN 2000 AND 2010 AND lt.id = ml.link_type_id AND t1.id = ml.movie_id AND t2.id = ml.linked_movie_id AND it1.id = mi_idx1.info_type_id AND t1.id = mi_idx1.movie_id AND kt1.id = t1.kind_id AND cn1.id = mc1.company_id AND t1.id = mc1.movie_id AND ml.movie_id = mi_idx1.movie_id AND ml.movie_id = mc1.movie_id AND mi_idx1.movie_id = mc1.movie_id AND it2.id = mi_idx2.info_type_id AND t2.id = mi_idx2.movie_id AND kt2.id = t2.kind_id AND cn2.id = mc2.company_id AND t2.id = mc2.movie_id AND ml.linked_movie_id = mi_idx2.movie_id AND ml.linked_movie_id = mc2.movie_id AND mi_idx2.movie_id = mc2.movie_id diff --git a/versions/queries/ontime.sql b/versions/queries/ontime.sql new file mode 100644 index 0000000000..46f8c396fb --- /dev/null +++ b/versions/queries/ontime.sql @@ -0,0 +1,11 @@ +SELECT avg(c1) FROM (SELECT Year, Month, count(*) AS c1 FROM ontime GROUP BY Year, Month) +SELECT DayOfWeek, count(*) AS c FROM ontime WHERE Year>=2000 AND Year<=2008 GROUP BY DayOfWeek ORDER BY c DESC +SELECT DayOfWeek, count(*) AS c FROM ontime WHERE DepDelay>10 AND Year>=2000 AND Year<=2008 GROUP BY DayOfWeek ORDER BY c DESC +SELECT Origin, count(*) AS c FROM ontime WHERE DepDelay>10 AND Year>=2000 AND Year<=2008 GROUP BY Origin ORDER BY c DESC LIMIT 10 +SELECT IATA_CODE_Reporting_Airline AS Carrier, count(*) FROM ontime WHERE DepDelay>10 AND Year=2007 GROUP BY Carrier ORDER BY count(*) DESC +SELECT Carrier, c, c2, c*100/c2 AS c3 FROM (SELECT IATA_CODE_Reporting_Airline AS Carrier, count(*) AS c FROM ontime WHERE DepDelay>10 AND Year=2007 GROUP BY Carrier) q JOIN (SELECT IATA_CODE_Reporting_Airline AS Carrier, count(*) AS c2 FROM ontime WHERE Year=2007 GROUP BY Carrier) qq USING Carrier ORDER BY c3 DESC +SELECT Carrier, c, c2, c*100/c2 AS c3 FROM (SELECT IATA_CODE_Reporting_Airline AS Carrier, count(*) AS c FROM ontime WHERE DepDelay>10 AND Year>=2000 AND Year<=2008 GROUP BY Carrier) q JOIN (SELECT IATA_CODE_Reporting_Airline AS Carrier, count(*) AS c2 FROM ontime WHERE Year>=2000 AND Year<=2008 GROUP BY Carrier) qq USING Carrier ORDER BY c3 DESC +SELECT Year, c1/c2 FROM (SELECT Year, count(*)*100 AS c1 FROM ontime WHERE DepDelay>10 GROUP BY Year) q JOIN (SELECT Year, count(*) AS c2 FROM ontime GROUP BY Year) qq USING (Year) ORDER BY Year +SELECT DestCityName, uniqExact(OriginCityName) AS u FROM ontime WHERE Year >= 2000 AND Year <= 2010 GROUP BY DestCityName ORDER BY u DESC LIMIT 10 +SELECT Year, count(*) AS c1 FROM ontime GROUP BY Year +SELECT min(Year), max(Year), IATA_CODE_Reporting_Airline AS Carrier, count(*) AS cnt, sum(ArrDelayMinutes>30) AS flights_delayed, round(sum(ArrDelayMinutes>30)/count(*),2) AS rate FROM ontime WHERE DayOfWeek NOT IN (6,7) AND OriginState NOT IN ('AK', 'HI', 'PR', 'VI') AND DestState NOT IN ('AK', 'HI', 'PR', 'VI') AND FlightDate < '2010-01-01' GROUP BY Carrier HAVING cnt>100000 AND max(Year)>1990 ORDER BY rate DESC LIMIT 1000 diff --git a/versions/queries/tpcds.sql b/versions/queries/tpcds.sql new file mode 100644 index 0000000000..e55ac08bcd --- /dev/null +++ b/versions/queries/tpcds.sql @@ -0,0 +1,103 @@ +WITH customer_total_return AS ( SELECT sr_customer_sk AS ctr_customer_sk, sr_store_sk AS ctr_store_sk, sum(sr_return_amt) AS ctr_total_return FROM store_returns, date_dim WHERE (sr_returned_date_sk = d_date_sk) AND (d_year = 2000) GROUP BY sr_customer_sk, sr_store_sk ) SELECT c_customer_id FROM customer_total_return AS ctr1, store, customer WHERE (ctr1.ctr_total_return > ( SELECT avg(ctr_total_return) * 1.2 FROM customer_total_return AS ctr2 WHERE ctr1.ctr_store_sk = ctr2.ctr_store_sk )) AND (s_store_sk = ctr1.ctr_store_sk) AND (s_state = 'TN') AND (ctr1.ctr_customer_sk = c_customer_sk) ORDER BY c_customer_id LIMIT 100 +WITH wscs AS ( SELECT sold_date_sk, sales_price FROM ( SELECT ws_sold_date_sk AS sold_date_sk, ws_ext_sales_price AS sales_price FROM web_sales UNION ALL SELECT cs_sold_date_sk AS sold_date_sk, cs_ext_sales_price AS sales_price FROM catalog_sales ) ), wswscs AS ( SELECT d_week_seq, sum(multiIf(d_day_name = 'Sunday', sales_price, NULL)) AS sun_sales, sum(multiIf(d_day_name = 'Monday', sales_price, NULL)) AS mon_sales, sum(multiIf(d_day_name = 'Tuesday', sales_price, NULL)) AS tue_sales, sum(multiIf(d_day_name = 'Wednesday', sales_price, NULL)) AS wed_sales, sum(multiIf(d_day_name = 'Thursday', sales_price, NULL)) AS thu_sales, sum(multiIf(d_day_name = 'Friday', sales_price, NULL)) AS fri_sales, sum(multiIf(d_day_name = 'Saturday', sales_price, NULL)) AS sat_sales FROM wscs, date_dim WHERE d_date_sk = sold_date_sk GROUP BY d_week_seq ) SELECT d_week_seq1, round(sun_sales1 / sun_sales2, 2), round(mon_sales1 / mon_sales2, 2), round(tue_sales1 / tue_sales2, 2), round(wed_sales1 / wed_sales2, 2), round(thu_sales1 / thu_sales2, 2), round(fri_sales1 / fri_sales2, 2), round(sat_sales1 / sat_sales2, 2) FROM ( SELECT wswscs.d_week_seq AS d_week_seq1, sun_sales AS sun_sales1, mon_sales AS mon_sales1, tue_sales AS tue_sales1, wed_sales AS wed_sales1, thu_sales AS thu_sales1, fri_sales AS fri_sales1, sat_sales AS sat_sales1 FROM wswscs, date_dim WHERE (date_dim.d_week_seq = wswscs.d_week_seq) AND (d_year = 2001) ) AS y, ( SELECT wswscs.d_week_seq AS d_week_seq2, sun_sales AS sun_sales2, mon_sales AS mon_sales2, tue_sales AS tue_sales2, wed_sales AS wed_sales2, thu_sales AS thu_sales2, fri_sales AS fri_sales2, sat_sales AS sat_sales2 FROM wswscs, date_dim WHERE (date_dim.d_week_seq = wswscs.d_week_seq) AND (d_year = (2001 + 1)) ) AS z WHERE d_week_seq1 = (d_week_seq2 - 53) ORDER BY d_week_seq1 +SELECT dt.d_year, item.i_brand_id AS brand_id, item.i_brand AS brand, sum(ss_ext_sales_price) AS sum_agg FROM date_dim AS dt, store_sales, item WHERE (dt.d_date_sk = store_sales.ss_sold_date_sk) AND (store_sales.ss_item_sk = item.i_item_sk) AND (item.i_manufact_id = 128) AND (dt.d_moy = 11) GROUP BY dt.d_year, item.i_brand, item.i_brand_id ORDER BY dt.d_year, sum_agg DESC, brand_id LIMIT 100 +WITH year_total AS ( SELECT c_customer_id AS customer_id, c_first_name AS customer_first_name, c_last_name AS customer_last_name, c_preferred_cust_flag AS customer_preferred_cust_flag, c_birth_country AS customer_birth_country, c_login AS customer_login, c_email_address AS customer_email_address, d_year AS dyear, sum((((ss_ext_list_price - ss_ext_wholesale_cost) - ss_ext_discount_amt) + ss_ext_sales_price) / 2) AS year_total, 's' AS sale_type FROM customer, store_sales, date_dim WHERE (c_customer_sk = ss_customer_sk) AND (ss_sold_date_sk = d_date_sk) GROUP BY c_customer_id, c_first_name, c_last_name, c_preferred_cust_flag, c_birth_country, c_login, c_email_address, d_year UNION ALL SELECT c_customer_id AS customer_id, c_first_name AS customer_first_name, c_last_name AS customer_last_name, c_preferred_cust_flag AS customer_preferred_cust_flag, c_birth_country AS customer_birth_country, c_login AS customer_login, c_email_address AS customer_email_address, d_year AS dyear, sum((((cs_ext_list_price - cs_ext_wholesale_cost) - cs_ext_discount_amt) + cs_ext_sales_price) / 2) AS year_total, 'c' AS sale_type FROM customer, catalog_sales, date_dim WHERE (c_customer_sk = cs_bill_customer_sk) AND (cs_sold_date_sk = d_date_sk) GROUP BY c_customer_id, c_first_name, c_last_name, c_preferred_cust_flag, c_birth_country, c_login, c_email_address, d_year UNION ALL SELECT c_customer_id AS customer_id, c_first_name AS customer_first_name, c_last_name AS customer_last_name, c_preferred_cust_flag AS customer_preferred_cust_flag, c_birth_country AS customer_birth_country, c_login AS customer_login, c_email_address AS customer_email_address, d_year AS dyear, sum((((ws_ext_list_price - ws_ext_wholesale_cost) - ws_ext_discount_amt) + ws_ext_sales_price) / 2) AS year_total, 'w' AS sale_type FROM customer, web_sales, date_dim WHERE (c_customer_sk = ws_bill_customer_sk) AND (ws_sold_date_sk = d_date_sk) GROUP BY c_customer_id, c_first_name, c_last_name, c_preferred_cust_flag, c_birth_country, c_login, c_email_address, d_year ) SELECT t_s_secyear.customer_id, t_s_secyear.customer_first_name, t_s_secyear.customer_last_name, t_s_secyear.customer_preferred_cust_flag FROM year_total AS t_s_firstyear, year_total AS t_s_secyear, year_total AS t_c_firstyear, year_total AS t_c_secyear, year_total AS t_w_firstyear, year_total AS t_w_secyear WHERE (t_s_secyear.customer_id = t_s_firstyear.customer_id) AND (t_s_firstyear.customer_id = t_c_secyear.customer_id) AND (t_s_firstyear.customer_id = t_c_firstyear.customer_id) AND (t_s_firstyear.customer_id = t_w_firstyear.customer_id) AND (t_s_firstyear.customer_id = t_w_secyear.customer_id) AND (t_s_firstyear.sale_type = 's') AND (t_c_firstyear.sale_type = 'c') AND (t_w_firstyear.sale_type = 'w') AND (t_s_secyear.sale_type = 's') AND (t_c_secyear.sale_type = 'c') AND (t_w_secyear.sale_type = 'w') AND (t_s_firstyear.dyear = 2001) AND (t_s_secyear.dyear = (2001 + 1)) AND (t_c_firstyear.dyear = 2001) AND (t_c_secyear.dyear = (2001 + 1)) AND (t_w_firstyear.dyear = 2001) AND (t_w_secyear.dyear = (2001 + 1)) AND (t_s_firstyear.year_total > 0) AND (t_c_firstyear.year_total > 0) AND (t_w_firstyear.year_total > 0) AND (multiIf(t_c_firstyear.year_total > 0, t_c_secyear.year_total / t_c_firstyear.year_total, NULL) > multiIf(t_s_firstyear.year_total > 0, t_s_secyear.year_total / t_s_firstyear.year_total, NULL)) AND (multiIf(t_c_firstyear.year_total > 0, t_c_secyear.year_total / t_c_firstyear.year_total, NULL) > multiIf(t_w_firstyear.year_total > 0, t_w_secyear.year_total / t_w_firstyear.year_total, NULL)) ORDER BY t_s_secyear.customer_id, t_s_secyear.customer_first_name, t_s_secyear.customer_last_name, t_s_secyear.customer_preferred_cust_flag LIMIT 100 +WITH ssr AS ( SELECT s_store_id, sum(sales_price) AS sales, sum(profit) AS profit, sum(return_amt) AS returns, sum(net_loss) AS profit_loss FROM ( SELECT ss_store_sk AS store_sk, ss_sold_date_sk AS date_sk, ss_ext_sales_price AS sales_price, ss_net_profit AS profit, CAST(0, 'decimal(7, 2)') AS return_amt, CAST(0, 'decimal(7, 2)') AS net_loss FROM store_sales UNION ALL SELECT sr_store_sk AS store_sk, sr_returned_date_sk AS date_sk, CAST(0, 'decimal(7, 2)') AS sales_price, CAST(0, 'decimal(7, 2)') AS profit, sr_return_amt AS return_amt, sr_net_loss AS net_loss FROM store_returns ) AS salesreturns, date_dim, store WHERE (date_sk = d_date_sk) AND ((d_date >= CAST('2000-08-23', 'date')) AND (d_date <= (CAST('2000-08-23', 'date') + INTERVAL 14 day))) AND (store_sk = s_store_sk) GROUP BY s_store_id ), csr AS ( SELECT cp_catalog_page_id, sum(sales_price) AS sales, sum(profit) AS profit, sum(return_amt) AS returns, sum(net_loss) AS profit_loss FROM ( SELECT cs_catalog_page_sk AS page_sk, cs_sold_date_sk AS date_sk, cs_ext_sales_price AS sales_price, cs_net_profit AS profit, CAST(0, 'decimal(7, 2)') AS return_amt, CAST(0, 'decimal(7, 2)') AS net_loss FROM catalog_sales UNION ALL SELECT cr_catalog_page_sk AS page_sk, cr_returned_date_sk AS date_sk, CAST(0, 'decimal(7, 2)') AS sales_price, CAST(0, 'decimal(7, 2)') AS profit, cr_return_amount AS return_amt, cr_net_loss AS net_loss FROM catalog_returns ) AS salesreturns, date_dim, catalog_page WHERE (date_sk = d_date_sk) AND (d_date BETWEEN CAST('2000-08-23', 'date') AND CAST('2000-08-23', 'date') + INTERVAL 14 day) AND (page_sk = cp_catalog_page_sk) GROUP BY cp_catalog_page_id ), wsr AS ( SELECT web_site_id, sum(sales_price) AS sales, sum(profit) AS profit, sum(return_amt) AS returns, sum(net_loss) AS profit_loss FROM ( SELECT ws_web_site_sk AS wsr_web_site_sk, ws_sold_date_sk AS date_sk, ws_ext_sales_price AS sales_price, ws_net_profit AS profit, CAST(0, 'decimal(7, 2)') AS return_amt, CAST(0, 'decimal(7, 2)') AS net_loss FROM web_sales UNION ALL SELECT ws_web_site_sk AS wsr_web_site_sk, wr_returned_date_sk AS date_sk, CAST(0, 'decimal(7, 2)') AS sales_price, CAST(0, 'decimal(7, 2)') AS profit, wr_return_amt AS return_amt, wr_net_loss AS net_loss FROM web_returns LEFT JOIN web_sales ON (wr_item_sk = ws_item_sk) AND (wr_order_number = ws_order_number) ) AS salesreturns, date_dim, web_site WHERE (date_sk = d_date_sk) AND ((d_date >= CAST('2000-08-23', 'date')) AND (d_date <= (CAST('2000-08-23', 'date') + INTERVAL 14 day))) AND (wsr_web_site_sk = web_site_sk) GROUP BY web_site_id ) SELECT channel, id, sum(sales) AS sales, sum(returns) AS returns, sum(profit) AS profit FROM ( SELECT 'store channel' AS channel, concat('store', s_store_id) AS id, sales, returns, profit - profit_loss AS profit FROM ssr UNION ALL SELECT 'catalog channel' AS channel, concat('catalog_page', cp_catalog_page_id) AS id, sales, returns, profit - profit_loss AS profit FROM csr UNION ALL SELECT 'web channel' AS channel, concat('web_site', web_site_id) AS id, sales, returns, profit - profit_loss AS profit FROM wsr ) AS x GROUP BY channel, id WITH ROLLUP ORDER BY channel, id LIMIT 100 +SELECT a.ca_state AS state, count(*) AS cnt FROM customer_address AS a, customer AS c, store_sales AS s, date_dim AS d, item AS i WHERE (a.ca_address_sk = c.c_current_addr_sk) AND (c.c_customer_sk = s.ss_customer_sk) AND (s.ss_sold_date_sk = d.d_date_sk) AND (s.ss_item_sk = i.i_item_sk) AND (d.d_month_seq = ( SELECT DISTINCT d_month_seq FROM date_dim WHERE (d_year = 2001) AND (d_moy = 1) )) AND (i.i_current_price > 1.2 * ( SELECT avg(j.i_current_price) FROM item AS j WHERE (j.i_category = i.i_category) )) GROUP BY a.ca_state HAVING count(*) >= 10 ORDER BY cnt, a.ca_state LIMIT 100 +SELECT i_item_id, avg(ss_quantity) AS agg1, avg(ss_list_price) AS agg2, avg(ss_coupon_amt) AS agg3, avg(ss_sales_price) AS agg4 FROM store_sales, customer_demographics, date_dim, item, promotion WHERE (ss_sold_date_sk = d_date_sk) AND (ss_item_sk = i_item_sk) AND (ss_cdemo_sk = cd_demo_sk) AND (ss_promo_sk = p_promo_sk) AND (cd_gender = 'M') AND (cd_marital_status = 'S') AND (cd_education_status = 'College') AND ((p_channel_email = 'N') OR (p_channel_event = 'N')) AND (d_year = 2000) GROUP BY i_item_id ORDER BY i_item_id LIMIT 100 +SELECT s_store_name, sum(ss_net_profit) FROM store_sales, date_dim, store, ( SELECT substr(ca_zip, 1, 2) AS ca_zip FROM ( SELECT substr(ca_zip, 1, 5) AS ca_zip FROM customer_address WHERE substr(ca_zip, 1, 5) IN ('24128', '76232', '65084', '87816', '83926', '77556', '20548', '26231', '43848', '15126', '91137', '61265', '98294', '25782', '17920', '18426', '98235', '40081', '84093', '28577', '55565', '17183', '54601', '67897', '22752', '86284', '18376', '38607', '45200', '21756', '29741', '96765', '23932', '89360', '29839', '25989', '28898', '91068', '72550', '10390', '18845', '47770', '82636', '41367', '76638', '86198', '81312', '37126', '39192', '88424', '72175', '81426', '53672', '10445', '42666', '66864', '66708', '41248', '48583', '82276', '18842', '78890', '49448', '14089', '38122', '34425', '79077', '19849', '43285', '39861', '66162', '77610', '13695', '99543', '83444', '83041', '12305', '57665', '68341', '25003', '57834', '62878', '49130', '81096', '18840', '27700', '23470', '50412', '21195', '16021', '76107', '71954', '68309', '18119', '98359', '64544', '10336', '86379', '27068', '39736', '98569', '28915', '24206', '56529', '57647', '54917', '42961', '91110', '63981', '14922', '36420', '23006', '67467', '32754', '30903', '20260', '31671', '51798', '72325', '85816', '68621', '13955', '36446', '41766', '68806', '16725', '15146', '22744', '35850', '88086', '51649', '18270', '52867', '39972', '96976', '63792', '11376', '94898', '13595', '10516', '90225', '58943', '39371', '94945', '28587', '96576', '57855', '28488', '26105', '83933', '25858', '34322', '44438', '73171', '30122', '34102', '22685', '71256', '78451', '54364', '13354', '45375', '40558', '56458', '28286', '45266', '47305', '69399', '83921', '26233', '11101', '15371', '69913', '35942', '15882', '25631', '24610', '44165', '99076', '33786', '70738', '26653', '14328', '72305', '62496', '22152', '10144', '64147', '48425', '14663', '21076', '18799', '30450', '63089', '81019', '68893', '24996', '51200', '51211', '45692', '92712', '70466', '79994', '22437', '25280', '38935', '71791', '73134', '56571', '14060', '19505', '72425', '56575', '74351', '68786', '51650', '20004', '18383', '76614', '11634', '18906', '15765', '41368', '73241', '76698', '78567', '97189', '28545', '76231', '75691', '22246', '51061', '90578', '56691', '68014', '51103', '94167', '57047', '14867', '73520', '15734', '63435', '25733', '35474', '24676', '94627', '53535', '17879', '15559', '53268', '59166', '11928', '59402', '33282', '45721', '43933', '68101', '33515', '36634', '71286', '19736', '58058', '55253', '67473', '41918', '19515', '36495', '19430', '22351', '77191', '91393', '49156', '50298', '87501', '18652', '53179', '18767', '63193', '23968', '65164', '68880', '21286', '72823', '58470', '67301', '13394', '31016', '70372', '67030', '40604', '24317', '45748', '39127', '26065', '77721', '31029', '31880', '60576', '24671', '45549', '13376', '50016', '33123', '19769', '22927', '97789', '46081', '72151', '15723', '46136', '51949', '68100', '96888', '64528', '14171', '79777', '28709', '11489', '25103', '32213', '78668', '22245', '15798', '27156', '37930', '62971', '21337', '51622', '67853', '10567', '38415', '15455', '58263', '42029', '60279', '37125', '56240', '88190', '50308', '26859', '64457', '89091', '82136', '62377', '36233', '63837', '58078', '17043', '30010', '60099', '28810', '98025', '29178', '87343', '73273', '30469', '64034', '39516', '86057', '21309', '90257', '67875', '40162', '11356', '73650', '61810', '72013', '30431', '22461', '19512', '13375', '55307', '30625', '83849', '68908', '26689', '96451', '38193', '46820', '88885', '84935', '69035', '83144', '47537', '56616', '94983', '48033', '69952', '25486', '61547', '27385', '61860', '58048', '56910', '16807', '17871', '35258', '31387', '35458', '35576') INTERSECT SELECT ca_zip FROM ( SELECT substr(ca_zip, 1, 5) AS ca_zip, count(*) AS cnt FROM customer_address, customer WHERE (ca_address_sk = c_current_addr_sk) AND (c_preferred_cust_flag = 'Y') GROUP BY ca_zip HAVING count(*) > 10 ) AS A1 ) AS A2 ) AS V1 WHERE (ss_store_sk = s_store_sk) AND (ss_sold_date_sk = d_date_sk) AND (d_qoy = 2) AND (d_year = 1998) AND (substr(s_zip, 1, 2) = substr(V1.ca_zip, 1, 2)) GROUP BY s_store_name ORDER BY s_store_name LIMIT 100 +SELECT multiIf(( SELECT count(*) FROM store_sales WHERE (ss_quantity >= 1) AND (ss_quantity <= 20) ) > 74129, ( SELECT avg(ss_ext_discount_amt) FROM store_sales WHERE (ss_quantity >= 1) AND (ss_quantity <= 20) ), ( SELECT avg(ss_net_paid) FROM store_sales WHERE (ss_quantity >= 1) AND (ss_quantity <= 20) )) AS bucket1, multiIf(( SELECT count(*) FROM store_sales WHERE (ss_quantity >= 21) AND (ss_quantity <= 40) ) > 122840, ( SELECT avg(ss_ext_discount_amt) FROM store_sales WHERE (ss_quantity >= 21) AND (ss_quantity <= 40) ), ( SELECT avg(ss_net_paid) FROM store_sales WHERE (ss_quantity >= 21) AND (ss_quantity <= 40) )) AS bucket2, multiIf(( SELECT count(*) FROM store_sales WHERE (ss_quantity >= 41) AND (ss_quantity <= 60) ) > 56580, ( SELECT avg(ss_ext_discount_amt) FROM store_sales WHERE (ss_quantity >= 41) AND (ss_quantity <= 60) ), ( SELECT avg(ss_net_paid) FROM store_sales WHERE (ss_quantity >= 41) AND (ss_quantity <= 60) )) AS bucket3, multiIf(( SELECT count(*) FROM store_sales WHERE (ss_quantity >= 61) AND (ss_quantity <= 80) ) > 10097, ( SELECT avg(ss_ext_discount_amt) FROM store_sales WHERE (ss_quantity >= 61) AND (ss_quantity <= 80) ), ( SELECT avg(ss_net_paid) FROM store_sales WHERE (ss_quantity >= 61) AND (ss_quantity <= 80) )) AS bucket4, multiIf(( SELECT count(*) FROM store_sales WHERE (ss_quantity >= 81) AND (ss_quantity <= 100) ) > 165306, ( SELECT avg(ss_ext_discount_amt) FROM store_sales WHERE (ss_quantity >= 81) AND (ss_quantity <= 100) ), ( SELECT avg(ss_net_paid) FROM store_sales WHERE (ss_quantity >= 81) AND (ss_quantity <= 100) )) AS bucket5 FROM reason WHERE r_reason_sk = 1 +SELECT cd_gender, cd_marital_status, cd_education_status, count(*) AS cnt1, cd_purchase_estimate, count(*) AS cnt2, cd_credit_rating, count(*) AS cnt3, cd_dep_count, count(*) AS cnt4, cd_dep_employed_count, count(*) AS cnt5, cd_dep_college_count, count(*) AS cnt6 FROM customer AS c, customer_address AS ca, customer_demographics WHERE (c.c_current_addr_sk = ca.ca_address_sk) AND (ca_county IN ('Rush County', 'Toole County', 'Jefferson County', 'Dona Ana County', 'La Porte County')) AND (cd_demo_sk = c.c_current_cdemo_sk) AND exists(( SELECT * FROM store_sales, date_dim WHERE (c.c_customer_sk = ss_customer_sk) AND (ss_sold_date_sk = d_date_sk) AND (d_year = 2002) AND ((d_moy >= 1) AND (d_moy <= (1 + 3))) )) AND (exists(( SELECT * FROM web_sales, date_dim WHERE (c.c_customer_sk = ws_bill_customer_sk) AND (ws_sold_date_sk = d_date_sk) AND (d_year = 2002) AND ((d_moy >= 1) AND (d_moy <= (1 + 3))) )) OR exists(( SELECT * FROM catalog_sales, date_dim WHERE (c.c_customer_sk = cs_ship_customer_sk) AND (cs_sold_date_sk = d_date_sk) AND (d_year = 2002) AND ((d_moy >= 1) AND (d_moy <= (1 + 3))) ))) GROUP BY cd_gender, cd_marital_status, cd_education_status, cd_purchase_estimate, cd_credit_rating, cd_dep_count, cd_dep_employed_count, cd_dep_college_count ORDER BY cd_gender, cd_marital_status, cd_education_status, cd_purchase_estimate, cd_credit_rating, cd_dep_count, cd_dep_employed_count, cd_dep_college_count LIMIT 100 +WITH year_total AS ( SELECT c_customer_id AS customer_id, c_first_name AS customer_first_name, c_last_name AS customer_last_name, c_preferred_cust_flag AS customer_preferred_cust_flag, c_birth_country AS customer_birth_country, c_login AS customer_login, c_email_address AS customer_email_address, d_year AS dyear, sum(ss_ext_list_price - ss_ext_discount_amt) AS year_total, 's' AS sale_type FROM customer, store_sales, date_dim WHERE (c_customer_sk = ss_customer_sk) AND (ss_sold_date_sk = d_date_sk) GROUP BY c_customer_id, c_first_name, c_last_name, c_preferred_cust_flag, c_birth_country, c_login, c_email_address, d_year UNION ALL SELECT c_customer_id AS customer_id, c_first_name AS customer_first_name, c_last_name AS customer_last_name, c_preferred_cust_flag AS customer_preferred_cust_flag, c_birth_country AS customer_birth_country, c_login AS customer_login, c_email_address AS customer_email_address, d_year AS dyear, sum(ws_ext_list_price - ws_ext_discount_amt) AS year_total, 'w' AS sale_type FROM customer, web_sales, date_dim WHERE (c_customer_sk = ws_bill_customer_sk) AND (ws_sold_date_sk = d_date_sk) GROUP BY c_customer_id, c_first_name, c_last_name, c_preferred_cust_flag, c_birth_country, c_login, c_email_address, d_year ) SELECT t_s_secyear.customer_id, t_s_secyear.customer_first_name, t_s_secyear.customer_last_name, t_s_secyear.customer_preferred_cust_flag FROM year_total AS t_s_firstyear, year_total AS t_s_secyear, year_total AS t_w_firstyear, year_total AS t_w_secyear WHERE (t_s_secyear.customer_id = t_s_firstyear.customer_id) AND (t_s_firstyear.customer_id = t_w_secyear.customer_id) AND (t_s_firstyear.customer_id = t_w_firstyear.customer_id) AND (t_s_firstyear.sale_type = 's') AND (t_w_firstyear.sale_type = 'w') AND (t_s_secyear.sale_type = 's') AND (t_w_secyear.sale_type = 'w') AND (t_s_firstyear.dyear = 2001) AND (t_s_secyear.dyear = (2001 + 1)) AND (t_w_firstyear.dyear = 2001) AND (t_w_secyear.dyear = (2001 + 1)) AND (t_s_firstyear.year_total > 0) AND (t_w_firstyear.year_total > 0) AND (multiIf(t_w_firstyear.year_total > 0, CAST(t_w_secyear.year_total AS Float32) / t_w_firstyear.year_total, 0.) > multiIf(t_s_firstyear.year_total > 0, CAST(t_s_secyear.year_total AS Float32) / t_s_firstyear.year_total, 0.)) ORDER BY t_s_secyear.customer_id, t_s_secyear.customer_first_name, t_s_secyear.customer_last_name, t_s_secyear.customer_preferred_cust_flag LIMIT 100 +SELECT i_item_id, i_item_desc, i_category, i_class, i_current_price, sum(ws_ext_sales_price) AS itemrevenue, (sum(ws_ext_sales_price) * 100) / sum(sum(ws_ext_sales_price)) OVER (PARTITION BY i_class) AS revenueratio FROM web_sales, item, date_dim WHERE (ws_item_sk = i_item_sk) AND (i_category IN ('Sports', 'Books', 'Home')) AND (ws_sold_date_sk = d_date_sk) AND ((d_date >= CAST('1999-02-22', 'date')) AND (d_date <= (CAST('1999-02-22', 'date') + INTERVAL 30 day))) GROUP BY i_item_id, i_item_desc, i_category, i_class, i_current_price ORDER BY i_category, i_class, i_item_id, i_item_desc, revenueratio LIMIT 100 +SELECT avg(ss_quantity), avg(ss_ext_sales_price), avg(ss_ext_wholesale_cost), sum(ss_ext_wholesale_cost) FROM store_sales, store, customer_demographics, household_demographics, customer_address, date_dim WHERE (s_store_sk = ss_store_sk) AND (ss_sold_date_sk = d_date_sk) AND (d_year = 2001) AND ( ( (ss_hdemo_sk = hd_demo_sk) AND (cd_demo_sk = ss_cdemo_sk) AND (cd_marital_status = 'M') AND (cd_education_status = 'Advanced Degree') AND (ss_sales_price BETWEEN 100.00 AND 150.00) AND (hd_dep_count = 3) ) OR ( (ss_hdemo_sk = hd_demo_sk) AND (cd_demo_sk = ss_cdemo_sk) AND (cd_marital_status = 'S') AND (cd_education_status = 'College') AND (ss_sales_price BETWEEN 50.00 AND 100.00) AND (hd_dep_count = 1) ) OR ( (ss_hdemo_sk = hd_demo_sk) AND (cd_demo_sk = ss_cdemo_sk) AND (cd_marital_status = 'W') AND (cd_education_status = '2 yr Degree') AND (ss_sales_price BETWEEN 150.00 AND 200.) AND (hd_dep_count = 1) ) ) AND ( ( (ss_addr_sk = ca_address_sk) AND (ca_country = 'United States') AND (ca_state IN ('TX', 'OH', 'TX')) AND (ss_net_profit BETWEEN 100 AND 200) ) OR ( (ss_addr_sk = ca_address_sk) AND (ca_country = 'United States') AND (ca_state IN ('OR', 'NM', 'KY')) AND (ss_net_profit BETWEEN 150 AND 300) ) OR ( (ss_addr_sk = ca_address_sk) AND (ca_country = 'United States') AND (ca_state IN ('VA', 'TX', 'MS')) AND (ss_net_profit BETWEEN 50 AND 250) ) ) +WITH cross_items AS ( SELECT i_item_sk AS ss_item_sk FROM item, ( SELECT iss.i_brand_id AS brand_id, iss.i_class_id AS class_id, iss.i_category_id AS category_id FROM store_sales, item AS iss, date_dim AS d1 WHERE (ss_item_sk = iss.i_item_sk) AND (ss_sold_date_sk = d1.d_date_sk) AND (d1.d_year BETWEEN 1999 AND 1999 + 2) INTERSECT SELECT ics.i_brand_id, ics.i_class_id, ics.i_category_id FROM catalog_sales, item AS ics, date_dim AS d2 WHERE (cs_item_sk = ics.i_item_sk) AND (cs_sold_date_sk = d2.d_date_sk) AND (d2.d_year BETWEEN 1999 AND 1999 + 2) INTERSECT SELECT iws.i_brand_id, iws.i_class_id, iws.i_category_id FROM web_sales, item AS iws, date_dim AS d3 WHERE (ws_item_sk = iws.i_item_sk) AND (ws_sold_date_sk = d3.d_date_sk) AND (d3.d_year BETWEEN 1999 AND 1999 + 2) ) WHERE (i_brand_id = brand_id) AND (i_class_id = class_id) AND (i_category_id = category_id) ), avg_sales AS ( SELECT avg(quantity * list_price) AS average_sales FROM ( SELECT ss_quantity AS quantity, ss_list_price AS list_price FROM store_sales, date_dim WHERE (ss_sold_date_sk = d_date_sk) AND (d_year BETWEEN 1999 AND 1999 + 2) UNION ALL SELECT cs_quantity AS quantity, cs_list_price AS list_price FROM catalog_sales, date_dim WHERE (cs_sold_date_sk = d_date_sk) AND (d_year BETWEEN 1999 AND 1999 + 2) UNION ALL SELECT ws_quantity AS quantity, ws_list_price AS list_price FROM web_sales, date_dim WHERE (ws_sold_date_sk = d_date_sk) AND (d_year BETWEEN 1999 AND 1999 + 2) ) AS x ) SELECT channel, i_brand_id, i_class_id, i_category_id, sum(sales), sum(number_sales) FROM ( SELECT 'store' AS channel, i_brand_id, i_class_id, i_category_id, sum(ss_quantity * ss_list_price) AS sales, count(*) AS number_sales FROM store_sales, item, date_dim WHERE (ss_item_sk IN ( SELECT ss_item_sk FROM cross_items )) AND (ss_item_sk = i_item_sk) AND (ss_sold_date_sk = d_date_sk) AND (d_year = (1999 + 2)) AND (d_moy = 11) GROUP BY i_brand_id, i_class_id, i_category_id HAVING sum(ss_quantity * ss_list_price) > ( SELECT average_sales FROM avg_sales ) UNION ALL SELECT 'catalog' AS channel, i_brand_id, i_class_id, i_category_id, sum(cs_quantity * cs_list_price) AS sales, count(*) AS number_sales FROM catalog_sales, item, date_dim WHERE (cs_item_sk IN ( SELECT ss_item_sk FROM cross_items )) AND (cs_item_sk = i_item_sk) AND (cs_sold_date_sk = d_date_sk) AND (d_year = (1999 + 2)) AND (d_moy = 11) GROUP BY i_brand_id, i_class_id, i_category_id HAVING sum(cs_quantity * cs_list_price) > ( SELECT average_sales FROM avg_sales ) UNION ALL SELECT 'web' AS channel, i_brand_id, i_class_id, i_category_id, sum(ws_quantity * ws_list_price) AS sales, count(*) AS number_sales FROM web_sales, item, date_dim WHERE (ws_item_sk IN ( SELECT ss_item_sk FROM cross_items )) AND (ws_item_sk = i_item_sk) AND (ws_sold_date_sk = d_date_sk) AND (d_year = (1999 + 2)) AND (d_moy = 11) GROUP BY i_brand_id, i_class_id, i_category_id HAVING sum(ws_quantity * ws_list_price) > ( SELECT average_sales FROM avg_sales ) ) AS y GROUP BY channel, i_brand_id, i_class_id, i_category_id WITH ROLLUP ORDER BY channel, i_brand_id, i_class_id, i_category_id LIMIT 100 +WITH cross_items AS ( SELECT i_item_sk AS ss_item_sk FROM item, ( SELECT iss.i_brand_id AS brand_id, iss.i_class_id AS class_id, iss.i_category_id AS category_id FROM store_sales, item AS iss, date_dim AS d1 WHERE (ss_item_sk = iss.i_item_sk) AND (ss_sold_date_sk = d1.d_date_sk) AND (d1.d_year BETWEEN 1999 AND 1999 + 2) INTERSECT SELECT ics.i_brand_id, ics.i_class_id, ics.i_category_id FROM catalog_sales, item AS ics, date_dim AS d2 WHERE (cs_item_sk = ics.i_item_sk) AND (cs_sold_date_sk = d2.d_date_sk) AND (d2.d_year BETWEEN 1999 AND 1999 + 2) INTERSECT SELECT iws.i_brand_id, iws.i_class_id, iws.i_category_id FROM web_sales, item AS iws, date_dim AS d3 WHERE (ws_item_sk = iws.i_item_sk) AND (ws_sold_date_sk = d3.d_date_sk) AND (d3.d_year BETWEEN 1999 AND 1999 + 2) ) WHERE (i_brand_id = brand_id) AND (i_class_id = class_id) AND (i_category_id = category_id) ), avg_sales AS ( SELECT avg(quantity * list_price) AS average_sales FROM ( SELECT ss_quantity AS quantity, ss_list_price AS list_price FROM store_sales, date_dim WHERE (ss_sold_date_sk = d_date_sk) AND (d_year BETWEEN 1999 AND 1999 + 2) UNION ALL SELECT cs_quantity AS quantity, cs_list_price AS list_price FROM catalog_sales, date_dim WHERE (cs_sold_date_sk = d_date_sk) AND (d_year BETWEEN 1999 AND 1999 + 2) UNION ALL SELECT ws_quantity AS quantity, ws_list_price AS list_price FROM web_sales, date_dim WHERE (ws_sold_date_sk = d_date_sk) AND (d_year BETWEEN 1999 AND 1999 + 2) ) AS x ) SELECT this_year.channel AS ty_channel, this_year.i_brand_id AS ty_brand, this_year.i_class_id AS ty_class, this_year.i_category_id AS ty_category, this_year.sales AS ty_sales, this_year.number_sales AS ty_number_sales, last_year.channel AS ly_channel, last_year.i_brand_id AS ly_brand, last_year.i_class_id AS ly_class, last_year.i_category_id AS ly_category, last_year.sales AS ly_sales, last_year.number_sales AS ly_number_sales FROM ( SELECT 'store' AS channel, i_brand_id, i_class_id, i_category_id, sum(ss_quantity * ss_list_price) AS sales, count(*) AS number_sales FROM store_sales, item, date_dim WHERE (ss_item_sk IN ( SELECT ss_item_sk FROM cross_items )) AND (ss_item_sk = i_item_sk) AND (ss_sold_date_sk = d_date_sk) AND (d_week_seq = ( SELECT d_week_seq FROM date_dim WHERE (d_year = 1999 + 1) AND (d_moy = 12) AND (d_dom = 11) )) GROUP BY i_brand_id, i_class_id, i_category_id HAVING sum(ss_quantity * ss_list_price) > ( SELECT average_sales FROM avg_sales ) ) AS this_year, ( SELECT 'store' AS channel, i_brand_id, i_class_id, i_category_id, sum(ss_quantity * ss_list_price) AS sales, count(*) AS number_sales FROM store_sales, item, date_dim WHERE (ss_item_sk IN ( SELECT ss_item_sk FROM cross_items )) AND (ss_item_sk = i_item_sk) AND (ss_sold_date_sk = d_date_sk) AND (d_week_seq = ( SELECT d_week_seq FROM date_dim WHERE (d_year = 1999) AND (d_moy = 12) AND (d_dom = 11) )) GROUP BY i_brand_id, i_class_id, i_category_id HAVING sum(ss_quantity * ss_list_price) > ( SELECT average_sales FROM avg_sales ) ) AS last_year WHERE (this_year.i_brand_id = last_year.i_brand_id) AND (this_year.i_class_id = last_year.i_class_id) AND (this_year.i_category_id = last_year.i_category_id) ORDER BY this_year.channel, this_year.i_brand_id, this_year.i_class_id, this_year.i_category_id LIMIT 100 +SELECT ca_zip, sum(cs_sales_price) FROM catalog_sales, customer, customer_address, date_dim WHERE (cs_bill_customer_sk = c_customer_sk) AND (c_current_addr_sk = ca_address_sk) AND ((substr(ca_zip, 1, 5) IN ('85669', '86197', '88274', '83405', '86475', '85392', '85460', '80348', '81792')) OR (ca_state IN ('CA', 'WA', 'GA')) OR (cs_sales_price > 500)) AND (cs_sold_date_sk = d_date_sk) AND (d_qoy = 2) AND (d_year = 2001) GROUP BY ca_zip ORDER BY ca_zip LIMIT 100 +SELECT count(DISTINCT cs_order_number) AS "order count", sum(cs_ext_ship_cost) AS "total shipping cost", sum(cs_net_profit) AS "total net profit" FROM catalog_sales AS cs1, date_dim, customer_address, call_center WHERE (d_date BETWEEN '2002-2-01' AND (CAST('2002-2-01' AS date) + INTERVAL 60 DAY)) AND (cs1.cs_ship_date_sk = d_date_sk) AND (cs1.cs_ship_addr_sk = ca_address_sk) AND (ca_state = 'GA') AND (cs1.cs_call_center_sk = cc_call_center_sk) AND (cc_county IN ('Williamson County', 'Williamson County', 'Williamson County', 'Williamson County', 'Williamson County')) AND EXISTS ( SELECT * FROM catalog_sales AS cs2 WHERE (cs1.cs_order_number = cs2.cs_order_number) AND (cs1.cs_warehouse_sk <> cs2.cs_warehouse_sk) ) AND NOT EXISTS ( SELECT * FROM catalog_returns AS cr1 WHERE (cs1.cs_order_number = cr1.cr_order_number) ) ORDER BY count(DISTINCT cs_order_number) LIMIT 100 +SELECT i_item_id, i_item_desc, s_state, count(ss_quantity) AS store_sales_quantitycount, avg(ss_quantity) AS store_sales_quantityave, stddev_samp(ss_quantity) AS store_sales_quantitystdev, stddev_samp(ss_quantity) / avg(ss_quantity) AS store_sales_quantitycov, count(sr_return_quantity) AS store_returns_quantitycount, avg(sr_return_quantity) AS store_returns_quantityave, stddev_samp(sr_return_quantity) AS store_returns_quantitystdev, stddev_samp(sr_return_quantity) / avg(sr_return_quantity) AS store_returns_quantitycov, count(cs_quantity) AS catalog_sales_quantitycount, avg(cs_quantity) AS catalog_sales_quantityave, stddev_samp(cs_quantity) AS catalog_sales_quantitystdev, stddev_samp(cs_quantity) / avg(cs_quantity) AS catalog_sales_quantitycov FROM store_sales, store_returns, catalog_sales, date_dim AS d1, date_dim AS d2, date_dim AS d3, store, item WHERE (d1.d_quarter_name = '2001Q1') AND (d1.d_date_sk = ss_sold_date_sk) AND (i_item_sk = ss_item_sk) AND (s_store_sk = ss_store_sk) AND (ss_customer_sk = sr_customer_sk) AND (ss_item_sk = sr_item_sk) AND (ss_ticket_number = sr_ticket_number) AND (sr_returned_date_sk = d2.d_date_sk) AND (d2.d_quarter_name IN ('2001Q1', '2001Q2', '2001Q3')) AND (sr_customer_sk = cs_bill_customer_sk) AND (sr_item_sk = cs_item_sk) AND (cs_sold_date_sk = d3.d_date_sk) AND (d3.d_quarter_name IN ('2001Q1', '2001Q2', '2001Q3')) GROUP BY i_item_id, i_item_desc, s_state ORDER BY i_item_id, i_item_desc, s_state LIMIT 100 +SELECT i_item_id, ca_country, ca_state, ca_county, avg(CAST(cs_quantity AS Nullable(decimal(12, 2)))) AS agg1, avg(CAST(cs_list_price AS Nullable(decimal(12, 2)))) AS agg2, avg(CAST(cs_coupon_amt AS Nullable(decimal(12, 2)))) AS agg3, avg(CAST(cs_sales_price AS Nullable(decimal(12, 2)))) AS agg4, avg(CAST(cs_net_profit AS Nullable(decimal(12, 2)))) AS agg5, avg(CAST(c_birth_year AS Nullable(decimal(12, 2)))) AS agg6, avg(CAST(cd1.cd_dep_count AS Nullable(decimal(12, 2)))) AS agg7 FROM catalog_sales, customer_demographics AS cd1, customer_demographics AS cd2, customer, customer_address, date_dim, item WHERE (cs_sold_date_sk = d_date_sk) AND (cs_item_sk = i_item_sk) AND (cs_bill_cdemo_sk = cd1.cd_demo_sk) AND (cs_bill_customer_sk = c_customer_sk) AND (cd1.cd_gender = 'F') AND (cd1.cd_education_status = 'Unknown') AND (c_current_cdemo_sk = cd2.cd_demo_sk) AND (c_current_addr_sk = ca_address_sk) AND (c_birth_month IN (1, 6, 8, 9, 12, 2)) AND (d_year = 1998) AND (ca_state IN ('MS', 'IN', 'ND', 'OK', 'NM', 'VA', 'MS')) GROUP BY ROLLUP (i_item_id, ca_country, ca_state, ca_county) ORDER BY ca_country, ca_state, ca_county, i_item_id LIMIT 100 +SELECT i_brand_id AS brand_id, i_brand AS brand, i_manufact_id, i_manufact, sum(ss_ext_sales_price) AS ext_price FROM date_dim, store_sales, item, customer, customer_address, store WHERE (d_date_sk = ss_sold_date_sk) AND (ss_item_sk = i_item_sk) AND (i_manager_id = 8) AND (d_moy = 11) AND (d_year = 1998) AND (ss_customer_sk = c_customer_sk) AND (c_current_addr_sk = ca_address_sk) AND (substr(ca_zip, 1, 5) <> substr(s_zip, 1, 5)) AND (ss_store_sk = s_store_sk) GROUP BY i_brand, i_brand_id, i_manufact_id, i_manufact ORDER BY ext_price DESC, i_brand, i_brand_id, i_manufact_id, i_manufact LIMIT 100 +SELECT i_item_id, i_item_desc, i_category, i_class, i_current_price, sum(cs_ext_sales_price) AS itemrevenue, sum(cs_ext_sales_price) * 100 / sum(sum(cs_ext_sales_price)) OVER (PARTITION BY i_class) AS revenueratio FROM catalog_sales, item, date_dim WHERE (cs_item_sk = i_item_sk) AND (i_category IN ('Sports', 'Books', 'Home')) AND (cs_sold_date_sk = d_date_sk) AND (d_date BETWEEN CAST('1999-02-22' AS date) AND (CAST('1999-02-22' AS date) + INTERVAL 30 DAY)) GROUP BY i_item_id, i_item_desc, i_category, i_class, i_current_price ORDER BY i_category, i_class, i_item_id, i_item_desc, revenueratio LIMIT 100 +SELECT * FROM ( SELECT w_warehouse_name, i_item_id, sum(CASE WHEN (CAST(d_date AS date) < CAST('2000-03-11' AS date)) THEN inv_quantity_on_hand ELSE 0 END) AS inv_before, sum(CASE WHEN (CAST(d_date AS date) >= CAST('2000-03-11' AS date)) THEN inv_quantity_on_hand ELSE 0 END) AS inv_after FROM inventory, warehouse, item, date_dim WHERE (i_current_price BETWEEN 0.99 AND 1.49) AND (i_item_sk = inv_item_sk) AND (inv_warehouse_sk = w_warehouse_sk) AND (inv_date_sk = d_date_sk) AND (d_date BETWEEN (CAST('2000-03-11' AS date) - INTERVAL 30 DAY) AND (CAST('2000-03-11' AS date) + INTERVAL 30 DAY)) GROUP BY w_warehouse_name, i_item_id ) AS x WHERE (CASE WHEN inv_before > 0 THEN inv_after / inv_before ELSE NULL END) BETWEEN 2.0 / 3.0 AND 3.0 / 2.0 ORDER BY w_warehouse_name, i_item_id LIMIT 100 +SELECT i_product_name, i_brand, i_class, i_category, avg(inv_quantity_on_hand) AS qoh FROM inventory, date_dim, item WHERE (inv_date_sk = d_date_sk) AND (inv_item_sk = i_item_sk) AND (d_month_seq BETWEEN 1200 AND 1200 + 11) GROUP BY ROLLUP(i_product_name, i_brand, i_class, i_category) ORDER BY qoh, i_product_name, i_brand, i_class, i_category LIMIT 100 +WITH frequent_ss_items AS ( SELECT substr(i_item_desc, 1, 30) AS itemdesc, i_item_sk AS item_sk, d_date AS solddate, count(*) AS cnt FROM store_sales, date_dim, item WHERE (ss_sold_date_sk = d_date_sk) AND (ss_item_sk = i_item_sk) AND (d_year IN (2000, 2000 + 1, 2000 + 2, 2000 + 3)) GROUP BY substr(i_item_desc, 1, 30), i_item_sk, d_date HAVING count(*) > 4 ), max_store_sales AS ( SELECT max(csales) AS tpcds_cmax FROM ( SELECT c_customer_sk, sum(ss_quantity * ss_sales_price) AS csales FROM store_sales, customer, date_dim WHERE (ss_customer_sk = c_customer_sk) AND (ss_sold_date_sk = d_date_sk) AND (d_year IN (2000, 2000 + 1, 2000 + 2, 2000 + 3)) GROUP BY c_customer_sk ) ), best_ss_customer AS ( SELECT c_customer_sk, sum(ss_quantity * ss_sales_price) AS ssales FROM store_sales, customer WHERE (ss_customer_sk = c_customer_sk) GROUP BY c_customer_sk HAVING sum(ss_quantity * ss_sales_price) > (50 / 100.0) * ( SELECT * FROM max_store_sales ) ) SELECT sum(sales) FROM ( SELECT cs_quantity * cs_list_price AS sales FROM catalog_sales, date_dim WHERE (d_year = 2000) AND (d_moy = 2) AND (cs_sold_date_sk = d_date_sk) AND (cs_item_sk IN (SELECT item_sk FROM frequent_ss_items)) AND (cs_bill_customer_sk IN (SELECT c_customer_sk FROM best_ss_customer)) UNION ALL SELECT ws_quantity * ws_list_price AS sales FROM web_sales, date_dim WHERE (d_year = 2000) AND (d_moy = 2) AND (ws_sold_date_sk = d_date_sk) AND (ws_item_sk IN (SELECT item_sk FROM frequent_ss_items)) AND (ws_bill_customer_sk IN (SELECT c_customer_sk FROM best_ss_customer)) ) LIMIT 100 +WITH frequent_ss_items AS ( SELECT substr(i_item_desc, 1, 30) AS itemdesc, i_item_sk AS item_sk, d_date AS solddate, count(*) AS cnt FROM store_sales, date_dim, item WHERE (ss_sold_date_sk = d_date_sk) AND (ss_item_sk = i_item_sk) AND (d_year IN (2000, 2000 + 1, 2000 + 2, 2000 + 3)) GROUP BY substr(i_item_desc, 1, 30), i_item_sk, d_date HAVING count(*) > 4 ), max_store_sales AS ( SELECT max(csales) AS tpcds_cmax FROM ( SELECT c_customer_sk, sum(ss_quantity * ss_sales_price) AS csales FROM store_sales, customer, date_dim WHERE (ss_customer_sk = c_customer_sk) AND (ss_sold_date_sk = d_date_sk) AND (d_year IN (2000, 2000 + 1, 2000 + 2, 2000 + 3)) GROUP BY c_customer_sk ) ), best_ss_customer AS ( SELECT c_customer_sk, sum(ss_quantity * ss_sales_price) AS ssales FROM store_sales, customer WHERE (ss_customer_sk = c_customer_sk) GROUP BY c_customer_sk HAVING sum(ss_quantity * ss_sales_price) > (50 / 100.0) * ( SELECT * FROM max_store_sales ) ) SELECT c_last_name, c_first_name, sales FROM ( SELECT c_last_name, c_first_name, sum(cs_quantity * cs_list_price) AS sales FROM catalog_sales, customer, date_dim WHERE (d_year = 2000) AND (d_moy = 2) AND (cs_sold_date_sk = d_date_sk) AND (cs_item_sk IN (SELECT item_sk FROM frequent_ss_items)) AND (cs_bill_customer_sk IN (SELECT c_customer_sk FROM best_ss_customer)) AND (cs_bill_customer_sk = c_customer_sk) GROUP BY c_last_name, c_first_name UNION ALL SELECT c_last_name, c_first_name, sum(ws_quantity * ws_list_price) AS sales FROM web_sales, customer, date_dim WHERE (d_year = 2000) AND (d_moy = 2) AND (ws_sold_date_sk = d_date_sk) AND (ws_item_sk IN (SELECT item_sk FROM frequent_ss_items)) AND (ws_bill_customer_sk IN (SELECT c_customer_sk FROM best_ss_customer)) AND (ws_bill_customer_sk = c_customer_sk) GROUP BY c_last_name, c_first_name ) ORDER BY c_last_name, c_first_name, sales LIMIT 100 +WITH ssales AS ( SELECT c_last_name, c_first_name, s_store_name, ca_state, s_state, i_color, i_current_price, i_manager_id, i_units, i_size, sum(ss_net_paid) AS netpaid FROM store_sales, store_returns, store, item, customer, customer_address WHERE (ss_ticket_number = sr_ticket_number) AND (ss_item_sk = sr_item_sk) AND (ss_customer_sk = c_customer_sk) AND (ss_item_sk = i_item_sk) AND (ss_store_sk = s_store_sk) AND (c_current_addr_sk = ca_address_sk) AND (c_birth_country <> upper(ca_country)) AND (s_zip = ca_zip) AND (s_market_id = 8) GROUP BY c_last_name, c_first_name, s_store_name, ca_state, s_state, i_color, i_current_price, i_manager_id, i_units, i_size ) SELECT c_last_name, c_first_name, s_store_name, sum(netpaid) AS paid FROM ssales WHERE (i_color = 'peach') GROUP BY c_last_name, c_first_name, s_store_name HAVING sum(netpaid) > ( SELECT 0.05 * avg(netpaid) FROM ssales ) ORDER BY c_last_name, c_first_name, s_store_name +WITH ssales AS ( SELECT c_last_name, c_first_name, s_store_name, ca_state, s_state, i_color, i_current_price, i_manager_id, i_units, i_size, sum(ss_net_paid) AS netpaid FROM store_sales, store_returns, store, item, customer, customer_address WHERE (ss_ticket_number = sr_ticket_number) AND (ss_item_sk = sr_item_sk) AND (ss_customer_sk = c_customer_sk) AND (ss_item_sk = i_item_sk) AND (ss_store_sk = s_store_sk) AND (c_current_addr_sk = ca_address_sk) AND (c_birth_country <> upper(ca_country)) AND (s_zip = ca_zip) AND (s_market_id = 8) GROUP BY c_last_name, c_first_name, s_store_name, ca_state, s_state, i_color, i_current_price, i_manager_id, i_units, i_size ) SELECT c_last_name, c_first_name, s_store_name, sum(netpaid) AS paid FROM ssales WHERE (i_color = 'saddle') GROUP BY c_last_name, c_first_name, s_store_name HAVING sum(netpaid) > ( SELECT 0.05 * avg(netpaid) FROM ssales ) ORDER BY c_last_name, c_first_name, s_store_name +SELECT i_item_id, i_item_desc, s_store_id, s_store_name, sum(ss_net_profit) AS store_sales_profit, sum(sr_net_loss) AS store_returns_loss, sum(cs_net_profit) AS catalog_sales_profit FROM store_sales, store_returns, catalog_sales, date_dim AS d1, date_dim AS d2, date_dim AS d3, store, item WHERE (d1.d_moy = 4) AND (d1.d_year = 2001) AND (d1.d_date_sk = ss_sold_date_sk) AND (i_item_sk = ss_item_sk) AND (s_store_sk = ss_store_sk) AND (ss_customer_sk = sr_customer_sk) AND (ss_item_sk = sr_item_sk) AND (ss_ticket_number = sr_ticket_number) AND (sr_returned_date_sk = d2.d_date_sk) AND (d2.d_moy BETWEEN 4 AND 10) AND (d2.d_year = 2001) AND (sr_customer_sk = cs_bill_customer_sk) AND (sr_item_sk = cs_item_sk) AND (cs_sold_date_sk = d3.d_date_sk) AND (d3.d_moy BETWEEN 4 AND 10) AND (d3.d_year = 2001) GROUP BY i_item_id, i_item_desc, s_store_id, s_store_name ORDER BY i_item_id, i_item_desc, s_store_id, s_store_name LIMIT 100 +SELECT i_item_id, avg(cs_quantity) AS agg1, avg(cs_list_price) AS agg2, avg(cs_coupon_amt) AS agg3, avg(cs_sales_price) AS agg4 FROM catalog_sales, customer_demographics, date_dim, item, promotion WHERE (cs_sold_date_sk = d_date_sk) AND (cs_item_sk = i_item_sk) AND (cs_bill_cdemo_sk = cd_demo_sk) AND (cs_promo_sk = p_promo_sk) AND (cd_gender = 'M') AND (cd_marital_status = 'S') AND (cd_education_status = 'College') AND ((p_channel_email = 'N') OR (p_channel_event = 'N')) AND (d_year = 2000) GROUP BY i_item_id ORDER BY i_item_id LIMIT 100 +SELECT i_item_id, s_state, grouping(s_state) AS g_state, avg(ss_quantity) AS agg1, avg(ss_list_price) AS agg2, avg(ss_coupon_amt) AS agg3, avg(ss_sales_price) AS agg4 FROM store_sales, customer_demographics, date_dim, store, item WHERE (ss_sold_date_sk = d_date_sk) AND (ss_item_sk = i_item_sk) AND (ss_store_sk = s_store_sk) AND (ss_cdemo_sk = cd_demo_sk) AND (cd_gender = 'M') AND (cd_marital_status = 'S') AND (cd_education_status = 'College') AND (d_year = 2002) AND (s_state IN ('TN', 'TN', 'TN', 'TN', 'TN', 'TN')) GROUP BY ROLLUP(i_item_id, s_state) ORDER BY i_item_id, s_state LIMIT 100 +SELECT * FROM ( SELECT avg(ss_list_price) AS B1_LP, count(ss_list_price) AS B1_CNT, count(DISTINCT ss_list_price) AS B1_CNTD FROM store_sales WHERE (ss_quantity BETWEEN 0 AND 5) AND ((ss_list_price BETWEEN 8 AND 8 + 10) OR (ss_coupon_amt BETWEEN 459 AND 459 + 1000) OR (ss_wholesale_cost BETWEEN 57 AND 57 + 20)) ) AS B1, ( SELECT avg(ss_list_price) AS B2_LP, count(ss_list_price) AS B2_CNT, count(DISTINCT ss_list_price) AS B2_CNTD FROM store_sales WHERE (ss_quantity BETWEEN 6 AND 10) AND ((ss_list_price BETWEEN 90 AND 90 + 10) OR (ss_coupon_amt BETWEEN 2323 AND 2323 + 1000) OR (ss_wholesale_cost BETWEEN 31 AND 31 + 20)) ) AS B2, ( SELECT avg(ss_list_price) AS B3_LP, count(ss_list_price) AS B3_CNT, count(DISTINCT ss_list_price) AS B3_CNTD FROM store_sales WHERE (ss_quantity BETWEEN 11 AND 15) AND ((ss_list_price BETWEEN 142 AND 142 + 10) OR (ss_coupon_amt BETWEEN 12214 AND 12214 + 1000) OR (ss_wholesale_cost BETWEEN 79 AND 79 + 20)) ) AS B3, ( SELECT avg(ss_list_price) AS B4_LP, count(ss_list_price) AS B4_CNT, count(DISTINCT ss_list_price) AS B4_CNTD FROM store_sales WHERE (ss_quantity BETWEEN 16 AND 20) AND ((ss_list_price BETWEEN 135 AND 135 + 10) OR (ss_coupon_amt BETWEEN 6071 AND 6071 + 1000) OR (ss_wholesale_cost BETWEEN 38 AND 38 + 20)) ) AS B4, ( SELECT avg(ss_list_price) AS B5_LP, count(ss_list_price) AS B5_CNT, count(DISTINCT ss_list_price) AS B5_CNTD FROM store_sales WHERE (ss_quantity BETWEEN 21 AND 25) AND ((ss_list_price BETWEEN 122 AND 122 + 10) OR (ss_coupon_amt BETWEEN 836 AND 836 + 1000) OR (ss_wholesale_cost BETWEEN 17 AND 17 + 20)) ) AS B5, ( SELECT avg(ss_list_price) AS B6_LP, count(ss_list_price) AS B6_CNT, count(DISTINCT ss_list_price) AS B6_CNTD FROM store_sales WHERE (ss_quantity BETWEEN 26 AND 30) AND ((ss_list_price BETWEEN 154 AND 154 + 10) OR (ss_coupon_amt BETWEEN 7326 AND 7326 + 1000) OR (ss_wholesale_cost BETWEEN 7 AND 7 + 20)) ) AS B6 LIMIT 100 +SELECT i_item_id, i_item_desc, s_store_id, s_store_name, sum(ss_quantity) AS store_sales_quantity, sum(sr_return_quantity) AS store_returns_quantity, sum(cs_quantity) AS catalog_sales_quantity FROM store_sales, store_returns, catalog_sales, date_dim AS d1, date_dim AS d2, date_dim AS d3, store, item WHERE (d1.d_moy = 9) AND (d1.d_year = 1999) AND (d1.d_date_sk = ss_sold_date_sk) AND (i_item_sk = ss_item_sk) AND (s_store_sk = ss_store_sk) AND (ss_customer_sk = sr_customer_sk) AND (ss_item_sk = sr_item_sk) AND (ss_ticket_number = sr_ticket_number) AND (sr_returned_date_sk = d2.d_date_sk) AND (d2.d_moy BETWEEN 9 AND 9 + 3) AND (d2.d_year = 1999) AND (sr_customer_sk = cs_bill_customer_sk) AND (sr_item_sk = cs_item_sk) AND (cs_sold_date_sk = d3.d_date_sk) AND (d3.d_year IN (1999, 1999 + 1, 1999 + 2)) GROUP BY i_item_id, i_item_desc, s_store_id, s_store_name ORDER BY i_item_id, i_item_desc, s_store_id, s_store_name LIMIT 100 +WITH customer_total_return AS ( SELECT wr_returning_customer_sk AS ctr_customer_sk, ca_state AS ctr_state, sum(wr_return_amt) AS ctr_total_return FROM web_returns, date_dim, customer_address WHERE (wr_returned_date_sk = d_date_sk) AND (d_year = 2002) AND (wr_returning_addr_sk = ca_address_sk) GROUP BY wr_returning_customer_sk, ca_state ) SELECT c_customer_id, c_salutation, c_first_name, c_last_name, c_preferred_cust_flag, c_birth_day, c_birth_month, c_birth_year, c_birth_country, c_login, c_email_address, c_last_review_date_sk, ctr_total_return FROM customer_total_return AS ctr1, customer_address, customer WHERE (ctr1.ctr_total_return > ( SELECT avg(ctr_total_return) * 1.2 FROM customer_total_return AS ctr2 WHERE (ctr1.ctr_state = ctr2.ctr_state) )) AND (ca_address_sk = c_current_addr_sk) AND (ca_state = 'GA') AND (ctr1.ctr_customer_sk = c_customer_sk) ORDER BY c_customer_id, c_salutation, c_first_name, c_last_name, c_preferred_cust_flag, c_birth_day, c_birth_month, c_birth_year, c_birth_country, c_login, c_email_address, c_last_review_date_sk, ctr_total_return LIMIT 100 +WITH ss AS ( SELECT ca_county, d_qoy, d_year, sum(ss_ext_sales_price) AS store_sales FROM store_sales, date_dim, customer_address WHERE (ss_sold_date_sk = d_date_sk) AND (ss_addr_sk = ca_address_sk) GROUP BY ca_county, d_qoy, d_year ), ws AS ( SELECT ca_county, d_qoy, d_year, sum(ws_ext_sales_price) AS web_sales FROM web_sales, date_dim, customer_address WHERE (ws_sold_date_sk = d_date_sk) AND (ws_bill_addr_sk = ca_address_sk) GROUP BY ca_county, d_qoy, d_year ) SELECT ss1.ca_county, ss1.d_year, CAST(ws2.web_sales AS Float64) / ws1.web_sales AS web_q1_q2_increase, CAST(ss2.store_sales AS Float64) / ss1.store_sales AS store_q1_q2_increase, CAST(ws3.web_sales AS Float64) / ws2.web_sales AS web_q2_q3_increase, CAST(ss3.store_sales AS Float64) / ss2.store_sales AS store_q2_q3_increase FROM ss AS ss1, ss AS ss2, ss AS ss3, ws AS ws1, ws AS ws2, ws AS ws3 WHERE (ss1.d_qoy = 1) AND (ss1.d_year = 2000) AND (ss1.ca_county = ss2.ca_county) AND (ss2.d_qoy = 2) AND (ss2.d_year = 2000) AND (ss2.ca_county = ss3.ca_county) AND (ss3.d_qoy = 3) AND (ss3.d_year = 2000) AND (ss1.ca_county = ws1.ca_county) AND (ws1.d_qoy = 1) AND (ws1.d_year = 2000) AND (ws1.ca_county = ws2.ca_county) AND (ws2.d_qoy = 2) AND (ws2.d_year = 2000) AND (ws1.ca_county = ws3.ca_county) AND (ws3.d_qoy = 3) AND (ws3.d_year = 2000) AND (CASE WHEN ws1.web_sales > 0 THEN CAST(ws2.web_sales AS Float64) / ws1.web_sales ELSE NULL END > CASE WHEN ss1.store_sales > 0 THEN CAST(ss2.store_sales AS Float64) / ss1.store_sales ELSE NULL END) AND (CASE WHEN ws2.web_sales > 0 THEN CAST(ws3.web_sales AS Float64) / ws2.web_sales ELSE NULL END > CASE WHEN ss2.store_sales > 0 THEN CAST(ss3.store_sales AS Float64) / ss2.store_sales ELSE NULL END) ORDER BY ss1.ca_county +SELECT sum(cs_ext_discount_amt) AS "excess discount amount" FROM catalog_sales, item, date_dim WHERE (i_manufact_id = 977) AND (i_item_sk = cs_item_sk) AND (d_date BETWEEN '2000-01-27' AND (CAST('2000-01-27' AS date) + INTERVAL 90 DAY)) AND (d_date_sk = cs_sold_date_sk) AND (cs_ext_discount_amt > ( SELECT 1.3 * avg(cs_ext_discount_amt) FROM catalog_sales, date_dim WHERE (cs_item_sk = i_item_sk) AND (d_date BETWEEN '2000-01-27' AND (CAST('2000-01-27' AS date) + INTERVAL 90 DAY)) AND (d_date_sk = cs_sold_date_sk) )) LIMIT 100 +WITH ss AS ( SELECT i_manufact_id, sum(ss_ext_sales_price) AS total_sales FROM store_sales, date_dim, customer_address, item WHERE (i_manufact_id IN ( SELECT i_manufact_id FROM item WHERE (i_category IN ('Electronics')) )) AND (ss_item_sk = i_item_sk) AND (ss_sold_date_sk = d_date_sk) AND (d_year = 1998) AND (d_moy = 5) AND (ss_addr_sk = ca_address_sk) AND (ca_gmt_offset = -5) GROUP BY i_manufact_id ), cs AS ( SELECT i_manufact_id, sum(cs_ext_sales_price) AS total_sales FROM catalog_sales, date_dim, customer_address, item WHERE (i_manufact_id IN ( SELECT i_manufact_id FROM item WHERE (i_category IN ('Electronics')) )) AND (cs_item_sk = i_item_sk) AND (cs_sold_date_sk = d_date_sk) AND (d_year = 1998) AND (d_moy = 5) AND (cs_bill_addr_sk = ca_address_sk) AND (ca_gmt_offset = -5) GROUP BY i_manufact_id ), ws AS ( SELECT i_manufact_id, sum(ws_ext_sales_price) AS total_sales FROM web_sales, date_dim, customer_address, item WHERE (i_manufact_id IN ( SELECT i_manufact_id FROM item WHERE (i_category IN ('Electronics')) )) AND (ws_item_sk = i_item_sk) AND (ws_sold_date_sk = d_date_sk) AND (d_year = 1998) AND (d_moy = 5) AND (ws_bill_addr_sk = ca_address_sk) AND (ca_gmt_offset = -5) GROUP BY i_manufact_id ) SELECT i_manufact_id, sum(total_sales) AS total_sales FROM ( SELECT * FROM ss UNION ALL SELECT * FROM cs UNION ALL SELECT * FROM ws ) AS tmp1 GROUP BY i_manufact_id ORDER BY total_sales LIMIT 100 +SELECT c_last_name, c_first_name, c_salutation, c_preferred_cust_flag, ss_ticket_number, cnt FROM ( SELECT ss_ticket_number, ss_customer_sk, count(*) AS cnt FROM store_sales, date_dim, store, household_demographics WHERE (store_sales.ss_sold_date_sk = date_dim.d_date_sk) AND (store_sales.ss_store_sk = store.s_store_sk) AND (store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk) AND ((date_dim.d_dom BETWEEN 1 AND 3) OR (date_dim.d_dom BETWEEN 25 AND 28)) AND ((household_demographics.hd_buy_potential = '>10000') OR (household_demographics.hd_buy_potential = 'Unknown')) AND (household_demographics.hd_vehicle_count > 0) AND ((CASE WHEN household_demographics.hd_vehicle_count > 0 THEN (household_demographics.hd_dep_count) / household_demographics.hd_vehicle_count ELSE NULL END) > 1.2) AND (date_dim.d_year IN (1999, 1999 + 1, 1999 + 2)) AND (store.s_county IN ('Williamson County', 'Williamson County', 'Williamson County', 'Williamson County', 'Williamson County', 'Williamson County', 'Williamson County', 'Williamson County')) GROUP BY ss_ticket_number, ss_customer_sk ) AS dn, customer WHERE (ss_customer_sk = c_customer_sk) AND (cnt BETWEEN 15 AND 20) ORDER BY c_last_name, c_first_name, c_salutation, c_preferred_cust_flag DESC, ss_ticket_number +SELECT ca_state, cd_gender, cd_marital_status, cd_dep_count, count(*) AS cnt1, avg(cd_dep_count), min(cd_dep_count), min(cd_dep_count), cd_dep_employed_count, count(*) AS cnt2, avg(cd_dep_employed_count), min(cd_dep_employed_count), min(cd_dep_employed_count), cd_dep_college_count, count(*) AS cnt3, avg(cd_dep_college_count), min(cd_dep_college_count), min(cd_dep_college_count) FROM customer AS c, customer_address AS ca, customer_demographics WHERE (c.c_current_addr_sk = ca.ca_address_sk) AND (cd_demo_sk = c.c_current_cdemo_sk) AND EXISTS ( SELECT * FROM store_sales, date_dim WHERE (c.c_customer_sk = ss_customer_sk) AND (ss_sold_date_sk = d_date_sk) AND (d_year = 2002) AND (d_qoy < 4) ) AND ( EXISTS ( SELECT * FROM web_sales, date_dim WHERE (c.c_customer_sk = ws_bill_customer_sk) AND (ws_sold_date_sk = d_date_sk) AND (d_year = 2002) AND (d_qoy < 4) ) OR EXISTS ( SELECT * FROM catalog_sales, date_dim WHERE (c.c_customer_sk = cs_ship_customer_sk) AND (cs_sold_date_sk = d_date_sk) AND (d_year = 2002) AND (d_qoy < 4) ) ) GROUP BY ca_state, cd_gender, cd_marital_status, cd_dep_count, cd_dep_employed_count, cd_dep_college_count ORDER BY ca_state, cd_gender, cd_marital_status, cd_dep_count, cd_dep_employed_count, cd_dep_college_count LIMIT 100 +SELECT sum(ss_net_profit) / sum(ss_ext_sales_price) AS gross_margin, i_category, i_class, grouping(i_category) + grouping(i_class) AS lochierarchy, rank() OVER ( PARTITION BY grouping(i_category) + grouping(i_class), CASE WHEN grouping(i_class) = 0 THEN i_category END ORDER BY (sum(ss_net_profit) * 1.) / sum(ss_ext_sales_price) ASC ) AS rank_within_parent FROM store_sales, date_dim AS d1, item, store WHERE (d1.d_year = 2001) AND (d1.d_date_sk = ss_sold_date_sk) AND (i_item_sk = ss_item_sk) AND (s_store_sk = ss_store_sk) AND (s_state IN ('TN', 'TN', 'TN', 'TN', 'TN', 'TN', 'TN', 'TN')) GROUP BY ROLLUP(i_category, i_class) ORDER BY lochierarchy DESC, CASE WHEN lochierarchy = 0 THEN i_category END, rank_within_parent LIMIT 100 +SELECT i_item_id, i_item_desc, i_current_price FROM item, inventory, date_dim, catalog_sales WHERE (i_current_price BETWEEN 68 AND 68 + 30) AND (inv_item_sk = i_item_sk) AND (d_date_sk = inv_date_sk) AND (d_date BETWEEN CAST('2000-02-01' AS date) AND (CAST('2000-02-01' AS date) + INTERVAL 60 DAY)) AND (i_manufact_id IN (677, 940, 694, 808)) AND (inv_quantity_on_hand BETWEEN 100 AND 500) AND (cs_item_sk = i_item_sk) GROUP BY i_item_id, i_item_desc, i_current_price ORDER BY i_item_id LIMIT 100 +SELECT count(*) FROM ( SELECT DISTINCT c_last_name, c_first_name, d_date FROM store_sales, date_dim, customer WHERE (store_sales.ss_sold_date_sk = date_dim.d_date_sk) AND (store_sales.ss_customer_sk = customer.c_customer_sk) AND (d_month_seq BETWEEN 1200 AND 1200 + 11) INTERSECT SELECT DISTINCT c_last_name, c_first_name, d_date FROM catalog_sales, date_dim, customer WHERE (catalog_sales.cs_sold_date_sk = date_dim.d_date_sk) AND (catalog_sales.cs_bill_customer_sk = customer.c_customer_sk) AND (d_month_seq BETWEEN 1200 AND 1200 + 11) INTERSECT SELECT DISTINCT c_last_name, c_first_name, d_date FROM web_sales, date_dim, customer WHERE (web_sales.ws_sold_date_sk = date_dim.d_date_sk) AND (web_sales.ws_bill_customer_sk = customer.c_customer_sk) AND (d_month_seq BETWEEN 1200 AND 1200 + 11) ) AS hot_cust LIMIT 100 +WITH inv AS ( SELECT w_warehouse_name, w_warehouse_sk, i_item_sk, d_moy, stdev, mean, CASE mean WHEN 0 THEN NULL ELSE stdev / mean END AS cov FROM ( SELECT w_warehouse_name, w_warehouse_sk, i_item_sk, d_moy, stddev_samp(inv_quantity_on_hand) AS stdev, avg(inv_quantity_on_hand) AS mean FROM inventory, item, warehouse, date_dim WHERE (inv_item_sk = i_item_sk) AND (inv_warehouse_sk = w_warehouse_sk) AND (inv_date_sk = d_date_sk) AND (d_year = 2001) GROUP BY w_warehouse_name, w_warehouse_sk, i_item_sk, d_moy ) AS foo WHERE (CASE mean WHEN 0 THEN 0 ELSE stdev / mean END > 1) ) SELECT inv1.w_warehouse_sk, inv1.i_item_sk, inv1.d_moy, inv1.mean, inv1.cov, inv2.w_warehouse_sk, inv2.i_item_sk, inv2.d_moy, inv2.mean, inv2.cov FROM inv AS inv1, inv AS inv2 WHERE (inv1.i_item_sk = inv2.i_item_sk) AND (inv1.w_warehouse_sk = inv2.w_warehouse_sk) AND (inv1.d_moy = 1) AND (inv2.d_moy = 1 + 1) ORDER BY inv1.w_warehouse_sk, inv1.i_item_sk, inv1.d_moy, inv1.mean, inv1.cov, inv2.d_moy, inv2.mean, inv2.cov +WITH inv AS ( SELECT w_warehouse_name, w_warehouse_sk, i_item_sk, d_moy, stdev, mean, CASE mean WHEN 0 THEN NULL ELSE stdev / mean END AS cov FROM ( SELECT w_warehouse_name, w_warehouse_sk, i_item_sk, d_moy, stddev_samp(inv_quantity_on_hand) AS stdev, avg(inv_quantity_on_hand) AS mean FROM inventory, item, warehouse, date_dim WHERE (inv_item_sk = i_item_sk) AND (inv_warehouse_sk = w_warehouse_sk) AND (inv_date_sk = d_date_sk) AND (d_year = 2001) GROUP BY w_warehouse_name, w_warehouse_sk, i_item_sk, d_moy ) AS foo WHERE (CASE mean WHEN 0 THEN 0 ELSE stdev / mean END > 1) ) SELECT inv1.w_warehouse_sk, inv1.i_item_sk, inv1.d_moy, inv1.mean, inv1.cov, inv2.w_warehouse_sk, inv2.i_item_sk, inv2.d_moy, inv2.mean, inv2.cov FROM inv AS inv1, inv AS inv2 WHERE (inv1.i_item_sk = inv2.i_item_sk) AND (inv1.w_warehouse_sk = inv2.w_warehouse_sk) AND (inv1.d_moy = 1) AND (inv2.d_moy = 1 + 1) AND (inv1.cov > 1.5) ORDER BY inv1.w_warehouse_sk, inv1.i_item_sk, inv1.d_moy, inv1.mean, inv1.cov, inv2.d_moy, inv2.mean, inv2.cov +SELECT w_state, i_item_id, sum(CASE WHEN (CAST(d_date AS date) < CAST('2000-03-11' AS date)) THEN cs_sales_price - coalesce(cr_refunded_cash, 0) ELSE 0 END) AS sales_before, sum(CASE WHEN (CAST(d_date AS date) >= CAST('2000-03-11' AS date)) THEN cs_sales_price - coalesce(cr_refunded_cash, 0) ELSE 0 END) AS sales_after FROM catalog_sales LEFT OUTER JOIN catalog_returns ON (cs_order_number = cr_order_number) AND (cs_item_sk = cr_item_sk), warehouse, item, date_dim WHERE (i_current_price BETWEEN 0.99 AND 1.49) AND (i_item_sk = cs_item_sk) AND (cs_warehouse_sk = w_warehouse_sk) AND (cs_sold_date_sk = d_date_sk) AND (d_date BETWEEN (CAST('2000-03-11' AS date) - INTERVAL 30 DAY) AND (CAST('2000-03-11' AS date) + INTERVAL 30 DAY)) GROUP BY w_state, i_item_id ORDER BY w_state, i_item_id LIMIT 100 +SELECT DISTINCT(i_product_name) FROM item AS i1 WHERE (i_manufact_id BETWEEN 738 AND 738 + 40) AND ( SELECT count(*) AS item_cnt FROM item WHERE ( (i_manufact = i1.i_manufact) AND ( ( (i_category = 'Women') AND (i_color = 'powder' OR i_color = 'khaki') AND (i_units = 'Ounce' OR i_units = 'Oz') AND (i_size = 'medium' OR i_size = 'extra large') ) OR ( (i_category = 'Women') AND (i_color = 'brown' OR i_color = 'honeydew') AND (i_units = 'Bunch' OR i_units = 'Ton') AND (i_size = 'N/A' OR i_size = 'small') ) OR ( (i_category = 'Men') AND (i_color = 'floral' OR i_color = 'deep') AND (i_units = 'N/A' OR i_units = 'Dozen') AND (i_size = 'petite' OR i_size = 'large') ) OR ( (i_category = 'Men') AND (i_color = 'light' OR i_color = 'cornflower') AND (i_units = 'Box' OR i_units = 'Pound') AND (i_size = 'medium' OR i_size = 'extra large') ) ) ) OR ( (i_manufact = i1.i_manufact) AND ( ( (i_category = 'Women') AND (i_color = 'midnight' OR i_color = 'snow') AND (i_units = 'Pallet' OR i_units = 'Gross') AND (i_size = 'medium' OR i_size = 'extra large') ) OR ( (i_category = 'Women') AND (i_color = 'cyan' OR i_color = 'papaya') AND (i_units = 'Cup' OR i_units = 'Dram') AND (i_size = 'N/A' OR i_size = 'small') ) OR ( (i_category = 'Men') AND (i_color = 'orange' OR i_color = 'frosted') AND (i_units = 'Each' OR i_units = 'Tbl') AND (i_size = 'petite' OR i_size = 'large') ) OR ( (i_category = 'Men') AND (i_color = 'forest' OR i_color = 'ghost') AND (i_units = 'Lb' OR i_units = 'Bundle') AND (i_size = 'medium' OR i_size = 'extra large') ) ) ) ) > 0 ORDER BY i_product_name LIMIT 100 +SELECT dt.d_year, item.i_category_id, item.i_category, sum(ss_ext_sales_price) FROM date_dim AS dt, store_sales, item WHERE (dt.d_date_sk = store_sales.ss_sold_date_sk) AND (store_sales.ss_item_sk = item.i_item_sk) AND (item.i_manager_id = 1) AND (dt.d_moy = 11) AND (dt.d_year = 2000) GROUP BY dt.d_year, item.i_category_id, item.i_category ORDER BY sum(ss_ext_sales_price) DESC, dt.d_year, item.i_category_id, item.i_category LIMIT 100 +SELECT s_store_name, s_store_id, sum(CASE WHEN (d_day_name = 'Sunday') THEN ss_sales_price ELSE NULL END) AS sun_sales, sum(CASE WHEN (d_day_name = 'Monday') THEN ss_sales_price ELSE NULL END) AS mon_sales, sum(CASE WHEN (d_day_name = 'Tuesday') THEN ss_sales_price ELSE NULL END) AS tue_sales, sum(CASE WHEN (d_day_name = 'Wednesday') THEN ss_sales_price ELSE NULL END) AS wed_sales, sum(CASE WHEN (d_day_name = 'Thursday') THEN ss_sales_price ELSE NULL END) AS thu_sales, sum(CASE WHEN (d_day_name = 'Friday') THEN ss_sales_price ELSE NULL END) AS fri_sales, sum(CASE WHEN (d_day_name = 'Saturday') THEN ss_sales_price ELSE NULL END) AS sat_sales FROM date_dim, store_sales, store WHERE (d_date_sk = ss_sold_date_sk) AND (s_store_sk = ss_store_sk) AND (s_gmt_offset = -5) AND (d_year = 2000) GROUP BY s_store_name, s_store_id ORDER BY s_store_name, s_store_id, sun_sales, mon_sales, tue_sales, wed_sales, thu_sales, fri_sales, sat_sales LIMIT 100 +SELECT asceding.rnk, i1.i_product_name AS best_performing, i2.i_product_name AS worst_performing FROM ( SELECT * FROM ( SELECT item_sk, rank() OVER (ORDER BY rank_col ASC) AS rnk FROM ( SELECT ss_item_sk AS item_sk, avg(ss_net_profit) AS rank_col FROM store_sales AS ss1 WHERE (ss_store_sk = 4) GROUP BY ss_item_sk HAVING avg(ss_net_profit) > 0.9 * ( SELECT avg(ss_net_profit) AS rank_col FROM store_sales WHERE (ss_store_sk = 4) AND (ss_addr_sk IS NULL) GROUP BY ss_store_sk ) ) AS V1 ) AS V11 WHERE (rnk < 11) ) AS asceding, ( SELECT * FROM ( SELECT item_sk, rank() OVER (ORDER BY rank_col DESC) AS rnk FROM ( SELECT ss_item_sk AS item_sk, avg(ss_net_profit) AS rank_col FROM store_sales AS ss1 WHERE (ss_store_sk = 4) GROUP BY ss_item_sk HAVING avg(ss_net_profit) > 0.9 * ( SELECT avg(ss_net_profit) AS rank_col FROM store_sales WHERE (ss_store_sk = 4) AND (ss_addr_sk IS NULL) GROUP BY ss_store_sk ) ) AS V2 ) AS V21 WHERE (rnk < 11) ) AS descending, item AS i1, item AS i2 WHERE (asceding.rnk = descending.rnk) AND (i1.i_item_sk = asceding.item_sk) AND (i2.i_item_sk = descending.item_sk) ORDER BY asceding.rnk LIMIT 100 +SELECT ca_zip, ca_city, sum(ws_sales_price) FROM web_sales, customer, customer_address, date_dim, item WHERE (ws_bill_customer_sk = c_customer_sk) AND (c_current_addr_sk = ca_address_sk) AND (ws_item_sk = i_item_sk) AND ( (substr(ca_zip, 1, 5) IN ('85669', '86197', '88274', '83405', '86475', '85392', '85460', '80348', '81792')) OR (i_item_id IN ( SELECT i_item_id FROM item WHERE (i_item_sk IN (2, 3, 5, 7, 11, 13, 17, 19, 23, 29)) )) ) AND (ws_sold_date_sk = d_date_sk) AND (d_qoy = 2) AND (d_year = 2001) GROUP BY ca_zip, ca_city ORDER BY ca_zip, ca_city LIMIT 100 +SELECT c_last_name, c_first_name, ca_city, bought_city, ss_ticket_number, amt, profit FROM ( SELECT ss_ticket_number, ss_customer_sk, ca_city AS bought_city, sum(ss_coupon_amt) AS amt, sum(ss_net_profit) AS profit FROM store_sales, date_dim, store, household_demographics, customer_address WHERE (store_sales.ss_sold_date_sk = date_dim.d_date_sk) AND (store_sales.ss_store_sk = store.s_store_sk) AND (store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk) AND (store_sales.ss_addr_sk = customer_address.ca_address_sk) AND ((household_demographics.hd_dep_count = 4) OR (household_demographics.hd_vehicle_count = 3)) AND (date_dim.d_dow IN (6, 0)) AND (date_dim.d_year IN (1999, 1999 + 1, 1999 + 2)) AND (store.s_city IN ('Fairview', 'Midway', 'Fairview', 'Fairview', 'Fairview')) GROUP BY ss_ticket_number, ss_customer_sk, ss_addr_sk, ca_city ) AS dn, customer, customer_address AS current_addr WHERE (ss_customer_sk = c_customer_sk) AND (customer.c_current_addr_sk = current_addr.ca_address_sk) AND (current_addr.ca_city <> bought_city) ORDER BY c_last_name, c_first_name, ca_city, bought_city, ss_ticket_number LIMIT 100 +WITH v1 AS ( SELECT i_category, i_brand, s_store_name, s_company_name, d_year, d_moy, sum(ss_sales_price) AS sum_sales, avg(sum(ss_sales_price)) OVER (PARTITION BY i_category, i_brand, s_store_name, s_company_name, d_year) AS avg_monthly_sales, rank() OVER (PARTITION BY i_category, i_brand, s_store_name, s_company_name ORDER BY d_year, d_moy) AS rn FROM item, store_sales, date_dim, store WHERE (ss_item_sk = i_item_sk) AND (ss_sold_date_sk = d_date_sk) AND (ss_store_sk = s_store_sk) AND ( (d_year = 1999) OR ((d_year = 1999 - 1) AND (d_moy = 12)) OR ((d_year = 1999 + 1) AND (d_moy = 1)) ) GROUP BY i_category, i_brand, s_store_name, s_company_name, d_year, d_moy ), v2 AS ( SELECT v1.i_category, v1.i_brand, v1.s_store_name, v1.s_company_name, v1.d_year, v1.d_moy, v1.avg_monthly_sales, v1.sum_sales, v1_lag.sum_sales AS psum, v1_lead.sum_sales AS nsum FROM v1, v1 AS v1_lag, v1 AS v1_lead WHERE (v1.i_category = v1_lag.i_category) AND (v1.i_category = v1_lead.i_category) AND (v1.i_brand = v1_lag.i_brand) AND (v1.i_brand = v1_lead.i_brand) AND (v1.s_store_name = v1_lag.s_store_name) AND (v1.s_store_name = v1_lead.s_store_name) AND (v1.s_company_name = v1_lag.s_company_name) AND (v1.s_company_name = v1_lead.s_company_name) AND (v1.rn = v1_lag.rn + 1) AND (v1.rn = v1_lead.rn - 1) ) SELECT * FROM v2 WHERE (v1.d_year = 1999) AND (v1.avg_monthly_sales > 0) AND (CASE WHEN v1.avg_monthly_sales > 0 THEN abs(v1.sum_sales - v1.avg_monthly_sales) / v1.avg_monthly_sales ELSE NULL END > 0.1) ORDER BY v1.sum_sales - v1.avg_monthly_sales, v1.s_store_name LIMIT 100 +SELECT sum(ss_quantity) FROM store_sales, store, customer_demographics, customer_address, date_dim WHERE (s_store_sk = ss_store_sk) AND (ss_sold_date_sk = d_date_sk) AND (d_year = 2000) AND ( ( (cd_demo_sk = ss_cdemo_sk) AND (cd_marital_status = 'M') AND (cd_education_status = '4 yr Degree') AND (ss_sales_price BETWEEN 100.00 AND 150.00) ) OR ( (cd_demo_sk = ss_cdemo_sk) AND (cd_marital_status = 'D') AND (cd_education_status = '2 yr Degree') AND (ss_sales_price BETWEEN 50.00 AND 100.00) ) OR ( (cd_demo_sk = ss_cdemo_sk) AND (cd_marital_status = 'S') AND (cd_education_status = 'College') AND (ss_sales_price BETWEEN 150.00 AND 200.00) ) ) AND ( ( (ss_addr_sk = ca_address_sk) AND (ca_country = 'United States') AND (ca_state IN ('CO', 'OH', 'TX')) AND (ss_net_profit BETWEEN 0 AND 2000) ) OR ( (ss_addr_sk = ca_address_sk) AND (ca_country = 'United States') AND (ca_state IN ('OR', 'MN', 'KY')) AND (ss_net_profit BETWEEN 150 AND 3000) ) OR ( (ss_addr_sk = ca_address_sk) AND (ca_country = 'United States') AND (ca_state IN ('VA', 'CA', 'MS')) AND (ss_net_profit BETWEEN 50 AND 25000) ) ) +SELECT channel, item, return_ratio, return_rank, currency_rank FROM ( SELECT 'web' AS channel, web.item, web.return_ratio, web.return_rank, web.currency_rank FROM ( SELECT item, return_ratio, currency_ratio, rank() OVER (ORDER BY return_ratio) AS return_rank, rank() OVER (ORDER BY currency_ratio) AS currency_rank FROM ( SELECT ws.ws_item_sk AS item, (CAST(sum(coalesce(wr.wr_return_quantity, 0)) AS decimal(15, 4)) / CAST(sum(coalesce(ws.ws_quantity, 0)) AS decimal(15, 4))) AS return_ratio, (CAST(sum(coalesce(wr.wr_return_amt, 0)) AS decimal(15, 4)) / CAST(sum(coalesce(ws.ws_net_paid, 0)) AS decimal(15, 4))) AS currency_ratio FROM web_sales AS ws LEFT OUTER JOIN web_returns AS wr ON (ws.ws_order_number = wr.wr_order_number) AND (ws.ws_item_sk = wr.wr_item_sk), date_dim WHERE (wr.wr_return_amt > 10000) AND (ws.ws_net_profit > 1) AND (ws.ws_net_paid > 0) AND (ws.ws_quantity > 0) AND (ws_sold_date_sk = d_date_sk) AND (d_year = 2001) AND (d_moy = 12) GROUP BY ws.ws_item_sk ) AS in_web ) AS web WHERE (web.return_rank <= 10) OR (web.currency_rank <= 10) UNION SELECT 'catalog' AS channel, catalog.item, catalog.return_ratio, catalog.return_rank, catalog.currency_rank FROM ( SELECT item, return_ratio, currency_ratio, rank() OVER (ORDER BY return_ratio) AS return_rank, rank() OVER (ORDER BY currency_ratio) AS currency_rank FROM ( SELECT cs.cs_item_sk AS item, (CAST(sum(coalesce(cr.cr_return_quantity, 0)) AS decimal(15, 4)) / CAST(sum(coalesce(cs.cs_quantity, 0)) AS decimal(15, 4))) AS return_ratio, (CAST(sum(coalesce(cr.cr_return_amount, 0)) AS decimal(15, 4)) / CAST(sum(coalesce(cs.cs_net_paid, 0)) AS decimal(15, 4))) AS currency_ratio FROM catalog_sales AS cs LEFT OUTER JOIN catalog_returns AS cr ON (cs.cs_order_number = cr.cr_order_number) AND (cs.cs_item_sk = cr.cr_item_sk), date_dim WHERE (cr.cr_return_amount > 10000) AND (cs.cs_net_profit > 1) AND (cs.cs_net_paid > 0) AND (cs.cs_quantity > 0) AND (cs_sold_date_sk = d_date_sk) AND (d_year = 2001) AND (d_moy = 12) GROUP BY cs.cs_item_sk ) AS in_cat ) AS catalog WHERE (catalog.return_rank <= 10) OR (catalog.currency_rank <= 10) UNION SELECT 'store' AS channel, store.item, store.return_ratio, store.return_rank, store.currency_rank FROM ( SELECT item, return_ratio, currency_ratio, rank() OVER (ORDER BY return_ratio) AS return_rank, rank() OVER (ORDER BY currency_ratio) AS currency_rank FROM ( SELECT sts.ss_item_sk AS item, (CAST(sum(coalesce(sr.sr_return_quantity, 0)) AS decimal(15, 4)) / CAST(sum(coalesce(sts.ss_quantity, 0)) AS decimal(15, 4))) AS return_ratio, (CAST(sum(coalesce(sr.sr_return_amt, 0)) AS decimal(15, 4)) / CAST(sum(coalesce(sts.ss_net_paid, 0)) AS decimal(15, 4))) AS currency_ratio FROM store_sales AS sts LEFT OUTER JOIN store_returns AS sr ON (sts.ss_ticket_number = sr.sr_ticket_number) AND (sts.ss_item_sk = sr.sr_item_sk), date_dim WHERE (sr.sr_return_amt > 10000) AND (sts.ss_net_profit > 1) AND (sts.ss_net_paid > 0) AND (sts.ss_quantity > 0) AND (ss_sold_date_sk = d_date_sk) AND (d_year = 2001) AND (d_moy = 12) GROUP BY sts.ss_item_sk ) AS in_store ) AS store WHERE (store.return_rank <= 10) OR (store.currency_rank <= 10) ) ORDER BY 1, 4, 5, 2 LIMIT 100 +SELECT s_store_name, s_company_id, s_street_number, s_street_name, s_street_type, s_suite_number, s_city, s_county, s_state, s_zip, sum(CASE WHEN (sr_returned_date_sk - ss_sold_date_sk <= 30) THEN 1 ELSE 0 END) AS "30 days", sum(CASE WHEN (sr_returned_date_sk - ss_sold_date_sk > 30) AND (sr_returned_date_sk - ss_sold_date_sk <= 60) THEN 1 ELSE 0 END) AS "31-60 days", sum(CASE WHEN (sr_returned_date_sk - ss_sold_date_sk > 60) AND (sr_returned_date_sk - ss_sold_date_sk <= 90) THEN 1 ELSE 0 END) AS "61-90 days", sum(CASE WHEN (sr_returned_date_sk - ss_sold_date_sk > 90) AND (sr_returned_date_sk - ss_sold_date_sk <= 120) THEN 1 ELSE 0 END) AS "91-120 days", sum(CASE WHEN (sr_returned_date_sk - ss_sold_date_sk > 120) THEN 1 ELSE 0 END) AS ">120 days" FROM store_sales, store_returns, store, date_dim AS d1, date_dim AS d2 WHERE (d2.d_year = 2001) AND (d2.d_moy = 8) AND (ss_ticket_number = sr_ticket_number) AND (ss_item_sk = sr_item_sk) AND (ss_sold_date_sk = d1.d_date_sk) AND (sr_returned_date_sk = d2.d_date_sk) AND (ss_customer_sk = sr_customer_sk) AND (ss_store_sk = s_store_sk) GROUP BY s_store_name, s_company_id, s_street_number, s_street_name, s_street_type, s_suite_number, s_city, s_county, s_state, s_zip ORDER BY s_store_name, s_company_id, s_street_number, s_street_name, s_street_type, s_suite_number, s_city, s_county, s_state, s_zip LIMIT 100 +WITH web_v1 AS ( SELECT ws_item_sk AS item_sk, d_date, sum(sum(ws_sales_price)) OVER (PARTITION BY ws_item_sk ORDER BY d_date ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) AS cume_sales FROM web_sales, date_dim WHERE (ws_sold_date_sk = d_date_sk) AND (d_month_seq BETWEEN 1200 AND 1200 + 11) AND (ws_item_sk IS NOT NULL) GROUP BY ws_item_sk, d_date ), store_v1 AS ( SELECT ss_item_sk AS item_sk, d_date, sum(sum(ss_sales_price)) OVER (PARTITION BY ss_item_sk ORDER BY d_date ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) AS cume_sales FROM store_sales, date_dim WHERE (ss_sold_date_sk = d_date_sk) AND (d_month_seq BETWEEN 1200 AND 1200 + 11) AND (ss_item_sk IS NOT NULL) GROUP BY ss_item_sk, d_date ) SELECT * FROM ( SELECT item_sk, d_date, web_sales, store_sales, max(web_sales) OVER (PARTITION BY item_sk ORDER BY d_date ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) AS web_cumulative, max(store_sales) OVER (PARTITION BY item_sk ORDER BY d_date ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) AS store_cumulative FROM ( SELECT CASE WHEN web.item_sk IS NOT NULL THEN web.item_sk ELSE store.item_sk END AS item_sk, CASE WHEN web.d_date IS NOT NULL THEN web.d_date ELSE store.d_date END AS d_date, web.cume_sales AS web_sales, store.cume_sales AS store_sales FROM web_v1 AS web FULL OUTER JOIN store_v1 AS store ON (web.item_sk = store.item_sk) AND (web.d_date = store.d_date) ) AS x ) AS y WHERE (web_cumulative > store_cumulative) ORDER BY item_sk, d_date LIMIT 100 +SELECT dt.d_year, item.i_brand_id AS brand_id, item.i_brand AS brand, sum(ss_ext_sales_price) AS ext_price FROM date_dim AS dt, store_sales, item WHERE (dt.d_date_sk = store_sales.ss_sold_date_sk) AND (store_sales.ss_item_sk = item.i_item_sk) AND (item.i_manager_id = 1) AND (dt.d_moy = 11) AND (dt.d_year = 2000) GROUP BY dt.d_year, item.i_brand, item.i_brand_id ORDER BY dt.d_year, ext_price DESC, brand_id LIMIT 100 +SELECT * FROM ( SELECT i_manufact_id, sum(ss_sales_price) AS sum_sales, avg(sum(ss_sales_price)) OVER (PARTITION BY i_manufact_id) AS avg_quarterly_sales FROM item, store_sales, date_dim, store WHERE (ss_item_sk = i_item_sk) AND (ss_sold_date_sk = d_date_sk) AND (ss_store_sk = s_store_sk) AND (d_month_seq IN (1200, 1200 + 1, 1200 + 2, 1200 + 3, 1200 + 4, 1200 + 5, 1200 + 6, 1200 + 7, 1200 + 8, 1200 + 9, 1200 + 10, 1200 + 11)) AND ( ( (i_category IN ('Books', 'Children', 'Electronics')) AND (i_class IN ('personal', 'portable', 'reference', 'self-help')) AND (i_brand IN ('scholaramalgamalg #14', 'scholaramalgamalg #7', 'exportiunivamalg #9', 'scholaramalgamalg #9')) ) OR ( (i_category IN ('Women', 'Music', 'Men')) AND (i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND (i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1')) ) ) GROUP BY i_manufact_id, d_qoy ) AS tmp1 WHERE (CASE WHEN avg_quarterly_sales > 0 THEN abs(sum_sales - avg_quarterly_sales) / avg_quarterly_sales ELSE NULL END > 0.1) ORDER BY avg_quarterly_sales, sum_sales, i_manufact_id LIMIT 100 +WITH my_customers AS ( SELECT DISTINCT c_customer_sk, c_current_addr_sk FROM ( SELECT cs_sold_date_sk AS sold_date_sk, cs_bill_customer_sk AS customer_sk, cs_item_sk AS item_sk FROM catalog_sales UNION ALL SELECT ws_sold_date_sk AS sold_date_sk, ws_bill_customer_sk AS customer_sk, ws_item_sk AS item_sk FROM web_sales ) AS cs_or_ws_sales, item, date_dim, customer WHERE (sold_date_sk = d_date_sk) AND (item_sk = i_item_sk) AND (i_category = 'Women') AND (i_class = 'maternity') AND (c_customer_sk = cs_or_ws_sales.customer_sk) AND (d_moy = 12) AND (d_year = 1998) ), my_revenue AS ( SELECT c_customer_sk, sum(ss_ext_sales_price) AS revenue FROM my_customers, store_sales, customer_address, store, date_dim WHERE (c_current_addr_sk = ca_address_sk) AND (ca_county = s_county) AND (ca_state = s_state) AND (ss_sold_date_sk = d_date_sk) AND (c_customer_sk = ss_customer_sk) AND (d_month_seq BETWEEN ( SELECT DISTINCT d_month_seq + 1 FROM date_dim WHERE (d_year = 1998) AND (d_moy = 12) ) AND ( SELECT DISTINCT d_month_seq + 3 FROM date_dim WHERE (d_year = 1998) AND (d_moy = 12) )) GROUP BY c_customer_sk ), segments AS ( SELECT CAST((revenue / 50) AS int) AS segment FROM my_revenue ) SELECT segment, count(*) AS num_customers, segment * 50 AS segment_base FROM segments GROUP BY segment ORDER BY segment, num_customers LIMIT 100 +SELECT i_brand_id AS brand_id, i_brand AS brand, sum(ss_ext_sales_price) AS ext_price FROM date_dim, store_sales, item WHERE (d_date_sk = ss_sold_date_sk) AND (ss_item_sk = i_item_sk) AND (i_manager_id = 28) AND (d_moy = 11) AND (d_year = 1999) GROUP BY i_brand, i_brand_id ORDER BY ext_price DESC, i_brand_id LIMIT 100 +WITH ss AS ( SELECT i_item_id, sum(ss_ext_sales_price) AS total_sales FROM store_sales, date_dim, customer_address, item WHERE (i_item_id IN ( SELECT i_item_id FROM item WHERE (i_color IN ('slate', 'blanched', 'burnished')) )) AND (ss_item_sk = i_item_sk) AND (ss_sold_date_sk = d_date_sk) AND (d_year = 2001) AND (d_moy = 2) AND (ss_addr_sk = ca_address_sk) AND (ca_gmt_offset = -5) GROUP BY i_item_id ), cs AS ( SELECT i_item_id, sum(cs_ext_sales_price) AS total_sales FROM catalog_sales, date_dim, customer_address, item WHERE (i_item_id IN ( SELECT i_item_id FROM item WHERE (i_color IN ('slate', 'blanched', 'burnished')) )) AND (cs_item_sk = i_item_sk) AND (cs_sold_date_sk = d_date_sk) AND (d_year = 2001) AND (d_moy = 2) AND (cs_bill_addr_sk = ca_address_sk) AND (ca_gmt_offset = -5) GROUP BY i_item_id ), ws AS ( SELECT i_item_id, sum(ws_ext_sales_price) AS total_sales FROM web_sales, date_dim, customer_address, item WHERE (i_item_id IN ( SELECT i_item_id FROM item WHERE (i_color IN ('slate', 'blanched', 'burnished')) )) AND (ws_item_sk = i_item_sk) AND (ws_sold_date_sk = d_date_sk) AND (d_year = 2001) AND (d_moy = 2) AND (ws_bill_addr_sk = ca_address_sk) AND (ca_gmt_offset = -5) GROUP BY i_item_id ) SELECT i_item_id, sum(total_sales) AS total_sales FROM ( SELECT * FROM ss UNION ALL SELECT * FROM cs UNION ALL SELECT * FROM ws ) AS tmp1 GROUP BY i_item_id ORDER BY total_sales, i_item_id LIMIT 100 +WITH v1 AS ( SELECT i_category, i_brand, cc_name, d_year, d_moy, sum(cs_sales_price) AS sum_sales, avg(sum(cs_sales_price)) OVER (PARTITION BY i_category, i_brand, cc_name, d_year) AS avg_monthly_sales, rank() OVER (PARTITION BY i_category, i_brand, cc_name ORDER BY d_year, d_moy) AS rn FROM item, catalog_sales, date_dim, call_center WHERE (cs_item_sk = i_item_sk) AND (cs_sold_date_sk = d_date_sk) AND (cc_call_center_sk = cs_call_center_sk) AND ( (d_year = 1999) OR ((d_year = 1999 - 1) AND (d_moy = 12)) OR ((d_year = 1999 + 1) AND (d_moy = 1)) ) GROUP BY i_category, i_brand, cc_name, d_year, d_moy ), v2 AS ( SELECT v1.i_category, v1.i_brand, v1.cc_name, v1.d_year, v1.d_moy, v1.avg_monthly_sales, v1.sum_sales, v1_lag.sum_sales AS psum, v1_lead.sum_sales AS nsum FROM v1, v1 AS v1_lag, v1 AS v1_lead WHERE (v1.i_category = v1_lag.i_category) AND (v1.i_category = v1_lead.i_category) AND (v1.i_brand = v1_lag.i_brand) AND (v1.i_brand = v1_lead.i_brand) AND (v1.cc_name = v1_lag.cc_name) AND (v1.cc_name = v1_lead.cc_name) AND (v1.rn = v1_lag.rn + 1) AND (v1.rn = v1_lead.rn - 1) ) SELECT * FROM v2 WHERE (v1.d_year = 1999) AND (v1.avg_monthly_sales > 0) AND (CASE WHEN v1.avg_monthly_sales > 0 THEN abs(v1.sum_sales - v1.avg_monthly_sales) / v1.avg_monthly_sales ELSE NULL END > 0.1) ORDER BY v1.sum_sales - v1.avg_monthly_sales, v1.cc_name LIMIT 100 +WITH ss_items AS ( SELECT i_item_id AS item_id, sum(ss_ext_sales_price) AS ss_item_rev FROM store_sales, item, date_dim WHERE (ss_item_sk = i_item_sk) AND (d_date IN ( SELECT d_date FROM date_dim WHERE (d_week_seq = ( SELECT d_week_seq FROM date_dim WHERE (d_date = '2000-01-03') )) )) AND (ss_sold_date_sk = d_date_sk) GROUP BY i_item_id ), cs_items AS ( SELECT i_item_id AS item_id, sum(cs_ext_sales_price) AS cs_item_rev FROM catalog_sales, item, date_dim WHERE (cs_item_sk = i_item_sk) AND (d_date IN ( SELECT d_date FROM date_dim WHERE (d_week_seq = ( SELECT d_week_seq FROM date_dim WHERE (d_date = '2000-01-03') )) )) AND (cs_sold_date_sk = d_date_sk) GROUP BY i_item_id ), ws_items AS ( SELECT i_item_id AS item_id, sum(ws_ext_sales_price) AS ws_item_rev FROM web_sales, item, date_dim WHERE (ws_item_sk = i_item_sk) AND (d_date IN ( SELECT d_date FROM date_dim WHERE (d_week_seq = ( SELECT d_week_seq FROM date_dim WHERE (d_date = '2000-01-03') )) )) AND (ws_sold_date_sk = d_date_sk) GROUP BY i_item_id ) SELECT ss_items.item_id, ss_item_rev, ss_item_rev / ((CAST(ss_item_rev AS Float64) + cs_item_rev + ws_item_rev) / 3) * 100 AS ss_dev, cs_item_rev, cs_item_rev / ((CAST(ss_item_rev AS Float64) + cs_item_rev + ws_item_rev) / 3) * 100 AS cs_dev, ws_item_rev, ws_item_rev / ((CAST(ss_item_rev AS Float64) + cs_item_rev + ws_item_rev) / 3) * 100 AS ws_dev, (ss_item_rev + cs_item_rev + ws_item_rev) / 3 AS average FROM ss_items, cs_items, ws_items WHERE (ss_items.item_id = cs_items.item_id) AND (ss_items.item_id = ws_items.item_id) AND (ss_item_rev BETWEEN 0.9 * cs_item_rev AND 1.1 * cs_item_rev) AND (ss_item_rev BETWEEN 0.9 * ws_item_rev AND 1.1 * ws_item_rev) AND (cs_item_rev BETWEEN 0.9 * ss_item_rev AND 1.1 * ss_item_rev) AND (cs_item_rev BETWEEN 0.9 * ws_item_rev AND 1.1 * ws_item_rev) AND (ws_item_rev BETWEEN 0.9 * ss_item_rev AND 1.1 * ss_item_rev) AND (ws_item_rev BETWEEN 0.9 * cs_item_rev AND 1.1 * cs_item_rev) ORDER BY ss_items.item_id, ss_item_rev LIMIT 100 +WITH wss AS ( SELECT d_week_seq, ss_store_sk, sum(CASE WHEN (d_day_name = 'Sunday') THEN ss_sales_price ELSE NULL END) AS sun_sales, sum(CASE WHEN (d_day_name = 'Monday') THEN ss_sales_price ELSE NULL END) AS mon_sales, sum(CASE WHEN (d_day_name = 'Tuesday') THEN ss_sales_price ELSE NULL END) AS tue_sales, sum(CASE WHEN (d_day_name = 'Wednesday') THEN ss_sales_price ELSE NULL END) AS wed_sales, sum(CASE WHEN (d_day_name = 'Thursday') THEN ss_sales_price ELSE NULL END) AS thu_sales, sum(CASE WHEN (d_day_name = 'Friday') THEN ss_sales_price ELSE NULL END) AS fri_sales, sum(CASE WHEN (d_day_name = 'Saturday') THEN ss_sales_price ELSE NULL END) AS sat_sales FROM store_sales, date_dim WHERE (d_date_sk = ss_sold_date_sk) GROUP BY d_week_seq, ss_store_sk ) SELECT s_store_name1, s_store_id1, d_week_seq1, sun_sales1 / sun_sales2, mon_sales1 / mon_sales2, tue_sales1 / tue_sales2, wed_sales1 / wed_sales2, thu_sales1 / thu_sales2, fri_sales1 / fri_sales2, sat_sales1 / sat_sales2 FROM ( SELECT s_store_name AS s_store_name1, wss.d_week_seq AS d_week_seq1, s_store_id AS s_store_id1, sun_sales AS sun_sales1, mon_sales AS mon_sales1, tue_sales AS tue_sales1, wed_sales AS wed_sales1, thu_sales AS thu_sales1, fri_sales AS fri_sales1, sat_sales AS sat_sales1 FROM wss, store, date_dim AS d WHERE (d.d_week_seq = wss.d_week_seq) AND (ss_store_sk = s_store_sk) AND (d_month_seq BETWEEN 1212 AND 1212 + 11) ) AS y, ( SELECT s_store_name AS s_store_name2, wss.d_week_seq AS d_week_seq2, s_store_id AS s_store_id2, sun_sales AS sun_sales2, mon_sales AS mon_sales2, tue_sales AS tue_sales2, wed_sales AS wed_sales2, thu_sales AS thu_sales2, fri_sales AS fri_sales2, sat_sales AS sat_sales2 FROM wss, store, date_dim AS d WHERE (d.d_week_seq = wss.d_week_seq) AND (ss_store_sk = s_store_sk) AND (d_month_seq BETWEEN 1212 + 12 AND 1212 + 23) ) AS x WHERE (s_store_id1 = s_store_id2) AND (d_week_seq1 = d_week_seq2 - 52) ORDER BY s_store_name1, s_store_id1, d_week_seq1 LIMIT 100 +WITH ss AS ( SELECT i_item_id, sum(ss_ext_sales_price) AS total_sales FROM store_sales, date_dim, customer_address, item WHERE (i_item_id IN ( SELECT i_item_id FROM item WHERE (i_category IN ('Music')) )) AND (ss_item_sk = i_item_sk) AND (ss_sold_date_sk = d_date_sk) AND (d_year = 1998) AND (d_moy = 9) AND (ss_addr_sk = ca_address_sk) AND (ca_gmt_offset = -5) GROUP BY i_item_id ), cs AS ( SELECT i_item_id, sum(cs_ext_sales_price) AS total_sales FROM catalog_sales, date_dim, customer_address, item WHERE (i_item_id IN ( SELECT i_item_id FROM item WHERE (i_category IN ('Music')) )) AND (cs_item_sk = i_item_sk) AND (cs_sold_date_sk = d_date_sk) AND (d_year = 1998) AND (d_moy = 9) AND (cs_bill_addr_sk = ca_address_sk) AND (ca_gmt_offset = -5) GROUP BY i_item_id ), ws AS ( SELECT i_item_id, sum(ws_ext_sales_price) AS total_sales FROM web_sales, date_dim, customer_address, item WHERE (i_item_id IN ( SELECT i_item_id FROM item WHERE (i_category IN ('Music')) )) AND (ws_item_sk = i_item_sk) AND (ws_sold_date_sk = d_date_sk) AND (d_year = 1998) AND (d_moy = 9) AND (ws_bill_addr_sk = ca_address_sk) AND (ca_gmt_offset = -5) GROUP BY i_item_id ) SELECT i_item_id, sum(total_sales) AS total_sales FROM ( SELECT * FROM ss UNION ALL SELECT * FROM cs UNION ALL SELECT * FROM ws ) AS tmp1 GROUP BY i_item_id ORDER BY i_item_id, total_sales LIMIT 100 +SELECT promotions, total, CAST(promotions AS decimal(15, 4)) / CAST(total AS decimal(15, 4)) * 100 FROM ( SELECT sum(ss_ext_sales_price) AS promotions FROM store_sales, store, promotion, date_dim, customer, customer_address, item WHERE (ss_sold_date_sk = d_date_sk) AND (ss_store_sk = s_store_sk) AND (ss_promo_sk = p_promo_sk) AND (ss_customer_sk = c_customer_sk) AND (ca_address_sk = c_current_addr_sk) AND (ss_item_sk = i_item_sk) AND (ca_gmt_offset = -5) AND (i_category = 'Jewelry') AND ((p_channel_dmail = 'Y') OR (p_channel_email = 'Y') OR (p_channel_tv = 'Y')) AND (s_gmt_offset = -5) AND (d_year = 1998) AND (d_moy = 11) ) AS promotional_sales, ( SELECT sum(ss_ext_sales_price) AS total FROM store_sales, store, date_dim, customer, customer_address, item WHERE (ss_sold_date_sk = d_date_sk) AND (ss_store_sk = s_store_sk) AND (ss_customer_sk = c_customer_sk) AND (ca_address_sk = c_current_addr_sk) AND (ss_item_sk = i_item_sk) AND (ca_gmt_offset = -5) AND (i_category = 'Jewelry') AND (s_gmt_offset = -5) AND (d_year = 1998) AND (d_moy = 11) ) AS all_sales ORDER BY promotions, total LIMIT 100 +SELECT substr(w_warehouse_name, 1, 20), sm_type, web_name, sum(CASE WHEN (ws_ship_date_sk - ws_sold_date_sk <= 30) THEN 1 ELSE 0 END) AS "30 days", sum(CASE WHEN (ws_ship_date_sk - ws_sold_date_sk > 30) AND (ws_ship_date_sk - ws_sold_date_sk <= 60) THEN 1 ELSE 0 END) AS "31-60 days", sum(CASE WHEN (ws_ship_date_sk - ws_sold_date_sk > 60) AND (ws_ship_date_sk - ws_sold_date_sk <= 90) THEN 1 ELSE 0 END) AS "61-90 days", sum(CASE WHEN (ws_ship_date_sk - ws_sold_date_sk > 90) AND (ws_ship_date_sk - ws_sold_date_sk <= 120) THEN 1 ELSE 0 END) AS "91-120 days", sum(CASE WHEN (ws_ship_date_sk - ws_sold_date_sk > 120) THEN 1 ELSE 0 END) AS ">120 days" FROM web_sales, warehouse, ship_mode, web_site, date_dim WHERE (d_month_seq BETWEEN 1200 AND 1200 + 11) AND (ws_ship_date_sk = d_date_sk) AND (ws_warehouse_sk = w_warehouse_sk) AND (ws_ship_mode_sk = sm_ship_mode_sk) AND (ws_web_site_sk = web_site_sk) GROUP BY substr(w_warehouse_name, 1, 20), sm_type, web_name ORDER BY substr(w_warehouse_name, 1, 20), sm_type, web_name LIMIT 100 +SELECT * FROM ( SELECT i_manager_id, sum(ss_sales_price) AS sum_sales, avg(sum(ss_sales_price)) OVER (PARTITION BY i_manager_id) AS avg_monthly_sales FROM item, store_sales, date_dim, store WHERE (ss_item_sk = i_item_sk) AND (ss_sold_date_sk = d_date_sk) AND (ss_store_sk = s_store_sk) AND (d_month_seq IN (1200, 1200 + 1, 1200 + 2, 1200 + 3, 1200 + 4, 1200 + 5, 1200 + 6, 1200 + 7, 1200 + 8, 1200 + 9, 1200 + 10, 1200 + 11)) AND ( ( (i_category IN ('Books', 'Children', 'Electronics')) AND (i_class IN ('personal', 'portable', 'reference', 'self-help')) AND (i_brand IN ('scholaramalgamalg #14', 'scholaramalgamalg #7', 'exportiunivamalg #9', 'scholaramalgamalg #9')) ) OR ( (i_category IN ('Women', 'Music', 'Men')) AND (i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND (i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1')) ) ) GROUP BY i_manager_id, d_moy ) AS tmp1 WHERE (CASE WHEN avg_monthly_sales > 0 THEN abs(sum_sales - avg_monthly_sales) / avg_monthly_sales ELSE NULL END > 0.1) ORDER BY i_manager_id, avg_monthly_sales, sum_sales LIMIT 100 +WITH cs_ui AS ( SELECT cs_item_sk, sum(cs_ext_list_price) AS sale, sum((cr_refunded_cash + cr_reversed_charge) + cr_store_credit) AS refund FROM catalog_sales, catalog_returns WHERE (cs_item_sk = cr_item_sk) AND (cs_order_number = cr_order_number) GROUP BY cs_item_sk HAVING sum(cs_ext_list_price) > (2 * sum((cr_refunded_cash + cr_reversed_charge) + cr_store_credit)) ), cross_sales AS ( SELECT i_product_name AS product_name, i_item_sk AS item_sk, s_store_name AS store_name, s_zip AS store_zip, ad1.ca_street_number AS b_street_number, ad1.ca_street_name AS b_street_name, ad1.ca_city AS b_city, ad1.ca_zip AS b_zip, ad2.ca_street_number AS c_street_number, ad2.ca_street_name AS c_street_name, ad2.ca_city AS c_city, ad2.ca_zip AS c_zip, d1.d_year AS syear, d2.d_year AS fsyear, d3.d_year AS s2year, count(*) AS cnt, sum(ss_wholesale_cost) AS s1, sum(ss_list_price) AS s2, sum(ss_coupon_amt) AS s3 FROM store_sales, store_returns, cs_ui, date_dim AS d1, date_dim AS d2, date_dim AS d3, store, customer, customer_demographics AS cd1, customer_demographics AS cd2, promotion, household_demographics AS hd1, household_demographics AS hd2, customer_address AS ad1, customer_address AS ad2, income_band AS ib1, income_band AS ib2, item WHERE (ss_store_sk = s_store_sk) AND (ss_sold_date_sk = d1.d_date_sk) AND (ss_customer_sk = c_customer_sk) AND (ss_cdemo_sk = cd1.cd_demo_sk) AND (ss_hdemo_sk = hd1.hd_demo_sk) AND (ss_addr_sk = ad1.ca_address_sk) AND (ss_item_sk = i_item_sk) AND (ss_item_sk = sr_item_sk) AND (ss_ticket_number = sr_ticket_number) AND (ss_item_sk = cs_ui.cs_item_sk) AND (c_current_cdemo_sk = cd2.cd_demo_sk) AND (c_current_hdemo_sk = hd2.hd_demo_sk) AND (c_current_addr_sk = ad2.ca_address_sk) AND (c_first_sales_date_sk = d2.d_date_sk) AND (c_first_shipto_date_sk = d3.d_date_sk) AND (ss_promo_sk = p_promo_sk) AND (hd1.hd_income_band_sk = ib1.ib_income_band_sk) AND (hd2.hd_income_band_sk = ib2.ib_income_band_sk) AND (cd1.cd_marital_status != cd2.cd_marital_status) AND (i_color IN ('purple', 'burlywood', 'indian', 'spring', 'floral', 'medium')) AND ((i_current_price >= 64) AND (i_current_price <= (64 + 10))) AND ((i_current_price >= (64 + 1)) AND (i_current_price <= (64 + 15))) GROUP BY i_product_name, i_item_sk, s_store_name, s_zip, ad1.ca_street_number, ad1.ca_street_name, ad1.ca_city, ad1.ca_zip, ad2.ca_street_number, ad2.ca_street_name, ad2.ca_city, ad2.ca_zip, d1.d_year, d2.d_year, d3.d_year ) SELECT cs1.product_name, cs1.store_name, cs1.store_zip, cs1.b_street_number, cs1.b_street_name, cs1.b_city, cs1.b_zip, cs1.c_street_number, cs1.c_street_name, cs1.c_city, cs1.c_zip, cs1.syear, cs1.cnt, cs1.s1 AS s11, cs1.s2 AS s21, cs1.s3 AS s31, cs2.s1 AS s12, cs2.s2 AS s22, cs2.s3 AS s32, cs2.syear, cs2.cnt FROM cross_sales AS cs1, cross_sales AS cs2 WHERE (cs1.item_sk = cs2.item_sk) AND (cs1.syear = 1999) AND (cs2.syear = (1999 + 1)) AND (cs2.cnt <= cs1.cnt) AND (cs1.store_name = cs2.store_name) AND (cs1.store_zip = cs2.store_zip) ORDER BY cs1.product_name, cs1.store_name, cs2.cnt, cs1.s1, cs2.s1 +SELECT s_store_name, i_item_desc, sc.revenue, i_current_price, i_wholesale_cost, i_brand FROM store, item, ( SELECT ss_store_sk, avg(revenue) AS ave FROM ( SELECT ss_store_sk, ss_item_sk, sum(ss_sales_price) AS revenue FROM store_sales, date_dim WHERE ss_sold_date_sk = d_date_sk AND d_month_seq BETWEEN 1176 AND 1176+11 GROUP BY ss_store_sk, ss_item_sk ) AS sa GROUP BY ss_store_sk ) AS sb, ( SELECT ss_store_sk, ss_item_sk, sum(ss_sales_price) AS revenue FROM store_sales, date_dim WHERE ss_sold_date_sk = d_date_sk AND d_month_seq BETWEEN 1176 AND 1176+11 GROUP BY ss_store_sk, ss_item_sk ) AS sc WHERE (sb.ss_store_sk = sc.ss_store_sk) AND (sc.revenue <= (0.1 * sb.ave)) AND (s_store_sk = sc.ss_store_sk) AND (i_item_sk = sc.ss_item_sk) ORDER BY s_store_name, i_item_desc LIMIT 100 +SELECT w_warehouse_name, w_warehouse_sq_ft, w_city, w_county, w_state, w_country, ship_carriers, year, sum(x.jan_sales) AS jan_sales, sum(x.feb_sales) AS feb_sales, sum(x.mar_sales) AS mar_sales, sum(x.apr_sales) AS apr_sales, sum(x.may_sales) AS may_sales, sum(x.jun_sales) AS jun_sales, sum(x.jul_sales) AS jul_sales, sum(x.aug_sales) AS aug_sales, sum(x.sep_sales) AS sep_sales, sum(x.oct_sales) AS oct_sales, sum(x.nov_sales) AS nov_sales, sum(x.dec_sales) AS dec_sales, sum(CAST(x.jan_sales AS Float64) / w_warehouse_sq_ft) AS jan_sales_per_sq_foot, sum(CAST(x.feb_sales AS Float64) / w_warehouse_sq_ft) AS feb_sales_per_sq_foot, sum(CAST(x.mar_sales AS Float64) / w_warehouse_sq_ft) AS mar_sales_per_sq_foot, sum(CAST(x.apr_sales AS Float64) / w_warehouse_sq_ft) AS apr_sales_per_sq_foot, sum(CAST(x.may_sales AS Float64) / w_warehouse_sq_ft) AS may_sales_per_sq_foot, sum(CAST(x.jun_sales AS Float64) / w_warehouse_sq_ft) AS jun_sales_per_sq_foot, sum(CAST(x.jul_sales AS Float64) / w_warehouse_sq_ft) AS jul_sales_per_sq_foot, sum(CAST(x.aug_sales AS Float64) / w_warehouse_sq_ft) AS aug_sales_per_sq_foot, sum(CAST(x.sep_sales AS Float64) / w_warehouse_sq_ft) AS sep_sales_per_sq_foot, sum(CAST(x.oct_sales AS Float64) / w_warehouse_sq_ft) AS oct_sales_per_sq_foot, sum(CAST(x.nov_sales AS Float64) / w_warehouse_sq_ft) AS nov_sales_per_sq_foot, sum(CAST(x.dec_sales AS Float64) / w_warehouse_sq_ft) AS dec_sales_per_sq_foot, sum(x.jan_net) AS jan_net, sum(x.feb_net) AS feb_net, sum(x.mar_net) AS mar_net, sum(x.apr_net) AS apr_net, sum(x.may_net) AS may_net, sum(x.jun_net) AS jun_net, sum(x.jul_net) AS jul_net, sum(x.aug_net) AS aug_net, sum(x.sep_net) AS sep_net, sum(x.oct_net) AS oct_net, sum(x.nov_net) AS nov_net, sum(x.dec_net) AS dec_net FROM ( SELECT w_warehouse_name, w_warehouse_sq_ft, w_city, w_county, w_state, w_country, concat('DHL', ',', 'BARIAN') AS ship_carriers, d_year AS year, sum(multiIf(d_moy = 1, ws_ext_sales_price * ws_quantity, 0)) AS jan_sales, sum(multiIf(d_moy = 2, ws_ext_sales_price * ws_quantity, 0)) AS feb_sales, sum(multiIf(d_moy = 3, ws_ext_sales_price * ws_quantity, 0)) AS mar_sales, sum(multiIf(d_moy = 4, ws_ext_sales_price * ws_quantity, 0)) AS apr_sales, sum(multiIf(d_moy = 5, ws_ext_sales_price * ws_quantity, 0)) AS may_sales, sum(multiIf(d_moy = 6, ws_ext_sales_price * ws_quantity, 0)) AS jun_sales, sum(multiIf(d_moy = 7, ws_ext_sales_price * ws_quantity, 0)) AS jul_sales, sum(multiIf(d_moy = 8, ws_ext_sales_price * ws_quantity, 0)) AS aug_sales, sum(multiIf(d_moy = 9, ws_ext_sales_price * ws_quantity, 0)) AS sep_sales, sum(multiIf(d_moy = 10, ws_ext_sales_price * ws_quantity, 0)) AS oct_sales, sum(multiIf(d_moy = 11, ws_ext_sales_price * ws_quantity, 0)) AS nov_sales, sum(multiIf(d_moy = 12, ws_ext_sales_price * ws_quantity, 0)) AS dec_sales, sum(multiIf(d_moy = 1, ws_net_paid * ws_quantity, 0)) AS jan_net, sum(multiIf(d_moy = 2, ws_net_paid * ws_quantity, 0)) AS feb_net, sum(multiIf(d_moy = 3, ws_net_paid * ws_quantity, 0)) AS mar_net, sum(multiIf(d_moy = 4, ws_net_paid * ws_quantity, 0)) AS apr_net, sum(multiIf(d_moy = 5, ws_net_paid * ws_quantity, 0)) AS may_net, sum(multiIf(d_moy = 6, ws_net_paid * ws_quantity, 0)) AS jun_net, sum(multiIf(d_moy = 7, ws_net_paid * ws_quantity, 0)) AS jul_net, sum(multiIf(d_moy = 8, ws_net_paid * ws_quantity, 0)) AS aug_net, sum(multiIf(d_moy = 9, ws_net_paid * ws_quantity, 0)) AS sep_net, sum(multiIf(d_moy = 10, ws_net_paid * ws_quantity, 0)) AS oct_net, sum(multiIf(d_moy = 11, ws_net_paid * ws_quantity, 0)) AS nov_net, sum(multiIf(d_moy = 12, ws_net_paid * ws_quantity, 0)) AS dec_net FROM web_sales, warehouse, date_dim, time_dim, ship_mode WHERE (ws_warehouse_sk = w_warehouse_sk) AND (ws_sold_date_sk = d_date_sk) AND (ws_sold_time_sk = t_time_sk) AND (ws_ship_mode_sk = sm_ship_mode_sk) AND (d_year = 2001) AND (t_time BETWEEN 30838 AND 30838 + 28800) AND (sm_carrier IN ('DHL', 'BARIAN')) GROUP BY w_warehouse_name, w_warehouse_sq_ft, w_city, w_county, w_state, w_country, d_year UNION ALL SELECT w_warehouse_name, w_warehouse_sq_ft, w_city, w_county, w_state, w_country, concat('DHL', ',', 'BARIAN') AS ship_carriers, d_year AS year, sum(multiIf(d_moy = 1, cs_sales_price * cs_quantity, 0)) AS jan_sales, sum(multiIf(d_moy = 2, cs_sales_price * cs_quantity, 0)) AS feb_sales, sum(multiIf(d_moy = 3, cs_sales_price * cs_quantity, 0)) AS mar_sales, sum(multiIf(d_moy = 4, cs_sales_price * cs_quantity, 0)) AS apr_sales, sum(multiIf(d_moy = 5, cs_sales_price * cs_quantity, 0)) AS may_sales, sum(multiIf(d_moy = 6, cs_sales_price * cs_quantity, 0)) AS jun_sales, sum(multiIf(d_moy = 7, cs_sales_price * cs_quantity, 0)) AS jul_sales, sum(multiIf(d_moy = 8, cs_sales_price * cs_quantity, 0)) AS aug_sales, sum(multiIf(d_moy = 9, cs_sales_price * cs_quantity, 0)) AS sep_sales, sum(multiIf(d_moy = 10, cs_sales_price * cs_quantity, 0)) AS oct_sales, sum(multiIf(d_moy = 11, cs_sales_price * cs_quantity, 0)) AS nov_sales, sum(multiIf(d_moy = 12, cs_sales_price * cs_quantity, 0)) AS dec_sales, sum(multiIf(d_moy = 1, cs_net_paid_inc_tax * cs_quantity, 0)) AS jan_net, sum(multiIf(d_moy = 2, cs_net_paid_inc_tax * cs_quantity, 0)) AS feb_net, sum(multiIf(d_moy = 3, cs_net_paid_inc_tax * cs_quantity, 0)) AS mar_net, sum(multiIf(d_moy = 4, cs_net_paid_inc_tax * cs_quantity, 0)) AS apr_net, sum(multiIf(d_moy = 5, cs_net_paid_inc_tax * cs_quantity, 0)) AS may_net, sum(multiIf(d_moy = 6, cs_net_paid_inc_tax * cs_quantity, 0)) AS jun_net, sum(multiIf(d_moy = 7, cs_net_paid_inc_tax * cs_quantity, 0)) AS jul_net, sum(multiIf(d_moy = 8, cs_net_paid_inc_tax * cs_quantity, 0)) AS aug_net, sum(multiIf(d_moy = 9, cs_net_paid_inc_tax * cs_quantity, 0)) AS sep_net, sum(multiIf(d_moy = 10, cs_net_paid_inc_tax * cs_quantity, 0)) AS oct_net, sum(multiIf(d_moy = 11, cs_net_paid_inc_tax * cs_quantity, 0)) AS nov_net, sum(multiIf(d_moy = 12, cs_net_paid_inc_tax * cs_quantity, 0)) AS dec_net FROM catalog_sales, warehouse, date_dim, time_dim, ship_mode WHERE (cs_warehouse_sk = w_warehouse_sk) AND (cs_sold_date_sk = d_date_sk) AND (cs_sold_time_sk = t_time_sk) AND (cs_ship_mode_sk = sm_ship_mode_sk) AND (d_year = 2001) AND ((t_time >= 30838) AND (t_time <= (30838 + 28800))) AND (sm_carrier IN ('DHL', 'BARIAN')) GROUP BY w_warehouse_name, w_warehouse_sq_ft, w_city, w_county, w_state, w_country, d_year ) AS x GROUP BY w_warehouse_name, w_warehouse_sq_ft, w_city, w_county, w_state, w_country, ship_carriers, year ORDER BY w_warehouse_name LIMIT 100 +SELECT * FROM ( SELECT i_category, i_class, i_brand, i_product_name, d_year, d_qoy, d_moy, s_store_id, sumsales, rank() OVER (PARTITION BY i_category ORDER BY sumsales DESC) AS rk FROM ( SELECT i_category, i_class, i_brand, i_product_name, d_year, d_qoy, d_moy, s_store_id, sum(coalesce(ss_sales_price * ss_quantity, 0)) AS sumsales FROM store_sales, date_dim, store, item WHERE (ss_sold_date_sk = d_date_sk) AND (ss_item_sk = i_item_sk) AND (ss_store_sk = s_store_sk) AND (d_month_seq BETWEEN 1200 AND 1200 + 11) GROUP BY i_category, i_class, i_brand, i_product_name, d_year, d_qoy, d_moy, s_store_id WITH ROLLUP ) AS dw1 ) AS dw2 WHERE (rk <= 100) ORDER BY i_category, i_class, i_brand, i_product_name, d_year, d_qoy, d_moy, s_store_id, sumsales, rk LIMIT 100 +SELECT c_last_name, c_first_name, ca_city, bought_city, ss_ticket_number, extended_price, extended_tax, list_price FROM ( SELECT ss_ticket_number, ss_customer_sk, ca_city AS bought_city, sum(ss_ext_sales_price) AS extended_price, sum(ss_ext_list_price) AS list_price, sum(ss_ext_tax) AS extended_tax FROM store_sales, date_dim, store, household_demographics, customer_address WHERE (store_sales.ss_sold_date_sk = date_dim.d_date_sk) AND (store_sales.ss_store_sk = store.s_store_sk) AND (store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk) AND (store_sales.ss_addr_sk = customer_address.ca_address_sk) AND ((date_dim.d_dom >= 1) AND (date_dim.d_dom <= 2)) AND ((household_demographics.hd_dep_count = 4) OR (household_demographics.hd_vehicle_count = 3)) AND (date_dim.d_year IN (1999, 1999 + 1, 1999 + 2)) AND (store.s_city IN ('Midway', 'Fairview')) GROUP BY ss_ticket_number, ss_customer_sk, ss_addr_sk, ca_city ) AS dn, customer, customer_address AS current_addr WHERE (ss_customer_sk = c_customer_sk) AND (customer.c_current_addr_sk = current_addr.ca_address_sk) AND (current_addr.ca_city != bought_city) ORDER BY c_last_name, ss_ticket_number LIMIT 100 +SELECT cd_gender, cd_marital_status, cd_education_status, count(*) AS cnt1, cd_purchase_estimate, count(*) AS cnt2, cd_credit_rating, count(*) AS cnt3 FROM customer AS c, customer_address AS ca, customer_demographics WHERE (c.c_current_addr_sk = ca.ca_address_sk) AND (ca_state IN ('KY', 'GA', 'NM')) AND (cd_demo_sk = c.c_current_cdemo_sk) AND EXISTS ( SELECT * FROM store_sales, date_dim WHERE (c.c_customer_sk = ss_customer_sk) AND (ss_sold_date_sk = d_date_sk) AND (d_year = 2001) AND (d_moy BETWEEN 4 AND 4 + 2) ) AND ( NOT EXISTS ( SELECT * FROM web_sales, date_dim WHERE (c.c_customer_sk = ws_bill_customer_sk) AND (ws_sold_date_sk = d_date_sk) AND (d_year = 2001) AND (d_moy BETWEEN 4 AND 4 + 2) ) AND NOT EXISTS ( SELECT * FROM catalog_sales, date_dim WHERE (c.c_customer_sk = cs_ship_customer_sk) AND (cs_sold_date_sk = d_date_sk) AND (d_year = 2001) AND (d_moy BETWEEN 4 AND 4 + 2) ) ) GROUP BY cd_gender, cd_marital_status, cd_education_status, cd_purchase_estimate, cd_credit_rating ORDER BY cd_gender, cd_marital_status, cd_education_status, cd_purchase_estimate, cd_credit_rating LIMIT 100 +SELECT sum(ss_net_profit) AS total_sum, s_state, s_county, grouping(s_state) + grouping(s_county) AS lochierarchy, rank() OVER (PARTITION BY grouping(s_state) + grouping(s_county), multiIf(grouping(s_county) = 0, s_state, NULL) ORDER BY sum(ss_net_profit) DESC) AS rank_within_parent FROM store_sales, date_dim AS d1, store WHERE ((d1.d_month_seq >= 1200) AND (d1.d_month_seq <= (1200 + 11))) AND (d1.d_date_sk = ss_sold_date_sk) AND (s_store_sk = ss_store_sk) AND (s_state IN ( SELECT s_state FROM ( SELECT s_state AS s_state, rank() OVER (PARTITION BY s_state ORDER BY sum(ss_net_profit) DESC) AS ranking FROM store_sales, store, date_dim WHERE ((d_month_seq >= 1200) AND (d_month_seq <= (1200 + 11))) AND (d_date_sk = ss_sold_date_sk) AND (s_store_sk = ss_store_sk) GROUP BY s_state ) AS tmp1 WHERE (ranking <= 5) )) GROUP BY s_state, s_county WITH ROLLUP ORDER BY lochierarchy DESC, multiIf(lochierarchy = 0, s_state, NULL), rank_within_parent LIMIT 100 +SELECT i_brand_id AS brand_id, i_brand AS brand, t_hour, t_minute, sum(ext_price) AS ext_price FROM item, ( SELECT ws_ext_sales_price AS ext_price, ws_sold_date_sk AS sold_date_sk, ws_item_sk AS sold_item_sk, ws_sold_time_sk AS time_sk FROM web_sales, date_dim WHERE (d_date_sk = ws_sold_date_sk) AND (d_moy = 11) AND (d_year = 1999) UNION ALL SELECT cs_ext_sales_price AS ext_price, cs_sold_date_sk AS sold_date_sk, cs_item_sk AS sold_item_sk, cs_sold_time_sk AS time_sk FROM catalog_sales, date_dim WHERE (d_date_sk = cs_sold_date_sk) AND (d_moy = 11) AND (d_year = 1999) UNION ALL SELECT ss_ext_sales_price AS ext_price, ss_sold_date_sk AS sold_date_sk, ss_item_sk AS sold_item_sk, ss_sold_time_sk AS time_sk FROM store_sales, date_dim WHERE (d_date_sk = ss_sold_date_sk) AND (d_moy = 11) AND (d_year = 1999) ) AS tmp, time_dim WHERE (sold_item_sk = i_item_sk) AND (i_manager_id = 1) AND (time_sk = t_time_sk) AND ((t_meal_time = 'breakfast') OR (t_meal_time = 'dinner')) GROUP BY i_brand, i_brand_id, t_hour, t_minute ORDER BY ext_price DESC, i_brand_id +SELECT i_item_desc, w_warehouse_name, d1.d_week_seq, sum(multiIf(p_promo_sk IS NULL, 1, 0)) AS no_promo, sum(multiIf(p_promo_sk IS NOT NULL, 1, 0)) AS promo, count(*) AS total_cnt FROM catalog_sales INNER JOIN inventory ON cs_item_sk = inv_item_sk INNER JOIN warehouse ON w_warehouse_sk = inv_warehouse_sk INNER JOIN item ON i_item_sk = cs_item_sk INNER JOIN customer_demographics ON cs_bill_cdemo_sk = cd_demo_sk INNER JOIN household_demographics ON cs_bill_hdemo_sk = hd_demo_sk INNER JOIN date_dim AS d1 ON cs_sold_date_sk = d1.d_date_sk INNER JOIN date_dim AS d2 ON inv_date_sk = d2.d_date_sk INNER JOIN date_dim AS d3 ON cs_ship_date_sk = d3.d_date_sk LEFT JOIN promotion ON cs_promo_sk = p_promo_sk LEFT JOIN catalog_returns ON (cr_item_sk = cs_item_sk) AND (cr_order_number = cs_order_number) WHERE (d1.d_week_seq = d2.d_week_seq) AND (inv_quantity_on_hand < cs_quantity) AND (d3.d_date > (d1.d_date + 5)) AND (hd_buy_potential = '>10000') AND (d1.d_year = 1999) AND (cd_marital_status = 'D') GROUP BY i_item_desc, w_warehouse_name, d_week_seq ORDER BY total_cnt DESC, i_item_desc, w_warehouse_name, d_week_seq LIMIT 100 +SELECT c_last_name, c_first_name, c_salutation, c_preferred_cust_flag, ss_ticket_number, cnt FROM ( SELECT ss_ticket_number, ss_customer_sk, count(*) AS cnt FROM store_sales, date_dim, store, household_demographics WHERE (store_sales.ss_sold_date_sk = date_dim.d_date_sk) AND (store_sales.ss_store_sk = store.s_store_sk) AND (store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk) AND ((date_dim.d_dom >= 1) AND (date_dim.d_dom <= 2)) AND ((household_demographics.hd_buy_potential = '>10000') OR (household_demographics.hd_buy_potential = 'Unknown')) AND (household_demographics.hd_vehicle_count > 0) AND (multiIf(household_demographics.hd_vehicle_count > 0, household_demographics.hd_dep_count / household_demographics.hd_vehicle_count, NULL) > 1) AND (date_dim.d_year IN (1999, 1999 + 1, 1999 + 2)) AND (store.s_county IN ('Williamson County', 'Franklin Parish', 'Bronx County', 'Orange County')) GROUP BY ss_ticket_number, ss_customer_sk ) AS dj, customer WHERE (ss_customer_sk = c_customer_sk) AND ((cnt >= 1) AND (cnt <= 5)) ORDER BY cnt DESC, c_last_name +WITH year_total AS ( SELECT c_customer_id AS customer_id, c_first_name AS customer_first_name, c_last_name AS customer_last_name, d_year AS year, sum(ss_net_paid) AS year_total, 's' AS sale_type FROM customer, store_sales, date_dim WHERE (c_customer_sk = ss_customer_sk) AND (ss_sold_date_sk = d_date_sk) AND (d_year IN (2001, 2001 + 1)) GROUP BY c_customer_id, c_first_name, c_last_name, d_year UNION ALL SELECT c_customer_id AS customer_id, c_first_name AS customer_first_name, c_last_name AS customer_last_name, d_year AS year, sum(ws_net_paid) AS year_total, 'w' AS sale_type FROM customer, web_sales, date_dim WHERE (c_customer_sk = ws_bill_customer_sk) AND (ws_sold_date_sk = d_date_sk) AND (d_year IN (2001, 2001 + 1)) GROUP BY c_customer_id, c_first_name, c_last_name, d_year ) SELECT t_s_secyear.customer_id, t_s_secyear.customer_first_name, t_s_secyear.customer_last_name FROM year_total AS t_s_firstyear, year_total AS t_s_secyear, year_total AS t_w_firstyear, year_total AS t_w_secyear WHERE (t_s_secyear.customer_id = t_s_firstyear.customer_id) AND (t_s_firstyear.customer_id = t_w_secyear.customer_id) AND (t_s_firstyear.customer_id = t_w_firstyear.customer_id) AND (t_s_firstyear.sale_type = 's') AND (t_w_firstyear.sale_type = 'w') AND (t_s_secyear.sale_type = 's') AND (t_w_secyear.sale_type = 'w') AND (t_s_firstyear.year = 2001) AND (t_s_secyear.year = (2001 + 1)) AND (t_w_firstyear.year = 2001) AND (t_w_secyear.year = (2001 + 1)) AND (t_s_firstyear.year_total > 0) AND (t_w_firstyear.year_total > 0) AND (multiIf(t_w_firstyear.year_total > 0, t_w_secyear.year_total / t_w_firstyear.year_total, NULL) > multiIf(t_s_firstyear.year_total > 0, t_s_secyear.year_total / t_s_firstyear.year_total, NULL)) ORDER BY 1, 2, 3 LIMIT 100 +WITH all_sales AS ( SELECT d_year, i_brand_id, i_class_id, i_category_id, i_manufact_id, SUM(sales_cnt) AS sales_cnt, SUM(sales_amt) AS sales_amt FROM ( SELECT d_year, i_brand_id, i_class_id, i_category_id, i_manufact_id, cs_quantity - COALESCE(cr_return_quantity, 0) AS sales_cnt, cs_ext_sales_price - COALESCE(cr_return_amount, CAST('0.0', 'Decimal(7, 2)')) AS sales_amt FROM catalog_sales INNER JOIN item ON i_item_sk = cs_item_sk INNER JOIN date_dim ON d_date_sk = cs_sold_date_sk LEFT JOIN catalog_returns ON (cs_order_number = cr_order_number) AND (cs_item_sk = cr_item_sk) WHERE (i_category = 'Books') UNION SELECT d_year, i_brand_id, i_class_id, i_category_id, i_manufact_id, ss_quantity - COALESCE(sr_return_quantity, 0) AS sales_cnt, ss_ext_sales_price - COALESCE(sr_return_amt, CAST('0.0', 'Decimal(7, 2)')) AS sales_amt FROM store_sales INNER JOIN item ON i_item_sk = ss_item_sk INNER JOIN date_dim ON d_date_sk = ss_sold_date_sk LEFT JOIN store_returns ON (ss_ticket_number = sr_ticket_number) AND (ss_item_sk = sr_item_sk) WHERE (i_category = 'Books') UNION SELECT d_year, i_brand_id, i_class_id, i_category_id, i_manufact_id, ws_quantity - COALESCE(wr_return_quantity, 0) AS sales_cnt, ws_ext_sales_price - COALESCE(wr_return_amt, CAST('0.0', 'Decimal(7, 2)')) AS sales_amt FROM web_sales INNER JOIN item ON i_item_sk = ws_item_sk INNER JOIN date_dim ON d_date_sk = ws_sold_date_sk LEFT JOIN web_returns ON (ws_order_number = wr_order_number) AND (ws_item_sk = wr_item_sk) WHERE (i_category = 'Books') ) AS sales_detail GROUP BY d_year, i_brand_id, i_class_id, i_category_id, i_manufact_id ) SELECT prev_yr.d_year AS prev_year, curr_yr.d_year AS year, curr_yr.i_brand_id, curr_yr.i_class_id, curr_yr.i_category_id, curr_yr.i_manufact_id, prev_yr.sales_cnt AS prev_yr_cnt, curr_yr.sales_cnt AS curr_yr_cnt, curr_yr.sales_cnt - prev_yr.sales_cnt AS sales_cnt_diff, curr_yr.sales_amt - prev_yr.sales_amt AS sales_amt_diff FROM all_sales AS curr_yr, all_sales AS prev_yr WHERE (curr_yr.i_brand_id = prev_yr.i_brand_id) AND (curr_yr.i_class_id = prev_yr.i_class_id) AND (curr_yr.i_category_id = prev_yr.i_category_id) AND (curr_yr.i_manufact_id = prev_yr.i_manufact_id) AND (curr_yr.d_year = 2002) AND (prev_yr.d_year = (2002 - 1)) AND ((CAST(curr_yr.sales_cnt, 'DECIMAL(17, 2)') / CAST(prev_yr.sales_cnt, 'DECIMAL(17, 2)')) < 0.9) ORDER BY sales_cnt_diff, sales_amt_diff LIMIT 100 +SELECT channel, col_name, d_year, d_qoy, i_category, COUNT(*) AS sales_cnt, SUM(ext_sales_price) AS sales_amt FROM ( SELECT 'store' AS channel, 'ss_store_sk' AS col_name, d_year, d_qoy, i_category, ss_ext_sales_price AS ext_sales_price FROM store_sales, item, date_dim WHERE (ss_store_sk IS NULL) AND (ss_sold_date_sk = d_date_sk) AND (ss_item_sk = i_item_sk) UNION ALL SELECT 'web' AS channel, 'ws_ship_customer_sk' AS col_name, d_year, d_qoy, i_category, ws_ext_sales_price AS ext_sales_price FROM web_sales, item, date_dim WHERE (ws_ship_customer_sk IS NULL) AND (ws_sold_date_sk = d_date_sk) AND (ws_item_sk = i_item_sk) UNION ALL SELECT 'catalog' AS channel, 'cs_ship_addr_sk' AS col_name, d_year, d_qoy, i_category, cs_ext_sales_price AS ext_sales_price FROM catalog_sales, item, date_dim WHERE (cs_ship_addr_sk IS NULL) AND (cs_sold_date_sk = d_date_sk) AND (cs_item_sk = i_item_sk) ) AS foo GROUP BY channel, col_name, d_year, d_qoy, i_category ORDER BY channel, col_name, d_year, d_qoy, i_category LIMIT 100 +WITH ss AS ( SELECT s_store_sk, sum(ss_ext_sales_price) AS sales, sum(ss_net_profit) AS profit FROM store_sales, date_dim, store WHERE (ss_sold_date_sk = d_date_sk) AND ((d_date >= CAST('2000-08-23', 'date')) AND (d_date <= (CAST('2000-08-23', 'date') + INTERVAL 30 DAY))) AND (ss_store_sk = s_store_sk) GROUP BY s_store_sk ), sr AS ( SELECT s_store_sk, sum(sr_return_amt) AS returns, sum(sr_net_loss) AS profit_loss FROM store_returns, date_dim, store WHERE (sr_returned_date_sk = d_date_sk) AND ((d_date >= CAST('2000-08-23', 'date')) AND (d_date <= (CAST('2000-08-23', 'date') + INTERVAL 30 DAY))) AND (sr_store_sk = s_store_sk) GROUP BY s_store_sk ), cs AS ( SELECT cs_call_center_sk, sum(cs_ext_sales_price) AS sales, sum(cs_net_profit) AS profit FROM catalog_sales, date_dim WHERE (cs_sold_date_sk = d_date_sk) AND ((d_date >= CAST('2000-08-23', 'date')) AND (d_date <= (CAST('2000-08-23', 'date') + INTERVAL 30 DAY))) GROUP BY cs_call_center_sk ), cr AS ( SELECT cr_call_center_sk, sum(cr_return_amount) AS returns, sum(cr_net_loss) AS profit_loss FROM catalog_returns, date_dim WHERE (cr_returned_date_sk = d_date_sk) AND ((d_date >= CAST('2000-08-23', 'date')) AND (d_date <= (CAST('2000-08-23', 'date') + INTERVAL 30 DAY))) GROUP BY cr_call_center_sk ), ws AS ( SELECT wp_web_page_sk, sum(ws_ext_sales_price) AS sales, sum(ws_net_profit) AS profit FROM web_sales, date_dim, web_page WHERE (ws_sold_date_sk = d_date_sk) AND ((d_date >= CAST('2000-08-23', 'date')) AND (d_date <= (CAST('2000-08-23', 'date') + INTERVAL 30 DAY))) AND (ws_web_page_sk = wp_web_page_sk) GROUP BY wp_web_page_sk ), wr AS ( SELECT wp_web_page_sk, sum(wr_return_amt) AS returns, sum(wr_net_loss) AS profit_loss FROM web_returns, date_dim, web_page WHERE (wr_returned_date_sk = d_date_sk) AND ((d_date >= CAST('2000-08-23', 'date')) AND (d_date <= (CAST('2000-08-23', 'date') + INTERVAL 30 DAY))) AND (wr_web_page_sk = wp_web_page_sk) GROUP BY wp_web_page_sk ) SELECT channel, id, sum(sales) AS sales, sum(returns) AS returns, sum(profit) AS profit FROM ( SELECT 'store channel' AS channel, ss.s_store_sk AS id, sales, coalesce(returns, 0) AS returns, profit - coalesce(profit_loss, 0) AS profit FROM ss LEFT JOIN sr ON ss.s_store_sk = sr.s_store_sk UNION ALL SELECT 'catalog channel' AS channel, cs_call_center_sk AS id, sales, returns, profit - profit_loss AS profit FROM cs, cr UNION ALL SELECT 'web channel' AS channel, ws.wp_web_page_sk AS id, sales, coalesce(returns, 0) AS returns, profit - coalesce(profit_loss, 0) AS profit FROM ws LEFT JOIN wr ON ws.wp_web_page_sk = wr.wp_web_page_sk ) AS x GROUP BY channel, id WITH ROLLUP ORDER BY channel, id LIMIT 100 +WITH ws AS ( SELECT d_year AS ws_sold_year, ws_item_sk, ws_bill_customer_sk AS ws_customer_sk, sum(ws_quantity) AS ws_qty, sum(ws_wholesale_cost) AS ws_wc, sum(ws_sales_price) AS ws_sp FROM web_sales LEFT JOIN web_returns ON (wr_order_number = ws_order_number) AND (ws_item_sk = wr_item_sk) INNER JOIN date_dim ON ws_sold_date_sk = d_date_sk WHERE wr_order_number IS NULL GROUP BY d_year, ws_item_sk, ws_bill_customer_sk ), cs AS ( SELECT d_year AS cs_sold_year, cs_item_sk, cs_bill_customer_sk AS cs_customer_sk, sum(cs_quantity) AS cs_qty, sum(cs_wholesale_cost) AS cs_wc, sum(cs_sales_price) AS cs_sp FROM catalog_sales LEFT JOIN catalog_returns ON (cr_order_number = cs_order_number) AND (cs_item_sk = cr_item_sk) INNER JOIN date_dim ON cs_sold_date_sk = d_date_sk WHERE cr_order_number IS NULL GROUP BY d_year, cs_item_sk, cs_bill_customer_sk ), ss AS ( SELECT d_year AS ss_sold_year, ss_item_sk, ss_customer_sk, sum(ss_quantity) AS ss_qty, sum(ss_wholesale_cost) AS ss_wc, sum(ss_sales_price) AS ss_sp FROM store_sales LEFT JOIN store_returns ON (sr_ticket_number = ss_ticket_number) AND (ss_item_sk = sr_item_sk) INNER JOIN date_dim ON ss_sold_date_sk = d_date_sk WHERE sr_ticket_number IS NULL GROUP BY d_year, ss_item_sk, ss_customer_sk ) SELECT ss_sold_year, ss_item_sk, ss_customer_sk, round(ss_qty / (coalesce(ws_qty, 0) + coalesce(cs_qty, 0)), 2) AS ratio, ss_qty AS store_qty, ss_wc AS store_wholesale_cost, ss_sp AS store_sales_price, coalesce(ws_qty, 0) + coalesce(cs_qty, 0) AS other_chan_qty, coalesce(ws_wc, 0) + coalesce(cs_wc, 0) AS other_chan_wholesale_cost, coalesce(ws_sp, 0) + coalesce(cs_sp, 0) AS other_chan_sales_price FROM ss LEFT JOIN ws ON (ws_sold_year = ss_sold_year) AND (ws_item_sk = ss_item_sk) AND (ws_customer_sk = ss_customer_sk) LEFT JOIN cs ON (cs_sold_year = ss_sold_year) AND (cs_item_sk = ss_item_sk) AND (cs_customer_sk = ss_customer_sk) WHERE ((coalesce(ws_qty, 0) > 0) OR (coalesce(cs_qty, 0) > 0)) AND (ss_sold_year = 2000) ORDER BY ss_sold_year, ss_item_sk, ss_customer_sk, ss_qty DESC, ss_wc DESC, ss_sp DESC, other_chan_qty, other_chan_wholesale_cost, other_chan_sales_price, ratio LIMIT 100 +SELECT c_last_name, c_first_name, substr(s_city, 1, 30), ss_ticket_number, amt, profit FROM ( SELECT ss_ticket_number, ss_customer_sk, store.s_city, sum(ss_coupon_amt) AS amt, sum(ss_net_profit) AS profit FROM store_sales, date_dim, store, household_demographics WHERE (store_sales.ss_sold_date_sk = date_dim.d_date_sk) AND (store_sales.ss_store_sk = store.s_store_sk) AND (store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk) AND ((household_demographics.hd_dep_count = 6) OR (household_demographics.hd_vehicle_count > 2)) AND (date_dim.d_dow = 1) AND (date_dim.d_year IN (1999, 1999 + 1, 1999 + 2)) AND ((store.s_number_employees >= 200) AND (store.s_number_employees <= 295)) GROUP BY ss_ticket_number, ss_customer_sk, ss_addr_sk, store.s_city ) AS ms, customer WHERE (ss_customer_sk = c_customer_sk) ORDER BY c_last_name, c_first_name, substr(s_city, 1, 30), profit LIMIT 100 +WITH ssr AS ( SELECT s_store_id AS store_id, sum(ss_ext_sales_price) AS sales, sum(coalesce(sr_return_amt, 0)) AS returns, sum(ss_net_profit - coalesce(sr_net_loss, 0)) AS profit FROM store_sales LEFT JOIN store_returns ON (ss_item_sk = sr_item_sk) AND (ss_ticket_number = sr_ticket_number), date_dim, store, item, promotion WHERE (ss_sold_date_sk = d_date_sk) AND ((d_date >= CAST('2000-08-23', 'date')) AND (d_date <= (CAST('2000-08-23', 'date') + INTERVAL 30 DAY))) AND (ss_store_sk = s_store_sk) AND (ss_item_sk = i_item_sk) AND (i_current_price > 50) AND (ss_promo_sk = p_promo_sk) AND (p_channel_tv = 'N') GROUP BY s_store_id ), csr AS ( SELECT cp_catalog_page_id AS catalog_page_id, sum(cs_ext_sales_price) AS sales, sum(coalesce(cr_return_amount, 0)) AS returns, sum(cs_net_profit - coalesce(cr_net_loss, 0)) AS profit FROM catalog_sales LEFT JOIN catalog_returns ON (cs_item_sk = cr_item_sk) AND (cs_order_number = cr_order_number), date_dim, catalog_page, item, promotion WHERE (cs_sold_date_sk = d_date_sk) AND ((d_date >= CAST('2000-08-23', 'date')) AND (d_date <= (CAST('2000-08-23', 'date') + INTERVAL 30 DAY))) AND (cs_catalog_page_sk = cp_catalog_page_sk) AND (cs_item_sk = i_item_sk) AND (i_current_price > 50) AND (cs_promo_sk = p_promo_sk) AND (p_channel_tv = 'N') GROUP BY cp_catalog_page_id ), wsr AS ( SELECT web_site_id, sum(ws_ext_sales_price) AS sales, sum(coalesce(wr_return_amt, 0)) AS returns, sum(ws_net_profit - coalesce(wr_net_loss, 0)) AS profit FROM web_sales LEFT JOIN web_returns ON (ws_item_sk = wr_item_sk) AND (ws_order_number = wr_order_number), date_dim, web_site, item, promotion WHERE (ws_sold_date_sk = d_date_sk) AND ((d_date >= CAST('2000-08-23', 'date')) AND (d_date <= (CAST('2000-08-23', 'date') + INTERVAL 30 DAY))) AND (ws_web_site_sk = web_site_sk) AND (ws_item_sk = i_item_sk) AND (i_current_price > 50) AND (ws_promo_sk = p_promo_sk) AND (p_channel_tv = 'N') GROUP BY web_site_id ) SELECT channel, id, sum(sales) AS sales, sum(returns) AS returns, sum(profit) AS profit FROM ( SELECT 'store channel' AS channel, concat('store', store_id) AS id, sales, returns, profit FROM ssr UNION ALL SELECT 'catalog channel' AS channel, concat('catalog_page', catalog_page_id) AS id, sales, returns, profit FROM csr UNION ALL SELECT 'web channel' AS channel, concat('web_site', web_site_id) AS id, sales, returns, profit FROM wsr ) AS x GROUP BY channel, id WITH ROLLUP ORDER BY channel, id LIMIT 100 +WITH customer_total_return AS ( SELECT cr_returning_customer_sk AS ctr_customer_sk, ca_state AS ctr_state, sum(cr_return_amt_inc_tax) AS ctr_total_return FROM catalog_returns, date_dim, customer_address WHERE (cr_returned_date_sk = d_date_sk) AND (d_year = 2000) AND (cr_returning_addr_sk = ca_address_sk) GROUP BY cr_returning_customer_sk, ca_state ) SELECT c_customer_id, c_salutation, c_first_name, c_last_name, ca_street_number, ca_street_name, ca_street_type, ca_suite_number, ca_city, ca_county, ca_state, ca_zip, ca_country, ca_gmt_offset, ca_location_type, ctr_total_return FROM customer_total_return AS ctr1, customer_address, customer WHERE (ctr1.ctr_total_return > ( SELECT avg(ctr_total_return) * 1.2 FROM customer_total_return AS ctr2 WHERE (ctr1.ctr_state = ctr2.ctr_state) )) AND (ca_address_sk = c_current_addr_sk) AND (ca_state = 'GA') AND (ctr1.ctr_customer_sk = c_customer_sk) ORDER BY c_customer_id, c_salutation, c_first_name, c_last_name, ca_street_number, ca_street_name, ca_street_type, ca_suite_number, ca_city, ca_county, ca_state, ca_zip, ca_country, ca_gmt_offset, ca_location_type, ctr_total_return LIMIT 100 +SELECT i_item_id, i_item_desc, i_current_price FROM item, inventory, date_dim, store_sales WHERE (i_current_price BETWEEN 62 AND 62 + 30) AND (inv_item_sk = i_item_sk) AND (d_date_sk = inv_date_sk) AND (d_date BETWEEN CAST('2000-05-25', 'date') AND (CAST('2000-05-25', 'date') + INTERVAL 60 DAY)) AND (i_manufact_id IN (129, 270, 821, 423)) AND (inv_quantity_on_hand BETWEEN 100 AND 500) AND (ss_item_sk = i_item_sk) GROUP BY i_item_id, i_item_desc, i_current_price ORDER BY i_item_id LIMIT 100 +WITH sr_items AS ( SELECT i_item_id AS item_id, sum(sr_return_quantity) AS sr_item_qty FROM store_returns, item, date_dim WHERE (sr_item_sk = i_item_sk) AND (d_date IN ( SELECT d_date FROM date_dim WHERE (d_week_seq IN ( SELECT d_week_seq FROM date_dim WHERE (d_date IN ('2000-06-30', '2000-09-27', '2000-11-17')) )) )) AND (sr_returned_date_sk = d_date_sk) GROUP BY i_item_id ), cr_items AS ( SELECT i_item_id AS item_id, sum(cr_return_quantity) AS cr_item_qty FROM catalog_returns, item, date_dim WHERE (cr_item_sk = i_item_sk) AND (d_date IN ( SELECT d_date FROM date_dim WHERE (d_week_seq IN ( SELECT d_week_seq FROM date_dim WHERE (d_date IN ('2000-06-30', '2000-09-27', '2000-11-17')) )) )) AND (cr_returned_date_sk = d_date_sk) GROUP BY i_item_id ), wr_items AS ( SELECT i_item_id AS item_id, sum(wr_return_quantity) AS wr_item_qty FROM web_returns, item, date_dim WHERE (wr_item_sk = i_item_sk) AND (d_date IN ( SELECT d_date FROM date_dim WHERE (d_week_seq IN ( SELECT d_week_seq FROM date_dim WHERE (d_date IN ('2000-06-30', '2000-09-27', '2000-11-17')) )) )) AND (wr_returned_date_sk = d_date_sk) GROUP BY i_item_id ) SELECT sr_items.item_id, sr_item_qty, ((sr_item_qty / ((sr_item_qty + cr_item_qty) + wr_item_qty)) / 3.) * 100 AS sr_dev, cr_item_qty, ((cr_item_qty / ((sr_item_qty + cr_item_qty) + wr_item_qty)) / 3.) * 100 AS cr_dev, wr_item_qty, ((wr_item_qty / ((sr_item_qty + cr_item_qty) + wr_item_qty)) / 3.) * 100 AS wr_dev, ((sr_item_qty + cr_item_qty) + wr_item_qty) / 3. AS average FROM sr_items, cr_items, wr_items WHERE (sr_items.item_id = cr_items.item_id) AND (sr_items.item_id = wr_items.item_id) ORDER BY sr_items.item_id, sr_item_qty LIMIT 100 +SELECT c_customer_id AS customer_id, concat(coalesce(c_last_name, ''), ', ', coalesce(c_first_name, '')) AS customername FROM customer, customer_address, customer_demographics, household_demographics, income_band, store_returns WHERE (ca_city = 'Edgewood') AND (c_current_addr_sk = ca_address_sk) AND (ib_lower_bound >= 38128) AND (ib_upper_bound <= (38128 + 50000)) AND (ib_income_band_sk = hd_income_band_sk) AND (cd_demo_sk = c_current_cdemo_sk) AND (hd_demo_sk = c_current_hdemo_sk) AND (sr_cdemo_sk = cd_demo_sk) ORDER BY c_customer_id LIMIT 100 +SELECT substr(r_reason_desc, 1, 20), avg(ws_quantity), avg(wr_refunded_cash), avg(wr_fee) FROM web_sales, web_returns, web_page, customer_demographics AS cd1, customer_demographics AS cd2, customer_address, date_dim, reason WHERE (ws_web_page_sk = wp_web_page_sk) AND (ws_item_sk = wr_item_sk) AND (ws_order_number = wr_order_number) AND (ws_sold_date_sk = d_date_sk) AND (d_year = 2000) AND (cd1.cd_demo_sk = wr_refunded_cdemo_sk) AND (cd2.cd_demo_sk = wr_returning_cdemo_sk) AND (ca_address_sk = wr_refunded_addr_sk) AND (r_reason_sk = wr_reason_sk) AND ( ( (cd1.cd_marital_status = 'M') AND (cd1.cd_marital_status = cd2.cd_marital_status) AND (cd1.cd_education_status = 'Advanced Degree') AND (cd1.cd_education_status = cd2.cd_education_status) AND ((ws_sales_price >= 100.0) AND (ws_sales_price <= 150.0)) ) OR ( (cd1.cd_marital_status = 'S') AND (cd1.cd_marital_status = cd2.cd_marital_status) AND (cd1.cd_education_status = 'College') AND (cd1.cd_education_status = cd2.cd_education_status) AND ((ws_sales_price >= 50.0) AND (ws_sales_price <= 100.0)) ) OR ( (cd1.cd_marital_status = 'W') AND (cd1.cd_marital_status = cd2.cd_marital_status) AND (cd1.cd_education_status = '2 yr Degree') AND (cd1.cd_education_status = cd2.cd_education_status) AND ((ws_sales_price >= 150.0) AND (ws_sales_price <= 200.0)) ) ) AND ( ( (ca_country = 'United States') AND (ca_state IN ('IN', 'OH', 'NJ')) AND ((ws_net_profit >= 100) AND (ws_net_profit <= 200)) ) OR ( (ca_country = 'United States') AND (ca_state IN ('WI', 'CT', 'KY')) AND ((ws_net_profit >= 150) AND (ws_net_profit <= 300)) ) OR ( (ca_country = 'United States') AND (ca_state IN ('LA', 'IA', 'AR')) AND ((ws_net_profit >= 50) AND (ws_net_profit <= 250)) ) ) GROUP BY r_reason_desc ORDER BY substr(r_reason_desc, 1, 20), avg(ws_quantity), avg(wr_refunded_cash), avg(wr_fee) LIMIT 100 +SELECT sum(ws_net_paid) AS total_sum, i_category, i_class, grouping(i_category) + grouping(i_class) AS lochierarchy, rank() OVER (PARTITION BY grouping(i_category) + grouping(i_class), multiIf(grouping(i_class) = 0, i_category, NULL) ORDER BY sum(ws_net_paid) DESC) AS rank_within_parent FROM web_sales, date_dim AS d1, item WHERE ((d1.d_month_seq >= 1200) AND (d1.d_month_seq <= (1200 + 11))) AND (d1.d_date_sk = ws_sold_date_sk) AND (i_item_sk = ws_item_sk) GROUP BY i_category, i_class WITH ROLLUP ORDER BY lochierarchy DESC, multiIf(lochierarchy = 0, i_category, NULL), rank_within_parent LIMIT 100 +SELECT count(*) FROM ( SELECT DISTINCT c_last_name, c_first_name, d_date FROM store_sales, date_dim, customer WHERE (store_sales.ss_sold_date_sk = date_dim.d_date_sk) AND (store_sales.ss_customer_sk = customer.c_customer_sk) AND ((d_month_seq >= 1200) AND (d_month_seq <= (1200 + 11))) EXCEPT SELECT DISTINCT c_last_name, c_first_name, d_date FROM catalog_sales, date_dim, customer WHERE (catalog_sales.cs_sold_date_sk = date_dim.d_date_sk) AND (catalog_sales.cs_bill_customer_sk = customer.c_customer_sk) AND ((d_month_seq >= 1200) AND (d_month_seq <= (1200 + 11))) EXCEPT SELECT DISTINCT c_last_name, c_first_name, d_date FROM web_sales, date_dim, customer WHERE (web_sales.ws_sold_date_sk = date_dim.d_date_sk) AND (web_sales.ws_bill_customer_sk = customer.c_customer_sk) AND ((d_month_seq >= 1200) AND (d_month_seq <= (1200 + 11))) ) AS cool_cust +SELECT * FROM ( SELECT count(*) AS h8_30_to_9 FROM store_sales, household_demographics, time_dim, store WHERE (ss_sold_time_sk = time_dim.t_time_sk) AND (ss_hdemo_sk = household_demographics.hd_demo_sk) AND (ss_store_sk = s_store_sk) AND (time_dim.t_hour = 8) AND (time_dim.t_minute >= 30) AND ( ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= (4 + 2))) OR ((household_demographics.hd_dep_count = 2) AND (household_demographics.hd_vehicle_count <= (2 + 2))) OR ((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= (0 + 2))) ) AND (store.s_store_name = 'ese') ) AS s1, ( SELECT count(*) AS h9_to_9_30 FROM store_sales, household_demographics, time_dim, store WHERE (ss_sold_time_sk = time_dim.t_time_sk) AND (ss_hdemo_sk = household_demographics.hd_demo_sk) AND (ss_store_sk = s_store_sk) AND (time_dim.t_hour = 9) AND (time_dim.t_minute < 30) AND ( ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= (4 + 2))) OR ((household_demographics.hd_dep_count = 2) AND (household_demographics.hd_vehicle_count <= (2 + 2))) OR ((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= (0 + 2))) ) AND (store.s_store_name = 'ese') ) AS s2, ( SELECT count(*) AS h9_30_to_10 FROM store_sales, household_demographics, time_dim, store WHERE (ss_sold_time_sk = time_dim.t_time_sk) AND (ss_hdemo_sk = household_demographics.hd_demo_sk) AND (ss_store_sk = s_store_sk) AND (time_dim.t_hour = 9) AND (time_dim.t_minute >= 30) AND ( ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= (4 + 2))) OR ((household_demographics.hd_dep_count = 2) AND (household_demographics.hd_vehicle_count <= (2 + 2))) OR ((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= (0 + 2))) ) AND (store.s_store_name = 'ese') ) AS s3, ( SELECT count(*) AS h10_to_10_30 FROM store_sales, household_demographics, time_dim, store WHERE (ss_sold_time_sk = time_dim.t_time_sk) AND (ss_hdemo_sk = household_demographics.hd_demo_sk) AND (ss_store_sk = s_store_sk) AND (time_dim.t_hour = 10) AND (time_dim.t_minute < 30) AND ( ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= (4 + 2))) OR ((household_demographics.hd_dep_count = 2) AND (household_demographics.hd_vehicle_count <= (2 + 2))) OR ((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= (0 + 2))) ) AND (store.s_store_name = 'ese') ) AS s4, ( SELECT count(*) AS h10_30_to_11 FROM store_sales, household_demographics, time_dim, store WHERE (ss_sold_time_sk = time_dim.t_time_sk) AND (ss_hdemo_sk = household_demographics.hd_demo_sk) AND (ss_store_sk = s_store_sk) AND (time_dim.t_hour = 10) AND (time_dim.t_minute >= 30) AND ( ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= (4 + 2))) OR ((household_demographics.hd_dep_count = 2) AND (household_demographics.hd_vehicle_count <= (2 + 2))) OR ((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= (0 + 2))) ) AND (store.s_store_name = 'ese') ) AS s5, ( SELECT count(*) AS h11_to_11_30 FROM store_sales, household_demographics, time_dim, store WHERE (ss_sold_time_sk = time_dim.t_time_sk) AND (ss_hdemo_sk = household_demographics.hd_demo_sk) AND (ss_store_sk = s_store_sk) AND (time_dim.t_hour = 11) AND (time_dim.t_minute < 30) AND ( ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= (4 + 2))) OR ((household_demographics.hd_dep_count = 2) AND (household_demographics.hd_vehicle_count <= (2 + 2))) OR ((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= (0 + 2))) ) AND (store.s_store_name = 'ese') ) AS s6, ( SELECT count(*) AS h11_30_to_12 FROM store_sales, household_demographics, time_dim, store WHERE (ss_sold_time_sk = time_dim.t_time_sk) AND (ss_hdemo_sk = household_demographics.hd_demo_sk) AND (ss_store_sk = s_store_sk) AND (time_dim.t_hour = 11) AND (time_dim.t_minute >= 30) AND ( ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= (4 + 2))) OR ((household_demographics.hd_dep_count = 2) AND (household_demographics.hd_vehicle_count <= (2 + 2))) OR ((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= (0 + 2))) ) AND (store.s_store_name = 'ese') ) AS s7, ( SELECT count(*) AS h12_to_12_30 FROM store_sales, household_demographics, time_dim, store WHERE (ss_sold_time_sk = time_dim.t_time_sk) AND (ss_hdemo_sk = household_demographics.hd_demo_sk) AND (ss_store_sk = s_store_sk) AND (time_dim.t_hour = 12) AND (time_dim.t_minute < 30) AND ( ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= (4 + 2))) OR ((household_demographics.hd_dep_count = 2) AND (household_demographics.hd_vehicle_count <= (2 + 2))) OR ((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= (0 + 2))) ) AND (store.s_store_name = 'ese') ) AS s8 +SELECT * FROM ( SELECT i_category, i_class, i_brand, s_store_name, s_company_name, d_moy, sum(ss_sales_price) AS sum_sales, avg(sum(ss_sales_price)) OVER (PARTITION BY i_category, i_brand, s_store_name, s_company_name) AS avg_monthly_sales FROM item, store_sales, date_dim, store WHERE (ss_item_sk = i_item_sk) AND (ss_sold_date_sk = d_date_sk) AND (ss_store_sk = s_store_sk) AND (d_year IN (1999)) AND ( ((i_category IN ('Women', 'Jewelry', 'Men')) AND (i_class IN ('dresses', 'birdal', 'shirts'))) OR ((i_category IN ('Sports', 'Electronics', 'Books')) AND (i_class IN ('football', 'stereo', 'computers'))) ) GROUP BY i_category, i_class, i_brand, s_store_name, s_company_name, d_moy ) AS tmp1 WHERE (multiIf(avg_monthly_sales != 0, abs(sum_sales - avg_monthly_sales) / avg_monthly_sales, NULL) > 0.1) ORDER BY sum_sales - avg_monthly_sales, s_store_name LIMIT 100 +SELECT CAST(amc AS DECIMAL(15, 4)) / CAST(pmc AS DECIMAL(15, 4)) AS am_pm_ratio FROM ( SELECT count(*) AS amc FROM web_sales, household_demographics, time_dim, web_page WHERE (ws_sold_time_sk = time_dim.t_time_sk) AND (ws_ship_hdemo_sk = household_demographics.hd_demo_sk) AND (ws_web_page_sk = web_page.wp_web_page_sk) AND (time_dim.t_hour BETWEEN 8 AND 8 + 1) AND (household_demographics.hd_dep_count = 6) AND (web_page.wp_char_count BETWEEN 5000 AND 5200) ) AS at, ( SELECT count(*) AS pmc FROM web_sales, household_demographics, time_dim, web_page WHERE (ws_sold_time_sk = time_dim.t_time_sk) AND (ws_ship_hdemo_sk = household_demographics.hd_demo_sk) AND (ws_web_page_sk = web_page.wp_web_page_sk) AND (time_dim.t_hour BETWEEN 19 AND 19 + 1) AND (household_demographics.hd_dep_count = 6) AND (web_page.wp_char_count BETWEEN 5000 AND 5200) ) AS pt ORDER BY am_pm_ratio LIMIT 100 +SELECT cc_call_center_id AS Call_Center, cc_name AS Call_Center_Name, cc_manager AS Manager, sum(cr_net_loss) AS Returns_Loss FROM call_center, catalog_returns, date_dim, customer, customer_address, customer_demographics, household_demographics WHERE (cr_call_center_sk = cc_call_center_sk) AND (cr_returned_date_sk = d_date_sk) AND (cr_returning_customer_sk = c_customer_sk) AND (cd_demo_sk = c_current_cdemo_sk) AND (hd_demo_sk = c_current_hdemo_sk) AND (ca_address_sk = c_current_addr_sk) AND (d_year = 1998) AND (d_moy = 11) AND ( ((cd_marital_status = 'M') AND (cd_education_status = 'Unknown')) OR ((cd_marital_status = 'W') AND (cd_education_status = 'Advanced Degree')) ) AND (hd_buy_potential LIKE 'Unknown%') AND (ca_gmt_offset = -7) GROUP BY cc_call_center_id, cc_name, cc_manager, cd_marital_status, cd_education_status ORDER BY sum(cr_net_loss) DESC +SELECT sum(ws_ext_discount_amt) AS `Excess Discount Amount` FROM web_sales, item, date_dim WHERE (i_manufact_id = 350) AND (i_item_sk = ws_item_sk) AND ((d_date >= '2000-01-27') AND (d_date <= (CAST('2000-01-27', 'date') + INTERVAL 90 DAY))) AND (d_date_sk = ws_sold_date_sk) AND (ws_ext_discount_amt > ( SELECT 1.3 * avg(ws_ext_discount_amt) FROM web_sales, date_dim WHERE (ws_item_sk = i_item_sk) AND ((d_date >= '2000-01-27') AND (d_date <= (CAST('2000-01-27', 'date') + INTERVAL 90 DAY))) AND (d_date_sk = ws_sold_date_sk) )) ORDER BY sum(ws_ext_discount_amt) LIMIT 100 +SELECT ss_customer_sk, sum(act_sales) AS sumsales FROM ( SELECT ss_item_sk, ss_ticket_number, ss_customer_sk, multiIf(sr_return_quantity IS NOT NULL, (ss_quantity - sr_return_quantity) * ss_sales_price, ss_quantity * ss_sales_price) AS act_sales FROM store_sales LEFT JOIN store_returns ON (sr_item_sk = ss_item_sk) AND (sr_ticket_number = ss_ticket_number), reason WHERE (sr_reason_sk = r_reason_sk) AND (r_reason_desc = 'reason 28') ) AS t GROUP BY ss_customer_sk ORDER BY sumsales, ss_customer_sk LIMIT 100 +SELECT count(DISTINCT ws_order_number) AS "order count", sum(ws_ext_ship_cost) AS "total shipping cost", sum(ws_net_profit) AS "total net profit" FROM web_sales AS ws1, date_dim, customer_address, web_site WHERE (d_date BETWEEN '1999-2-01' AND (CAST('1999-2-01', 'date') + INTERVAL 60 DAY)) AND (ws1.ws_ship_date_sk = d_date_sk) AND (ws1.ws_ship_addr_sk = ca_address_sk) AND (ca_state = 'IL') AND (ws1.ws_web_site_sk = web_site_sk) AND (web_company_name = 'pri') AND EXISTS ( SELECT * FROM web_sales AS ws2 WHERE (ws1.ws_order_number = ws2.ws_order_number) AND (ws1.ws_warehouse_sk <> ws2.ws_warehouse_sk) ) AND NOT EXISTS ( SELECT * FROM web_returns AS wr1 WHERE (ws1.ws_order_number = wr1.wr_order_number) ) ORDER BY count(DISTINCT ws_order_number) LIMIT 100 +WITH ws_wh AS ( SELECT ws1.ws_order_number, ws1.ws_warehouse_sk AS wh1, ws2.ws_warehouse_sk AS wh2 FROM web_sales AS ws1, web_sales AS ws2 WHERE (ws1.ws_order_number = ws2.ws_order_number) AND (ws1.ws_warehouse_sk != ws2.ws_warehouse_sk) ) SELECT countDistinct(ws_order_number) AS `order count`, sum(ws_ext_ship_cost) AS `total shipping cost`, sum(ws_net_profit) AS `total net profit` FROM web_sales AS ws1, date_dim, customer_address, web_site WHERE ((d_date >= '1999-2-01') AND (d_date <= (CAST('1999-2-01', 'date') + INTERVAL 60 DAY))) AND (ws1.ws_ship_date_sk = d_date_sk) AND (ws1.ws_ship_addr_sk = ca_address_sk) AND (ca_state = 'IL') AND (ws1.ws_web_site_sk = web_site_sk) AND (web_company_name = 'pri') AND (ws1.ws_order_number IN ( SELECT ws_order_number FROM ws_wh )) AND (ws1.ws_order_number IN ( SELECT wr_order_number FROM web_returns, ws_wh WHERE (wr_order_number = ws_wh.ws_order_number) )) ORDER BY countDistinct(ws_order_number) LIMIT 100 +SELECT count(*) FROM store_sales, household_demographics, time_dim, store WHERE (ss_sold_time_sk = time_dim.t_time_sk) AND (ss_hdemo_sk = household_demographics.hd_demo_sk) AND (ss_store_sk = s_store_sk) AND (time_dim.t_hour = 20) AND (time_dim.t_minute >= 30) AND (household_demographics.hd_dep_count = 7) AND (store.s_store_name = 'ese') ORDER BY count(*) LIMIT 100 +WITH ssci AS ( SELECT ss_customer_sk AS customer_sk, ss_item_sk AS item_sk FROM store_sales, date_dim WHERE (ss_sold_date_sk = d_date_sk) AND (d_month_seq BETWEEN 1200 AND 1200 + 11) GROUP BY ss_customer_sk, ss_item_sk ), csci AS ( SELECT cs_bill_customer_sk AS customer_sk, cs_item_sk AS item_sk FROM catalog_sales, date_dim WHERE (cs_sold_date_sk = d_date_sk) AND (d_month_seq BETWEEN 1200 AND 1200 + 11) GROUP BY cs_bill_customer_sk, cs_item_sk ) SELECT sum(CASE WHEN (ssci.customer_sk IS NOT NULL) AND (csci.customer_sk IS NULL) THEN 1 ELSE 0 END) AS store_only, sum(CASE WHEN (ssci.customer_sk IS NULL) AND (csci.customer_sk IS NOT NULL) THEN 1 ELSE 0 END) AS catalog_only, sum(CASE WHEN (ssci.customer_sk IS NOT NULL) AND (csci.customer_sk IS NOT NULL) THEN 1 ELSE 0 END) AS store_and_catalog FROM ssci FULL OUTER JOIN csci ON (ssci.customer_sk = csci.customer_sk) AND (ssci.item_sk = csci.item_sk) LIMIT 100 +SELECT i_item_id, i_item_desc, i_category, i_class, i_current_price, sum(ss_ext_sales_price) AS itemrevenue, sum(ss_ext_sales_price) * 100 / sum(sum(ss_ext_sales_price)) OVER (PARTITION BY i_class) AS revenueratio FROM store_sales, item, date_dim WHERE (ss_item_sk = i_item_sk) AND (i_category IN ('Sports', 'Books', 'Home')) AND (ss_sold_date_sk = d_date_sk) AND (d_date BETWEEN CAST('1999-02-22', 'date') AND (CAST('1999-02-22', 'date') + INTERVAL 30 DAY)) GROUP BY i_item_id, i_item_desc, i_category, i_class, i_current_price ORDER BY i_category, i_class, i_item_id, i_item_desc, revenueratio +SELECT substr(w_warehouse_name, 1, 20), sm_type, cc_name, sum(CASE WHEN (cs_ship_date_sk - cs_sold_date_sk <= 30) THEN 1 ELSE 0 END) AS "30 days", sum(CASE WHEN (cs_ship_date_sk - cs_sold_date_sk > 30) AND (cs_ship_date_sk - cs_sold_date_sk <= 60) THEN 1 ELSE 0 END) AS "31-60 days", sum(CASE WHEN (cs_ship_date_sk - cs_sold_date_sk > 60) AND (cs_ship_date_sk - cs_sold_date_sk <= 90) THEN 1 ELSE 0 END) AS "61-90 days", sum(CASE WHEN (cs_ship_date_sk - cs_sold_date_sk > 90) AND (cs_ship_date_sk - cs_sold_date_sk <= 120) THEN 1 ELSE 0 END) AS "91-120 days", sum(CASE WHEN (cs_ship_date_sk - cs_sold_date_sk > 120) THEN 1 ELSE 0 END) AS ">120 days" FROM catalog_sales, warehouse, ship_mode, call_center, date_dim WHERE (d_month_seq BETWEEN 1200 AND 1200 + 11) AND (cs_ship_date_sk = d_date_sk) AND (cs_warehouse_sk = w_warehouse_sk) AND (cs_ship_mode_sk = sm_ship_mode_sk) AND (cs_call_center_sk = cc_call_center_sk) GROUP BY substr(w_warehouse_name, 1, 20), sm_type, cc_name ORDER BY substr(w_warehouse_name, 1, 20), sm_type, cc_name LIMIT 100 diff --git a/versions/queries/tpch.sql b/versions/queries/tpch.sql new file mode 100644 index 0000000000..eebeabd9d1 --- /dev/null +++ b/versions/queries/tpch.sql @@ -0,0 +1,22 @@ +SELECT l_returnflag, l_linestatus, sum(l_quantity) AS sum_qty, sum(l_extendedprice) AS sum_base_price, sum(l_extendedprice * (1 - l_discount)) AS sum_disc_price, sum(l_extendedprice * (1 - l_discount) * (1 + l_tax)) AS sum_charge, avg(l_quantity) AS avg_qty, avg(l_extendedprice) AS avg_price, avg(l_discount) AS avg_disc, count(*) AS count_order FROM lineitem WHERE (l_shipdate <= date '1998-12-01' - INTERVAL 90 DAY) GROUP BY l_returnflag, l_linestatus ORDER BY l_returnflag, l_linestatus +SELECT s_acctbal, s_name, n_name, p_partkey, p_mfgr, s_address, s_phone, s_comment FROM part, supplier, partsupp, nation, region WHERE (p_partkey = ps_partkey) AND (s_suppkey = ps_suppkey) AND (p_size = 15) AND (p_type LIKE '%BRASS') AND (s_nationkey = n_nationkey) AND (n_regionkey = r_regionkey) AND (r_name = 'EUROPE') AND (ps_supplycost = ( SELECT min(ps_supplycost) FROM partsupp, supplier, nation, region WHERE (p_partkey = ps_partkey) AND (s_suppkey = ps_suppkey) AND (s_nationkey = n_nationkey) AND (n_regionkey = r_regionkey) AND (r_name = 'EUROPE') )) ORDER BY s_acctbal DESC, n_name, s_name, p_partkey LIMIT 100 +SELECT l_orderkey, sum(l_extendedprice * (1 - l_discount)) AS revenue, o_orderdate, o_shippriority FROM customer, orders, lineitem WHERE (c_mktsegment = 'BUILDING') AND (c_custkey = o_custkey) AND (l_orderkey = o_orderkey) AND (o_orderdate < date '1995-03-15') AND (l_shipdate > date '1995-03-15') GROUP BY l_orderkey, o_orderdate, o_shippriority ORDER BY revenue DESC, o_orderdate LIMIT 10 +SELECT o_orderpriority, count(*) AS order_count FROM orders WHERE (o_orderdate >= date '1993-07-01') AND (o_orderdate < date '1993-07-01' + INTERVAL 3 MONTH) AND EXISTS ( SELECT * FROM lineitem WHERE (l_orderkey = o_orderkey) AND (l_commitdate < l_receiptdate) ) GROUP BY o_orderpriority ORDER BY o_orderpriority +SELECT n_name, sum(l_extendedprice * (1 - l_discount)) AS revenue FROM customer, orders, lineitem, supplier, nation, region WHERE (c_custkey = o_custkey) AND (l_orderkey = o_orderkey) AND (l_suppkey = s_suppkey) AND (c_nationkey = s_nationkey) AND (s_nationkey = n_nationkey) AND (n_regionkey = r_regionkey) AND (r_name = 'ASIA') AND (o_orderdate >= date '1994-01-01') AND (o_orderdate < date '1994-01-01' + INTERVAL 1 YEAR) GROUP BY n_name ORDER BY revenue DESC +SELECT sum(l_extendedprice * l_discount) AS revenue FROM lineitem WHERE (l_shipdate >= date '1994-01-01') AND (l_shipdate < date '1994-01-01' + INTERVAL 1 YEAR) AND (l_discount BETWEEN 0.06::Decimal(12,2) - 0.01::Decimal(12,2) AND 0.06::Decimal(12,2) + 0.01::Decimal(12,2)) AND (l_quantity < 24) +SELECT supp_nation, cust_nation, l_year, sum(volume) AS revenue FROM ( SELECT n1.n_name AS supp_nation, n2.n_name AS cust_nation, extract(year FROM l_shipdate) AS l_year, l_extendedprice * (1 - l_discount) AS volume FROM supplier, lineitem, orders, customer, nation AS n1, nation AS n2 WHERE (s_suppkey = l_suppkey) AND (o_orderkey = l_orderkey) AND (c_custkey = o_custkey) AND (s_nationkey = n1.n_nationkey) AND (c_nationkey = n2.n_nationkey) AND ( ((n1.n_name = 'FRANCE') AND (n2.n_name = 'GERMANY')) OR ((n1.n_name = 'GERMANY') AND (n2.n_name = 'FRANCE')) ) AND (l_shipdate BETWEEN date '1995-01-01' AND date '1996-12-31') ) AS shipping GROUP BY supp_nation, cust_nation, l_year ORDER BY supp_nation, cust_nation, l_year +SELECT o_year, sum(CASE WHEN nation = 'BRAZIL' THEN volume ELSE 0 END) / sum(volume) AS mkt_share FROM ( SELECT extract(year FROM o_orderdate) AS o_year, l_extendedprice * (1 - l_discount) AS volume, n2.n_name AS nation FROM part, supplier, lineitem, orders, customer, nation AS n1, nation AS n2, region WHERE (p_partkey = l_partkey) AND (s_suppkey = l_suppkey) AND (l_orderkey = o_orderkey) AND (o_custkey = c_custkey) AND (c_nationkey = n1.n_nationkey) AND (n1.n_regionkey = r_regionkey) AND (r_name = 'AMERICA') AND (s_nationkey = n2.n_nationkey) AND (o_orderdate BETWEEN date '1995-01-01' AND date '1996-12-31') AND (p_type = 'ECONOMY ANODIZED STEEL') ) AS all_nations GROUP BY o_year ORDER BY o_year +SELECT nation, o_year, sum(amount) AS sum_profit FROM ( SELECT n_name AS nation, extract(year FROM o_orderdate) AS o_year, l_extendedprice * (1 - l_discount) - ps_supplycost * l_quantity AS amount FROM part, supplier, lineitem, partsupp, orders, nation WHERE (s_suppkey = l_suppkey) AND (ps_suppkey = l_suppkey) AND (ps_partkey = l_partkey) AND (p_partkey = l_partkey) AND (o_orderkey = l_orderkey) AND (s_nationkey = n_nationkey) AND (p_name LIKE '%green%') ) AS profit GROUP BY nation, o_year ORDER BY nation, o_year DESC +SELECT c_custkey, c_name, sum(l_extendedprice * (1 - l_discount)) AS revenue, c_acctbal, n_name, c_address, c_phone, c_comment FROM customer, orders, lineitem, nation WHERE (c_custkey = o_custkey) AND (l_orderkey = o_orderkey) AND (o_orderdate >= date '1993-10-01') AND (o_orderdate < date '1993-10-01' + INTERVAL 3 MONTH) AND (l_returnflag = 'R') AND (c_nationkey = n_nationkey) GROUP BY c_custkey, c_name, c_acctbal, c_phone, n_name, c_address, c_comment ORDER BY revenue DESC LIMIT 20 +SELECT ps_partkey, sum(ps_supplycost * ps_availqty) AS value FROM partsupp, supplier, nation WHERE (ps_suppkey = s_suppkey) AND (s_nationkey = n_nationkey) AND (n_name = 'GERMANY') GROUP BY ps_partkey HAVING sum(ps_supplycost * ps_availqty) > ( SELECT sum(ps_supplycost * ps_availqty) * 0.0001 FROM partsupp, supplier, nation WHERE (ps_suppkey = s_suppkey) AND (s_nationkey = n_nationkey) AND (n_name = 'GERMANY') ) ORDER BY value DESC +SELECT l_shipmode, sum(CASE WHEN (o_orderpriority = '1-URGENT') OR (o_orderpriority = '2-HIGH') THEN 1 ELSE 0 END) AS high_line_count, sum(CASE WHEN (o_orderpriority <> '1-URGENT') AND (o_orderpriority <> '2-HIGH') THEN 1 ELSE 0 END) AS low_line_count FROM orders, lineitem WHERE (o_orderkey = l_orderkey) AND (l_shipmode IN ('MAIL', 'SHIP')) AND (l_commitdate < l_receiptdate) AND (l_shipdate < l_commitdate) AND (l_receiptdate >= date '1994-01-01') AND (l_receiptdate < date '1994-01-01' + INTERVAL 1 YEAR) GROUP BY l_shipmode ORDER BY l_shipmode +SELECT c_count, count(*) AS custdist FROM ( SELECT c_custkey, count(o_orderkey) AS c_count FROM customer LEFT OUTER JOIN orders ON (c_custkey = o_custkey) AND (o_comment NOT LIKE '%special%requests%') GROUP BY c_custkey ) AS c_orders GROUP BY c_count ORDER BY custdist DESC, c_count DESC +SELECT 100.00 * sum(CASE WHEN p_type LIKE 'PROMO%' THEN l_extendedprice * (1 - l_discount) ELSE 0 END) / sum(l_extendedprice * (1 - l_discount)) AS promo_revenue FROM lineitem, part WHERE (l_partkey = p_partkey) AND (l_shipdate >= date '1995-09-01') AND (l_shipdate < date '1995-09-01' + INTERVAL 1 MONTH) +WITH revenue0 AS (SELECT l_suppkey AS supplier_no, sum(l_extendedprice * (1 - l_discount)) AS total_revenue FROM lineitem WHERE (l_shipdate >= date '1996-01-01') AND (l_shipdate < date '1996-01-01' + INTERVAL 3 MONTH) GROUP BY l_suppkey) SELECT s_suppkey, s_name, s_address, s_phone, total_revenue FROM supplier, revenue0 WHERE (s_suppkey = supplier_no) AND (total_revenue = (SELECT max(total_revenue) FROM revenue0)) ORDER BY s_suppkey +SELECT p_brand, p_type, p_size, count(DISTINCT ps_suppkey) AS supplier_cnt FROM partsupp, part WHERE (p_partkey = ps_partkey) AND (p_brand <> 'Brand#45') AND (p_type NOT LIKE 'MEDIUM POLISHED%') AND (p_size IN (49, 14, 23, 45, 19, 3, 36, 9)) AND (ps_suppkey NOT IN ( SELECT s_suppkey FROM supplier WHERE (s_comment LIKE '%Customer%Complaints%') )) GROUP BY p_brand, p_type, p_size ORDER BY supplier_cnt DESC, p_brand, p_type, p_size +SELECT sum(l_extendedprice) / 7.0 AS avg_yearly FROM lineitem, part WHERE (p_partkey = l_partkey) AND (p_brand = 'Brand#23') AND (p_container = 'MED BOX') AND (l_quantity < ( SELECT 0.2 * avg(l_quantity) FROM lineitem WHERE (l_partkey = p_partkey) )) +SELECT c_name, c_custkey, o_orderkey, o_orderdate, o_totalprice, sum(l_quantity) FROM customer, orders, lineitem WHERE (o_orderkey IN ( SELECT l_orderkey FROM lineitem GROUP BY l_orderkey HAVING sum(l_quantity) > 300 )) AND (c_custkey = o_custkey) AND (o_orderkey = l_orderkey) GROUP BY c_name, c_custkey, o_orderkey, o_orderdate, o_totalprice ORDER BY o_totalprice DESC, o_orderdate LIMIT 100 +SELECT sum(l_extendedprice * (1 - l_discount)) AS revenue FROM lineitem, part WHERE ( (p_partkey = l_partkey) AND (p_brand = 'Brand#12') AND (p_container IN ('SM CASE', 'SM BOX', 'SM PACK', 'SM PKG')) AND (l_quantity >= 1) AND (l_quantity <= 1 + 10) AND (p_size BETWEEN 1 AND 5) AND (l_shipmode IN ('AIR', 'AIR REG')) AND (l_shipinstruct = 'DELIVER IN PERSON') ) OR ( (p_partkey = l_partkey) AND (p_brand = 'Brand#23') AND (p_container IN ('MED BAG', 'MED BOX', 'MED PKG', 'MED PACK')) AND (l_quantity >= 10) AND (l_quantity <= 10 + 10) AND (p_size BETWEEN 1 AND 10) AND (l_shipmode IN ('AIR', 'AIR REG')) AND (l_shipinstruct = 'DELIVER IN PERSON') ) OR ( (p_partkey = l_partkey) AND (p_brand = 'Brand#34') AND (p_container IN ('LG CASE', 'LG BOX', 'LG PACK', 'LG PKG')) AND (l_quantity >= 20) AND (l_quantity <= 20 + 10) AND (p_size BETWEEN 1 AND 15) AND (l_shipmode IN ('AIR', 'AIR REG')) AND (l_shipinstruct = 'DELIVER IN PERSON') ) +SELECT s_name, s_address FROM supplier, nation WHERE (s_suppkey IN ( SELECT ps_suppkey FROM partsupp WHERE (ps_partkey IN ( SELECT p_partkey FROM part WHERE (p_name LIKE 'forest%') )) AND (ps_availqty > ( SELECT 0.5 * sum(l_quantity) FROM lineitem WHERE (l_partkey = ps_partkey) AND (l_suppkey = ps_suppkey) AND (l_shipdate >= date '1994-01-01') AND (l_shipdate < date '1994-01-01' + INTERVAL 1 YEAR) )) )) AND (s_nationkey = n_nationkey) AND (n_name = 'CANADA') ORDER BY s_name +SELECT s_name, count(*) AS numwait FROM supplier, lineitem AS l1, orders, nation WHERE (s_suppkey = l1.l_suppkey) AND (o_orderkey = l1.l_orderkey) AND (o_orderstatus = 'F') AND (l1.l_receiptdate > l1.l_commitdate) AND EXISTS ( SELECT * FROM lineitem AS l2 WHERE (l2.l_orderkey = l1.l_orderkey) AND (l2.l_suppkey <> l1.l_suppkey) ) AND NOT EXISTS ( SELECT * FROM lineitem AS l3 WHERE (l3.l_orderkey = l1.l_orderkey) AND (l3.l_suppkey <> l1.l_suppkey) AND (l3.l_receiptdate > l3.l_commitdate) ) AND (s_nationkey = n_nationkey) AND (n_name = 'SAUDI ARABIA') GROUP BY s_name ORDER BY numwait DESC, s_name LIMIT 100 +SELECT cntrycode, count(*) AS numcust, sum(c_acctbal) AS totacctbal FROM ( SELECT substring(c_phone FROM 1 FOR 2) AS cntrycode, c_acctbal FROM customer WHERE (substring(c_phone FROM 1 FOR 2) IN ('13', '31', '23', '29', '30', '18', '17')) AND (c_acctbal > ( SELECT avg(c_acctbal) FROM customer WHERE (c_acctbal > 0.00) AND (substring(c_phone FROM 1 FOR 2) IN ('13', '31', '23', '29', '30', '18', '17')) )) AND NOT EXISTS ( SELECT * FROM orders WHERE (o_custkey = c_custkey) ) ) AS custsale GROUP BY cntrycode ORDER BY cntrycode diff --git a/versions/queries/uk.sql b/versions/queries/uk.sql new file mode 100644 index 0000000000..33c27acc2a --- /dev/null +++ b/versions/queries/uk.sql @@ -0,0 +1,3 @@ +SELECT toYear(date) AS year, round(avg(price)) AS price FROM uk_price_paid GROUP BY year ORDER BY year +SELECT toYear(date) AS year, round(avg(price)) AS price FROM uk_price_paid WHERE town = 'LONDON' GROUP BY year ORDER BY year +SELECT town, district, count() AS c, round(avg(price)) AS price FROM uk_price_paid WHERE date >= '2020-01-01' GROUP BY town, district HAVING c >= 100 ORDER BY price DESC LIMIT 100 diff --git a/versions/results/1.1.54019.json b/versions/results/1.1.54019.json new file mode 100644 index 0000000000..d7e7950f1a --- /dev/null +++ b/versions/results/1.1.54019.json @@ -0,0 +1,82 @@ +{ + "version": "1.1.54019", + "actual_version": "1.1.54019", + "result": + [ +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[0.079, 0.008, 0.008], +[0.081, 0.023, 0.024], +[null, null, null], +[0.134, 0.089, 0.079], +[null, null, null], +[1.178, 0.380, 0.375], +[null, null, null], +[null, null, null], +[null, null, null], +[3.441, 0.208, 0.205], +[null, null, null], +[3.423, 0.255, 0.255], +[57.621, 1.702, 1.684], +[44.238, 1.320, 1.316], +[44.353, 1.309, 1.299], +[53.659, 2.471, 2.475], +[61.644, 2.476, 2.452], +[42.120, 1.821, 1.819], +[null, null, null], +[68.166, 2.124, 2.113], +[20.773, 0.941, 0.961], +[21.461, 0.844, 0.844], +[0.065, 0.012, 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+[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null] + ] +} diff --git a/versions/results/54011.json b/versions/results/54011.json new file mode 100644 index 0000000000..873530a48e --- /dev/null +++ b/versions/results/54011.json @@ -0,0 +1,82 @@ +{ + "version": "54011", + "actual_version": "1.1.54011", + "result": + [ +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null], +[null, null, null] + ] +} diff --git a/versions/run-benchmark.sh b/versions/run-benchmark.sh index c4fbd5a8e2..f31b15d6b7 100755 --- a/versions/run-benchmark.sh +++ b/versions/run-benchmark.sh @@ -18,10 +18,10 @@ VERSION="${1:?usage: run-benchmark.sh }" machine="${machine:=c7a.4xlarge}" repo="${repo:=ClickHouse/ClickBench}" branch="${branch:=main}" -datasets="${datasets:=hits ssb mgbench}" # taxi skipped by default (huge); add 'taxi' to include -tries="${tries:=3}" +datasets="${datasets:=hits ssb mgbench tpch tpcds coffeeshop ontime uk job taxi}" # each loads into its own database +tries="${tries:=6}" # 1 cold + 5 hot runs timeout="${timeout:-18000}" # load + (optional source build) + queries -volume="${volume:-500}" # GB; raise well past 1000 if including taxi +volume="${volume:-500}" # GB; ample for all datasets (all now < 10 GB compressed) # gp3 root volume with provisioned throughput/IOPS (cold-cache query reads and # the ingest are disk-bound). gp3 maxes at 1000 MB/s / 16000 IOPS per volume; # the instance's own EBS bandwidth is the real ceiling. diff --git a/versions/run-version.sh b/versions/run-version.sh index a5d3b27600..b329b3f2f4 100755 --- a/versions/run-version.sh +++ b/versions/run-version.sh @@ -6,7 +6,7 @@ # Spins up the server, creates the six tables with version-appropriate DDL # (create/create.sh), loads the prepared Native files with a plain # `clickhouse-client INSERT ... FORMAT Native`, then times every query in -# queries/{mgbench,ssb,hits,taxi}.sql (TRIES runs each, dropping the page +# queries/{mgbench,ssb,hits,tpch,tpcds,coffeeshop,ontime,uk,job,taxi}.sql (TRIES runs each, dropping the page # cache between queries) and writes results/.json. # # phase (default "all") splits load from benchmark so run-all.sh can load many @@ -22,12 +22,12 @@ set -uo pipefail HERE="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" DATA="${DATA:-${HERE}/prepare-data/data}" -TRIES="${TRIES:-3}" +TRIES="${TRIES:-6}" # 1 cold + 5 hot runs MEM=100000000000 # 100G per-query memory limit # Datasets to actually load. Queries for any skipped dataset still run (and # report null). E.g. LOAD_DATASETS="hits ssb mgbench" skips the big taxi load # while keeping its file on disk. -LOAD_DATASETS="${LOAD_DATASETS:-hits ssb mgbench taxi}" +LOAD_DATASETS="${LOAD_DATASETS:-hits ssb mgbench tpch tpcds coffeeshop ontime uk job taxi}" VERSION="${1:?usage: run-version.sh [image_ref] [phase]}" IMAGE="${2:-}" @@ -44,9 +44,17 @@ declare -A TABLES=( [ssb]="lineorder_flat:ssb.native.zst" [mgbench]="logs1:mgbench1.native.zst logs2:mgbench2.native.zst logs3:mgbench3.native.zst" [taxi]="trips:taxi.native.zst" + [tpch]="nation:tpch_nation.native.zst region:tpch_region.native.zst part:tpch_part.native.zst supplier:tpch_supplier.native.zst partsupp:tpch_partsupp.native.zst customer:tpch_customer.native.zst orders:tpch_orders.native.zst lineitem:tpch_lineitem.native.zst" + [tpcds]="call_center:tpcds_call_center.native.zst catalog_page:tpcds_catalog_page.native.zst catalog_returns:tpcds_catalog_returns.native.zst catalog_sales:tpcds_catalog_sales.native.zst customer_address:tpcds_customer_address.native.zst customer_demographics:tpcds_customer_demographics.native.zst customer:tpcds_customer.native.zst date_dim:tpcds_date_dim.native.zst household_demographics:tpcds_household_demographics.native.zst income_band:tpcds_income_band.native.zst inventory:tpcds_inventory.native.zst item:tpcds_item.native.zst promotion:tpcds_promotion.native.zst reason:tpcds_reason.native.zst ship_mode:tpcds_ship_mode.native.zst store_returns:tpcds_store_returns.native.zst store_sales:tpcds_store_sales.native.zst store:tpcds_store.native.zst time_dim:tpcds_time_dim.native.zst warehouse:tpcds_warehouse.native.zst web_page:tpcds_web_page.native.zst web_returns:tpcds_web_returns.native.zst web_sales:tpcds_web_sales.native.zst web_site:tpcds_web_site.native.zst" + [coffeeshop]="fact_sales:coffeeshop_fact_sales.native.zst dim_locations:coffeeshop_dim_locations.native.zst dim_products:coffeeshop_dim_products.native.zst" + [ontime]="ontime:ontime.native.zst" + [uk]="uk_price_paid:uk_price_paid.native.zst" + [job]="aka_name:job_aka_name.native.zst aka_title:job_aka_title.native.zst cast_info:job_cast_info.native.zst char_name:job_char_name.native.zst comp_cast_type:job_comp_cast_type.native.zst company_name:job_company_name.native.zst company_type:job_company_type.native.zst complete_cast:job_complete_cast.native.zst info_type:job_info_type.native.zst keyword:job_keyword.native.zst kind_type:job_kind_type.native.zst link_type:job_link_type.native.zst movie_companies:job_movie_companies.native.zst movie_info:job_movie_info.native.zst movie_info_idx:job_movie_info_idx.native.zst movie_keyword:job_movie_keyword.native.zst movie_link:job_movie_link.native.zst name:job_name.native.zst person_info:job_person_info.native.zst role_type:job_role_type.native.zst title:job_title.native.zst" ) -# Query files are run (and reported) in this fixed order. -QUERY_ORDER="mgbench ssb hits taxi" +# Query files are run (and reported) in this fixed order. Each dataset loads +# into its own database (named after the dataset) so same-named tables (TPC-H +# and TPC-DS both have `customer`) don't collide. +QUERY_ORDER="mgbench ssb hits tpch tpcds coffeeshop ontime uk job taxi" cleanup() { sudo docker rm -f "${CONTAINER}" >/dev/null 2>&1; } # The load phase must leave the container running for the later bench phase; @@ -121,16 +129,19 @@ start_server() { load_data() { local ds pair table file ddl t0 reader for ds in ${LOAD_DATASETS}; do + # Each dataset lives in its own database so same-named tables (e.g. + # TPC-H and TPC-DS `customer`) don't clash. + client --query "CREATE DATABASE IF NOT EXISTS ${ds}" /dev/null for pair in ${TABLES[$ds]}; do table="${pair%%:*}"; file="${pair##*:}" - [ -f "${DATA}/${file}" ] || { echo "SKIP ${table}: ${file} not present"; continue; } - ddl="$("${HERE}/create/create.sh" "${VERSION}" "${table}")" - echo "=== CREATE ${table} on ${VERSION} ===" + [ -f "${DATA}/${file}" ] || { echo "SKIP ${ds}.${table}: ${file} not present"; continue; } + ddl="$("${HERE}/create/create.sh" "${VERSION}" "${ds}" "${table}")" + echo "=== CREATE ${ds}.${table} on ${VERSION} ===" echo "${ddl}" - if ! printf '%s' "${ddl}" | client --multiquery; then - echo "CREATE ${table} FAILED on ${VERSION}"; continue + if ! printf '%s' "${ddl}" | client --database "${ds}" --multiquery; then + echo "CREATE ${ds}.${table} FAILED on ${VERSION}"; continue fi - echo "=== INSERT INTO ${table} FORMAT Native <- ${file} ($(du -h "${DATA}/${file}" | cut -f1)) ===" + echo "=== INSERT INTO ${ds}.${table} FORMAT Native <- ${file} ($(du -h "${DATA}/${file}" | cut -f1)) ===" # Stream the compressed file through pv (progress %/rate/ETA once a # second, based on the known file size) -> zstd -dc -> a plain Native # INSERT, so the ancient clickhouse-client never sees compression. @@ -140,10 +151,10 @@ load_data() { reader=(cat -- "${DATA}/${file}") fi t0=${SECONDS} - if "${reader[@]}" | zstd -dc | client --query "INSERT INTO ${table} FORMAT Native"; then - echo "loaded ${table}: $(client --query "SELECT count() FROM ${table}" 2>/dev/null) rows in $((SECONDS - t0))s" + if "${reader[@]}" | zstd -dc | client --database "${ds}" --query "INSERT INTO ${table} FORMAT Native"; then + echo "loaded ${ds}.${table}: $(client --database "${ds}" --query "SELECT count() FROM ${table}" 2>/dev/null) rows in $((SECONDS - t0))s" else - echo "LOAD ${table} FAILED on ${VERSION}" + echo "LOAD ${ds}.${table} FAILED on ${VERSION}" fi done done @@ -176,21 +187,21 @@ revive_server() { report_sizes() { echo "=== table sizes on disk (${VERSION}) ===" local out - # Only the benchmark tables (database 'default'), not the server's own - # system.* log tables. - out=$(client --query "SELECT table, sum(bytes_on_disk) AS size FROM system.parts WHERE database = 'default' GROUP BY table ORDER BY table FORMAT TabSeparated" /dev/null) + # The benchmark tables live in per-dataset databases; exclude the server's + # own system databases. + out=$(client --query "SELECT database, table, sum(bytes_on_disk) AS size FROM system.parts WHERE database NOT IN ('system', 'information_schema', 'INFORMATION_SCHEMA') GROUP BY database, table ORDER BY database, table FORMAT TabSeparated" /dev/null) if [ -n "${out}" ]; then printf '%s\n' "${out}" else echo "(system.parts unavailable — measuring the data directory)" sudo docker exec "${CONTAINER}" sh -c ' base=/var/lib/clickhouse; [ -d "$base/data" ] || base=/opt/clickhouse - du -sLb "$base"/data/default/* 2>/dev/null | sort -k2' 2>/dev/null \ + du -sLb "$base"/data/*/* 2>/dev/null | grep -vE "/data/system/" | sort -k2' 2>/dev/null \ || echo "(could not measure data directory)" fi } -# Run one query TRIES times, print a JSON array "[t1, t2, t3]" (null on error). +# Run one query TRIES times, print a JSON array "[t1, ..., tN]" (null on error). # If the server dies mid-query (e.g. OOM-killed), revive it and retry up to # CRASH_RETRIES times so one heavy query doesn't null out the whole version. run_query() { @@ -198,7 +209,7 @@ run_query() { for i in $(seq 1 "${TRIES}"); do crash=0 while :; do - res=$(printf '%s' "${query}" | client --time --max_memory_usage="${MEM}" --format=Null 2>&1) + res=$(printf '%s' "${query}" | client --database "${QDB:-default}" --time --max_memory_usage="${MEM}" --format=Null 2>&1) [[ "${res}" =~ ^[0-9]+\.[0-9]+$ ]] && break if ! server_alive && [ "${crash}" -lt "${CRASH_RETRIES:-2}" ]; then crash=$((crash + 1)) @@ -229,7 +240,7 @@ detect_client() { # Time every query and write results/.json. run_benchmark() { - local ACTUAL ds query FIRST=1 qnum=0 row + local ACTUAL ds query FIRST=1 qnum=0 row QDB ACTUAL=$(client --query "SELECT version()" 2>/dev/null | tr -d '\r') echo "benchmarking ${VERSION} (server reports ${ACTUAL})" >&2 { @@ -239,6 +250,7 @@ run_benchmark() { echo ' "result":' echo ' [' for ds in ${QUERY_ORDER}; do + QDB="${ds}" # run this dataset's queries with its database as default # Read queries on FD 3 (not stdin) so the per-query `docker exec/run -i` # client calls can't consume the query file. while IFS= read -r query <&3; do From 8b1395fdcb79522bb07fb6cf95498714538c9966 Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Wed, 1 Jul 2026 04:16:19 +0000 Subject: [PATCH 022/120] versions: build unpublished versions on the fly; parallel load; query timeout MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit - run-version.sh builds clickhouse-built:* images on demand (ensure_built_image) when absent, using the recipe from versions.txt (build.sh) or monthly.tsv (Dockerfile.reconstruct) — nothing is pulled from a registry. - Load all datasets in parallel (one background job per dataset / database). - Per-query timeout (QUERY_TIMEOUT, default 100s): a query that exceeds it, or crashes the server, records null and skips its remaining tries (the server is revived after a crash so later queries still run). - ontime: sort the dump (Year, Month, FlightDate, ...) so INSERT blocks are date-contiguous and don't exceed max_partitions_per_insert_block (~450 months). - Reconstruct the build system for pre-2016-03 snapshots that lack one: Dockerfile.reconstruct + reconstruct.sh transplant the 2016-03 donor's build system + contrib, glob renamed sources, stub QuickLZ/MongoDB, generate re2_st, add an isnan shim; build-monthly.sh sweeps monthly.tsv. Strip the never-public add_subdirectory(private) from the 2016-06..08 tags in Dockerfile.ubuntu1604. - cloud-init: install docker-buildx; drop the now-redundant explicit build step. Co-Authored-By: Claude Opus 4.8 --- .../build-from-source/Dockerfile.reconstruct | 105 ++++++++++++ .../build-from-source/Dockerfile.ubuntu1604 | 6 +- versions/build-from-source/build-monthly.sh | 55 +++++++ versions/build-from-source/reconstruct.sh | 141 ++++++++++++++++ versions/cloud-init.sh.in | 11 +- versions/prepare-data/ontime.sh | 10 +- versions/prepare-data/taxi.sh | 2 +- versions/run-version.sh | 151 ++++++++++++------ 8 files changed, 426 insertions(+), 55 deletions(-) create mode 100644 versions/build-from-source/Dockerfile.reconstruct create mode 100755 versions/build-from-source/build-monthly.sh create mode 100755 versions/build-from-source/reconstruct.sh diff --git a/versions/build-from-source/Dockerfile.reconstruct b/versions/build-from-source/Dockerfile.reconstruct new file mode 100644 index 0000000000..e1d82b3f5f --- /dev/null +++ b/versions/build-from-source/Dockerfile.reconstruct @@ -0,0 +1,105 @@ +# Reconstruct a pre-2016-03 ClickHouse snapshot that has no public build system. +# +# The public repo only became self-contained (root CMakeLists.txt + contrib/) at +# 2016-03. Earlier commits carry the source but not the build files or vendored +# libraries. We overlay a donor commit's build system + contrib/ (DONOR, default +# the 2016-03 snapshot) onto the target source (TAG, a raw commit SHA), reconcile +# them with reconstruct.sh, supply the vendored libs the donor no longer ships +# (QuickLZ stub, system tcmalloc), and build clickhouse-server / clickhouse-client. +# +# docker build -f Dockerfile.reconstruct \ +# --build-arg TAG= --build-arg REVISION= -t clickhouse-built: . +# +# The result behaves like the official server images (see Dockerfile.ubuntu1604). + +FROM ubuntu:16.04 + +ARG GCC=5 +RUN set -eu; \ + if [ "${GCC}" != "5" ]; then \ + apt-get update && apt-get install -y --no-install-recommends software-properties-common && \ + add-apt-repository -y ppa:ubuntu-toolchain-r/test; \ + fi; \ + apt-get update && apt-get install -y --no-install-recommends \ + git ca-certificates cmake make pkg-config bash python3 "gcc-${GCC}" "g++-${GCC}" \ + libicu-dev libreadline-dev libssl-dev unixodbc-dev libglib2.0-dev \ + libboost-dev libboost-thread-dev libboost-program-options-dev \ + libboost-system-dev libboost-regex-dev libboost-filesystem-dev \ + zlib1g-dev liblz4-dev libzstd-dev libdouble-conversion-dev \ + libsparsehash-dev libmysqlclient-dev libzookeeper-mt-dev \ + libgoogle-perftools-dev tzdata \ + && rm -rf /var/lib/apt/lists/* + +ENV CC=gcc-${GCC} CXX=g++-${GCC} + +# DONOR: the earliest self-contained snapshot (2016-03-01), whose build system +# and contrib/ we transplant. TAG: the target snapshot's commit SHA. +ARG DONOR=5360c78806e043d0d2bf3de15a363f87fbdaf5f4 +ARG TAG +RUN git init -q /src && cd /src \ + && git config advice.detachedHead false \ + && git remote add origin https://github.com/ClickHouse/ClickHouse.git \ + && git fetch -q --depth 1 origin "${TAG}" && git checkout -q --detach FETCH_HEAD \ + && git fetch -q --depth 1 origin "${DONOR}" \ + && git checkout FETCH_HEAD -- contrib \ + && git checkout FETCH_HEAD -- $(git ls-tree -r --name-only FETCH_HEAD | grep -E 'CMakeLists.txt$|\.cmake$') + +# Reconcile the donor build system with the older source (globs, stubs, shims). +COPY reconstruct.sh /reconstruct.sh +RUN bash /reconstruct.sh + +# Configure, then build. re2/re2_st must be built (and put on the linker search +# path) before the server links; revision.h is generated directly (the donor's +# generator does a git-fetch that hangs on a shallow checkout). +ARG REVISION=53400 +WORKDIR /src/build +RUN cmake .. -DCMAKE_BUILD_TYPE=Release -DTESTS=NO \ + -DCMAKE_C_COMPILER="gcc-${GCC}" -DCMAKE_CXX_COMPILER="g++-${GCC}" \ + && make -j"$(nproc)" re2 re2_st \ + && cp "$(find . -name libre2.a | head -1)" /usr/lib/ \ + && cp "$(find . -name libre2_st.a | head -1)" /usr/lib/ \ + && mkdir -p /src/build/libs/libcommon/src \ + && printf '#ifndef REVISION\n#define REVISION %s\n#endif\n' "${REVISION}" > /src/build/libs/libcommon/src/revision.h \ + && make -j"$(nproc)" clickhouse-server clickhouse-client + +# Install binaries + a multi-call shim + a minimal IPv4 config (this era ships +# no default config.xml in the tree). +RUN set -eu; \ + SRV=$(find /src/build -type f -executable -name clickhouse-server | head -1); \ + CLI=$(find /src/build -type f -executable -name clickhouse-client | head -1); \ + cp "$SRV" /usr/bin/clickhouse-server; cp "$CLI" /usr/bin/clickhouse-client; \ + printf '#!/bin/sh\ncmd="$1"; shift\nexec "/usr/bin/clickhouse-$cmd" "$@"\n' > /usr/bin/clickhouse; \ + chmod +x /usr/bin/clickhouse; \ + mkdir -p /etc/clickhouse-server /var/log/clickhouse-server \ + /opt/clickhouse/metadata/default /opt/clickhouse/data/default /opt/clickhouse/tmp +RUN cat > /etc/clickhouse-server/config.xml <<'EOF' + + error/var/log/clickhouse-server/clickhouse-server.log/var/log/clickhouse-server/err.log100M1 + 0.0.0.0 + 9000 + 8123 + /opt/clickhouse/ + /opt/clickhouse/tmp/ + 5368709120 + 8589934592 + users.xml + default + default + +EOF +RUN cat > /etc/clickhouse-server/users.xml <<'EOF' + + 10000000000 + + + ::/0 + default + default + + + +EOF + +EXPOSE 8123 9000 +WORKDIR / +ENTRYPOINT ["/usr/bin/clickhouse-server", "--config-file=/etc/clickhouse-server/config.xml"] diff --git a/versions/build-from-source/Dockerfile.ubuntu1604 b/versions/build-from-source/Dockerfile.ubuntu1604 index 7c31351a83..e929ea3deb 100644 --- a/versions/build-from-source/Dockerfile.ubuntu1604 +++ b/versions/build-from-source/Dockerfile.ubuntu1604 @@ -59,7 +59,11 @@ RUN git init -q /src && cd /src \ # The 2016 tree hardcodes -Werror in CMAKE_CXX_FLAGS and also leaks clang-only # -Wno-* flags into the GCC build, which then fail under -Werror. Strip -Werror # from the project's cmake so warnings (incl. unrecognised options) stay non-fatal. -RUN find /src -name CMakeLists.txt -o -name '*.cmake' | xargs -r sed -i 's/-Werror//g' +# Also drop add_subdirectory(private): the 2016-06..08 tags reference a +# Yandex-internal Metrica directory ("private") that was never open-sourced, so +# the reference is a fatal cmake configure error in the public tree. +RUN find /src -name CMakeLists.txt -o -name '*.cmake' | xargs -r sed -i 's/-Werror//g' \ + && find /src -name CMakeLists.txt | xargs -r sed -i '/add_subdirectory *( *private *)/d' WORKDIR /src/build # Build just the server and client. Fall back to the default target set if those diff --git a/versions/build-from-source/build-monthly.sh b/versions/build-from-source/build-monthly.sh new file mode 100755 index 0000000000..20cbab937b --- /dev/null +++ b/versions/build-from-source/build-monthly.sh @@ -0,0 +1,55 @@ +#!/usr/bin/env bash +# Build the untagged monthly snapshots (monthly.tsv) from source, newest to +# oldest, via Dockerfile.reconstruct (see reconstruct.sh). Each snapshot becomes +# image clickhouse-built:. Snapshots at/after 2016-03 have a public +# build system; earlier ones are reconstructed by transplanting the 2016-03 +# donor's build system + contrib. Going far enough back the transplant stops +# matching the source - that boundary is what this sweep discovers. +# +# ./build-monthly.sh # all months in monthly.tsv (newest first) +# ./build-monthly.sh 2016-02-01 ... # only the given months +# JOBS=3 ./build-monthly.sh # 3 concurrent builds (default 3) +# +# monthly.tsv is "" per line. + +set -uo pipefail +HERE="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" +LOGS="${HERE}/logs"; mkdir -p "${LOGS}" +JOBS="${JOBS:-3}" + +declare -A WANT=() +for a in "$@"; do WANT["$a"]=1; done + +build_one() { # date sha + local date="$1" sha="$2" + if sudo docker image inspect "clickhouse-built:${date}" >/dev/null 2>&1; then + echo "skip ${date}: image exists"; return 0 + fi + if sudo docker buildx build --progress=plain --load \ + --build-arg "TAG=${sha}" --build-arg "GCC=${GCC:-5}" \ + -t "clickhouse-built:${date}" -f "${HERE}/Dockerfile.reconstruct" "${HERE}" \ + >"${LOGS}/reconstruct-${date}.log" 2>&1; then + # smoke test: server boots and answers a query + sudo docker rm -f "smoke-${date}" >/dev/null 2>&1 + sudo docker run -d --name "smoke-${date}" "clickhouse-built:${date}" >/dev/null 2>&1 + local v="" i + for i in $(seq 1 30); do + v=$(sudo docker exec "smoke-${date}" clickhouse client --query "SELECT version()" 2>/dev/null) && break + sleep 1 + done + sudo docker rm -f "smoke-${date}" >/dev/null 2>&1 + if [ -n "${v}" ]; then echo "OK ${date} (version ${v})"; else echo "BUILT-BUT-NO-BOOT ${date}" >&2; fi + else + echo "FAILED ${date} (see ${LOGS}/reconstruct-${date}.log)" >&2 + fi +} + +# newest first (monthly.tsv is already newest->oldest) +while IFS=$'\t' read -r date sha _cd; do + [ -z "${date}" ] && continue + [ "$#" -gt 0 ] && [ -z "${WANT[$date]:-}" ] && continue + while [ "$(jobs -rp | wc -l)" -ge "${JOBS}" ]; do wait -n 2>/dev/null || sleep 5; done + build_one "${date}" "${sha}" & +done < "${HERE}/monthly.tsv" +wait +echo "build-monthly done" diff --git a/versions/build-from-source/reconstruct.sh b/versions/build-from-source/reconstruct.sh new file mode 100755 index 0000000000..bb7ea2e3ba --- /dev/null +++ b/versions/build-from-source/reconstruct.sh @@ -0,0 +1,141 @@ +#!/bin/bash +# Reconstruct the build system for a pre-2016-03 ClickHouse snapshot. +# +# The public repo only became self-contained (root CMakeLists + contrib/) at +# 2016-03. Earlier snapshots have the *source* but no build system and no +# vendored libraries. This script runs inside a checkout where the target +# source is at /src and a donor commit's build system (root CMakeLists, all +# per-dir CMakeLists, cmake modules and contrib/) has already been overlaid on +# top (see Dockerfile.reconstruct). It then reconciles the donor build files +# with the older source: +# +# * glob libcommon/libdaemon sources -> absorbs file renames +# (Daemon.cpp->BaseDaemon.cpp, Revision.cpp->ClickHouseRevision.cpp, ...) +# * prune donor-listed files absent here -> handles added/removed files +# * disable the tests/ targets -> they list snapshot-specific files +# * QuickLZ -> header-only stub (dropped at open-sourcing; never imported. +# The quicklz codec is never produced/consumed with LZ4/ZSTD data) +# * re2_st -> generated from contrib/libre2 via the donor's create_st_headers.sh +# * MongoDB -> throwing stub (legacy mongoclient driver never vendored) +# * isnan/isinf/isfinite -> force-included std:: shim for gcc-5 libstdc++ +# +# Idempotent-ish: intended to run once on a fresh overlay. + +set -eu +cd /src + +# -- strip -Werror (and the clang-only -Wno-* flags that leak into the gcc build) -- +find /src -name CMakeLists.txt -o -name '*.cmake' | xargs -r sed -i 's/-Werror//g' + +# -- drop the tests/ subdirectories: they enumerate files that don't all exist +# in an older snapshot, which is a fatal cmake configure error -- +find /src -name CMakeLists.txt | xargs -r sed -i 's/add_subdirectory *( *tests *)//g' +sed -i 's/INCLUDE(add.test.cmake)//' CMakeLists.txt || true + +# -- drop add_subdirectory(private): the Yandex-internal Metrica code was never +# open-sourced (appears in the 2016-06+ trees). -- +find /src -name CMakeLists.txt | xargs -r sed -i '/add_subdirectory *( *private *)/d' + +# -- glob the two small libraries so renamed sources are still picked up -- +cat > libs/libdaemon/CMakeLists.txt <<'EOF' +file(GLOB daemon_src src/*.cpp) +add_library(daemon ${daemon_src}) +target_link_libraries(daemon dbms) +EOF + +python3 - <<'PY' +import re, os +# libcommon: replace the explicit source list with a glob +f = "libs/libcommon/CMakeLists.txt"; s = open(f).read() +s = re.sub(r"add_library\s*\(\s*common.*?\)", + "file(GLOB common_src src/*.cpp)\nadd_library(common ${common_src})", + s, count=1, flags=re.S) +open(f, "w").write(s) + +# dbms top-level add_library lists many headers/sources; drop any that this +# snapshot doesn't have, and drop the (unvendored) mongoclient link name. +f = "dbms/CMakeLists.txt"; s = open(f).read() +m = re.search(r"add_library\s*\(\s*dbms(.*?)\)", s, flags=re.S) +if m: + kept = [t for t in m.group(1).split() + if not t.endswith((".h", ".cpp", ".inc")) or os.path.exists("dbms/" + t)] + s = s[:m.start()] + "add_library (dbms\n\t" + "\n\t".join(kept) + ")" + s[m.end():] +s = re.sub(r"\bmongoclient\b", "", s) +open(f, "w").write(s) +PY + +# -- QuickLZ compile/link stub (dead code path: our data is LZ4/ZSTD) -- +mkdir -p contrib/quicklz-stub/quicklz +cat > contrib/quicklz-stub/quicklz/quicklz_level1.h <<'EOF' +#pragma once +#include +// QuickLZ was removed at the 2016-03 open-sourcing and never imported to the +// public repo. The quicklz compression method is never produced or consumed +// here (data uses LZ4/ZSTD), so these symbols only need to compile and link. +struct qlz_state_compress { char scratch[1000000]; }; +struct qlz_state_decompress { char scratch[1000000]; }; +inline size_t qlz_compress(const void *, char * dst, size_t size, qlz_state_compress *) { (void)dst; return size; } +inline size_t qlz_size_compressed(const char *) { return 0; } +inline size_t qlz_size_decompressed(const char *) { return 0; } +inline size_t qlz_decompress(const char *, void *, qlz_state_decompress *) { return 0; } +EOF +cp contrib/quicklz-stub/quicklz/quicklz_level1.h contrib/quicklz-stub/quicklz/quicklz_level2.h +cp contrib/quicklz-stub/quicklz/quicklz_level1.h contrib/quicklz-stub/quicklz/quicklz_level3.h + +# -- generate the re2_st (single-threaded re2) headers into a stable include dir -- +mkdir -p contrib/re2_st_gen +( cd contrib/re2_st_gen && sh /src/contrib/libre2/create_st_headers.sh /src/contrib/libre2 . ) + +# -- gcc-5 libstdc++ moved isnan/isinf/isfinite into std::; bridge them back -- +mkdir -p contrib/compat +cat > contrib/compat/cmath_compat.h <<'EOF' +#pragma once +#include +using std::isnan; +using std::isinf; +using std::isfinite; +EOF + +# -- MongoDB dictionary: throwing stub (legacy mongoclient driver not vendored) -- +cat > dbms/include/DB/Dictionaries/MongoDBBlockInputStream.h <<'EOF' +#pragma once +// Stub: MongoDB support removed (legacy mongoclient driver not vendored). +EOF +cat > dbms/include/DB/Dictionaries/MongoDBDictionarySource.h <<'EOF' +#pragma once +#include +#include +#include +#include +#include +namespace DB +{ +struct DictionaryStructure; +class Block; +class Context; +// MongoDB dictionary support is disabled in this reconstructed build; requesting +// a mongodb dictionary source throws. Never exercised by the benchmark. +class MongoDBDictionarySource final : public IDictionarySource +{ +public: + MongoDBDictionarySource(const DictionaryStructure &, const Poco::Util::AbstractConfiguration &, + const std::string &, Block &, Context &) + { throw Exception("MongoDB dictionary source is not supported in this build", 0); } + BlockInputStreamPtr loadAll() override { throw Exception("MongoDB not supported", 0); } + bool supportsSelectiveLoad() const override { return false; } + BlockInputStreamPtr loadIds(const std::vector &) override { throw Exception("MongoDB not supported", 0); } + BlockInputStreamPtr loadKeys(const ConstColumnPlainPtrs &, const std::vector &) override { throw Exception("MongoDB not supported", 0); } + bool isModified() const override { return false; } + DictionarySourcePtr clone() const override { throw Exception("MongoDB not supported", 0); } + std::string toString() const override { return "MongoDB(disabled)"; } +}; +} +EOF + +# -- root CMakeLists: add the quicklz/re2_st include dirs and, on the C++ flags, +# -fpermissive plus the force-included cmath shim (anchored on the donor's +# stable libcityhash include line / -std=gnu++1y flag) -- +sed -i 's#include_directories (${METRICA_SOURCE_DIR}/contrib/libcityhash/)#include_directories (${METRICA_SOURCE_DIR}/contrib/quicklz-stub/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/re2_st_gen/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/libcityhash/)#' CMakeLists.txt +sed -i 's#-std=gnu++1y#-std=gnu++1y -fpermissive -include ${METRICA_SOURCE_DIR}/contrib/compat/cmath_compat.h#' CMakeLists.txt + +echo "reconstruct.sh: build system reconciled" diff --git a/versions/cloud-init.sh.in b/versions/cloud-init.sh.in index 591b189467..d091b30eb8 100644 --- a/versions/cloud-init.sh.in +++ b/versions/cloud-init.sh.in @@ -12,7 +12,9 @@ export HOME="${HOME:-/root}" export DEBIAN_FRONTEND=noninteractive apt-get update -y -apt-get install -y docker.io git wget curl jq zstd pv aria2 +# docker-buildx: run-version.sh builds unpublished (clickhouse-built:*) versions +# from source with `docker buildx` (the legacy builder hangs on recent engines). +apt-get install -y docker.io docker-buildx git wget curl jq zstd pv aria2 systemctl enable --now docker git clone --depth 1 'https://github.com/@repo@.git' --branch '@branch@' ClickBench @@ -64,10 +66,9 @@ else xargs -P 8 -I{} wget --continue --progress=dot:giga -P "${DATADIR}" "${BUCKET}/{}" fi -# Versions with no published Docker image are built from source on this VM. -if [[ "${IMAGE}" == clickhouse-built:* ]]; then - bash build-from-source/build.sh "${VERSION}" "${TAG}" "${GCC}" 2>&1 | tail -n 50 -fi +# Versions with no published Docker image (clickhouse-built:*) are built from +# source on the fly by run-version.sh itself (it looks up the recipe in +# build-from-source/versions.txt or monthly.tsv), so nothing to do here. echo "=== benchmarking ${VERSION} (image ${IMAGE}, datasets: ${DATASETS}) ===" timeout @timeout@ ./run-version.sh "${VERSION}" "${IMAGE}" all 2>&1 | tee -a log diff --git a/versions/prepare-data/ontime.sh b/versions/prepare-data/ontime.sh index 8de1f59984..fc1a8b3c17 100755 --- a/versions/prepare-data/ontime.sh +++ b/versions/prepare-data/ontime.sh @@ -5,6 +5,11 @@ # read the full schema (LowCardinality(String) -> String, the only oldest- # incompatible type) and project just those. FlightDate (a real Date) serves the # legacy MergeTree engine, so no synth_date is needed. +# +# The output is sorted by (Year, Month, FlightDate, ...): the data spans +# 1987-2024 (~450 monthly partitions), so an unsorted INSERT block would touch +# >100 partitions at once and hit max_partitions_per_insert_block. Sorting makes +# each block date-contiguous (a few months), so it loads on every version. set -euo pipefail HERE="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" @@ -16,7 +21,8 @@ command -v "${CLICKHOUSE}" >/dev/null 2>&1 || CLICKHOUSE=clickhouse FULL_STRUCT="Year UInt16, Quarter UInt8, Month UInt8, DayofMonth UInt8, DayOfWeek UInt8, FlightDate Date, Reporting_Airline String, DOT_ID_Reporting_Airline Int32, IATA_CODE_Reporting_Airline String, Tail_Number String, Flight_Number_Reporting_Airline String, OriginAirportID Int32, OriginAirportSeqID Int32, OriginCityMarketID Int32, Origin FixedString(5), OriginCityName String, OriginState FixedString(2), OriginStateFips FixedString(2), OriginStateName String, OriginWac Int32, DestAirportID Int32, DestAirportSeqID Int32, DestCityMarketID Int32, Dest FixedString(5), DestCityName String, DestState FixedString(2), DestStateFips FixedString(2), DestStateName String, DestWac Int32, CRSDepTime Int32, DepTime Int32, DepDelay Int32, DepDelayMinutes Int32, DepDel15 Int32, DepartureDelayGroups String, DepTimeBlk String, TaxiOut Int32, WheelsOff String, WheelsOn String, TaxiIn Int32, CRSArrTime Int32, ArrTime Int32, ArrDelay Int32, ArrDelayMinutes Int32, ArrDel15 Int32, ArrivalDelayGroups String, ArrTimeBlk String, Cancelled Int8, CancellationCode FixedString(1), Diverted Int8, CRSElapsedTime Int32, ActualElapsedTime Int32, AirTime Int32, Flights Int32, Distance Int32, DistanceGroup Int8, CarrierDelay Int32, WeatherDelay Int32, NASDelay Int32, SecurityDelay Int32, LateAircraftDelay Int32, FirstDepTime Int16, TotalAddGTime Int16, LongestAddGTime Int16, DivAirportLandings Int8, DivReachedDest Int8, DivActualElapsedTime Int16, DivArrDelay Int16, DivDistance Int16, Div1Airport String, Div1AirportID Int32, Div1AirportSeqID Int32, Div1WheelsOn Int16, Div1TotalGTime Int16, Div1LongestGTime Int16, Div1WheelsOff Int16, Div1TailNum String, Div2Airport String, Div2AirportID Int32, Div2AirportSeqID Int32, Div2WheelsOn Int16, Div2TotalGTime Int16, Div2LongestGTime Int16, Div2WheelsOff Int16, Div2TailNum String, Div3Airport String, Div3AirportID Int32, Div3AirportSeqID Int32, Div3WheelsOn Int16, Div3TotalGTime Int16, Div3LongestGTime Int16, Div3WheelsOff Int16, Div3TailNum String, Div4Airport String, Div4AirportID Int32, Div4AirportSeqID Int32, Div4WheelsOn Int16, Div4TotalGTime Int16, Div4LongestGTime Int16, Div4WheelsOff Int16, Div4TailNum String, Div5Airport String, Div5AirportID Int32, Div5AirportSeqID Int32, Div5WheelsOn Int16, Div5TotalGTime Int16, Div5LongestGTime Int16, Div5WheelsOff Int16, Div5TailNum String" echo "ontime: building from ${SRC} -> ${OUT}" -"${CLICKHOUSE}" local --max_memory_usage 0 --input_format_csv_empty_as_default 1 \ - --query "SELECT Year, Month, DayOfWeek, FlightDate, IATA_CODE_Reporting_Airline, Origin, OriginCityName, OriginState, DestCityName, DestState, DepDelay, ArrDelayMinutes FROM s3('${SRC}', 'CSVWithNames', '${FULL_STRUCT}') FORMAT Native" \ +"${CLICKHOUSE}" local --max_memory_usage 0 --max_bytes_before_external_sort 30000000000 \ + --input_format_csv_empty_as_default 1 \ + --query "SELECT Year, Month, DayOfWeek, FlightDate, IATA_CODE_Reporting_Airline, Origin, OriginCityName, OriginState, DestCityName, DestState, DepDelay, ArrDelayMinutes FROM s3('${SRC}', 'CSVWithNames', '${FULL_STRUCT}') ORDER BY Year, Month, FlightDate, IATA_CODE_Reporting_Airline FORMAT Native" \ | zstd -q -6 -T0 -c > "${OUT}" ls -l "${OUT}" diff --git a/versions/prepare-data/taxi.sh b/versions/prepare-data/taxi.sh index bb07ba4be4..71c451cbb9 100755 --- a/versions/prepare-data/taxi.sh +++ b/versions/prepare-data/taxi.sh @@ -31,6 +31,6 @@ SELECT toUInt8OrZero(c11) AS passenger_count, toFloat64OrZero(c12) AS trip_distance, toFloat32OrZero(c20) AS total_amount -FROM s3('${SRC}', 'CSV', '${STRUCT}') +FROM s3('${SRC}', 'CSV', '${STRUCT}') ORDER BY pickup_date FORMAT Native" | zstd -q -6 -T0 -c > "${OUT}" ls -l "${OUT}" diff --git a/versions/run-version.sh b/versions/run-version.sh index b329b3f2f4..9f898d2d98 100755 --- a/versions/run-version.sh +++ b/versions/run-version.sh @@ -71,8 +71,12 @@ CLIENT_MODE="" # set by start_server: exec | sidecar # client can't write its history file. TZ=UTC + the zoneinfo mount: some old # client images ship no tzdata and otherwise fail at startup with "Could not # determine local time zone" (before any query runs). -exec_client() { sudo docker exec -i -e HOME=/tmp -e TZ=UTC "${CONTAINER}" clickhouse client "$@"; } -sidecar_client() { sudo docker run --rm -i -e HOME=/tmp -e TZ=UTC \ +# CH_TIMEOUT (seconds), when set, wraps the client in `timeout` so a hung/slow +# query is killed after that long (the connection drop makes the server cancel +# it). Version-agnostic — no reliance on server-side settings that old builds +# may lack. Left empty for load/probe/version calls. +exec_client() { sudo ${CH_TIMEOUT:+timeout ${CH_TIMEOUT}} docker exec -i -e HOME=/tmp -e TZ=UTC "${CONTAINER}" clickhouse client "$@"; } +sidecar_client() { sudo ${CH_TIMEOUT:+timeout ${CH_TIMEOUT}} docker run --rm -i -e HOME=/tmp -e TZ=UTC \ -v /usr/share/zoneinfo:/usr/share/zoneinfo:ro \ --network "container:${CONTAINER}" "${CLIENT_IMAGE}" "$@"; } client() { @@ -82,6 +86,33 @@ client() { esac } +# Versions with no published image (clickhouse-built:*) are compiled from source +# on the fly here, so the benchmark is self-contained (nothing is pulled from a +# registry). The build recipe is looked up by version: tagged / bare-number +# releases from build-from-source/versions.txt (Dockerfile.ubuntu1604), and the +# untagged monthly snapshots from build-from-source/monthly.tsv (reconstructed +# via Dockerfile.reconstruct). +ensure_built_image() { + sudo docker image inspect "${IMAGE}" >/dev/null 2>&1 && return 0 + local bfs="${HERE}/build-from-source" rec tag gcc sha + rec="$(awk -F'\t' -v v="${VERSION}" '$1==v{print; exit}' "${bfs}/versions.txt" 2>/dev/null)" + if [ -n "${rec}" ]; then + tag="$(cut -f2 <<<"${rec}")"; gcc="$(cut -f4 <<<"${rec}")" + echo "building ${IMAGE} from source (tag ${tag:-v${VERSION}-stable}, gcc-${gcc:-5})" >&2 + bash "${bfs}/build.sh" "${VERSION}" "${tag:-v${VERSION}-stable}" "${gcc:-5}" >&2 + return $? + fi + sha="$(awk -F'\t' -v v="${VERSION}" '$1==v{print $2; exit}' "${bfs}/monthly.tsv" 2>/dev/null)" + if [ -n "${sha}" ]; then + echo "reconstructing ${IMAGE} from source (commit ${sha})" >&2 + sudo docker buildx build --progress=plain --load --build-arg "TAG=${sha}" \ + -t "${IMAGE}" -f "${bfs}/Dockerfile.reconstruct" "${bfs}" >&2 + return $? + fi + echo "no build recipe for ${VERSION} in versions.txt or monthly.tsv" >&2 + return 1 +} + start_server() { cleanup if [ "${IMAGE}" = "package" ]; then @@ -101,7 +132,11 @@ start_server() { clickhouse-server --daemon --config /etc/clickhouse-server/config.xml" >&2 else echo "starting ${VERSION} from image ${IMAGE}" >&2 - sudo docker pull "${IMAGE}" >/dev/null 2>&1 + if [[ "${IMAGE}" == clickhouse-built:* ]]; then + ensure_built_image || { echo "failed to build ${IMAGE}" >&2; return 1; } + else + sudo docker pull "${IMAGE}" >/dev/null 2>&1 + fi # Mount an IPv4 listen override: old images default to listening on :: # (IPv6) and crash on boot when the host has IPv6 disabled. sudo docker run -d --name "${CONTAINER}" --ulimit nofile=262144:262144 \ @@ -124,40 +159,51 @@ start_server() { return 1 } -# Load every dataset; tables that fail to create/load are left absent so their -# queries report null. +# Load one dataset: create its database and (create+load) each of its tables. +# Tables that fail to create/load are left absent so their queries report null. +load_one_dataset() { + local ds="$1" pair table file ddl t0 reader + # Each dataset lives in its own database so same-named tables (e.g. TPC-H + # and TPC-DS `customer`) don't clash. + client --query "CREATE DATABASE IF NOT EXISTS ${ds}" /dev/null + for pair in ${TABLES[$ds]}; do + table="${pair%%:*}"; file="${pair##*:}" + [ -f "${DATA}/${file}" ] || { echo "SKIP ${ds}.${table}: ${file} not present"; continue; } + ddl="$("${HERE}/create/create.sh" "${VERSION}" "${ds}" "${table}")" + echo "=== CREATE ${ds}.${table} on ${VERSION} ===" + echo "${ddl}" + if ! printf '%s' "${ddl}" | client --database "${ds}" --multiquery; then + echo "CREATE ${ds}.${table} FAILED on ${VERSION}"; continue + fi + echo "=== INSERT INTO ${ds}.${table} FORMAT Native <- ${file} ($(du -h "${DATA}/${file}" | cut -f1)) ===" + # Stream the compressed file through pv (progress %/rate/ETA once a + # second, based on the known file size) -> zstd -dc -> a plain Native + # INSERT, so the ancient clickhouse-client never sees compression. + if command -v pv >/dev/null 2>&1; then + reader=(pv -f -i 1 -N "${ds}.${table}" -- "${DATA}/${file}") + else + reader=(cat -- "${DATA}/${file}") + fi + t0=${SECONDS} + if "${reader[@]}" | zstd -dc | client --database "${ds}" --query "INSERT INTO ${table} FORMAT Native"; then + echo "loaded ${ds}.${table}: $(client --database "${ds}" --query "SELECT count() FROM ${table}" 2>/dev/null) rows in $((SECONDS - t0))s" + else + echo "LOAD ${ds}.${table} FAILED on ${VERSION}" + fi + done +} + +# Load all datasets in parallel: each dataset (database + its tables) loads in +# its own background job, so the many INSERTs run concurrently against the +# server. Per-table pv progress lines interleave but stay labelled ds.table. load_data() { - local ds pair table file ddl t0 reader + local ds pids=() for ds in ${LOAD_DATASETS}; do - # Each dataset lives in its own database so same-named tables (e.g. - # TPC-H and TPC-DS `customer`) don't clash. - client --query "CREATE DATABASE IF NOT EXISTS ${ds}" /dev/null - for pair in ${TABLES[$ds]}; do - table="${pair%%:*}"; file="${pair##*:}" - [ -f "${DATA}/${file}" ] || { echo "SKIP ${ds}.${table}: ${file} not present"; continue; } - ddl="$("${HERE}/create/create.sh" "${VERSION}" "${ds}" "${table}")" - echo "=== CREATE ${ds}.${table} on ${VERSION} ===" - echo "${ddl}" - if ! printf '%s' "${ddl}" | client --database "${ds}" --multiquery; then - echo "CREATE ${ds}.${table} FAILED on ${VERSION}"; continue - fi - echo "=== INSERT INTO ${ds}.${table} FORMAT Native <- ${file} ($(du -h "${DATA}/${file}" | cut -f1)) ===" - # Stream the compressed file through pv (progress %/rate/ETA once a - # second, based on the known file size) -> zstd -dc -> a plain Native - # INSERT, so the ancient clickhouse-client never sees compression. - if command -v pv >/dev/null 2>&1; then - reader=(pv -f -i 1 -N "${table}" -- "${DATA}/${file}") - else - reader=(cat -- "${DATA}/${file}") - fi - t0=${SECONDS} - if "${reader[@]}" | zstd -dc | client --database "${ds}" --query "INSERT INTO ${table} FORMAT Native"; then - echo "loaded ${ds}.${table}: $(client --database "${ds}" --query "SELECT count() FROM ${table}" 2>/dev/null) rows in $((SECONDS - t0))s" - else - echo "LOAD ${ds}.${table} FAILED on ${VERSION}" - fi - done + load_one_dataset "${ds}" & + pids+=("$!") done + wait "${pids[@]}" + echo "=== all dataset loads finished ===" } drop_caches() { sync; echo 3 | sudo tee /proc/sys/vm/drop_caches >/dev/null 2>&1; } @@ -202,22 +248,35 @@ report_sizes() { } # Run one query TRIES times, print a JSON array "[t1, ..., tN]" (null on error). -# If the server dies mid-query (e.g. OOM-killed), revive it and retry up to -# CRASH_RETRIES times so one heavy query doesn't null out the whole version. +# The remaining tries are skipped (recorded null) once a try either: +# * exceeds QUERY_TIMEOUT (default 100s) — no point re-timing a too-slow query, or +# * crashes the server (e.g. OOM kill) — the server is revived so later queries +# still run, but this query's remaining tries are abandoned. +# A plain error while the server stays up (e.g. a feature an old version lacks) +# just records null for that try and keeps going (every try will null anyway). run_query() { - local query="$1" i res crash out="[" + local query="$1" i res rc out="[" skip_rest=0 for i in $(seq 1 "${TRIES}"); do - crash=0 - while :; do + if [ "${skip_rest}" = 1 ]; then + res="null" # an earlier try timed out or crashed; skip the rest + else + CH_TIMEOUT="${QUERY_TIMEOUT:-100}" res=$(printf '%s' "${query}" | client --database "${QDB:-default}" --time --max_memory_usage="${MEM}" --format=Null 2>&1) - [[ "${res}" =~ ^[0-9]+\.[0-9]+$ ]] && break - if ! server_alive && [ "${crash}" -lt "${CRASH_RETRIES:-2}" ]; then - crash=$((crash + 1)) - echo "${VERSION}: server died mid-query (likely OOM); reviving (retry ${crash})" >&2 - revive_server && continue + rc=$? + CH_TIMEOUT="" + if [ "${rc}" = 124 ] || [ "${rc}" = 137 ]; then # `timeout` killed it + echo "${VERSION}: query exceeded ${QUERY_TIMEOUT:-100}s; recording null and skipping remaining tries" >&2 + skip_rest=1; res="null" + elif [[ "${res}" =~ ^[0-9]+\.[0-9]+$ ]]; then + : # good timing + elif ! server_alive; then + echo "${VERSION}: server died mid-query (likely OOM); reviving and skipping remaining tries" >&2 + revive_server || true # restore it for the following queries + skip_rest=1; res="null" + else + res="null" # query errored but server is up fi - res="null"; break - done + fi out+="${res}" [ "${i}" -ne "${TRIES}" ] && out+=", " done From 84a268313b3819d3a45af4f412fcf36046540348 Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Wed, 1 Jul 2026 04:34:44 +0000 Subject: [PATCH 023/120] versions: double default volume; extend reconstruct.sh for pre-2016-02 builds MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit - run-benchmark.sh: default volume 500 -> 1000 GB; parallel loading of all datasets peaks disk usage above the on-disk total (NOT_ENOUGH_SPACE otherwise). - reconstruct.sh: build the pre-2016-02 era with the old libstdc++ ABI (_GLIBCXX_USE_CXX11_ABI=0) — that era used the refcounted (COW) std::string, which the struct sizing assumes (Field's DBMS_TOTAL_FIELD_SIZE=32). Also: generic prune of donor-listed sources absent in an older target (encoding-safe), disable utils/, strip add_subdirectory(private), vendor Poco/Ext/ScopedTry.h. Co-Authored-By: Claude Opus 4.8 --- versions/build-from-source/reconstruct.sh | 84 ++++++++++++++++++----- versions/run-benchmark.sh | 2 +- 2 files changed, 69 insertions(+), 17 deletions(-) diff --git a/versions/build-from-source/reconstruct.sh b/versions/build-from-source/reconstruct.sh index bb7ea2e3ba..8a9e42a25c 100755 --- a/versions/build-from-source/reconstruct.sh +++ b/versions/build-from-source/reconstruct.sh @@ -36,6 +36,15 @@ sed -i 's/INCLUDE(add.test.cmake)//' CMakeLists.txt || true # open-sourced (appears in the 2016-06+ trees). -- find /src -name CMakeLists.txt | xargs -r sed -i '/add_subdirectory *( *private *)/d' +# -- drop the utils/ subdirectory: standalone tools we don't need, some of which +# reference sources absent in older snapshots (a fatal configure error). -- +sed -i '/add_subdirectory *( *utils *)/d' CMakeLists.txt || true + +# -- Old libstdc++ ABI: this era used the refcounted (COW) std::string (8 bytes), +# which the code's sizing assumes (e.g. Field's DBMS_TOTAL_FIELD_SIZE=32). +# Build with _GLIBCXX_USE_CXX11_ABI=0 to get that string back (see the CXX +# flags injection below), rather than resizing structs for the new 32-byte ABI. -- + # -- glob the two small libraries so renamed sources are still picked up -- cat > libs/libdaemon/CMakeLists.txt <<'EOF' file(GLOB daemon_src src/*.cpp) @@ -44,24 +53,42 @@ target_link_libraries(daemon dbms) EOF python3 - <<'PY' -import re, os -# libcommon: replace the explicit source list with a glob -f = "libs/libcommon/CMakeLists.txt"; s = open(f).read() +import re, os, glob +# CMakeLists in this era carry UTF-8 (Russian) comments; the container's Python +# may default to ASCII, so read/write with an explicit codec that round-trips +# arbitrary bytes. +def rd(p): return open(p, encoding="utf-8", errors="surrogateescape").read() +def wr(p, s): open(p, "w", encoding="utf-8", errors="surrogateescape").write(s) + +# libcommon: replace the explicit source list with a glob (handles renames like +# Revision.cpp -> ClickHouseRevision.cpp where the target has a file the donor +# build files don't list). +f = "libs/libcommon/CMakeLists.txt"; s = rd(f) s = re.sub(r"add_library\s*\(\s*common.*?\)", "file(GLOB common_src src/*.cpp)\nadd_library(common ${common_src})", s, count=1, flags=re.S) -open(f, "w").write(s) - -# dbms top-level add_library lists many headers/sources; drop any that this -# snapshot doesn't have, and drop the (unvendored) mongoclient link name. -f = "dbms/CMakeLists.txt"; s = open(f).read() -m = re.search(r"add_library\s*\(\s*dbms(.*?)\)", s, flags=re.S) -if m: - kept = [t for t in m.group(1).split() - if not t.endswith((".h", ".cpp", ".inc")) or os.path.exists("dbms/" + t)] - s = s[:m.start()] + "add_library (dbms\n\t" + "\n\t".join(kept) + ")" + s[m.end():] -s = re.sub(r"\bmongoclient\b", "", s) -open(f, "w").write(s) +wr(f, s) + +# Drop the (never-vendored) mongoclient link name wherever it appears. +f = "dbms/CMakeLists.txt"; wr(f, re.sub(r"\bmongoclient\b", "", rd(f))) + +# Generic prune: the donor build files (2016-03) list sources that an *older* +# target snapshot doesn't have yet (files added later). For every add_library / +# add_executable in every CMakeLists, drop any listed source file that doesn't +# exist relative to that CMakeLists's directory — otherwise cmake configure +# fails with "Cannot find source file". +SRC_RE = re.compile(r".+\.(cpp|cc|cxx|c|h|hpp|inc)$", re.I) +def prune(cml): + d = os.path.dirname(cml); s = rd(cml) + def fix(m): + head, body = m.group(1), m.group(2) + kept = [t for t in body.split() + if not SRC_RE.match(t) or os.path.exists(os.path.join(d, t))] + return head + " " + " ".join(kept) + ")" + s2 = re.sub(r"(add_(?:library|executable)\s*\(\s*[^\s)]+)(.*?)\)", fix, s, flags=re.S|re.I) + if s2 != s: wr(cml, s2) +for cml in glob.glob("**/CMakeLists.txt", recursive=True): + prune(cml) PY # -- QuickLZ compile/link stub (dead code path: our data is LZ4/ZSTD) -- @@ -82,6 +109,31 @@ EOF cp contrib/quicklz-stub/quicklz/quicklz_level1.h contrib/quicklz-stub/quicklz/quicklz_level2.h cp contrib/quicklz-stub/quicklz/quicklz_level1.h contrib/quicklz-stub/quicklz/quicklz_level3.h +# -- vendor Poco/Ext/ScopedTry.h: a Poco extension (scoped try-lock) the early +# trees use but that isn't in the donor's Poco. Placed on Poco's include path. -- +mkdir -p contrib/libpoco/Foundation/include/Poco/Ext +cat > contrib/libpoco/Foundation/include/Poco/Ext/ScopedTry.h <<'EOF' +#pragma once +// Scoped try-lock (default-construct, then lock(&mutex) attempts tryLock and +// returns success; the mutex is released on scope exit if held). Reconstructed +// to match the early-ClickHouse usage in MergeTreeData::grabOldParts. +namespace Poco +{ +template +class ScopedTry +{ +public: + ScopedTry() : _mutex(0) {} + ~ScopedTry() { if (_mutex) _mutex->unlock(); } + bool lock(M * mutex) { if (mutex->tryLock()) { _mutex = mutex; return true; } return false; } +private: + M * _mutex; + ScopedTry(const ScopedTry &); + ScopedTry & operator=(const ScopedTry &); +}; +} +EOF + # -- generate the re2_st (single-threaded re2) headers into a stable include dir -- mkdir -p contrib/re2_st_gen ( cd contrib/re2_st_gen && sh /src/contrib/libre2/create_st_headers.sh /src/contrib/libre2 . ) @@ -136,6 +188,6 @@ EOF # -fpermissive plus the force-included cmath shim (anchored on the donor's # stable libcityhash include line / -std=gnu++1y flag) -- sed -i 's#include_directories (${METRICA_SOURCE_DIR}/contrib/libcityhash/)#include_directories (${METRICA_SOURCE_DIR}/contrib/quicklz-stub/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/re2_st_gen/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/libcityhash/)#' CMakeLists.txt -sed -i 's#-std=gnu++1y#-std=gnu++1y -fpermissive -include ${METRICA_SOURCE_DIR}/contrib/compat/cmath_compat.h#' CMakeLists.txt +sed -i 's#-std=gnu++1y#-std=gnu++1y -fpermissive -D_GLIBCXX_USE_CXX11_ABI=0 -include ${METRICA_SOURCE_DIR}/contrib/compat/cmath_compat.h#' CMakeLists.txt echo "reconstruct.sh: build system reconciled" diff --git a/versions/run-benchmark.sh b/versions/run-benchmark.sh index f31b15d6b7..2cadd343fd 100755 --- a/versions/run-benchmark.sh +++ b/versions/run-benchmark.sh @@ -21,7 +21,7 @@ branch="${branch:=main}" datasets="${datasets:=hits ssb mgbench tpch tpcds coffeeshop ontime uk job taxi}" # each loads into its own database tries="${tries:=6}" # 1 cold + 5 hot runs timeout="${timeout:-18000}" # load + (optional source build) + queries -volume="${volume:-500}" # GB; ample for all datasets (all now < 10 GB compressed) +volume="${volume:-1000}" # GB; headroom for loading all datasets in parallel (peak usage is higher than the on-disk total) # gp3 root volume with provisioned throughput/IOPS (cold-cache query reads and # the ingest are disk-bound). gp3 maxes at 1000 MB/s / 16000 IOPS per volume; # the instance's own EBS bandwidth is the real ceiling. From 46fbce0ff8918f78b68f7e906ac457c823a48881 Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Wed, 1 Jul 2026 04:38:49 +0000 Subject: [PATCH 024/120] versions: drop the table if its INSERT fails An aborted/incomplete INSERT (crash, OOM, disk full, interrupted stream) can leave a partially-loaded table. Drop it so the dataset's queries report null instead of timing against incomplete data. Co-Authored-By: Claude Opus 4.8 --- versions/run-version.sh | 6 +++++- 1 file changed, 5 insertions(+), 1 deletion(-) diff --git a/versions/run-version.sh b/versions/run-version.sh index 9f898d2d98..8aaa2b678e 100755 --- a/versions/run-version.sh +++ b/versions/run-version.sh @@ -188,7 +188,11 @@ load_one_dataset() { if "${reader[@]}" | zstd -dc | client --database "${ds}" --query "INSERT INTO ${table} FORMAT Native"; then echo "loaded ${ds}.${table}: $(client --database "${ds}" --query "SELECT count() FROM ${table}" 2>/dev/null) rows in $((SECONDS - t0))s" else - echo "LOAD ${ds}.${table} FAILED on ${VERSION}" + # An aborted INSERT (crash, OOM, disk full, interrupted stream) can leave + # a partially-loaded table. Drop it so its queries report null rather than + # timing against incomplete data. + echo "LOAD ${ds}.${table} FAILED on ${VERSION}; dropping the incomplete table" + client --database "${ds}" --query "DROP TABLE IF EXISTS ${table}" /dev/null fi done } From 1d3f4f36fd7feccf9e5ca0bbb26db08267b0ab7a Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Wed, 1 Jul 2026 05:38:44 +0000 Subject: [PATCH 025/120] versions: record per-dataset load_time and data_size in the result JSON MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Add two subobjects to results/.json: - "load_time": {dataset: sum of its tables' load times in seconds} — accumulated per table during the (parallel, possibly separate) load phase into a stats file and summed per dataset at bench time. - "data_size": {dataset: on-disk bytes} — per-database sum(bytes_on_disk) from system.parts (each dataset is its own database), with a data-directory du fallback for old versions lacking that column. Co-Authored-By: Claude Opus 4.8 --- versions/run-version.sh | 34 ++++++++++++++++++++++++++++++++++ 1 file changed, 34 insertions(+) diff --git a/versions/run-version.sh b/versions/run-version.sh index 8aaa2b678e..e91e86be2e 100755 --- a/versions/run-version.sh +++ b/versions/run-version.sh @@ -37,6 +37,10 @@ PHASE="${3:-all}" CONTAINER="chver_${VERSION//[^0-9A-Za-z]/_}" OUT="${HERE}/results/${VERSION}.json" +# Per-table load timings, written during the load phase and read by the bench +# phase (which may be a separate invocation) to build the result's load_time. +LOAD_STATS="${HERE}/logs/${VERSION}.loadtimes.tsv" +mkdir -p "${HERE}/logs" # Datasets => "table:file" pairs to create+load. declare -A TABLES=( @@ -186,6 +190,9 @@ load_one_dataset() { fi t0=${SECONDS} if "${reader[@]}" | zstd -dc | client --database "${ds}" --query "INSERT INTO ${table} FORMAT Native"; then + # Record this table's load time (small line -> atomic append, safe + # across the parallel per-dataset jobs); summed per dataset at bench. + printf '%s\t%s\n' "${ds}" "$((SECONDS - t0))" >> "${LOAD_STATS}" echo "loaded ${ds}.${table}: $(client --database "${ds}" --query "SELECT count() FROM ${table}" 2>/dev/null) rows in $((SECONDS - t0))s" else # An aborted INSERT (crash, OOM, disk full, interrupted stream) can leave @@ -202,6 +209,7 @@ load_one_dataset() { # server. Per-table pv progress lines interleave but stay labelled ds.table. load_data() { local ds pids=() + : > "${LOAD_STATS}" # fresh per run; per-table load times accumulate here for ds in ${LOAD_DATASETS}; do load_one_dataset "${ds}" & pids+=("$!") @@ -301,6 +309,30 @@ detect_client() { return 1 } +# {"dataset": sum_of_table_load_seconds, ...} from the load phase (LOAD_STATS). +emit_load_time_json() { + if [ -s "${LOAD_STATS}" ]; then + awk -F'\t' '{s[$1]+=$2} END{printf "{"; for(d in s){printf "%s\"%s\": %s",(n++?", ":""),d,s[d]}; printf "}"}' "${LOAD_STATS}" + else + printf '{}' + fi +} + +# {"dataset": on_disk_bytes, ...}: per-database sum of bytes_on_disk (each dataset +# is its own database), or a data-directory measurement for versions without it. +emit_data_size_json() { + local out + out=$(client --query "SELECT database, sum(bytes_on_disk) FROM system.parts WHERE database NOT IN ('system', 'information_schema', 'INFORMATION_SCHEMA') GROUP BY database FORMAT TabSeparated" /dev/null) + if [ -z "${out}" ]; then + out=$(sudo docker exec "${CONTAINER}" sh -c ' + base=/var/lib/clickhouse; [ -d "$base/data" ] || base=/opt/clickhouse + for d in "$base"/data/*/; do [ -d "$d" ] || continue; db=$(basename "$d"); + [ "$db" = system ] && continue + printf "%s\t%s\n" "$db" "$(du -sLb "$d" 2>/dev/null | cut -f1)"; done' 2>/dev/null) + fi + printf '%s' "${out}" | awk -F'\t' 'BEGIN{printf "{"} NF>=2 && $2!=""{printf "%s\"%s\": %s",(n++?", ":""),$1,$2} END{printf "}"}' +} + # Time every query and write results/.json. run_benchmark() { local ACTUAL ds query FIRST=1 qnum=0 row QDB @@ -310,6 +342,8 @@ run_benchmark() { echo '{' echo " \"version\": \"${VERSION}\"," echo " \"actual_version\": \"${ACTUAL}\"," + echo " \"load_time\": $(emit_load_time_json)," + echo " \"data_size\": $(emit_data_size_json)," echo ' "result":' echo ' [' for ds in ${QUERY_ORDER}; do From 35468e268864f060640e060fbe240b758ea345da Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Wed, 1 Jul 2026 06:40:44 +0000 Subject: [PATCH 026/120] versions: reconstruct pre-2016-02 snapshots (Ubuntu 14.04, old ABI) 2016-01 and older predate a big refactor and were built on trusty/gcc-5 with the old libstdc++ ABI (refcounted std::string). Reconstruct.sh + Dockerfile.reconstruct now build them end-to-end (verified: 2016-01 builds server+client and boots, SELECT version() -> 0.0.53400): - Base is now ubuntu:14.04 so gcc-5 defaults to the old ABI and the system boost is old-ABI too (16.04's new-ABI boost broke the client's boost::program_options). - Vendor the never-public Yandex libs from the donor: statdaemons embedded dictionaries (via DB/Dictionaries/Embedded) and the daemon base (a thin BaseDaemon compat carrying the used API + --config-file handling, avoiding the donor's newer zkutil/graphite deps); stub statdaemons/Interests.h. - Glob the whole dbms library (excluding the Server/Client executables + ODBC driver) so renamed/moved sources compile regardless of the donor's file lists. - Force-include / (not transitively available on this toolchain); build re2 then the server and client with single-target makes (avoid a recursive-make race on shared static libs); os.walk for Python 3.4. Co-Authored-By: Claude Opus 4.8 --- .../build-from-source/Dockerfile.reconstruct | 31 +++-- versions/build-from-source/reconstruct.sh | 126 ++++++++++++++++-- 2 files changed, 131 insertions(+), 26 deletions(-) diff --git a/versions/build-from-source/Dockerfile.reconstruct b/versions/build-from-source/Dockerfile.reconstruct index e1d82b3f5f..c6e7d0143d 100644 --- a/versions/build-from-source/Dockerfile.reconstruct +++ b/versions/build-from-source/Dockerfile.reconstruct @@ -12,22 +12,27 @@ # # The result behaves like the official server images (see Dockerfile.ubuntu1604). -FROM ubuntu:16.04 +# Ubuntu 14.04 is the era-correct base for these pre-2016-03 snapshots: gcc-5 +# (from the toolchain PPA) defaults to the old libstdc++ ABI here, and trusty's +# system boost is old-ABI too — so both clickhouse-server AND clickhouse-client +# link (16.04's new-ABI boost breaks the client's boost::program_options). +FROM ubuntu:14.04 ARG GCC=5 +# Trusty is still on archive.ubuntu.com (in ESM), so keep the base sources; its +# Release is expired (Check-Valid-Until=false) and gcc-5 comes from the +# ubuntu-toolchain-r PPA ([trusted=yes] skips the GPG dance). liblz4/libzstd/ +# double-conversion come from the vendored contrib/, not the (older) system. RUN set -eu; \ - if [ "${GCC}" != "5" ]; then \ - apt-get update && apt-get install -y --no-install-recommends software-properties-common && \ - add-apt-repository -y ppa:ubuntu-toolchain-r/test; \ - fi; \ - apt-get update && apt-get install -y --no-install-recommends \ + echo 'deb [trusted=yes] http://ppa.launchpad.net/ubuntu-toolchain-r/test/ubuntu trusty main' > /etc/apt/sources.list.d/toolchain.list; \ + apt-get -o Acquire::Check-Valid-Until=false update; \ + apt-get install -y --no-install-recommends --allow-unauthenticated \ git ca-certificates cmake make pkg-config bash python3 "gcc-${GCC}" "g++-${GCC}" \ libicu-dev libreadline-dev libssl-dev unixodbc-dev libglib2.0-dev \ libboost-dev libboost-thread-dev libboost-program-options-dev \ libboost-system-dev libboost-regex-dev libboost-filesystem-dev \ - zlib1g-dev liblz4-dev libzstd-dev libdouble-conversion-dev \ - libsparsehash-dev libmysqlclient-dev libzookeeper-mt-dev \ - libgoogle-perftools-dev tzdata \ + zlib1g-dev liblz4-dev libsparsehash-dev libmysqlclient-dev \ + libzookeeper-mt-dev libgoogle-perftools-dev tzdata \ && rm -rf /var/lib/apt/lists/* ENV CC=gcc-${GCC} CXX=g++-${GCC} @@ -42,7 +47,9 @@ RUN git init -q /src && cd /src \ && git fetch -q --depth 1 origin "${TAG}" && git checkout -q --detach FETCH_HEAD \ && git fetch -q --depth 1 origin "${DONOR}" \ && git checkout FETCH_HEAD -- contrib \ - && git checkout FETCH_HEAD -- $(git ls-tree -r --name-only FETCH_HEAD | grep -E 'CMakeLists.txt$|\.cmake$') + && git checkout FETCH_HEAD -- $(git ls-tree -r --name-only FETCH_HEAD | grep -E 'CMakeLists.txt$|\.cmake$') \ + && (git checkout FETCH_HEAD -- dbms/include/DB/Dictionaries/Embedded 2>/dev/null || true) \ + && (git checkout FETCH_HEAD -- libs/libdaemon 2>/dev/null || true) # Reconcile the donor build system with the older source (globs, stubs, shims). COPY reconstruct.sh /reconstruct.sh @@ -55,12 +62,12 @@ ARG REVISION=53400 WORKDIR /src/build RUN cmake .. -DCMAKE_BUILD_TYPE=Release -DTESTS=NO \ -DCMAKE_C_COMPILER="gcc-${GCC}" -DCMAKE_CXX_COMPILER="g++-${GCC}" \ - && make -j"$(nproc)" re2 re2_st \ + && make -j"$(nproc)" re2 && make -j"$(nproc)" re2_st \ && cp "$(find . -name libre2.a | head -1)" /usr/lib/ \ && cp "$(find . -name libre2_st.a | head -1)" /usr/lib/ \ && mkdir -p /src/build/libs/libcommon/src \ && printf '#ifndef REVISION\n#define REVISION %s\n#endif\n' "${REVISION}" > /src/build/libs/libcommon/src/revision.h \ - && make -j"$(nproc)" clickhouse-server clickhouse-client + && make -j"$(nproc)" clickhouse-server && make -j"$(nproc)" clickhouse-client # Install binaries + a multi-call shim + a minimal IPv4 config (this era ships # no default config.xml in the tree). diff --git a/versions/build-from-source/reconstruct.sh b/versions/build-from-source/reconstruct.sh index 8a9e42a25c..540b473be0 100755 --- a/versions/build-from-source/reconstruct.sh +++ b/versions/build-from-source/reconstruct.sh @@ -17,7 +17,6 @@ # The quicklz codec is never produced/consumed with LZ4/ZSTD data) # * re2_st -> generated from contrib/libre2 via the donor's create_st_headers.sh # * MongoDB -> throwing stub (legacy mongoclient driver never vendored) -# * isnan/isinf/isfinite -> force-included std:: shim for gcc-5 libstdc++ # # Idempotent-ish: intended to run once on a fresh overlay. @@ -72,6 +71,28 @@ wr(f, s) # Drop the (never-vendored) mongoclient link name wherever it appears. f = "dbms/CMakeLists.txt"; wr(f, re.sub(r"\bmongoclient\b", "", rd(f))) +# The dbms library is one huge explicit source list in dbms/CMakeLists.txt. +# Replace it with a recursive glob so sources renamed/moved between the target +# snapshot and the donor are all compiled (Server/Client are separate +# executables, tests are disabled). cmake 3.5 has no list(FILTER), so filter in +# a foreach. +f = "dbms/CMakeLists.txt"; s = rd(f) +glob_block = ( + 'file(GLOB_RECURSE dbms_all_sources src/*.cpp)\n' + 'set(dbms_sources "")\n' + 'foreach(f ${dbms_all_sources})\n' + ' if((NOT f MATCHES "/(Server|ODBC|tests)/") AND (NOT f MATCHES "/Client/(Client|Benchmark).cpp"))\n' + ' list(APPEND dbms_sources ${f})\n' + ' endif()\n' + 'endforeach()\n' + 'add_library (dbms ${dbms_sources})' +) +# The dbms lib includes the Client library code (Connection*.cpp) but not the +# client executable mains (Client.cpp/Benchmark.cpp); all of Server/ is the +# server executable; ODBC is a separate driver; tests are disabled. +s = re.sub(r"add_library\s*\(\s*dbms\b.*?\)", glob_block, s, count=1, flags=re.S) +wr(f, s) + # Generic prune: the donor build files (2016-03) list sources that an *older* # target snapshot doesn't have yet (files added later). For every add_library / # add_executable in every CMakeLists, drop any listed source file that doesn't @@ -87,8 +108,10 @@ def prune(cml): return head + " " + " ".join(kept) + ")" s2 = re.sub(r"(add_(?:library|executable)\s*\(\s*[^\s)]+)(.*?)\)", fix, s, flags=re.S|re.I) if s2 != s: wr(cml, s2) -for cml in glob.glob("**/CMakeLists.txt", recursive=True): - prune(cml) +# os.walk (not glob(recursive=), which needs Python 3.5+; trusty ships 3.4). +for root, _dirs, files in os.walk("."): + if "CMakeLists.txt" in files: + prune(os.path.join(root, "CMakeLists.txt")) PY # -- QuickLZ compile/link stub (dead code path: our data is LZ4/ZSTD) -- @@ -134,19 +157,90 @@ private: } EOF +# -- statdaemons compat: the early trees pull several headers from an external +# Yandex library ("statdaemons") that the donor split up and renamed: +# * the embedded dictionaries -> DB/Dictionaries/Embedded/ (header-only), and +# * the daemon base class Daemon -> libs/libdaemon's BaseDaemon. +# Both were overlaid from the donor by the Dockerfile. Expose them at the old +# paths (dict headers forward to Embedded; daemon.h forwards +# to BaseDaemon with a typedef for the old class name; Interests.h — legacy +# OLAP interest categories, unused by the benchmark — is an empty stub). -- +mkdir -p contrib/statdaemons-compat/statdaemons +for h in RegionsHierarchies RegionsHierarchy RegionsNames TechDataHierarchy; do + [ -f "dbms/include/DB/Dictionaries/Embedded/${h}.h" ] && \ + echo "#pragma once +#include " > "contrib/statdaemons-compat/statdaemons/${h}.h" +done +if [ -f libs/libdaemon/include/daemon/BaseDaemon.h ]; then + printf '#pragma once\n#include \ntypedef BaseDaemon Daemon;\n' \ + > contrib/statdaemons-compat/statdaemons/daemon.h + # The donor's BaseDaemon is newer and drags in evolved deps (zkutil/graphite) + # the older tree lacks. Replace it with a thin no-op base carrying just the + # API the early Server/TCPHandler use (Poco::Util::ServerApplication plus + # isCancelled/writeToGraphite/getGraphiteWriter, and the Application + # using-decl the old daemon.h exposed). Metrics/cancellation become no-ops, + # which is fine for the benchmark. + cat > libs/libdaemon/include/daemon/GraphiteWriter.h <<'EOF' +#pragma once +#include +#include +#include +#include +class GraphiteWriter +{ +public: + template using KeyValuePair = std::pair; + template using KeyValueVector = std::vector>; + template void write(const std::string &, const T &, time_t = 0, const std::string & = "") {} + template void write(const KeyValueVector &, time_t = 0, const std::string & = "") {} +}; +EOF + cat > libs/libdaemon/include/daemon/BaseDaemon.h <<'EOF' +#pragma once +#include +#include +#include +#include +#include +#include +#include +using Poco::Util::Application; +class BaseDaemon : public Poco::Util::ServerApplication +{ +public: + bool isCancelled() { return is_cancelled; } + static BaseDaemon & instance() { return dynamic_cast(Poco::Util::Application::instance()); } + template void writeToGraphite(const std::string & key, const T & value, time_t timestamp = 0, const std::string & custom_root_path = "") { if (graphite_writer) graphite_writer->write(key, value, timestamp, custom_root_path); } + template void writeToGraphite(const GraphiteWriter::KeyValueVector & key_vals, time_t timestamp = 0, const std::string & custom_root_path = "") { if (graphite_writer) graphite_writer->write(key_vals, timestamp, custom_root_path); } + GraphiteWriter * getGraphiteWriter() { return graphite_writer.get(); } +protected: + // The real daemon registered --config-file and loaded it; replicate that so + // the server accepts the entrypoint's --config-file and reads its config. + void defineOptions(Poco::Util::OptionSet & options) override + { + Poco::Util::ServerApplication::defineOptions(options); + options.addOption(Poco::Util::Option("config-file", "C", "config file").required(false) + .repeatable(false).argument("").binding("config-file")); + } + void initialize(Poco::Util::Application & self) override + { + if (config().hasProperty("config-file")) + loadConfiguration(config().getString("config-file")); + Poco::Util::ServerApplication::initialize(self); + } + bool is_cancelled = false; + std::unique_ptr graphite_writer; +}; +EOF + rm -f libs/libdaemon/src/*.cpp + printf '// minimal daemon base (see reconstruct.sh)\n' > libs/libdaemon/src/BaseDaemon.cpp +fi +echo '#pragma once' > contrib/statdaemons-compat/statdaemons/Interests.h + # -- generate the re2_st (single-threaded re2) headers into a stable include dir -- mkdir -p contrib/re2_st_gen ( cd contrib/re2_st_gen && sh /src/contrib/libre2/create_st_headers.sh /src/contrib/libre2 . ) -# -- gcc-5 libstdc++ moved isnan/isinf/isfinite into std::; bridge them back -- -mkdir -p contrib/compat -cat > contrib/compat/cmath_compat.h <<'EOF' -#pragma once -#include -using std::isnan; -using std::isinf; -using std::isfinite; -EOF # -- MongoDB dictionary: throwing stub (legacy mongoclient driver not vendored) -- cat > dbms/include/DB/Dictionaries/MongoDBBlockInputStream.h <<'EOF' @@ -187,7 +281,11 @@ EOF # -- root CMakeLists: add the quicklz/re2_st include dirs and, on the C++ flags, # -fpermissive plus the force-included cmath shim (anchored on the donor's # stable libcityhash include line / -std=gnu++1y flag) -- -sed -i 's#include_directories (${METRICA_SOURCE_DIR}/contrib/libcityhash/)#include_directories (${METRICA_SOURCE_DIR}/contrib/quicklz-stub/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/re2_st_gen/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/libcityhash/)#' CMakeLists.txt -sed -i 's#-std=gnu++1y#-std=gnu++1y -fpermissive -D_GLIBCXX_USE_CXX11_ABI=0 -include ${METRICA_SOURCE_DIR}/contrib/compat/cmath_compat.h#' CMakeLists.txt +sed -i 's#include_directories (${METRICA_SOURCE_DIR}/contrib/libcityhash/)#include_directories (${METRICA_SOURCE_DIR}/contrib/quicklz-stub/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/re2_st_gen/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/statdaemons-compat/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/libcityhash/)#' CMakeLists.txt +# Force-include a few standard headers: on this (trusty) toolchain they aren't +# pulled in transitively the way the newer 16.04/boost-1.58 headers were, so code +# that assumes std::accumulate () / std::mt19937 () is in scope +# fails to compile without them. +sed -i 's#-std=gnu++1y#-std=gnu++1y -fpermissive -D_GLIBCXX_USE_CXX11_ABI=0 -include numeric -include random#' CMakeLists.txt echo "reconstruct.sh: build system reconciled" From a75081770bef9a85b60f04bfe945e14dd49d07d7 Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Wed, 1 Jul 2026 18:14:17 +0000 Subject: [PATCH 027/120] versions: log query errors, skip unsupported queries, reorder datasets, robust revive MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Improvements to the versions-benchmark runner driven by inspecting the live results in sink.data: - Log the reason for every null: on a query failure run-version.sh now emits the server's error text (unsupported syntax/function), a timeout notice, or a crash notice — once per query, tagged with its "qN [dataset]" label. Errors were previously discarded silently. - Per-query minimum supported version (queries/.minver, aligned to .sql): "0" runs everywhere, a version is the first release known to run the query, "26.7" (future) means never seen to succeed. Below a query's minimum the runner records null without running it, saving time and avoiding crashes that would null later queries. Annotations computed from the 32 full runs. - Reorder QUERY_ORDER so the heavy, crash-/timeout-prone datasets (tpch, tpcds, job) run last: a late crash can no longer null earlier datasets as collateral (as happened to taxi on 20.4). - Best-effort revive_server: also relaunch the daemon in-place when the server process dies but the container stays up (previously a no-op for image providers), fall back to docker restart, use a longer timeout, and log container state/logs so a persistent failure is diagnosable. Co-Authored-By: Claude Opus 4.8 --- versions/queries/coffeeshop.minver | 17 ++++ versions/queries/hits.minver | 43 ++++++++++ versions/queries/job.minver | 113 +++++++++++++++++++++++++ versions/queries/mgbench.minver | 15 ++++ versions/queries/ontime.minver | 11 +++ versions/queries/ssb.minver | 13 +++ versions/queries/taxi.minver | 4 + versions/queries/tpcds.minver | 103 +++++++++++++++++++++++ versions/queries/tpch.minver | 22 +++++ versions/queries/uk.minver | 3 + versions/run-version.sh | 131 ++++++++++++++++++++++++----- 11 files changed, 454 insertions(+), 21 deletions(-) create mode 100644 versions/queries/coffeeshop.minver create mode 100644 versions/queries/hits.minver create mode 100644 versions/queries/job.minver create mode 100644 versions/queries/mgbench.minver create mode 100644 versions/queries/ontime.minver create mode 100644 versions/queries/ssb.minver create mode 100644 versions/queries/taxi.minver create mode 100644 versions/queries/tpcds.minver create mode 100644 versions/queries/tpch.minver create mode 100644 versions/queries/uk.minver diff --git a/versions/queries/coffeeshop.minver b/versions/queries/coffeeshop.minver new file mode 100644 index 0000000000..f55fbea275 --- /dev/null +++ b/versions/queries/coffeeshop.minver @@ -0,0 +1,17 @@ +21.9 +21.10 +21.10 +25.1 +21.9 +25.1 +21.4 +25.1 +21.9 +25.1 +25.1 +25.1 +25.1 +25.1 +25.1 +25.1 +25.1 diff --git a/versions/queries/hits.minver b/versions/queries/hits.minver new file mode 100644 index 0000000000..fff3f3d4f7 --- /dev/null +++ b/versions/queries/hits.minver @@ -0,0 +1,43 @@ +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +20.5 +20.5 +20.5 +20.5 +20.5 +20.5 +20.5 +20.5 +20.5 +0 +0 +0 +0 +0 +0 +20.5 +20.5 +20.5 +20.5 +20.5 +20.5 +20.5 +20.5 +20.5 +0 +0 diff --git a/versions/queries/job.minver b/versions/queries/job.minver new file mode 100644 index 0000000000..326f1696c5 --- /dev/null +++ b/versions/queries/job.minver @@ -0,0 +1,113 @@ +21.4 +0 +0 +0 +0 +0 +0 +25.1 +0 +0 +0 +0 +0 +0 +0 +0 +0 +25.1 +25.1 +25.1 +25.1 +25.1 +25.1 +25.1 +20.5 +21.4 +25.1 +25.1 +25.1 +25.1 +25.1 +25.1 +25.1 +25.1 +25.1 +0 +20.5 +0 +20.5 +21.4 +25.1 +20.5 +21.4 +0 +20.5 +21.4 +21.4 +20.5 +20.5 +21.4 +21.4 +25.1 +25.1 +25.1 +25.1 +25.1 +25.1 +25.1 +25.1 +25.1 +25.1 +25.1 +25.1 +25.1 +25.1 +20.5 +20.5 +20.5 +25.1 +25.1 +25.1 +25.1 +25.1 +25.1 +25.1 +0 +0 +0 +25.1 +25.1 +25.1 +25.1 +25.1 +25.1 +25.1 +25.1 +25.1 +25.1 +25.1 +25.1 +25.1 +25.1 +25.1 +0 +0 +0 +25.1 +25.1 +25.1 +25.1 +25.1 +25.1 +25.1 +25.1 +25.1 +25.1 +25.1 +25.1 +20.5 +25.1 +25.1 +25.1 +25.1 diff --git a/versions/queries/mgbench.minver b/versions/queries/mgbench.minver new file mode 100644 index 0000000000..9cf92df3ca --- /dev/null +++ b/versions/queries/mgbench.minver @@ -0,0 +1,15 @@ +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 diff --git a/versions/queries/ontime.minver b/versions/queries/ontime.minver new file mode 100644 index 0000000000..c4f459c5fe --- /dev/null +++ b/versions/queries/ontime.minver @@ -0,0 +1,11 @@ +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 diff --git a/versions/queries/ssb.minver b/versions/queries/ssb.minver new file mode 100644 index 0000000000..17bbd2c80f --- /dev/null +++ b/versions/queries/ssb.minver @@ -0,0 +1,13 @@ +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 diff --git a/versions/queries/taxi.minver b/versions/queries/taxi.minver new file mode 100644 index 0000000000..44e0be8e35 --- /dev/null +++ b/versions/queries/taxi.minver @@ -0,0 +1,4 @@ +0 +0 +0 +0 diff --git a/versions/queries/tpcds.minver b/versions/queries/tpcds.minver new file mode 100644 index 0000000000..1da6bf80b0 --- /dev/null +++ b/versions/queries/tpcds.minver @@ -0,0 +1,103 @@ +25.8 +21.4 +0 +21.7 +26.7 +25.8 +21.4 +21.9 +0 +25.8 +21.4 +25.1 +25.1 +26.7 +26.7 +21.4 +25.8 +0 +25.1 +20.5 +25.1 +20.5 +20.5 +21.4 +21.4 +21.4 +21.4 +0 +21.4 +25.1 +20.7 +20.5 +25.8 +21.4 +25.8 +21.4 +21.4 +25.8 +25.1 +0 +21.9 +21.4 +21.4 +0 +25.8 +0 +0 +21.9 +21.4 +21.4 +25.1 +25.1 +26.7 +20.5 +21.9 +0 +21.9 +21.4 +0 +21.4 +25.1 +21.4 +21.4 +21.4 +21.4 +0 +21.9 +25.1 +0 +0 +25.1 +21.4 +25.8 +25.1 +21.4 +26.2 +21.4 +21.9 +26.7 +0 +21.4 +21.4 +25.1 +21.4 +25.8 +0 +21.4 +0 +21.4 +25.1 +21.9 +21.4 +21.9 +0 +21.4 +25.8 +0 +25.8 +21.9 +0 +21.4 +25.1 +0 diff --git a/versions/queries/tpch.minver b/versions/queries/tpch.minver new file mode 100644 index 0000000000..f9ecebd3e4 --- /dev/null +++ b/versions/queries/tpch.minver @@ -0,0 +1,22 @@ +0 +25.8 +0 +25.8 +20.5 +22.1 +21.4 +25.1 +25.1 +0 +20.5 +20.5 +21.9 +20.5 +21.4 +20.5 +25.8 +20.5 +25.1 +25.8 +25.10 +25.8 diff --git a/versions/queries/uk.minver b/versions/queries/uk.minver new file mode 100644 index 0000000000..bb0b1cf658 --- /dev/null +++ b/versions/queries/uk.minver @@ -0,0 +1,3 @@ +0 +0 +0 diff --git a/versions/run-version.sh b/versions/run-version.sh index e91e86be2e..1ca59856f4 100755 --- a/versions/run-version.sh +++ b/versions/run-version.sh @@ -58,7 +58,13 @@ declare -A TABLES=( # Query files are run (and reported) in this fixed order. Each dataset loads # into its own database (named after the dataset) so same-named tables (TPC-H # and TPC-DS both have `customer`) don't collide. -QUERY_ORDER="mgbench ssb hits tpch tpcds coffeeshop ontime uk job taxi" +# +# Order matters for resilience: a query that OOMs/crashes the server nulls not +# just itself but every query that runs before the server is revived. So the +# reliable, light datasets run FIRST and the heavy, crash-/timeout-prone ones +# (tpch, tpcds, job — big multi-way joins, INTERSECT, self-joins) run LAST, so a +# late crash can't take down the earlier datasets' results as collateral. +QUERY_ORDER="mgbench ssb hits uk ontime taxi coffeeshop tpch tpcds job" cleanup() { sudo docker rm -f "${CONTAINER}" >/dev/null 2>&1; } # The load phase must leave the container running for the later bench phase; @@ -225,18 +231,50 @@ drop_caches() { sync; echo 3 | sudo tee /proc/sys/vm/drop_caches >/dev/null 2>&1 # stdin, so a bare probe here would swallow the remaining queries. server_alive() { client --query "SELECT 1" /dev/null 2>&1; } -# Bring the server back after a crash. An OOM kill takes down clickhouse-server -# (PID 1 for image providers), so the container exits — but its data layer -# survives, so `docker start` restarts it with the loaded tables intact. For the -# package provider the container (PID 1 = sleep) stays up, so relaunch the daemon. +# Bring the server back after a crash — best effort, several strategies in turn. +# A crash lands in one of two container states: +# * container EXITED — clickhouse-server was PID 1 (most image providers) and the +# OOM kill took it (and the container) down. `docker start` relaunches it with +# the loaded tables intact. +# * container still RUNNING — the server *process* died but PID 1 survived: the +# package provider (PID 1 = sleep), or an image whose entrypoint is a wrapper +# script that didn't exec the server. Here `docker start` is a no-op, so we +# must relaunch the daemon *inside* the container. +# We try both, wait (a server re-attaching billions of rows of parts can take a +# while — hence a generous timeout), and fall back to a full `docker restart`. +# Every step is logged so a persistent failure is diagnosable from the run log. +launch_daemon_in_container() { + sudo docker exec -d "${CONTAINER}" sh -c \ + 'clickhouse-server --daemon --config /etc/clickhouse-server/config.xml 2>/dev/null \ + || clickhouse server --daemon --config /etc/clickhouse-server/config.xml 2>/dev/null \ + || clickhouse-server --config /etc/clickhouse-server/config.xml 2>/dev/null' 2>/dev/null || true +} +wait_alive() { local i; for i in $(seq 1 "${1:-180}"); do server_alive && return 0; sleep 1; done; return 1; } revive_server() { - if [ "$(sudo docker inspect -f '{{.State.Running}}' "${CONTAINER}" 2>/dev/null)" != "true" ]; then - sudo docker start "${CONTAINER}" >/dev/null 2>&1 - elif [ "${IMAGE}" = "package" ]; then - sudo docker exec -d "${CONTAINER}" clickhouse-server --daemon --config /etc/clickhouse-server/config.xml 2>/dev/null + local running + running="$(sudo docker inspect -f '{{.State.Running}}' "${CONTAINER}" 2>/dev/null)" + echo "${VERSION}: reviving server (container running=${running:-unknown}); recent container logs:" >&2 + sudo docker logs --tail 8 "${CONTAINER}" 2>&1 | sed 's/^/ | /' >&2 || true + + # Strategy 1: exited container -> start it back up. + if [ "${running}" != "true" ]; then + sudo docker start "${CONTAINER}" >/dev/null 2>&1 || echo "${VERSION}: 'docker start' failed" >&2 fi - local i - for i in $(seq 1 "${READY_TIMEOUT:-90}"); do server_alive && return 0; sleep 1; done + # Strategy 2: container up but server process dead -> relaunch the daemon inside. + if [ "$(sudo docker inspect -f '{{.State.Running}}' "${CONTAINER}" 2>/dev/null)" = "true" ] && ! server_alive; then + launch_daemon_in_container + fi + wait_alive "${REVIVE_TIMEOUT:-180}" && { echo "${VERSION}: server back up" >&2; return 0; } + + # Strategy 3 (last resort): force a full container restart, then relaunch the + # daemon (needed for the package provider, whose PID 1 is sleep, not the server). + echo "${VERSION}: still down after ${REVIVE_TIMEOUT:-180}s; forcing 'docker restart'" >&2 + sudo docker restart -t 5 "${CONTAINER}" >/dev/null 2>&1 || echo "${VERSION}: 'docker restart' failed" >&2 + server_alive || launch_daemon_in_container + wait_alive "${REVIVE_TIMEOUT:-180}" && { echo "${VERSION}: server back up after restart" >&2; return 0; } + + echo "${VERSION}: could not revive server; final container logs:" >&2 + sudo docker logs --tail 30 "${CONTAINER}" 2>&1 | sed 's/^/ | /' >&2 || true return 1 } @@ -259,6 +297,37 @@ report_sizes() { fi } +# Collapse a (possibly multi-line) client error into one tidy, capped log line. +fmt_err() { printf '%s' "$1" | tr '\n\t' ' ' | sed 's/ */ /g; s/^ //' | cut -c1-800; } + +# Version ordering across the whole timeline. Normalise any version we run to a +# 4-number key (major minor patch build): +# * a bare build number (e.g. 53982) is a 2016 1.1.x snapshot -> 1.1..0 +# * 1.1.54378 / 20.5 / 26.6.1.1193 -> their dotted components (missing => 0) +# so 1.1.54378 and the bare 53982 both sort *below* any calendar release. +version_key() { + local v="$1" a b c d + if [[ "$v" =~ ^[0-9]+$ ]]; then echo "1 1 $v 0"; return; fi + IFS='.' read -r a b c d _ <<<"$v" + echo "${a:-0} ${b:-0} ${c:-0} ${d:-0}" +} +# version_ge A B -> true if A >= B +version_ge() { + local -a x y; read -ra x <<<"$(version_key "$1")"; read -ra y <<<"$(version_key "$2")" + local i + for i in 0 1 2 3; do + [ "${x[i]}" -gt "${y[i]}" ] && return 0 + [ "${x[i]}" -lt "${y[i]}" ] && return 1 + done + return 0 +} +# A results row of all-null (used when a query is skipped as unsupported). +null_row() { + local i out="[" + for i in $(seq 1 "${TRIES}"); do out+="null"; [ "${i}" -ne "${TRIES}" ] && out+=", "; done + echo "${out}]" +} + # Run one query TRIES times, print a JSON array "[t1, ..., tN]" (null on error). # The remaining tries are skipped (recorded null) once a try either: # * exceeds QUERY_TIMEOUT (default 100s) — no point re-timing a too-slow query, or @@ -266,8 +335,11 @@ report_sizes() { # still run, but this query's remaining tries are abandoned. # A plain error while the server stays up (e.g. a feature an old version lacks) # just records null for that try and keeps going (every try will null anyway). +# Whatever the failure mode, the reason (and the server's error text, when there is +# one) is written to the log ONCE per query — tagged with the query's label — so a +# null in the results can be traced to an unsupported feature, a timeout or a crash. run_query() { - local query="$1" i res rc out="[" skip_rest=0 + local query="$1" label="${2:-query}" i res rc out="[" skip_rest=0 logged=0 for i in $(seq 1 "${TRIES}"); do if [ "${skip_rest}" = 1 ]; then res="null" # an earlier try timed out or crashed; skip the rest @@ -277,16 +349,19 @@ run_query() { rc=$? CH_TIMEOUT="" if [ "${rc}" = 124 ] || [ "${rc}" = 137 ]; then # `timeout` killed it - echo "${VERSION}: query exceeded ${QUERY_TIMEOUT:-100}s; recording null and skipping remaining tries" >&2 - skip_rest=1; res="null" + [ "${logged}" = 0 ] && echo "${label}: FAILED (timeout >${QUERY_TIMEOUT:-100}s); recording null, skipping remaining tries" >&2 + logged=1; skip_rest=1; res="null" elif [[ "${res}" =~ ^[0-9]+\.[0-9]+$ ]]; then : # good timing elif ! server_alive; then - echo "${VERSION}: server died mid-query (likely OOM); reviving and skipping remaining tries" >&2 - revive_server || true # restore it for the following queries + [ "${logged}" = 0 ] && echo "${label}: FAILED (server died mid-query, likely OOM); reviving, skipping remaining tries. Last output: $(fmt_err "${res}")" >&2 + logged=1; revive_server || true # restore it for the following queries skip_rest=1; res="null" else - res="null" # query errored but server is up + # Query errored but the server is up (e.g. unsupported syntax/function + # on an old version). Record null and log the server's error message. + [ "${logged}" = 0 ] && echo "${label}: FAILED (error): $(fmt_err "${res}")" >&2 + logged=1; res="null" fi fi out+="${res}" @@ -335,7 +410,7 @@ emit_data_size_json() { # Time every query and write results/.json. run_benchmark() { - local ACTUAL ds query FIRST=1 qnum=0 row QDB + local ACTUAL ds query FIRST=1 qnum=0 row QDB MINVERS mv lidx ACTUAL=$(client --query "SELECT version()" 2>/dev/null | tr -d '\r') echo "benchmarking ${VERSION} (server reports ${ACTUAL})" >&2 { @@ -348,15 +423,29 @@ run_benchmark() { echo ' [' for ds in ${QUERY_ORDER}; do QDB="${ds}" # run this dataset's queries with its database as default + # Per-query minimum supported version (queries/.minver, one token per + # query, aligned to .sql): "0" = runs everywhere, a version = first + # release known to run it, "26.7"(future) = never seen to succeed. When + # the current version is below a query's minimum we record null WITHOUT + # running it — the outcome is known and running it only wastes time (and + # risks a crash that would null later queries too). + MINVERS=(); [ -f "${HERE}/queries/${ds}.minver" ] && mapfile -t MINVERS < "${HERE}/queries/${ds}.minver" + lidx=0 # Read queries on FD 3 (not stdin) so the per-query `docker exec/run -i` # client calls can't consume the query file. while IFS= read -r query <&3; do [ -z "${query}" ] && continue query="${query%;}" # strip trailing semicolon - drop_caches qnum=$((qnum + 1)) - row="$(run_query "${query}")" - echo "q${qnum} [${ds}]: ${row}" >&2 # live timings to the log + mv="${MINVERS[lidx]:-0}"; lidx=$((lidx + 1)) + if [ "${mv}" != "0" ] && ! version_ge "${VERSION}" "${mv}"; then + row="$(null_row)" + echo "q${qnum} [${ds}]: SKIPPED (min supported ${mv}); recording null" >&2 + else + drop_caches + row="$(run_query "${query}" "q${qnum} [${ds}]")" + echo "q${qnum} [${ds}]: ${row}" >&2 # live timings to the log + fi [ "${FIRST}" = 0 ] && echo ',' FIRST=0 printf '%s' "${row}" From f122bcb8a58a39b3b93e3f29c04176e490c83bd4 Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Wed, 1 Jul 2026 18:14:29 +0000 Subject: [PATCH 028/120] versions: reconstruct pre-2015-12 builds (break the external stats-library wall) Extend the from-source reconstruction below 2015-12. At the 2015-11 -> 2015-12 boundary a coordinated refactor inlined several never-public external Yandex libraries and reshaped core containers; reproduce that so 2015-11 builds+boots (0.0.53350): - stats/*: append the templated intHash32+IntHash32 to the era's Hash.h (where 2015-12 moved it) and forward there; overlay the UniquesHashSet / ReservoirSampler{,Deterministic} algorithms from a "last known-good month" PATCH_REF and forward the old paths to them. - ReservoirSampler: retarget its PODArray> buffer to std::vector to avoid back-porting the templated allocator through every container. - Strip illegal virt-specifiers from member-function templates (a modern gcc-5 error the era's compiler tolerated). - Extend the statdaemons compat auto-map to DB/Core (Exception.h etc. lived there in the oldest trees), make the MongoDB stub era-agnostic. - Dockerfile.reconstruct: PATCH_REF/PATCH_FILES overlay mechanism for the few gcc-hostile files fixed by 2015-12 (SummingSortedBlockInputStream, the stats algorithms). monthly-built.tsv records 2015-11 alongside 2015-12/2016-01/2016-02. Co-Authored-By: Claude Opus 4.8 --- .../build-from-source/Dockerfile.reconstruct | 15 +- versions/build-from-source/build-monthly.sh | 21 ++- versions/build-from-source/monthly-built.tsv | 4 + versions/build-from-source/reconstruct.sh | 153 ++++++++++++++++-- 4 files changed, 174 insertions(+), 19 deletions(-) create mode 100644 versions/build-from-source/monthly-built.tsv diff --git a/versions/build-from-source/Dockerfile.reconstruct b/versions/build-from-source/Dockerfile.reconstruct index c6e7d0143d..f321d5b260 100644 --- a/versions/build-from-source/Dockerfile.reconstruct +++ b/versions/build-from-source/Dockerfile.reconstruct @@ -40,6 +40,14 @@ ENV CC=gcc-${GCC} CXX=g++-${GCC} # DONOR: the earliest self-contained snapshot (2016-03-01), whose build system # and contrib/ we transplant. TAG: the target snapshot's commit SHA. ARG DONOR=5360c78806e043d0d2bf3de15a363f87fbdaf5f4 +# PATCH_REF: the last cleanly-building month (2015-12). A handful of files in the +# older trees use C++14 that this era's gcc-5 accepted but a modern gcc-5 rejects +# (recursive generic lambdas etc.); by 2015-12 they had been rewritten. We overlay +# those specific files from PATCH_REF ("an equivalent from a slightly newer +# version"). PATCH_FILES is the space-separated allowlist, extended as new +# gcc-hostile files surface while sweeping backwards. +ARG PATCH_REF=a7387d9ce431a1f288d1a4898fa0c0c36c765abc +ARG PATCH_FILES="dbms/include/DB/DataStreams/SummingSortedBlockInputStream.h dbms/src/DataStreams/SummingSortedBlockInputStream.cpp dbms/include/DB/AggregateFunctions/UniquesHashSet.h dbms/include/DB/AggregateFunctions/ReservoirSampler.h dbms/include/DB/AggregateFunctions/ReservoirSamplerDeterministic.h" ARG TAG RUN git init -q /src && cd /src \ && git config advice.detachedHead false \ @@ -49,7 +57,12 @@ RUN git init -q /src && cd /src \ && git checkout FETCH_HEAD -- contrib \ && git checkout FETCH_HEAD -- $(git ls-tree -r --name-only FETCH_HEAD | grep -E 'CMakeLists.txt$|\.cmake$') \ && (git checkout FETCH_HEAD -- dbms/include/DB/Dictionaries/Embedded 2>/dev/null || true) \ - && (git checkout FETCH_HEAD -- libs/libdaemon 2>/dev/null || true) + && (git checkout FETCH_HEAD -- libs/libdaemon 2>/dev/null || true) \ + && (git checkout FETCH_HEAD -- libs/libcommon 2>/dev/null || true) \ + && if [ "${PATCH_REF}" != "${TAG}" ] && [ -n "${PATCH_FILES}" ]; then \ + git fetch -q --depth 1 origin "${PATCH_REF}" \ + && for f in ${PATCH_FILES}; do (git checkout FETCH_HEAD -- "$f" 2>/dev/null || true); done; \ + fi # Reconcile the donor build system with the older source (globs, stubs, shims). COPY reconstruct.sh /reconstruct.sh diff --git a/versions/build-from-source/build-monthly.sh b/versions/build-from-source/build-monthly.sh index 20cbab937b..88d484ff16 100755 --- a/versions/build-from-source/build-monthly.sh +++ b/versions/build-from-source/build-monthly.sh @@ -20,10 +20,19 @@ JOBS="${JOBS:-3}" declare -A WANT=() for a in "$@"; do WANT["$a"]=1; done -build_one() { # date sha - local date="$1" sha="$2" +# Successfully built+booted monthly snapshots are recorded here (date, sha, +# commit-date), one per line — the record of every reconstructed patch set. +BUILT_RECORD="${HERE}/monthly-built.tsv" + +record_built() { # date sha commit_date + # append if not already recorded (atomic small-line append across jobs) + grep -q "^$1 " "${BUILT_RECORD}" 2>/dev/null || printf '%s\t%s\t%s\n' "$1" "$2" "$3" >> "${BUILT_RECORD}" +} + +build_one() { # date sha commit_date + local date="$1" sha="$2" cd="$3" if sudo docker image inspect "clickhouse-built:${date}" >/dev/null 2>&1; then - echo "skip ${date}: image exists"; return 0 + echo "skip ${date}: image exists"; record_built "${date}" "${sha}" "${cd}"; return 0 fi if sudo docker buildx build --progress=plain --load \ --build-arg "TAG=${sha}" --build-arg "GCC=${GCC:-5}" \ @@ -38,18 +47,18 @@ build_one() { # date sha sleep 1 done sudo docker rm -f "smoke-${date}" >/dev/null 2>&1 - if [ -n "${v}" ]; then echo "OK ${date} (version ${v})"; else echo "BUILT-BUT-NO-BOOT ${date}" >&2; fi + if [ -n "${v}" ]; then echo "OK ${date} (version ${v})"; record_built "${date}" "${sha}" "${cd}"; else echo "BUILT-BUT-NO-BOOT ${date}" >&2; fi else echo "FAILED ${date} (see ${LOGS}/reconstruct-${date}.log)" >&2 fi } # newest first (monthly.tsv is already newest->oldest) -while IFS=$'\t' read -r date sha _cd; do +while IFS=$'\t' read -r date sha cd; do [ -z "${date}" ] && continue [ "$#" -gt 0 ] && [ -z "${WANT[$date]:-}" ] && continue while [ "$(jobs -rp | wc -l)" -ge "${JOBS}" ]; do wait -n 2>/dev/null || sleep 5; done - build_one "${date}" "${sha}" & + build_one "${date}" "${sha}" "${cd}" & done < "${HERE}/monthly.tsv" wait echo "build-monthly done" diff --git a/versions/build-from-source/monthly-built.tsv b/versions/build-from-source/monthly-built.tsv new file mode 100644 index 0000000000..6faf1754ee --- /dev/null +++ b/versions/build-from-source/monthly-built.tsv @@ -0,0 +1,4 @@ +2016-02-01 21fb1cca7c1342f02cda0b8df08df08a737eb7ee 2016-01-30 +2016-01-01 a6b01ee987c44a8291c616ffdedb63677ef0780a 2015-12-30 +2015-12-01 a7387d9ce431a1f288d1a4898fa0c0c36c765abc 2015-11-30 +2015-11-01 b17cc7181edbb05637b23f2f632d44d092e276e5 0.0.53350 diff --git a/versions/build-from-source/reconstruct.sh b/versions/build-from-source/reconstruct.sh index 540b473be0..967d0c55c1 100755 --- a/versions/build-from-source/reconstruct.sh +++ b/versions/build-from-source/reconstruct.sh @@ -166,10 +166,19 @@ EOF # to BaseDaemon with a typedef for the old class name; Interests.h — legacy # OLAP interest categories, unused by the benchmark — is an empty stub). -- mkdir -p contrib/statdaemons-compat/statdaemons -for h in RegionsHierarchies RegionsHierarchy RegionsNames TechDataHierarchy; do - [ -f "dbms/include/DB/Dictionaries/Embedded/${h}.h" ] && \ - echo "#pragma once -#include " > "contrib/statdaemons-compat/statdaemons/${h}.h" +# Auto-map every donor header of the same basename to the old +# path: the statdaemons library's contents were dispersed into DB/Common/, +# common/ and DB/Dictionaries/Embedded/ (e.g. Exception.h -> DB/Common/Exception.h, +# RegionsHierarchies.h -> Embedded/). First match wins (DB/Common preferred). +# (DB/Core is scanned last so the newer DB/Common location wins when both exist: +# in the oldest trees Exception.h/etc. still lived under DB/Core, not DB/Common.) +for pair in "dbms/include/DB/Common:DB/Common" "libs/libcommon/include/common:common" "dbms/include/DB/Dictionaries/Embedded:DB/Dictionaries/Embedded" "dbms/include/DB/Core:DB/Core"; do + dir="${pair%%:*}"; inc="${pair##*:}"; [ -d "$dir" ] || continue + for h in "$dir"/*.h; do + [ -f "$h" ] || continue; base="$(basename "$h")" + w="contrib/statdaemons-compat/statdaemons/${base}" + [ -e "$w" ] || printf '#pragma once\n#include <%s/%s>\n' "$inc" "$base" > "$w" + done done if [ -f libs/libdaemon/include/daemon/BaseDaemon.h ]; then printf '#pragma once\n#include \ntypedef BaseDaemon Daemon;\n' \ @@ -237,6 +246,86 @@ EOF fi echo '#pragma once' > contrib/statdaemons-compat/statdaemons/Interests.h +# -- Yandex/ -> common/: the old include prefix for the common utilities that the +# donor renamed to common/ (e.g. == ). +# Expose the donor's common headers under the old Yandex/ prefix. -- +if [ -d libs/libcommon/include/common ]; then + mkdir -p contrib/yandex-compat + ln -sfn "$(pwd)/libs/libcommon/include/common" contrib/yandex-compat/Yandex +fi + +# -- double-conversion: the old code includes ; the +# donor's header is double-conversion/double-conversion.h (same namespace). -- +if [ -f contrib/libdouble-conversion/double-conversion/double-conversion.h ]; then + mkdir -p contrib/dc-compat/src + printf '#pragma once\n#include \n' > contrib/dc-compat/src/double-conversion.h +fi + +# -- stats/*: the pre-2015-12 trees include several headers from an external Yandex +# "stats" library that was never open-sourced. At the 2015-11 -> 2015-12 boundary +# these were inlined into the repo (a coordinated refactor). We reproduce that: +# * stats/IntHash.h -> the templated intHash32+IntHash32 functor, which +# 2015-12 moved into DB/Common/HashTable/Hash.h. Append them to the era's +# own Hash.h (which lacks intHash32) so they are visible everywhere Hash.h is +# included -- notably the overlaid UniquesHashSet -- and forward the old +# path there. (Appending, not a separate compat definition, +# avoids a double-definition when both headers land in one TU.) +# * stats/{UniquesHashSet,ReservoirSampler,ReservoirSamplerDeterministic}.h -> +# the algorithms, overlaid in-tree from PATCH_REF and forwarded. -- +mkdir -p contrib/stats-compat/stats +HASH_H=dbms/include/DB/Common/HashTable/Hash.h +# (Match the definition `intHash32(` -- not the prose comment that mentions the +# name -- so we don't skip the append on a false positive.) +if [ -f "$HASH_H" ] && ! grep -q 'intHash32(' "$HASH_H"; then + cat >> "$HASH_H" <<'EOF' + +/// Added by reconstruct.sh: the templated salted UInt64 -> UInt32 hash (ttwang) and +/// its container functor. Before 2015-12 these lived in the external ; +/// 2015-12 moved them into this header. Kept identical to the 2015-12 definition. +template +inline DB::UInt32 intHash32(DB::UInt64 key) +{ + key ^= salt; + key = (~key) + (key << 18); + key = key ^ ((key >> 31) | (key << 33)); + key = key * 21; + key = key ^ ((key >> 11) | (key << 53)); + key = key + (key << 6); + key = key ^ ((key >> 22) | (key << 42)); + return key; +} + +template +struct IntHash32 +{ + size_t operator() (const T & key) const { return intHash32(key); } +}; +EOF +fi +printf '#pragma once\n#include \n' > contrib/stats-compat/stats/IntHash.h + +# The overlaid 2015-12 ReservoirSampler{,Deterministic}.h back a small sample buffer +# with DB::PODArray, N>> -- but +# 2015-11's Allocator is a non-template class and lacks AllocatorWithStackMemory, and +# back-porting the templated allocator would ripple through every container. The +# buffer only ever needs push_back / [] / size / resize / begin / end / clear / swap, +# so retarget it to std::vector (the first PODArray template arg is the element type). +# quantile() is unused by the benchmark, so exact reservoir behaviour is immaterial. +for f in dbms/include/DB/AggregateFunctions/ReservoirSampler.h \ + dbms/include/DB/AggregateFunctions/ReservoirSamplerDeterministic.h; do + [ -f "$f" ] || continue + sed -i 's#include #include #' "$f" + sed -i 's#using Array = DB::PODArray<\([^,]*\),[^;]*>;#using Array = std::vector<\1>;#' "$f" +done + +# Forward the old algorithm paths to the overlaid in-tree headers. +for base in ReservoirSampler ReservoirSamplerDeterministic UniquesHashSet; do + if [ -f "dbms/include/DB/AggregateFunctions/${base}.h" ]; then + printf '#pragma once\n#include \n' "$base" \ + > "contrib/stats-compat/stats/${base}.h" + fi +done + # -- generate the re2_st (single-threaded re2) headers into a stable include dir -- mkdir -p contrib/re2_st_gen ( cd contrib/re2_st_gen && sh /src/contrib/libre2/create_st_headers.sh /src/contrib/libre2 . ) @@ -267,21 +356,61 @@ public: MongoDBDictionarySource(const DictionaryStructure &, const Poco::Util::AbstractConfiguration &, const std::string &, Block &, Context &) { throw Exception("MongoDB dictionary source is not supported in this build", 0); } - BlockInputStreamPtr loadAll() override { throw Exception("MongoDB not supported", 0); } - bool supportsSelectiveLoad() const override { return false; } - BlockInputStreamPtr loadIds(const std::vector &) override { throw Exception("MongoDB not supported", 0); } - BlockInputStreamPtr loadKeys(const ConstColumnPlainPtrs &, const std::vector &) override { throw Exception("MongoDB not supported", 0); } - bool isModified() const override { return false; } - DictionarySourcePtr clone() const override { throw Exception("MongoDB not supported", 0); } - std::string toString() const override { return "MongoDB(disabled)"; } + // No `override` on these: the exact IDictionarySource virtuals vary across the + // era (e.g. loadKeys did not exist before ~2015-12). Omitting the keyword makes + // each an implicit override where the matching virtual exists and a harmless + // extra method where it doesn't, so the stub is concrete for every snapshot. + BlockInputStreamPtr loadAll() { throw Exception("MongoDB not supported", 0); } + bool supportsSelectiveLoad() const { return false; } + BlockInputStreamPtr loadIds(const std::vector &) { throw Exception("MongoDB not supported", 0); } + BlockInputStreamPtr loadKeys(const ConstColumnPlainPtrs &, const std::vector &) { throw Exception("MongoDB not supported", 0); } + bool isModified() const { return false; } + DictionarySourcePtr clone() const { throw Exception("MongoDB not supported", 0); } + std::string toString() const { return "MongoDB(disabled)"; } }; } EOF +# -- member-template virt-specifiers: the early trees mark templated member +# functions with `override`/`final` (e.g. `template bool +# execute(...) override` in FunctionsMiscellaneous.h). A member template can +# never be virtual, so this is ill-formed; the era's compiler accepted it but +# gcc-5 rejects it ("member template ... may not have virt-specifiers"). Strip +# the trailing specifier from any method whose immediately-preceding non-blank +# line opens a `template<...>` declaration. -- +python3 - <<'PYEOF' +import os, re +# ") ... override|final" at end of a declaration line (body brace on next line) +spec = re.compile(r'\)\s*(?:const\s*)?(?:override|final)(?:\s+(?:override|final))?\s*$') +tmpl = re.compile(r'^\s*template\s*<') +for root, _dirs, files in os.walk('dbms'): + for fn in files: + if not fn.endswith(('.h', '.hpp', '.cpp')): + continue + p = os.path.join(root, fn) + try: + with open(p, encoding='utf-8', errors='surrogateescape') as f: + lines = f.readlines() + except OSError: + continue + changed = False + prev_nonblank = '' + for i, ln in enumerate(lines): + if spec.search(ln) and tmpl.match(prev_nonblank): + # drop just the virt-specifier keyword(s), keep the rest verbatim + lines[i] = re.sub(r'\s*(?:override|final)(?:\s+(?:override|final))?\s*$', '\n', ln) + changed = True + if ln.strip(): + prev_nonblank = ln + if changed: + with open(p, 'w', encoding='utf-8', errors='surrogateescape') as f: + f.writelines(lines) +PYEOF + # -- root CMakeLists: add the quicklz/re2_st include dirs and, on the C++ flags, # -fpermissive plus the force-included cmath shim (anchored on the donor's # stable libcityhash include line / -std=gnu++1y flag) -- -sed -i 's#include_directories (${METRICA_SOURCE_DIR}/contrib/libcityhash/)#include_directories (${METRICA_SOURCE_DIR}/contrib/quicklz-stub/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/re2_st_gen/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/statdaemons-compat/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/libcityhash/)#' CMakeLists.txt +sed -i 's#include_directories (${METRICA_SOURCE_DIR}/contrib/libcityhash/)#include_directories (${METRICA_SOURCE_DIR}/contrib/quicklz-stub/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/re2_st_gen/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/statdaemons-compat/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/yandex-compat/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/dc-compat/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/stats-compat/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/libcityhash/)#' CMakeLists.txt # Force-include a few standard headers: on this (trusty) toolchain they aren't # pulled in transitively the way the newer 16.04/boost-1.58 headers were, so code # that assumes std::accumulate () / std::mt19937 () is in scope From 0c793a79ab04255f1be036567c45c8bd7a6bfe8c Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Wed, 1 Jul 2026 21:09:04 +0000 Subject: [PATCH 029/120] versions: reconstruct 2015-10, skip fully-unsupported dataset loads, add earlyoom MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Reconstruction — break the 2015-10 -> 2015-11 external-statdaemons boundary so 2015-10 builds and boots (0.0.53340). Before 2015-11 the codebase pulled the bulk of its infrastructure from the never-public external "statdaemons"/"stats" Yandex libraries; they were inlined in-repo at that boundary. Reproduce that: - Vendor DB::Exception + StackTrace + ErrnoException (the class itself was external here; DB/Core/Exception.h only #included it and added free functions). - Back-port the statdaemons infra from PATCH_REF (Stopwatch, ConfigProcessor, Pool{,WithFailover}Base, OptimizedRegularExpression(+.inl), HTMLForm, AIO, the HyperLogLog trio, NetException, Increment+CounterInFile, SimpleCache, threadpool, and the uniq/quantile algorithms), forwarding the old (+ ext/*.hpp) include paths to them. - strconvert compat (escape.h escaped_for_like + hash64.h; MySQL dicts/OLAP are never exercised), Yandex/Revision.h stub, DB/Common/Exception.h and DB/Core/FieldVisitors.h forwards, ConnectionPoolWithFailover::getMany adapted to the newer 2-arg base (distributed plumbing, compile-only), BaseDaemon::sleep. - Overlay is now split so it can't downgrade newer, self-contained months: PATCH_FILES overwrites (only the gcc-hostile SummingSorted), PATCH_FILL adds the infra only when absent. monthly-built.tsv records 2015-10. Runner — skip loading a dataset when the version supports none of its queries: dataset_supported() checks the per-query .minver annotations; if every query is below the version's minimum (e.g. coffeeshop on 20.4), the dataset isn't loaded at all (its queries are recorded null anyway), saving load time and disk. Cloud-init — install and enable earlyoom (as the main ClickBench cloud-init does): loading all datasets in parallel (and heavy joins on old, less memory-efficient versions) can exhaust RAM; without earlyoom the kernel thrashes and the VM gets stuck. earlyoom kills the offender early; the server crash is then recovered by revive_server (or the query is recorded null). Co-Authored-By: Claude Opus 4.8 --- .../build-from-source/Dockerfile.reconstruct | 22 ++- versions/build-from-source/monthly-built.tsv | 1 + versions/build-from-source/reconstruct.sh | 156 +++++++++++++++++- versions/cloud-init.sh.in | 9 +- versions/run-version.sh | 20 ++- 5 files changed, 201 insertions(+), 7 deletions(-) diff --git a/versions/build-from-source/Dockerfile.reconstruct b/versions/build-from-source/Dockerfile.reconstruct index f321d5b260..2a1c163759 100644 --- a/versions/build-from-source/Dockerfile.reconstruct +++ b/versions/build-from-source/Dockerfile.reconstruct @@ -47,7 +47,20 @@ ARG DONOR=5360c78806e043d0d2bf3de15a363f87fbdaf5f4 # version"). PATCH_FILES is the space-separated allowlist, extended as new # gcc-hostile files surface while sweeping backwards. ARG PATCH_REF=a7387d9ce431a1f288d1a4898fa0c0c36c765abc -ARG PATCH_FILES="dbms/include/DB/DataStreams/SummingSortedBlockInputStream.h dbms/src/DataStreams/SummingSortedBlockInputStream.cpp dbms/include/DB/AggregateFunctions/UniquesHashSet.h dbms/include/DB/AggregateFunctions/ReservoirSampler.h dbms/include/DB/AggregateFunctions/ReservoirSamplerDeterministic.h" +# Two overlay sets from PATCH_REF, applied only to targets older than it: +# PATCH_FILES — OVERWRITE. Files that exist in the target but are broken there: +# SummingSortedBlockInputStream uses a recursive generic lambda that this era's +# gcc-5 accepted but a modern gcc-5 rejects; it was rewritten by PATCH_REF. Must +# replace the target's copy. (SummingMergeTree is unused by the benchmark, so a +# newer copy on a newer target is harmless.) +# PATCH_FILL — FILL, only when ABSENT in the target. The statdaemons-library +# components (Stopwatch, pools, HLL, Increment, the uniq/quantile algorithms, +# …) that pre-2015-11 trees pulled from the external ; they were +# inlined in-repo at the 2015-10 -> 2015-11 boundary. Filling only-if-missing +# means newer, self-contained trees keep their own copies (no downgrade). +# reconstruct.sh forwards the old paths to them. +ARG PATCH_FILES="dbms/include/DB/DataStreams/SummingSortedBlockInputStream.h dbms/src/DataStreams/SummingSortedBlockInputStream.cpp" +ARG PATCH_FILL="dbms/include/DB/AggregateFunctions/UniquesHashSet.h dbms/include/DB/AggregateFunctions/ReservoirSampler.h dbms/include/DB/AggregateFunctions/ReservoirSamplerDeterministic.h dbms/include/DB/Common/Stopwatch.h dbms/include/DB/Common/ConfigProcessor.h dbms/include/DB/Common/PoolBase.h dbms/include/DB/Common/PoolWithFailoverBase.h dbms/include/DB/Common/OptimizedRegularExpression.h dbms/include/DB/Common/OptimizedRegularExpression.inl dbms/include/DB/Common/HTMLForm.h dbms/include/DB/Common/AIO.h dbms/include/DB/Common/HyperLogLogCounter.h dbms/include/DB/Common/HyperLogLogBiasEstimator.h dbms/include/DB/Common/CompactArray.h dbms/include/DB/Common/NetException.h dbms/src/Common/ConfigProcessor.cpp libs/libcommon/include/common/threadpool.hpp dbms/include/DB/Common/Increment.h dbms/include/DB/Common/CounterInFile.h dbms/include/DB/Common/SimpleCache.h" ARG TAG RUN git init -q /src && cd /src \ && git config advice.detachedHead false \ @@ -59,9 +72,10 @@ RUN git init -q /src && cd /src \ && (git checkout FETCH_HEAD -- dbms/include/DB/Dictionaries/Embedded 2>/dev/null || true) \ && (git checkout FETCH_HEAD -- libs/libdaemon 2>/dev/null || true) \ && (git checkout FETCH_HEAD -- libs/libcommon 2>/dev/null || true) \ - && if [ "${PATCH_REF}" != "${TAG}" ] && [ -n "${PATCH_FILES}" ]; then \ - git fetch -q --depth 1 origin "${PATCH_REF}" \ - && for f in ${PATCH_FILES}; do (git checkout FETCH_HEAD -- "$f" 2>/dev/null || true); done; \ + && if [ "${PATCH_REF}" != "${TAG}" ]; then \ + git fetch -q --depth 1 origin "${PATCH_REF}"; \ + for f in ${PATCH_FILES}; do (git checkout FETCH_HEAD -- "$f" 2>/dev/null || true); done; \ + for f in ${PATCH_FILL}; do [ -e "$f" ] || (git checkout FETCH_HEAD -- "$f" 2>/dev/null || true); done; \ fi # Reconcile the donor build system with the older source (globs, stubs, shims). diff --git a/versions/build-from-source/monthly-built.tsv b/versions/build-from-source/monthly-built.tsv index 6faf1754ee..9f62e6782b 100644 --- a/versions/build-from-source/monthly-built.tsv +++ b/versions/build-from-source/monthly-built.tsv @@ -2,3 +2,4 @@ 2016-01-01 a6b01ee987c44a8291c616ffdedb63677ef0780a 2015-12-30 2015-12-01 a7387d9ce431a1f288d1a4898fa0c0c36c765abc 2015-11-30 2015-11-01 b17cc7181edbb05637b23f2f632d44d092e276e5 0.0.53350 +2015-10-01 c915538fa788697feea7910c7de5339f6b5a2ce2 0.0.53340 diff --git a/versions/build-from-source/reconstruct.sh b/versions/build-from-source/reconstruct.sh index 967d0c55c1..f26acf088e 100755 --- a/versions/build-from-source/reconstruct.sh +++ b/versions/build-from-source/reconstruct.sh @@ -166,6 +166,89 @@ EOF # to BaseDaemon with a typedef for the old class name; Interests.h — legacy # OLAP interest categories, unused by the benchmark — is an empty stub). -- mkdir -p contrib/statdaemons-compat/statdaemons +# -- DB::Exception: in the oldest trees (pre ~2015-11) the class itself lived in the +# never-public external -- DB/Core/Exception.h merely +# #includes it and adds free functions (throwFromErrno etc.). Later the class was +# inlined in-repo (DB/Common/Exception.h). If the tree defines it we let the +# auto-map below forward there; otherwise vendor an +# equivalent class (matching what 2015-12 inlined). It is created *before* the +# auto-map so the auto-map leaves it untouched. Header-only, so it adds no link +# symbols and the era's own Exception.cpp still provides the free functions. The +# StackTrace it carries was external in that era too, so stub it (no-op +# toString(); stack traces are diagnostic only, never needed by the benchmark). -- +if ! grep -rqlE 'class Exception[[:space:]]*:[[:space:]]*public[[:space:]]+Poco::Exception' dbms/include 2>/dev/null; then + cat > contrib/statdaemons-compat/statdaemons/Exception.h <<'EOF' +#pragma once +// Vendored DB::Exception + StackTrace for pre-2015-11 trees (both lived in the +// never-public external statdaemons library). Interface matches the version +// 2015-12 inlined into DB/Common/Exception.h. +#include +#include +#include + +/// Stub: real stack capture was in the external lib; only toString() is ever used +/// (for diagnostics), so an empty trace is sufficient for the benchmark. +class StackTrace +{ +public: + StackTrace() {} + std::string toString() const { return {}; } +}; + +namespace DB +{ + +class Exception : public Poco::Exception +{ +public: + Exception(int code = 0) : Poco::Exception(code) {} + Exception(const std::string & msg, int code = 0) : Poco::Exception(msg, code) {} + Exception(const std::string & msg, const std::string & arg, int code = 0) : Poco::Exception(msg, arg, code) {} + Exception(const std::string & msg, const Exception & exc, int code = 0) : Poco::Exception(msg, exc, code), trace(exc.trace) {} + Exception(const Exception & exc) : Poco::Exception(exc), trace(exc.trace) {} + explicit Exception(const Poco::Exception & exc) : Poco::Exception(exc.displayText()) {} + ~Exception() throw() {} + Exception & operator = (const Exception & exc) { Poco::Exception::operator=(exc); trace = exc.trace; return *this; } + const char * name() const throw() { return "DB::Exception"; } + const char * className() const throw() { return "DB::Exception"; } + DB::Exception * clone() const { return new DB::Exception(*this); } + void rethrow() const { throw *this; } + void addMessage(const std::string & arg) { extendedMessage(arg); } + const StackTrace & getStackTrace() const { return trace; } +private: + StackTrace trace; +}; + +/// Carries a saved errno; thrown by throwFromErrno(). (Also external in this era.) +class ErrnoException : public Exception +{ +public: + ErrnoException(int code = 0, int saved_errno_ = 0) : Exception(code), saved_errno(saved_errno_) {} + ErrnoException(const std::string & msg, int code = 0, int saved_errno_ = 0) : Exception(msg, code), saved_errno(saved_errno_) {} + ErrnoException(const std::string & msg, const std::string & arg, int code = 0, int saved_errno_ = 0) : Exception(msg, arg, code), saved_errno(saved_errno_) {} + ErrnoException(const std::string & msg, const Exception & exc, int code = 0, int saved_errno_ = 0) : Exception(msg, exc, code), saved_errno(saved_errno_) {} + ErrnoException(const ErrnoException & exc) : Exception(exc), saved_errno(exc.saved_errno) {} + int getErrno() const { return saved_errno; } +private: + int saved_errno; +}; + +} +EOF + # Some back-ported (newer) headers, e.g. NetException.h, include + # ; in this era Exception lives at DB/Core. Forward the + # DB/Common path to it (only when the tree has no real DB/Common/Exception.h). + if [ ! -e dbms/include/DB/Common/Exception.h ]; then + mkdir -p dbms/include/DB/Common + printf '#pragma once\n#include \n' > dbms/include/DB/Common/Exception.h + fi +fi +# The back-ported SummingSortedBlockInputStream.h includes ; +# before that split the Field visitors (FieldVisitorSum etc.) lived in DB/Core/Field.h. +# Forward the newer path to Field.h when the split-out header is absent. +if [ ! -e dbms/include/DB/Core/FieldVisitors.h ] && [ -e dbms/include/DB/Core/Field.h ]; then + printf '#pragma once\n#include \n' > dbms/include/DB/Core/FieldVisitors.h +fi # Auto-map every donor header of the same basename to the old # path: the statdaemons library's contents were dispersed into DB/Common/, # common/ and DB/Dictionaries/Embedded/ (e.g. Exception.h -> DB/Common/Exception.h, @@ -213,12 +296,17 @@ EOF #include #include #include +#include +#include using Poco::Util::Application; class BaseDaemon : public Poco::Util::ServerApplication { public: bool isCancelled() { return is_cancelled; } static BaseDaemon & instance() { return dynamic_cast(Poco::Util::Application::instance()); } + // The real daemon's sleep() woke early on shutdown; a plain sleep is fine here + // (used only for retry backoff, e.g. mysqlxx connection-pool reconnects). + void sleep(double seconds) { std::this_thread::sleep_for(std::chrono::duration(seconds)); } template void writeToGraphite(const std::string & key, const T & value, time_t timestamp = 0, const std::string & custom_root_path = "") { if (graphite_writer) graphite_writer->write(key, value, timestamp, custom_root_path); } template void writeToGraphite(const GraphiteWriter::KeyValueVector & key_vals, time_t timestamp = 0, const std::string & custom_root_path = "") { if (graphite_writer) graphite_writer->write(key_vals, timestamp, custom_root_path); } GraphiteWriter * getGraphiteWriter() { return graphite_writer.get(); } @@ -246,12 +334,31 @@ EOF fi echo '#pragma once' > contrib/statdaemons-compat/statdaemons/Interests.h +# The auto-map above only handles ; the pre-2015-11 trees also +# pull and (.hpp / a subdir). +# By PATCH_REF these live in-tree as and +# (overlaid); forward the old paths to them. +[ -f libs/libcommon/include/common/threadpool.hpp ] && \ + printf '#pragma once\n#include \n' > contrib/statdaemons-compat/statdaemons/threadpool.hpp +if [ -d libs/libcommon/include/ext ]; then + mkdir -p contrib/statdaemons-compat/statdaemons/ext + for h in libs/libcommon/include/ext/*.hpp; do + [ -f "$h" ] || continue; base="$(basename "$h")" + printf '#pragma once\n#include \n' "$base" > "contrib/statdaemons-compat/statdaemons/ext/${base}" + done +fi + # -- Yandex/ -> common/: the old include prefix for the common utilities that the # donor renamed to common/ (e.g. == ). # Expose the donor's common headers under the old Yandex/ prefix. -- if [ -d libs/libcommon/include/common ]; then mkdir -p contrib/yandex-compat ln -sfn "$(pwd)/libs/libcommon/include/common" contrib/yandex-compat/Yandex + # Yandex/Revision.h: the tiny public revision header, external in that era. The + # in-tree libcommon/src/Revision.cpp defines Revision::get() (reading REVISION + # from the generated revision.h); just declare it so the include resolves. + [ -e libs/libcommon/include/common/Revision.h ] || \ + printf '#pragma once\nnamespace Revision { unsigned get(); }\n' > libs/libcommon/include/common/Revision.h fi # -- double-conversion: the old code includes ; the @@ -261,6 +368,42 @@ if [ -f contrib/libdouble-conversion/double-conversion/double-conversion.h ]; th printf '#pragma once\n#include \n' > contrib/dc-compat/src/double-conversion.h fi +# -- strconvert/escape.h: another never-public Yandex string-escaping header. The +# only compiled use is MySQLDictionarySource's escaped_for_like (MySQL external +# dictionaries -- never exercised by the benchmark); strconvert::hash appears only +# in the OLAP server code, which is excluded from the build. Provide equivalents +# (escaped_for_like is identity-safe for compile-only use). -- +mkdir -p contrib/strconvert-compat/strconvert +cat > contrib/strconvert-compat/strconvert/escape.h <<'EOF' +#pragma once +#include +#include +namespace strconvert +{ + // MySQL external dictionaries are unsupported in this reconstructed build, so + // the escaping only needs to compile (this path is never executed). + inline std::string escaped_for_like(const std::string & s) { return s; } + inline std::size_t hash(const std::string & s) { std::size_t h = 0; for (char c : s) h = h * 131 + static_cast(c); return h; } +} +EOF +# strconvert/hash64.h: used by the legacy OLAP server code (OLAPAttributesMetadata) +# to hash attribute names. A deterministic 64-bit hash (FNV-1a) suffices; the OLAP +# protocol is not exercised by the benchmark. +cat > contrib/strconvert-compat/strconvert/hash64.h <<'EOF' +#pragma once +#include +#include +namespace strconvert +{ + inline std::uint64_t hash64(const std::string & s) + { + std::uint64_t h = 14695981039346656037ULL; + for (char c : s) { h ^= static_cast(c); h *= 1099511628211ULL; } + return h; + } +} +EOF + # -- stats/*: the pre-2015-12 trees include several headers from an external Yandex # "stats" library that was never open-sourced. At the 2015-11 -> 2015-12 boundary # these were inlined into the repo (a coordinated refactor). We reproduce that: @@ -407,10 +550,21 @@ for root, _dirs, files in os.walk('dbms'): f.writelines(lines) PYEOF +# -- ConnectionPoolWithFailover: the external (pre-2015-11) PoolWithFailoverBase +# exposed a 1-arg virtual getMany(settings); the back-ported base has a 2-arg +# getMany(settings, get_all) (non-virtual). Adapt the derived client's override +# so it compiles against the newer base. This is distributed-query plumbing the +# single-node benchmark never exercises, so only compilation matters. -- +CPF=dbms/include/DB/Client/ConnectionPoolWithFailover.h +if [ -f "$CPF" ] && grep -q 'getMany(const Settings \* settings = nullptr) override' "$CPF"; then + sed -i 's#getMany(const Settings \* settings = nullptr) override#getMany(const Settings * settings = nullptr, bool get_all = false)#' "$CPF" + sed -i 's#return Base::getMany(settings);#return Base::getMany(settings, get_all);#' "$CPF" +fi + # -- root CMakeLists: add the quicklz/re2_st include dirs and, on the C++ flags, # -fpermissive plus the force-included cmath shim (anchored on the donor's # stable libcityhash include line / -std=gnu++1y flag) -- -sed -i 's#include_directories (${METRICA_SOURCE_DIR}/contrib/libcityhash/)#include_directories (${METRICA_SOURCE_DIR}/contrib/quicklz-stub/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/re2_st_gen/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/statdaemons-compat/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/yandex-compat/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/dc-compat/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/stats-compat/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/libcityhash/)#' CMakeLists.txt +sed -i 's#include_directories (${METRICA_SOURCE_DIR}/contrib/libcityhash/)#include_directories (${METRICA_SOURCE_DIR}/contrib/quicklz-stub/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/re2_st_gen/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/statdaemons-compat/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/yandex-compat/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/dc-compat/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/stats-compat/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/strconvert-compat/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/libcityhash/)#' CMakeLists.txt # Force-include a few standard headers: on this (trusty) toolchain they aren't # pulled in transitively the way the newer 16.04/boost-1.58 headers were, so code # that assumes std::accumulate () / std::mt19937 () is in scope diff --git a/versions/cloud-init.sh.in b/versions/cloud-init.sh.in index d091b30eb8..c97fdc3c0a 100644 --- a/versions/cloud-init.sh.in +++ b/versions/cloud-init.sh.in @@ -14,8 +14,15 @@ export DEBIAN_FRONTEND=noninteractive apt-get update -y # docker-buildx: run-version.sh builds unpublished (clickhouse-built:*) versions # from source with `docker buildx` (the legacy builder hangs on recent engines). -apt-get install -y docker.io docker-buildx git wget curl jq zstd pv aria2 +# earlyoom: loading all datasets in parallel (and heavy joins on old, less +# memory-efficient versions) can exhaust RAM; without it the kernel thrashes and +# the whole VM gets stuck (never terminating, wasting the instance). earlyoom kills +# the offending process early instead — the server crash is then recovered by +# run-version.sh's revive_server, or the query is just recorded null. Same as the +# main ClickBench cloud-init. +apt-get install -y docker.io docker-buildx git wget curl jq zstd pv aria2 earlyoom systemctl enable --now docker +systemctl enable --now earlyoom git clone --depth 1 'https://github.com/@repo@.git' --branch '@branch@' ClickBench cd ClickBench/versions diff --git a/versions/run-version.sh b/versions/run-version.sh index 1ca59856f4..a4639d7034 100755 --- a/versions/run-version.sh +++ b/versions/run-version.sh @@ -217,10 +217,14 @@ load_data() { local ds pids=() : > "${LOAD_STATS}" # fresh per run; per-table load times accumulate here for ds in ${LOAD_DATASETS}; do + if ! dataset_supported "${ds}"; then + echo "=== skipping load of ${ds}: no query supported on ${VERSION} (all below min version) ===" >&2 + continue + fi load_one_dataset "${ds}" & pids+=("$!") done - wait "${pids[@]}" + [ "${#pids[@]}" -gt 0 ] && wait "${pids[@]}" echo "=== all dataset loads finished ===" } @@ -327,6 +331,20 @@ null_row() { for i in $(seq 1 "${TRIES}"); do out+="null"; [ "${i}" -ne "${TRIES}" ] && out+=", "; done echo "${out}]" } +# Is any query of runnable on the current VERSION? Reads the per-query +# minimum-version annotations (queries/.minver). Returns success if at least +# one query is supported ("0" or version >= its minver). When none are, the whole +# dataset is unsupported on this version, so there is no point loading it — every +# query would be recorded null anyway (see the skip logic in run_benchmark). +dataset_supported() { + local ds="$1" mvf="${HERE}/queries/${ds}.minver" mv + [ -f "${mvf}" ] || return 0 # no annotation -> assume supported + while IFS= read -r mv; do + [ -z "${mv}" ] && continue + { [ "${mv}" = "0" ] || version_ge "${VERSION}" "${mv}"; } && return 0 + done < "${mvf}" + return 1 +} # Run one query TRIES times, print a JSON array "[t1, ..., tN]" (null on error). # The remaining tries are skipped (recorded null) once a try either: From afdfdae98ead697a21bc594fc9cfd37d3f284187 Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Wed, 1 Jul 2026 21:32:08 +0000 Subject: [PATCH 030/120] versions: back off on all transient AWS errors (incl. API throttling) when launching MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit run-benchmark.sh already retried run-instances on capacity/quota errors (as the main ClickBench launcher does), but a version sweep fires dozens of launches back-to-back and hits EC2 API throttling (RequestLimitExceeded / Throttling) far more than the single-shot main launcher. A throttled call was treated as a hard error and skipped that version — a likely cause of the large contiguous gaps in the runs (e.g. whole 23.x / 24.x missing). Add RequestLimitExceeded / Throttling to the retry set and factor the backoff into an aws_retry helper used for run-instances AND the pre-launch describe-instance-types / describe-images calls (a throttled describe would otherwise blank arch/ami and make the launch fail non-retryably). Genuine config errors still fail fast. Co-Authored-By: Claude Opus 4.8 --- versions/run-benchmark.sh | 50 ++++++++++++++++++++++++--------------- 1 file changed, 31 insertions(+), 19 deletions(-) diff --git a/versions/run-benchmark.sh b/versions/run-benchmark.sh index 2cadd343fd..06b51bd4e7 100755 --- a/versions/run-benchmark.sh +++ b/versions/run-benchmark.sh @@ -28,6 +28,29 @@ volume="${volume:-1000}" # GB; headroom for loading all datas iops="${iops:-16000}" throughput="${throughput:-1000}" # MB/s +# Transient AWS errors that clear on their own: spare capacity frees as instances +# drain, service quotas free as other benchmarks finish, and API throttling +# (RequestLimitExceeded / Throttling) clears within seconds. A version sweep fires +# dozens of launches back-to-back and hits throttling far more than the single-shot +# main launcher, so we retry those too. aws_retry also guards the pre-launch +# describe-* calls — a throttled describe would blank arch/ami and make the launch +# fail with a non-retryable error, silently skipping that version. Genuine config +# errors (bad AMI, missing IAM perms, malformed user-data) don't match and fail +# fast, so a broken invocation never loops forever. +RETRY_RE='InsufficientInstanceCapacity|VcpuLimitExceeded|InstanceLimitExceeded|MaxSpotInstanceCountExceeded|RequestLimitExceeded|Throttling' +aws_retry() { + local out rc + while :; do + out=$(AWS_PAGER='' "$@" 2>&1) && rc=0 || rc=$? + if [ "${rc}" -eq 0 ]; then printf '%s\n' "${out}"; return 0; fi + if printf '%s' "${out}" | grep -qE "${RETRY_RE}"; then + printf 'aws: %s, retrying in 60s...\n' "$(printf '%s' "${out}" | grep -oE "${RETRY_RE}" | head -n1)" >&2 + sleep 60; continue + fi + printf '%s\n' "${out}" >&2; return "${rc}" # different error — don't loop + done +} + # Resolve the version against list-versions.sh: accept an exact version # (26.6.1.1193, 1.1.54378, 53973) or a prefix at a dot boundary, choosing the # latest match by version sort (26.6 -> 26.6.1.1193, 24 -> 24.12.x, 1.1 -> the @@ -50,8 +73,8 @@ if [[ "${image}" == clickhouse-built:* ]]; then [ -z "${tag}" ] && { echo "no build recipe for ${VERSION} in versions.txt" >&2; exit 1; } fi -arch=$(aws ec2 describe-instance-types --instance-types "$machine" --query 'InstanceTypes[0].ProcessorInfo.SupportedArchitectures' --output text) -ami=$(aws ec2 describe-images --owners amazon --filters "Name=name,Values=ubuntu/images/hvm-ssd-gp3/ubuntu-noble-24.04*" "Name=architecture,Values=${arch}" "Name=state,Values=available" --query 'sort_by(Images, &CreationDate) | [-1].[ImageId]' --output text) +arch=$(aws_retry aws ec2 describe-instance-types --instance-types "$machine" --query 'InstanceTypes[0].ProcessorInfo.SupportedArchitectures' --output text) +ami=$(aws_retry aws ec2 describe-images --owners amazon --filters "Name=name,Values=ubuntu/images/hvm-ssd-gp3/ubuntu-noble-24.04*" "Name=architecture,Values=${arch}" "Name=state,Values=available" --query 'sort_by(Images, &CreationDate) | [-1].[ImageId]' --output text) awk -v repo="$repo" -v branch="$branch" -v version="$VERSION" -v image="$image" \ -v tag="$tag" -v gcc="$gcc" -v datasets="$datasets" -v tries="$tries" -v t="$timeout" ' @@ -62,20 +85,9 @@ awk -v repo="$repo" -v branch="$branch" -v version="$VERSION" -v image="$image" print }' cloud-init.sh.in > "cloud-init.${VERSION}.sh" -# Retry on transient capacity / quota errors (same shape as the main launcher). -RETRY_RE='InsufficientInstanceCapacity|VcpuLimitExceeded|InstanceLimitExceeded|MaxSpotInstanceCountExceeded' -while :; do - out=$(AWS_PAGER='' aws ec2 run-instances --image-id "$ami" --instance-type "$machine" \ - --block-device-mappings "DeviceName=/dev/sda1,Ebs={DeleteOnTermination=true,VolumeSize=${volume},VolumeType=gp3,Iops=${iops},Throughput=${throughput}}" \ - --instance-initiated-shutdown-behavior terminate \ - --tag-specifications "ResourceType=instance,Tags=[{Key=Name,Value=clickbench-versions-${VERSION}}]" \ - --user-data "file://cloud-init.${VERSION}.sh" 2>&1) && rc=0 || rc=$? - - if [ "$rc" -eq 0 ]; then printf '%s\n' "$out"; break; fi - reason=$(printf '%s' "$out" | grep -oE "$RETRY_RE" | head -n1) - if [ -n "$reason" ]; then - printf 'run-instances: %s for %s, retrying in 60s...\n' "$reason" "$machine" >&2 - sleep 60; continue - fi - printf '%s\n' "$out" >&2; exit "$rc" -done +# Launch the VM, backing off on transient capacity / quota / throttling errors. +aws_retry aws ec2 run-instances --image-id "$ami" --instance-type "$machine" \ + --block-device-mappings "DeviceName=/dev/sda1,Ebs={DeleteOnTermination=true,VolumeSize=${volume},VolumeType=gp3,Iops=${iops},Throughput=${throughput}}" \ + --instance-initiated-shutdown-behavior terminate \ + --tag-specifications "ResourceType=instance,Tags=[{Key=Name,Value=clickbench-versions-${VERSION}}]" \ + --user-data "file://cloud-init.${VERSION}.sh" From 94fde03c56b1f2d09b5bf9e31cab27f0076efd50 Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Wed, 1 Jul 2026 22:58:56 +0000 Subject: [PATCH 031/120] versions: record reconstructed 2015-09 build MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit 2015-09 (0.0.53330) reconstructs and boots with no new fixes — the 2015-10 back-port (vendored Exception/statdaemons infra/strconvert) covers it. Recorded in monthly-built.tsv. 2015-09 is the clean reconstruction floor. Earlier months hit deep, era-specific walls that are not mechanical reconstruction: * 2015-08 — uniqHLL12 instantiates the HyperLogLog counter on raw Float32/Float64, but the back-ported (2015-12) HLL bit-shifts the hash value and cannot compile for float; 2015-09 restructured that code, and the era's float-capable HLL was in the never-public external stats library. * 2015-07 and earlier — the DateLUT API was refactored at the 2015-07 -> 2015-08 boundary (DateLUT::instance() returned DateLUT& with a Values struct; the donor provides const DateLUTImpl&), and DateLUT is used pervasively. Co-Authored-By: Claude Opus 4.8 --- versions/build-from-source/monthly-built.tsv | 1 + 1 file changed, 1 insertion(+) diff --git a/versions/build-from-source/monthly-built.tsv b/versions/build-from-source/monthly-built.tsv index 9f62e6782b..a3535cb341 100644 --- a/versions/build-from-source/monthly-built.tsv +++ b/versions/build-from-source/monthly-built.tsv @@ -3,3 +3,4 @@ 2015-12-01 a7387d9ce431a1f288d1a4898fa0c0c36c765abc 2015-11-30 2015-11-01 b17cc7181edbb05637b23f2f632d44d092e276e5 0.0.53350 2015-10-01 c915538fa788697feea7910c7de5339f6b5a2ce2 0.0.53340 +2015-09-01 bc5007fc36ba2a81a6b45b9e9b0b26ff09efa994 0.0.53330 From 8c147b5d93180c7976282f467ba7dd69e34421b9 Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Wed, 1 Jul 2026 23:20:44 +0000 Subject: [PATCH 032/120] versions: reconstruct 2015-08 (creative float-uniq + HLL counter arg-order fix) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit 2015-08 (0.0.53320) now builds and boots. Two era-specific fixes, both no-ops on newer months: * HyperLogLog counter template arg order — pre-2015-09 HyperLogLogWithSmallSetOptimization instantiates the counter as HyperLogLogCounter (old 3-arg form), but the back-ported counter inserted a HashValueType 3rd parameter, so the old call put DenominatorType (float) in the HashValueType slot and the counter tried to bit-shift a float. Insert the UInt32 HashValueType (the IntHash32 result type), matching 2015-09+. CombinedCardinalityEstimator reaches the counter through SmallSetOptimization, so this one line covers both paths. The sed only matches the old 3-arg form, so newer trees are untouched. * uniq on Float32/Float64 — AggregateFunctionUniq{HLL12,Combined}Data typedef their Set over the raw column type, while OneAdder inserts the hashed value (UInt64). Add Float32/Float64 data specializations that use a UInt64 Set (as the existing specialization does), so the HLL is only ever built on UInt64 — both correct and consistent with the back-ported counter. Also append ErrorCodes::NO_AVAILABLE_DATA (added to the enum after 2015-08) when absent, so the back-ported CompactArray/HLL compile. monthly-built.tsv records 2015-08. Co-Authored-By: Claude Opus 4.8 --- versions/build-from-source/monthly-built.tsv | 1 + versions/build-from-source/reconstruct.sh | 63 ++++++++++++++++++++ 2 files changed, 64 insertions(+) diff --git a/versions/build-from-source/monthly-built.tsv b/versions/build-from-source/monthly-built.tsv index a3535cb341..6637c214c5 100644 --- a/versions/build-from-source/monthly-built.tsv +++ b/versions/build-from-source/monthly-built.tsv @@ -4,3 +4,4 @@ 2015-11-01 b17cc7181edbb05637b23f2f632d44d092e276e5 0.0.53350 2015-10-01 c915538fa788697feea7910c7de5339f6b5a2ce2 0.0.53340 2015-09-01 bc5007fc36ba2a81a6b45b9e9b0b26ff09efa994 0.0.53330 +2015-08-01 3eb7c149aba7bc650e27cc40885cf29e3332c94b 0.0.53320 diff --git a/versions/build-from-source/reconstruct.sh b/versions/build-from-source/reconstruct.sh index f26acf088e..e2c5e315df 100755 --- a/versions/build-from-source/reconstruct.sh +++ b/versions/build-from-source/reconstruct.sh @@ -561,6 +561,69 @@ if [ -f "$CPF" ] && grep -q 'getMany(const Settings \* settings = nullptr) overr sed -i 's#return Base::getMany(settings);#return Base::getMany(settings, get_all);#' "$CPF" fi +# -- ErrorCodes::NO_AVAILABLE_DATA: the back-ported CompactArray/HyperLogLog throw +# with this code, added to the enum only after 2015-08. Append it (with a free +# number) to the era's enum when absent, so those overlaid headers compile. -- +EC=dbms/include/DB/Core/ErrorCodes.h +if [ -f "$EC" ] && ! grep -q 'NO_AVAILABLE_DATA' "$EC"; then + python3 - "$EC" <<'PYEOF' +import sys, re +p = sys.argv[1] +s = open(p, encoding='utf-8', errors='surrogateescape').read() +m = re.search(r'enum ErrorCodes\s*\{', s) +if m: + end = s.index('};', m.end()) + nums = [int(n) for n in re.findall(r'=\s*(\d+)', s[m.end():end])] + s = s[:end] + ('\t\tNO_AVAILABLE_DATA = %d,\n\t' % ((max(nums) + 1) if nums else 10000)) + s[end:] + open(p, 'w', encoding='utf-8', errors='surrogateescape').write(s) +PYEOF +fi + +# -- uniq on Float32/Float64 (pre-2015-09): AggregateFunctionUniq{HLL12,Combined}Data +# typedef their HyperLogLog / CombinedCardinalityEstimator Set over the raw column +# type T, so uniq(Float) instantiates the HLL on `float`. But OneAdder inserts the +# *hashed* value (AggregateFunctionUniqTraits::hash -> UInt64), and the +# back-ported HLL bit-shifts its value type (can't be float). Add Float32/Float64 +# data specializations that use a UInt64 Set (exactly as the existing +# specialization does) -- the HLL is then only ever built on UInt64, which both +# compiles and is correct (2015-09+ restructured the code the same way). -- +AFU=dbms/include/DB/AggregateFunctions/AggregateFunctionUniq.h +if [ -f "$AFU" ] && grep -q 'AggregateFunctionUniqHLL12Data' "$AFU" \ + && ! grep -q 'AggregateFunctionUniqHLL12Data' "$AFU"; then + python3 - "$AFU" <<'PYEOF' +import sys +p = sys.argv[1] +s = open(p, encoding='utf-8', errors='surrogateescape').read() +def add_after_string_spec(s, base, body): + key = 'struct %s' % base + if key not in s: + return s + j = s.index('};', s.index(key)) + 2 # end of the specialization + return s[:j] + body + s[j:] +hll = ''.join('\n\ntemplate <>\nstruct AggregateFunctionUniqHLL12Data<%s>\n{\n' + '\ttypedef HyperLogLogWithSmallSetOptimization Set;\n\tSet set;\n' + '\tstatic String getName() { return "uniqHLL12"; }\n};' % t for t in ('Float32', 'Float64')) +comb = ''.join('\n\ntemplate <>\nstruct AggregateFunctionUniqCombinedData<%s>\n{\n' + '\tusing Key = UInt64;\n\tusing Set = CombinedCardinalityEstimator, HashTableGrower<4> >, 16, 16, 19>;\n\tSet set;\n' + '\tstatic String getName() { return "uniqCombined"; }\n};' % t for t in ('Float32', 'Float64')) +s = add_after_string_spec(s, 'AggregateFunctionUniqHLL12Data', hll) +s = add_after_string_spec(s, 'AggregateFunctionUniqCombinedData', comb) +open(p, 'w', encoding='utf-8', errors='surrogateescape').write(s) +PYEOF +fi + +# -- HyperLogLog counter template arg order: pre-2015-09 +# HyperLogLogWithSmallSetOptimization instantiates the counter as +# HyperLogLogCounter (old 3-arg form). The back-ported +# (PATCH_REF) counter inserted a HashValueType 3rd parameter, so the old call puts +# DenominatorType (float) in the HashValueType slot -> the counter bit-shifts a +# float and won't compile. Insert the UInt32 HashValueType (the IntHash32 result +# type), matching 2015-09+. CombinedCardinalityEstimator reaches the counter +# through SmallSetOptimization, so this single fix covers both. The sed only +# matches the old 3-arg form, so it's a no-op on trees that already pass 4 args. -- +SSO=dbms/include/DB/Common/HyperLogLogWithSmallSetOptimization.h +[ -f "$SSO" ] && sed -i 's#HyperLogLogCounter#HyperLogLogCounter#' "$SSO" + # -- root CMakeLists: add the quicklz/re2_st include dirs and, on the C++ flags, # -fpermissive plus the force-included cmath shim (anchored on the donor's # stable libcityhash include line / -std=gnu++1y flag) -- From 8bb5ba4f58501cd22cc63c3f9e25c718b6a8053f Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Wed, 1 Jul 2026 23:39:12 +0000 Subject: [PATCH 033/120] versions: reconstruct 2015-07 (DateLUT split migration + assertChar + column rename) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit 2015-07 (0.0.53310) now builds and boots. Three era-specific source migrations in reconstruct.sh, all guarded to be no-ops on already-migrated trees (2015-08+): * DateLUT split — the monolithic calendar class DateLUT was split into DateLUT (a singleton whose instance() returns `const DateLUTImpl &`) and DateLUTImpl (the calendar, carrying the Values struct). The donor supplies the split (its DateLUT.cpp/DateLUTImpl.cpp overwrite the era's). A python pass migrates the era's ~15 consumers exactly as 2015-08 did: `DateLUT & x = DateLUT::instance()` -> `const auto & x = ...`, `DateLUT::Values` -> `DateLUTImpl::Values`, and any remaining reference/pointer to the (read-only) calendar -> `const DateLUTImpl &`. `DateLUT::instance().()`, `DateLUT::` statics and `Singleton` are left alone; the DateLUT headers themselves are skipped. * assertChar — the back-ported Embedded dictionaries call DB::assertChar, a ReadHelpers function added after 2015-07. Add it inline in terms of the era's existing assertString (no new .cpp / error code). * ColumnWithNameAndType -> ColumnWithTypeAndName — the struct was renamed after 2015-07; the back-ported SummingSorted uses the new name. Add a compat alias against the old type (guarded on the old header existing and the new one not). Verified 2015-08 still builds (the migrations are no-ops there). monthly-built.tsv records 2015-07. Co-Authored-By: Claude Opus 4.8 --- versions/build-from-source/monthly-built.tsv | 1 + versions/build-from-source/reconstruct.sh | 77 ++++++++++++++++++++ 2 files changed, 78 insertions(+) diff --git a/versions/build-from-source/monthly-built.tsv b/versions/build-from-source/monthly-built.tsv index 6637c214c5..dff985fa2a 100644 --- a/versions/build-from-source/monthly-built.tsv +++ b/versions/build-from-source/monthly-built.tsv @@ -5,3 +5,4 @@ 2015-10-01 c915538fa788697feea7910c7de5339f6b5a2ce2 0.0.53340 2015-09-01 bc5007fc36ba2a81a6b45b9e9b0b26ff09efa994 0.0.53330 2015-08-01 3eb7c149aba7bc650e27cc40885cf29e3332c94b 0.0.53320 +2015-07-01 719f0ee89cc560a96bec8d527ff7316f13101b33 0.0.53310 diff --git a/versions/build-from-source/reconstruct.sh b/versions/build-from-source/reconstruct.sh index e2c5e315df..c506862037 100755 --- a/versions/build-from-source/reconstruct.sh +++ b/versions/build-from-source/reconstruct.sh @@ -624,6 +624,83 @@ fi SSO=dbms/include/DB/Common/HyperLogLogWithSmallSetOptimization.h [ -f "$SSO" ] && sed -i 's#HyperLogLogCounter#HyperLogLogCounter#' "$SSO" +# -- DateLUT API migration (pre-2015-08): the monolithic calendar class DateLUT was +# split into DateLUT (a singleton whose instance() returns `const DateLUTImpl &`) +# and DateLUTImpl (the calendar, carrying the `Values` struct). The donor supplies +# that split (and its DateLUT.cpp/DateLUTImpl.cpp overwrite the era's old ones), so +# migrate the era's consumers exactly as 2015-08 did: +# * `DateLUT & x = DateLUT::instance(...)` -> `const auto & x = DateLUT::instance(...)` +# (the returned reference is now `const DateLUTImpl &`), and +# * `DateLUT::Values` -> `DateLUTImpl::Values`. +# `DateLUT::instance().()` already works (it returns a DateLUTImpl). A no-op +# on trees already migrated (2015-08+), which have neither pattern. -- +python3 - <<'PYEOF' +import os, re +# `DateLUT & x = DateLUT::instance(...)` -> `const auto & x = ...` (the reference is +# now const, so `const auto &` is required; a bare `DateLUTImpl &` would fail const). +ref = re.compile(r'(?:const\s+)?DateLUT\s*&\s*([A-Za-z_]\w*)\s*=\s*DateLUT::instance\(([^)]*)\)') +for base in ('dbms', 'libs'): + for root, _dirs, files in os.walk(base): + for fn in files: + if not fn.endswith(('.h', '.hpp', '.cpp', '.inl')): + continue + if fn.startswith('DateLUT'): # don't rewrite the headers that DEFINE the classes + continue + p = os.path.join(root, fn) + try: + with open(p, encoding='utf-8', errors='surrogateescape') as f: + s = f.read() + except OSError: + continue + if 'DateLUT' not in s: + continue + ns = ref.sub(r'const auto & \1 = DateLUT::instance(\2)', s) + ns = ns.replace('DateLUT::Values', 'DateLUTImpl::Values') + # Any remaining reference/pointer to `DateLUT` (e.g. a `DateLUT &` function + # parameter carrying the calendar) is really the DateLUTImpl now — and it is + # read-only, since DateLUT::instance() returns `const DateLUTImpl &`, so make + # the target const (a non-const ref won't bind the const instance). Do the + # already-const forms first so we never produce `const const`. `DateLUT::` + # (instance()/statics) and `Singleton` have no ` &`/`*` and are left + # alone. + ns = ns.replace('const DateLUT &', 'const DateLUTImpl &').replace('DateLUT &', 'const DateLUTImpl &') + ns = ns.replace('const DateLUT&', 'const DateLUTImpl&').replace('DateLUT&', 'const DateLUTImpl&') + ns = ns.replace('const DateLUT *', 'const DateLUTImpl *').replace('DateLUT *', 'const DateLUTImpl *') + ns = ns.replace('const DateLUT*', 'const DateLUTImpl*').replace('DateLUT*', 'const DateLUTImpl*') + if ns != s: + with open(p, 'w', encoding='utf-8', errors='surrogateescape') as f: + f.write(ns) +PYEOF + +# -- assertChar: the back-ported Embedded dictionaries (RegionsHierarchy/RegionsNames) +# call DB::assertChar, a ReadHelpers function added after 2015-07. Add it inline in +# terms of the era's existing assertString (no new .cpp / error code) when absent. -- +RH=dbms/include/DB/IO/ReadHelpers.h +if [ -f "$RH" ] && ! grep -q 'assertChar' "$RH"; then + python3 - "$RH" <<'PYEOF' +import sys +p = sys.argv[1] +s = open(p, encoding='utf-8', errors='surrogateescape').read() +anchor = 'void assertString(const char * s, ReadBuffer & buf);' +if anchor in s: + i = s.index(anchor) + len(anchor) + add = ('\n\n/// Added by reconstruct.sh: assertChar (used by the back-ported Embedded' + '\n/// dictionaries); implemented via the era\'s existing assertString.' + '\ninline void assertChar(char symbol, ReadBuffer & buf)' + '\n{\n\tconst char s[2] = { symbol, 0 };\n\tassertString(s, buf);\n}') + open(p, 'w', encoding='utf-8', errors='surrogateescape').write(s[:i] + add + s[i:]) +PYEOF +fi + +# -- ColumnWithNameAndType -> ColumnWithTypeAndName: the struct was renamed after +# 2015-07. The back-ported SummingSorted uses the new name; add a compat alias so +# it resolves against the era's old type. Guarded on the old header existing and +# the new one not, so it's a no-op once the rename landed (2015-08+). -- +CWN=dbms/include/DB/Core/ColumnWithNameAndType.h +if [ -f "$CWN" ] && [ ! -f dbms/include/DB/Core/ColumnWithTypeAndName.h ]; then + printf '\nnamespace DB { using ColumnWithTypeAndName = ColumnWithNameAndType; }\n' >> "$CWN" +fi + # -- root CMakeLists: add the quicklz/re2_st include dirs and, on the C++ flags, # -fpermissive plus the force-included cmath shim (anchored on the donor's # stable libcityhash include line / -std=gnu++1y flag) -- From a4e5968b0fcbfa87672a2ece844a19888572c469 Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Wed, 1 Jul 2026 23:54:13 +0000 Subject: [PATCH 034/120] versions: reconstruct 2015-06 (vendor the old 2-arg PoolWithFailoverBase) 2015-06 builds and boots (SELECT 1 works; the version() SQL function postdates this era). The failover connection-pool base was reworked from a 2-arg template (external statdaemons lib) into a single-arg in-repo class in 2015-07, so the back-ported 1-arg version is incompatible with this era's ConnectionPoolWithFailover (wrong template arity; also wants a later Settings::skip_unavailable_shards field). Only ConnectionPoolWithFailover derives from the base, and the single-node benchmark never configures remote_servers (the pool is never constructed), so vendor a minimal 2-arg PoolWithFailoverBase exposing just the surface the derived class uses (ctor, nested_pools[].pool/.state.priority, get/getMany/tryGet); get()/getMany() throw if ever called. It is created before the statdaemons auto-map so it wins over the 1-arg forward, which also means the incompatible filled base is never included (killing the skip_unavailable_shards error). Guarded on the 2-arg form, so it is skipped on 2015-07+. monthly-built.tsv records 2015-06. Co-Authored-By: Claude Opus 4.8 --- versions/build-from-source/monthly-built.tsv | 1 + versions/build-from-source/reconstruct.sh | 75 ++++++++++++++++++++ 2 files changed, 76 insertions(+) diff --git a/versions/build-from-source/monthly-built.tsv b/versions/build-from-source/monthly-built.tsv index dff985fa2a..c8d88b18f8 100644 --- a/versions/build-from-source/monthly-built.tsv +++ b/versions/build-from-source/monthly-built.tsv @@ -6,3 +6,4 @@ 2015-09-01 bc5007fc36ba2a81a6b45b9e9b0b26ff09efa994 0.0.53330 2015-08-01 3eb7c149aba7bc650e27cc40885cf29e3332c94b 0.0.53320 2015-07-01 719f0ee89cc560a96bec8d527ff7316f13101b33 0.0.53310 +2015-06-01 d378c76964b58eae67fbe41fa9d54694b5e88f99 boots(pre-version()) diff --git a/versions/build-from-source/reconstruct.sh b/versions/build-from-source/reconstruct.sh index c506862037..263e33ee63 100755 --- a/versions/build-from-source/reconstruct.sh +++ b/versions/build-from-source/reconstruct.sh @@ -249,6 +249,81 @@ fi if [ ! -e dbms/include/DB/Core/FieldVisitors.h ] && [ -e dbms/include/DB/Core/Field.h ]; then printf '#pragma once\n#include \n' > dbms/include/DB/Core/FieldVisitors.h fi + +# -- PoolWithFailoverBase (pre-2015-07): the failover connection-pool base lived in +# the never-public external statdaemons library and took TWO template args +# . It was reworked into a single-arg in-repo class in +# 2015-07; the back-ported (PATCH_FILL) 1-arg version is incompatible with this +# era's ConnectionPoolWithFailover (wrong arity, needs Settings::skip_unavailable_shards). +# Only ConnectionPoolWithFailover derives from it, and the single-node benchmark +# never configures remote_servers, so the pool is never even constructed. Vendor a +# minimal 2-arg base exposing just the surface the derived class uses (ctor, +# nested_pools[].pool/.state.priority, get/getMany/tryGet); get/getMany simply +# throw. Created before the auto-map so it wins over the 1-arg forward, which means +# the incompatible filled base is never included. Guarded on the 2-arg form, so it +# is skipped on 2015-07+ (their 1-arg ConnectionPoolWithFailover uses the fill). -- +if [ -f dbms/include/DB/Client/ConnectionPoolWithFailover.h ] \ + && grep -qE 'PoolWithFailoverBase<[^,>]+,' dbms/include/DB/Client/ConnectionPoolWithFailover.h; then + cat > contrib/statdaemons-compat/statdaemons/PoolWithFailoverBase.h <<'EOF' +#pragma once +// Vendored 2-argument PoolWithFailoverBase for pre-2015-07 trees (the failover pool +// base was external then). Distributed connections are never opened by the +// single-node benchmark, so this only needs to compile and expose the small surface +// ConnectionPoolWithFailover uses; get()/getMany() throw if ever called. +#include +#include +#include +#include +#include +#include +#include + +template +class PoolWithFailoverBase +{ +public: + using NestedPool = TNestedPool; + using NestedPoolPtr = Poco::SharedPtr; + using Entry = typename TNestedPool::Entry; + + struct PoolState { std::size_t priority = 0; }; + struct PoolWithState { NestedPoolPtr pool; PoolState state; }; + using NestedPools = std::vector; + + PoolWithFailoverBase(NestedPools & nested_pools_, std::size_t max_tries_, + time_t decrease_error_period_, Poco::Logger * log_) + : max_tries(max_tries_), decrease_error_period(decrease_error_period_), log(log_) + { + nested_pools.reserve(nested_pools_.size()); + for (const auto & p : nested_pools_) + { + PoolWithState pws; + pws.pool = p; + nested_pools.push_back(pws); + } + } + virtual ~PoolWithFailoverBase() {} + + Entry get(TSettings) + { + throw Poco::Exception("Distributed connection pool is not available in this reconstructed build"); + } + std::vector getMany(TSettings) + { + throw Poco::Exception("Distributed connection pool is not available in this reconstructed build"); + } + +protected: + virtual bool tryGet(NestedPoolPtr pool, TSettings settings, Entry & out_entry, + std::stringstream & fail_message) = 0; + + std::vector nested_pools; + std::size_t max_tries; + time_t decrease_error_period; + Poco::Logger * log; +}; +EOF +fi # Auto-map every donor header of the same basename to the old # path: the statdaemons library's contents were dispersed into DB/Common/, # common/ and DB/Dictionaries/Embedded/ (e.g. Exception.h -> DB/Common/Exception.h, From 8e2d01365ee03f67c2f981c147a5fe16f21d4a02 Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Thu, 2 Jul 2026 00:10:26 +0000 Subject: [PATCH 035/120] versions: reconstruct 2015-03..2015-05 (flat pool priority + tryLogCurrentException overload) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit 2015-04 and 2015-05 build with no new fixes (the 2015-06 pool vendoring carries). 2015-03 needed two small era-specific additions, both guarded no-ops on newer trees: * the vendored 2-arg PoolWithFailoverBase's element now carries priority both directly (.priority, ~2015-03) and nested (.state.priority, ~2015-06), so either era's ConnectionPoolWithFailover compiles; * tryLogCurrentException(Poco::Logger *) overload — added after 2015-03 but called by the back-ported ErrorHandlers.h; the synthesized DB/Common/Exception.h forward now supplies it (forwarding to the era's name-based overload) only when the tree lacks it, so it doesn't clash on 2015-04+. All boot (SELECT 1; version() postdates this era). Verified 2015-06 still builds. monthly-built.tsv records 2015-03/04/05. Co-Authored-By: Claude Opus 4.8 --- versions/build-from-source/monthly-built.tsv | 3 +++ versions/build-from-source/reconstruct.sh | 17 +++++++++++++++-- 2 files changed, 18 insertions(+), 2 deletions(-) diff --git a/versions/build-from-source/monthly-built.tsv b/versions/build-from-source/monthly-built.tsv index c8d88b18f8..f86fd47efc 100644 --- a/versions/build-from-source/monthly-built.tsv +++ b/versions/build-from-source/monthly-built.tsv @@ -7,3 +7,6 @@ 2015-08-01 3eb7c149aba7bc650e27cc40885cf29e3332c94b 0.0.53320 2015-07-01 719f0ee89cc560a96bec8d527ff7316f13101b33 0.0.53310 2015-06-01 d378c76964b58eae67fbe41fa9d54694b5e88f99 boots(pre-version()) +2015-05-01 9dfd271c684c7f7792751a9ea7c72c11604afda5 boots(pre-version()) +2015-04-01 54397c6c7a99cfa7cb293651356c8b65143669e1 boots(pre-version()) +2015-03-01 3e1dafe3cb96b69fc34df13cd10bdc79adfe2818 boots(pre-version()) diff --git a/versions/build-from-source/reconstruct.sh b/versions/build-from-source/reconstruct.sh index 263e33ee63..62adbb59d4 100755 --- a/versions/build-from-source/reconstruct.sh +++ b/versions/build-from-source/reconstruct.sh @@ -240,7 +240,17 @@ EOF # DB/Common path to it (only when the tree has no real DB/Common/Exception.h). if [ ! -e dbms/include/DB/Common/Exception.h ]; then mkdir -p dbms/include/DB/Common - printf '#pragma once\n#include \n' > dbms/include/DB/Common/Exception.h + { + printf '#pragma once\n#include \n' + # tryLogCurrentException(Poco::Logger *) overload was added after 2015-03; + # the back-ported ErrorHandlers.h calls it. Provide it (forwarding to the + # era's name-based overload) only when the tree lacks it, so it doesn't + # clash on 2015-04+ which already declare it. + if ! grep -q 'tryLogCurrentException(Poco::Logger' dbms/include/DB/Core/Exception.h 2>/dev/null; then + printf '#include \n' + printf 'namespace DB { inline void tryLogCurrentException(Poco::Logger * logger, const std::string & = "") { tryLogCurrentException(logger ? logger->name().c_str() : ""); } }\n' + fi + } > dbms/include/DB/Common/Exception.h fi fi # The back-ported SummingSortedBlockInputStream.h includes ; @@ -286,8 +296,11 @@ public: using NestedPoolPtr = Poco::SharedPtr; using Entry = typename TNestedPool::Entry; + // The element carries priority both directly (.priority, ~2015-03 era) and nested + // (.state.priority, ~2015-06 era) so either era's ConnectionPoolWithFailover + // compiles. get()/getMany() throw, so the value is never actually consulted. struct PoolState { std::size_t priority = 0; }; - struct PoolWithState { NestedPoolPtr pool; PoolState state; }; + struct PoolWithState { NestedPoolPtr pool; PoolState state; std::size_t priority = 0; }; using NestedPools = std::vector; PoolWithFailoverBase(NestedPools & nested_pools_, std::size_t max_tries_, From ccf0c808532b405284d3e5fd5b8867d6ba355bb3 Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Thu, 2 Jul 2026 00:19:25 +0000 Subject: [PATCH 036/120] versions: reconstruct 2015-01 and 2015-02 (ext::make_unique + CategoriesHierarchy stub) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit 2015-01 and 2015-02 build and boot. Two more era-specific compat additions: * ext/memory.hpp — provided ext::make_unique before C++14's std::make_unique and lived in the external statdaemons ext/; the donor dropped it. Vendor it (a thin make_unique) when not already forwarded. * CategoriesHierarchy — a Metrica embedded dictionary the donor removed, so the auto-map can't forward it. Stub it with the small interface Dictionaries.h / FunctionsDictionaries.h use (reload + templated toParent/toMostAncestor/ toSecondLevel/in); the benchmark never loads category dictionaries. The from-source reconstruction is now continuous from 2015-01 through 2016-02, joining the tagged 1.1.x / bare 2016 builds and every published image to today. Co-Authored-By: Claude Opus 4.8 --- versions/build-from-source/monthly-built.tsv | 2 ++ versions/build-from-source/reconstruct.sh | 36 ++++++++++++++++++++ 2 files changed, 38 insertions(+) diff --git a/versions/build-from-source/monthly-built.tsv b/versions/build-from-source/monthly-built.tsv index f86fd47efc..efef763f85 100644 --- a/versions/build-from-source/monthly-built.tsv +++ b/versions/build-from-source/monthly-built.tsv @@ -10,3 +10,5 @@ 2015-05-01 9dfd271c684c7f7792751a9ea7c72c11604afda5 boots(pre-version()) 2015-04-01 54397c6c7a99cfa7cb293651356c8b65143669e1 boots(pre-version()) 2015-03-01 3e1dafe3cb96b69fc34df13cd10bdc79adfe2818 boots(pre-version()) +2015-02-01 bd51359819f6ade46cf5de2e22e1fafc1d2080fc boots(pre-version()) +2015-01-01 43c75bb37b3b2f27d473296cc12d7e6314520505 boots(pre-version()) diff --git a/versions/build-from-source/reconstruct.sh b/versions/build-from-source/reconstruct.sh index 62adbb59d4..ace64ca755 100755 --- a/versions/build-from-source/reconstruct.sh +++ b/versions/build-from-source/reconstruct.sh @@ -421,6 +421,27 @@ EOF printf '// minimal daemon base (see reconstruct.sh)\n' > libs/libdaemon/src/BaseDaemon.cpp fi echo '#pragma once' > contrib/statdaemons-compat/statdaemons/Interests.h +# CategoriesHierarchy: a Metrica embedded dictionary the donor dropped (so the +# auto-map can't forward it). The benchmark never loads category dictionaries, so a +# no-op stub with the small interface Dictionaries.h / FunctionsDictionaries.h use is +# enough (templated methods avoid depending on the era's integer typedefs). Created +# only if the auto-map didn't already forward a real one. +if [ ! -e contrib/statdaemons-compat/statdaemons/CategoriesHierarchy.h ]; then + cat > contrib/statdaemons-compat/statdaemons/CategoriesHierarchy.h <<'EOF' +#pragma once +/// Stub for the never-vendored Metrica category hierarchy (unused by the benchmark). +class CategoriesHierarchy +{ +public: + CategoriesHierarchy() {} + void reload() {} + template T toParent(T x) const { return x; } + template T toMostAncestor(T x) const { return x; } + template T toSecondLevel(T x) const { return x; } + template bool in(T, T) const { return false; } +}; +EOF +fi # The auto-map above only handles ; the pre-2015-11 trees also # pull and (.hpp / a subdir). @@ -435,6 +456,21 @@ if [ -d libs/libcommon/include/ext ]; then printf '#pragma once\n#include \n' "$base" > "contrib/statdaemons-compat/statdaemons/ext/${base}" done fi +# ext/memory.hpp provided ext::make_unique before C++14's std::make_unique; the old +# statdaemons ext/ had it, the donor dropped it. Vendor it if not already forwarded. +if [ ! -e contrib/statdaemons-compat/statdaemons/ext/memory.hpp ]; then + mkdir -p contrib/statdaemons-compat/statdaemons/ext + cat > contrib/statdaemons-compat/statdaemons/ext/memory.hpp <<'EOF' +#pragma once +#include +#include +namespace ext +{ + template + std::unique_ptr make_unique(Args &&... args) { return std::unique_ptr(new T(std::forward(args)...)); } +} +EOF +fi # -- Yandex/ -> common/: the old include prefix for the common utilities that the # donor renamed to common/ (e.g. == ). From e7c042e8183ef811b51011dd520d41350cbb2a1f Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Thu, 2 Jul 2026 00:54:52 +0000 Subject: [PATCH 037/120] versions: reconstruct 2014-12 (RegionsNames::Language rename + intHashCRC32) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit First pre-2015 month. Two guarded, no-op-on-newer additions: * RegionsNames::SupportedLanguages::Enum/::RU -> Language/Language::RU — the region-name language enum was renamed (getLanguageEnum/getRegionName kept their names), so regionToName in FunctionsDictionaries matches the donor's RegionsNames. * intHashCRC32 (CRC32C via SSE4.2) was added to Hash.h after 2014-12 but is used by the back-ported UniquesHashSet; append it when absent, next to the intHash32 append. 2014-12 boots (SELECT 1). monthly-built.tsv records it. Co-Authored-By: Claude Opus 4.8 --- versions/build-from-source/monthly-built.tsv | 1 + versions/build-from-source/reconstruct.sh | 25 ++++++++++++++++++++ 2 files changed, 26 insertions(+) diff --git a/versions/build-from-source/monthly-built.tsv b/versions/build-from-source/monthly-built.tsv index efef763f85..3d8431f696 100644 --- a/versions/build-from-source/monthly-built.tsv +++ b/versions/build-from-source/monthly-built.tsv @@ -12,3 +12,4 @@ 2015-03-01 3e1dafe3cb96b69fc34df13cd10bdc79adfe2818 boots(pre-version()) 2015-02-01 bd51359819f6ade46cf5de2e22e1fafc1d2080fc boots(pre-version()) 2015-01-01 43c75bb37b3b2f27d473296cc12d7e6314520505 boots(pre-version()) +2014-12-01 da4c4a05663581f9729ad1bd000481fbcd1a0353 boots(pre-version()) diff --git a/versions/build-from-source/reconstruct.sh b/versions/build-from-source/reconstruct.sh index ace64ca755..69cae0baaa 100755 --- a/versions/build-from-source/reconstruct.sh +++ b/versions/build-from-source/reconstruct.sh @@ -569,6 +569,22 @@ struct IntHash32 }; EOF fi +# intHashCRC32 (CRC32C via SSE4.2) was added to Hash.h after 2014-12, but the +# back-ported UniquesHashSet uses it. Append it when absent (identical to the later +# definition). Matched on the definition, not the prose comment. +if [ -f "$HASH_H" ] && ! grep -q 'intHashCRC32(' "$HASH_H"; then + cat >> "$HASH_H" <<'EOF' + +/// Added by reconstruct.sh: CRC32C-based UInt64 -> UInt64 hash (SSE4.2), added to +/// this header after 2014-12; used by the back-ported UniquesHashSet. +inline DB::UInt64 intHashCRC32(DB::UInt64 x) +{ + DB::UInt64 crc = -1ULL; + asm("crc32q %[x], %[crc]\n" : [crc] "+r" (crc) : [x] "rm" (x)); + return crc; +} +EOF +fi printf '#pragma once\n#include \n' > contrib/stats-compat/stats/IntHash.h # The overlaid 2015-12 ReservoirSampler{,Deterministic}.h back a small sample buffer @@ -825,6 +841,15 @@ if [ -f "$CWN" ] && [ ! -f dbms/include/DB/Core/ColumnWithTypeAndName.h ]; then printf '\nnamespace DB { using ColumnWithTypeAndName = ColumnWithNameAndType; }\n' >> "$CWN" fi +# -- RegionsNames::SupportedLanguages -> Language: the region-name language enum was +# renamed (SupportedLanguages::Enum / ::RU -> Language / Language::RU); the methods +# getLanguageEnum() and getRegionName() kept their names. Rename the old references +# (regionToName in FunctionsDictionaries) to match the donor's RegionsNames. A +# no-op on 2015-01+, which no longer name the enum. -- +grep -rlZ 'RegionsNames::SupportedLanguages' dbms 2>/dev/null | while IFS= read -r -d '' f; do + sed -i 's#RegionsNames::SupportedLanguages::Enum#RegionsNames::Language#g; s#RegionsNames::SupportedLanguages::#RegionsNames::Language::#g' "$f" +done + # -- root CMakeLists: add the quicklz/re2_st include dirs and, on the C++ flags, # -fpermissive plus the force-included cmath shim (anchored on the donor's # stable libcityhash include line / -std=gnu++1y flag) -- From 339f4d17689c89501cbedaabc56cb947d28a1ac8 Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Thu, 2 Jul 2026 01:13:13 +0000 Subject: [PATCH 038/120] versions: reconstruct 2014-11 (conditional SummingSorted overlay + stdext + time2str) 2014-11 builds and boots. Changes, all guarded no-ops on newer months: * SummingSorted overlay is now CONDITIONAL: only the ~2015-05..2015-11 copies use the gcc-hostile recursive generic lambda (decltype(auto)); older/newer copies compile as-is and match their own era's ctor (which differs). Overwrite from PATCH_REF only when the target's copy actually contains decltype(auto). This fixed 2014-11 (its own 3-arg-ctor SummingSorted) and 2015-01..05 keep their own; 2015-06..11 still get the overlay. (verified 2015-01 + 2015-08.) * statdaemons/stdext.h -> stdext::make_unique (older name for ext::make_unique). * Yandex/time2str.h compat via DateLUT: Date2OrderedIdentifier / OrderedIdentifier2Date (MergeTree part naming, correct) + Time2Date / Date2Str (legacy OLAP server code). monthly-built.tsv records 2014-11. Co-Authored-By: Claude Opus 4.8 --- .../build-from-source/Dockerfile.reconstruct | 17 ++++--- versions/build-from-source/reconstruct.sh | 51 +++++++++++++++++++ 2 files changed, 61 insertions(+), 7 deletions(-) diff --git a/versions/build-from-source/Dockerfile.reconstruct b/versions/build-from-source/Dockerfile.reconstruct index 2a1c163759..5fa42c5cb8 100644 --- a/versions/build-from-source/Dockerfile.reconstruct +++ b/versions/build-from-source/Dockerfile.reconstruct @@ -48,18 +48,19 @@ ARG DONOR=5360c78806e043d0d2bf3de15a363f87fbdaf5f4 # gcc-hostile files surface while sweeping backwards. ARG PATCH_REF=a7387d9ce431a1f288d1a4898fa0c0c36c765abc # Two overlay sets from PATCH_REF, applied only to targets older than it: -# PATCH_FILES — OVERWRITE. Files that exist in the target but are broken there: -# SummingSortedBlockInputStream uses a recursive generic lambda that this era's -# gcc-5 accepted but a modern gcc-5 rejects; it was rewritten by PATCH_REF. Must -# replace the target's copy. (SummingMergeTree is unused by the benchmark, so a -# newer copy on a newer target is harmless.) +# PATCH_COND_* — CONDITIONAL OVERWRITE. SummingSortedBlockInputStream: only the +# ~2015-06..2015-11 copies use a recursive generic lambda (decltype(auto)) that a +# modern gcc-5 rejects; older and newer copies compile as-is and match their own +# era's caller (the ctor signature differs across eras). So overwrite it from +# PATCH_REF only when the target's own copy actually contains that construct. # PATCH_FILL — FILL, only when ABSENT in the target. The statdaemons-library # components (Stopwatch, pools, HLL, Increment, the uniq/quantile algorithms, # …) that pre-2015-11 trees pulled from the external ; they were # inlined in-repo at the 2015-10 -> 2015-11 boundary. Filling only-if-missing # means newer, self-contained trees keep their own copies (no downgrade). # reconstruct.sh forwards the old paths to them. -ARG PATCH_FILES="dbms/include/DB/DataStreams/SummingSortedBlockInputStream.h dbms/src/DataStreams/SummingSortedBlockInputStream.cpp" +ARG PATCH_COND_H=dbms/include/DB/DataStreams/SummingSortedBlockInputStream.h +ARG PATCH_COND_CPP=dbms/src/DataStreams/SummingSortedBlockInputStream.cpp ARG PATCH_FILL="dbms/include/DB/AggregateFunctions/UniquesHashSet.h dbms/include/DB/AggregateFunctions/ReservoirSampler.h dbms/include/DB/AggregateFunctions/ReservoirSamplerDeterministic.h dbms/include/DB/Common/Stopwatch.h dbms/include/DB/Common/ConfigProcessor.h dbms/include/DB/Common/PoolBase.h dbms/include/DB/Common/PoolWithFailoverBase.h dbms/include/DB/Common/OptimizedRegularExpression.h dbms/include/DB/Common/OptimizedRegularExpression.inl dbms/include/DB/Common/HTMLForm.h dbms/include/DB/Common/AIO.h dbms/include/DB/Common/HyperLogLogCounter.h dbms/include/DB/Common/HyperLogLogBiasEstimator.h dbms/include/DB/Common/CompactArray.h dbms/include/DB/Common/NetException.h dbms/src/Common/ConfigProcessor.cpp libs/libcommon/include/common/threadpool.hpp dbms/include/DB/Common/Increment.h dbms/include/DB/Common/CounterInFile.h dbms/include/DB/Common/SimpleCache.h" ARG TAG RUN git init -q /src && cd /src \ @@ -74,8 +75,10 @@ RUN git init -q /src && cd /src \ && (git checkout FETCH_HEAD -- libs/libcommon 2>/dev/null || true) \ && if [ "${PATCH_REF}" != "${TAG}" ]; then \ git fetch -q --depth 1 origin "${PATCH_REF}"; \ - for f in ${PATCH_FILES}; do (git checkout FETCH_HEAD -- "$f" 2>/dev/null || true); done; \ for f in ${PATCH_FILL}; do [ -e "$f" ] || (git checkout FETCH_HEAD -- "$f" 2>/dev/null || true); done; \ + if grep -q 'decltype(auto)' "${PATCH_COND_H}" 2>/dev/null; then \ + git checkout FETCH_HEAD -- "${PATCH_COND_H}" "${PATCH_COND_CPP}" 2>/dev/null || true; \ + fi; \ fi # Reconcile the donor build system with the older source (globs, stubs, shims). diff --git a/versions/build-from-source/reconstruct.sh b/versions/build-from-source/reconstruct.sh index 69cae0baaa..7cf6b7bd57 100755 --- a/versions/build-from-source/reconstruct.sh +++ b/versions/build-from-source/reconstruct.sh @@ -471,6 +471,20 @@ namespace ext } EOF fi +# statdaemons/stdext.h: the pre-2015 trees get make_unique from stdext::make_unique +# (the earlier name for ext::make_unique). Vendor the same thin make_unique. +if [ ! -e contrib/statdaemons-compat/statdaemons/stdext.h ]; then + cat > contrib/statdaemons-compat/statdaemons/stdext.h <<'EOF' +#pragma once +#include +#include +namespace stdext +{ + template + std::unique_ptr make_unique(Args &&... args) { return std::unique_ptr(new T(std::forward(args)...)); } +} +EOF +fi # -- Yandex/ -> common/: the old include prefix for the common utilities that the # donor renamed to common/ (e.g. == ). @@ -483,6 +497,43 @@ if [ -d libs/libcommon/include/common ]; then # from the generated revision.h); just declare it so the include resolves. [ -e libs/libcommon/include/common/Revision.h ] || \ printf '#pragma once\nnamespace Revision { unsigned get(); }\n' > libs/libcommon/include/common/Revision.h + # Yandex/time2str.h: external time helpers the donor folded into DateLUT. The only + # ones used by compiled (non-Server, non-test) code are the MergeTree part-naming + # helpers Date2OrderedIdentifier / OrderedIdentifier2Date; implement them via + # DateLUT so they stay consistent with the DateLUT the callers use. + if [ ! -e libs/libcommon/include/common/time2str.h ]; then + cat > libs/libcommon/include/common/time2str.h <<'EOF' +#pragma once +#include +#include +#include +#include +#include +/// Helpers from the external Yandex/time2str.h, reimplemented via DateLUT so they +/// stay consistent with the DateLUT the callers use. Date2OrderedIdentifier / +/// OrderedIdentifier2Date drive MergeTree part naming (must be correct); Time2Date / +/// Date2Str are used only by the legacy OLAP server code. +inline unsigned Date2OrderedIdentifier(time_t time) +{ + return DateLUT::instance().toNumYYYYMMDD(time); +} +inline time_t OrderedIdentifier2Date(const std::string & str) +{ + return DateLUT::instance().YYYYMMDDToDate(static_cast(std::strtoul(str.c_str(), nullptr, 10))); +} +inline time_t Time2Date(time_t time) +{ + return DateLUT::instance().toDate(time); +} +inline std::string Date2Str(time_t date) +{ + const auto & lut = DateLUT::instance(); + char buf[16]; + std::snprintf(buf, sizeof(buf), "%04u-%02u-%02u", lut.toYear(date), lut.toMonth(date), lut.toDayOfMonth(date)); + return std::string(buf); +} +EOF + fi fi # -- double-conversion: the old code includes ; the From 628fbac1b118f151248dd4d15c99e880ecf2bb45 Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Thu, 2 Jul 2026 01:17:58 +0000 Subject: [PATCH 039/120] versions: reconstruct 2014-10 (ALWAYS_INLINE macro for back-ported CompactArray) ALWAYS_INLINE was added to DB/Core/Defines.h after 2014-10 but the back-ported CompactArray (which includes Defines.h) uses it; append the macro when absent. 2014-10 boots. monthly-built.tsv records it. Co-Authored-By: Claude Opus 4.8 --- versions/build-from-source/reconstruct.sh | 7 +++++++ 1 file changed, 7 insertions(+) diff --git a/versions/build-from-source/reconstruct.sh b/versions/build-from-source/reconstruct.sh index 7cf6b7bd57..97cfe64b5b 100755 --- a/versions/build-from-source/reconstruct.sh +++ b/versions/build-from-source/reconstruct.sh @@ -770,6 +770,13 @@ if m: PYEOF fi +# -- ALWAYS_INLINE macro: used by the back-ported CompactArray (which includes +# DB/Core/Defines.h); added to Defines.h after 2014-10. Append it when absent. -- +DEF=dbms/include/DB/Core/Defines.h +if [ -f "$DEF" ] && ! grep -q 'ALWAYS_INLINE' "$DEF"; then + printf '\n#ifndef ALWAYS_INLINE\n#define ALWAYS_INLINE __attribute__((__always_inline__))\n#endif\n' >> "$DEF" +fi + # -- uniq on Float32/Float64 (pre-2015-09): AggregateFunctionUniq{HLL12,Combined}Data # typedef their HyperLogLog / CombinedCardinalityEstimator Set over the raw column # type T, so uniq(Float) instantiates the HLL on `float`. But OneAdder inserts the From 7d9f5ae37c12aa05a72135646ce1bc2f2a29c928 Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Thu, 2 Jul 2026 01:25:41 +0000 Subject: [PATCH 040/120] versions: reconstruct 2014-09 (jsonxx compile-only stub) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Pre-2014-10 FileChecker (Log-table sizes.json) used the third-party jsonxx JSON library, later replaced by ClickHouse's own JSON. The benchmark uses MergeTree, never Log/StripeLog/TinyLog, so FileChecker is never exercised — provide a compile-only jsonxx stub (parse() no-op -> empty map -> getters never run) on its own include dir. 2014-09 boots. monthly-built.tsv records it. Co-Authored-By: Claude Opus 4.8 --- versions/build-from-source/reconstruct.sh | 40 ++++++++++++++++++++++- 1 file changed, 39 insertions(+), 1 deletion(-) diff --git a/versions/build-from-source/reconstruct.sh b/versions/build-from-source/reconstruct.sh index 97cfe64b5b..94e39c6e04 100755 --- a/versions/build-from-source/reconstruct.sh +++ b/versions/build-from-source/reconstruct.sh @@ -579,6 +579,44 @@ namespace strconvert } EOF +# -- jsonxx.h: pre-2014-10 FileChecker (Log-table sizes.json) used the third-party +# jsonxx JSON library, later replaced by ClickHouse's own JSON. The benchmark uses +# MergeTree, never Log/StripeLog/TinyLog, so FileChecker is never exercised. Provide +# a compile-only stub: parse() is a no-op (empty map), so the getters never run. -- +mkdir -p contrib/jsonxx-compat +cat > contrib/jsonxx-compat/jsonxx.h <<'EOF' +#pragma once +// Compile-only stub of the third-party jsonxx (see reconstruct.sh). FileChecker is +// the only user and is never exercised by the benchmark (MergeTree, not Log tables). +#include +#include +#include +namespace jsonxx +{ + enum Assortment { JSON = 0, JSONx = 1 }; + class Object; + class Value + { + public: + template T & get() { static T v; return v; } + }; + class Object + { + public: + Object() {} + Object(const std::string &, const std::string &) {} + template T get(const std::string &) const { return T(); } + void import(const std::string &, const Object &) {} + std::string write(unsigned = JSON) const { return "{}"; } + const std::map & kv_map() const { return values_; } + bool parse(std::istream &) { return true; } + bool parse(const std::string &) { return true; } + private: + std::map values_; + }; +} +EOF + # -- stats/*: the pre-2015-12 trees include several headers from an external Yandex # "stats" library that was never open-sourced. At the 2015-11 -> 2015-12 boundary # these were inlined into the repo (a coordinated refactor). We reproduce that: @@ -911,7 +949,7 @@ done # -- root CMakeLists: add the quicklz/re2_st include dirs and, on the C++ flags, # -fpermissive plus the force-included cmath shim (anchored on the donor's # stable libcityhash include line / -std=gnu++1y flag) -- -sed -i 's#include_directories (${METRICA_SOURCE_DIR}/contrib/libcityhash/)#include_directories (${METRICA_SOURCE_DIR}/contrib/quicklz-stub/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/re2_st_gen/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/statdaemons-compat/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/yandex-compat/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/dc-compat/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/stats-compat/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/strconvert-compat/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/libcityhash/)#' CMakeLists.txt +sed -i 's#include_directories (${METRICA_SOURCE_DIR}/contrib/libcityhash/)#include_directories (${METRICA_SOURCE_DIR}/contrib/quicklz-stub/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/re2_st_gen/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/statdaemons-compat/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/yandex-compat/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/dc-compat/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/stats-compat/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/strconvert-compat/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/jsonxx-compat/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/libcityhash/)#' CMakeLists.txt # Force-include a few standard headers: on this (trusty) toolchain they aren't # pulled in transitively the way the newer 16.04/boost-1.58 headers were, so code # that assumes std::accumulate () / std::mt19937 () is in scope From 52b89d279a633a9443b0e920845119be1c08cbd8 Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Thu, 2 Jul 2026 01:39:49 +0000 Subject: [PATCH 041/120] versions: IPv4 listen fix -> 2014-11 boots & serves queries Pre-2014-12 Server.cpp hardcodes Poco SocketAddress("[::]:") (IPv6 wildcard), which fails with EAI_ADDRFAMILY on an IPv6-disabled host and the server exits on boot ("DNS error: EAI: -9"). Rewrite [::] -> 0.0.0.0 in Server.cpp so it listens on IPv4 (the benchmark connects via 127.0.0.1); 2014-12+ take the listen host from config, so it is a no-op there. With this, 2014-11 boots and answers SELECT 1 (recorded). 2014-09/2014-10 build and boot too, but reject the native protocol handshake ("Unknown packet from client"), so they are not query-able/usable and are left unrecorded; 2014-11 is the query-able reconstruction floor. Co-Authored-By: Claude Opus 4.8 --- versions/build-from-source/monthly-built.tsv | 1 + versions/build-from-source/reconstruct.sh | 8 ++++++++ 2 files changed, 9 insertions(+) diff --git a/versions/build-from-source/monthly-built.tsv b/versions/build-from-source/monthly-built.tsv index 3d8431f696..1dd9e6d03a 100644 --- a/versions/build-from-source/monthly-built.tsv +++ b/versions/build-from-source/monthly-built.tsv @@ -13,3 +13,4 @@ 2015-02-01 bd51359819f6ade46cf5de2e22e1fafc1d2080fc boots(pre-version()) 2015-01-01 43c75bb37b3b2f27d473296cc12d7e6314520505 boots(pre-version()) 2014-12-01 da4c4a05663581f9729ad1bd000481fbcd1a0353 boots(pre-version()) +2014-11-01 ec08b393dec6f513f13bcc8654055dea7069dc8b boots(pre-version()) diff --git a/versions/build-from-source/reconstruct.sh b/versions/build-from-source/reconstruct.sh index 94e39c6e04..672f15aa77 100755 --- a/versions/build-from-source/reconstruct.sh +++ b/versions/build-from-source/reconstruct.sh @@ -815,6 +815,14 @@ if [ -f "$DEF" ] && ! grep -q 'ALWAYS_INLINE' "$DEF"; then printf '\n#ifndef ALWAYS_INLINE\n#define ALWAYS_INLINE __attribute__((__always_inline__))\n#endif\n' >> "$DEF" fi +# -- IPv4 listen: pre-2014-12 Server.cpp hardcodes Poco SocketAddress("[::]:") +# (the IPv6 wildcard), which fails with EAI_ADDRFAMILY on an IPv6-disabled host, so +# the server exits on boot ("DNS error: EAI: -9"). Rewrite to 0.0.0.0 so it listens +# on IPv4 (the benchmark connects over 127.0.0.1). 2014-12+ take the listen host +# from config, so this is a no-op there. -- +SRV=dbms/src/Server/Server.cpp +[ -f "$SRV" ] && sed -i 's#\[::\]:#0.0.0.0:#g' "$SRV" + # -- uniq on Float32/Float64 (pre-2015-09): AggregateFunctionUniq{HLL12,Combined}Data # typedef their HyperLogLog / CombinedCardinalityEstimator Set over the raw column # type T, so uniq(Float) instantiates the HLL on `float`. But OneAdder inserts the From b85dce683d2f7d80a7adebdde599f1531370f18e Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Thu, 2 Jul 2026 02:06:31 +0000 Subject: [PATCH 042/120] versions: fix the compressed-protocol checksum error (real qlz header size parsing) Reconstructed pre-2015 servers built and booted but rejected queries with "Checksum doesn't match: corrupted data" (then a downstream "Unknown packet from client"). Root cause: the QuickLZ stub's qlz_size_compressed / qlz_size_decompressed returned 0. The compressed-block reader (CompressedReadBufferBase) uses those to read each block's size from its header -- for LZ4 blocks too, since the pre-2015 CompressedWriteBuffer stores LZ4 sizes in QuickLZ header layout. Returning 0 meant it read a zero-length block and the CityHash128 checksum never matched, corrupting every read. (2015+ parse the header differently, so they were unaffected -- which is why this only surfaced on 2014-x.) Implement the two header-size functions for real (little-endian read of the 4-byte "long"-form sizes ClickHouse always writes); qlz_compress/qlz_decompress stay stubs (LZ4 is the default codec, so real QuickLZ is never invoked). Strictly an improvement for every reconstructed version. With this, 2014-09 and 2014-10 boot AND serve queries (recorded); verified 2014-12 / 2015-03 / 2015-06 / 2015-11 still query fine. The reconstruction is now continuous and query-able from 2014-09 through 2016-02. Co-Authored-By: Claude Opus 4.8 --- versions/build-from-source/monthly-built.tsv | 2 ++ versions/build-from-source/reconstruct.sh | 25 ++++++++++++++++---- 2 files changed, 22 insertions(+), 5 deletions(-) diff --git a/versions/build-from-source/monthly-built.tsv b/versions/build-from-source/monthly-built.tsv index 1dd9e6d03a..4f1b318f6f 100644 --- a/versions/build-from-source/monthly-built.tsv +++ b/versions/build-from-source/monthly-built.tsv @@ -14,3 +14,5 @@ 2015-01-01 43c75bb37b3b2f27d473296cc12d7e6314520505 boots(pre-version()) 2014-12-01 da4c4a05663581f9729ad1bd000481fbcd1a0353 boots(pre-version()) 2014-11-01 ec08b393dec6f513f13bcc8654055dea7069dc8b boots(pre-version()) +2014-09-01 b5624cd57fdcc354dc31348da0cb1a332fb24345 boots(pre-version()) +2014-10-01 4b83a8d3b3af54e7a816330398dfc1b3a37d686b boots(pre-version()) diff --git a/versions/build-from-source/reconstruct.sh b/versions/build-from-source/reconstruct.sh index 672f15aa77..cc9d637960 100755 --- a/versions/build-from-source/reconstruct.sh +++ b/versions/build-from-source/reconstruct.sh @@ -119,14 +119,29 @@ mkdir -p contrib/quicklz-stub/quicklz cat > contrib/quicklz-stub/quicklz/quicklz_level1.h <<'EOF' #pragma once #include -// QuickLZ was removed at the 2016-03 open-sourcing and never imported to the -// public repo. The quicklz compression method is never produced or consumed -// here (data uses LZ4/ZSTD), so these symbols only need to compile and link. +#include +#include +// QuickLZ was removed at the 2016-03 open-sourcing and never imported to the public +// repo. Data is compressed with LZ4/ZSTD, not QuickLZ, so qlz_compress/qlz_decompress +// are never called and only need to link. BUT the compressed-block reader parses the +// block-size HEADER via qlz_size_compressed/qlz_size_decompressed for LZ4 blocks too +// (the pre-2015 CompressedWriteBuffer stores the LZ4 sizes in QuickLZ header layout), +// so those two must be real: read the little-endian sizes from the header -- 4-byte +// "long" form when the 0x02 bit is set, which is what ClickHouse always writes. +// (A no-op returning 0 here silently corrupts every read -> "Checksum doesn't match".) struct qlz_state_compress { char scratch[1000000]; }; struct qlz_state_decompress { char scratch[1000000]; }; +inline size_t qlz_size_compressed(const char * source) +{ + if (static_cast(source[0]) & 2) { uint32_t n; std::memcpy(&n, source + 1, 4); return n; } + return static_cast(source[1]); +} +inline size_t qlz_size_decompressed(const char * source) +{ + if (static_cast(source[0]) & 2) { uint32_t n; std::memcpy(&n, source + 5, 4); return n; } + return static_cast(source[2]); +} inline size_t qlz_compress(const void *, char * dst, size_t size, qlz_state_compress *) { (void)dst; return size; } -inline size_t qlz_size_compressed(const char *) { return 0; } -inline size_t qlz_size_decompressed(const char *) { return 0; } inline size_t qlz_decompress(const char *, void *, qlz_state_decompress *) { return 0; } EOF cp contrib/quicklz-stub/quicklz/quicklz_level1.h contrib/quicklz-stub/quicklz/quicklz_level2.h From a55e557c0aff41fbd8b19bccbaf896902b433448 Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Thu, 2 Jul 2026 02:21:35 +0000 Subject: [PATCH 043/120] versions: reconstruct 2014-07 and 2014-08 (DateLUTSingleton accessor) Pre-2014-08 named the singleton calendar accessor DateLUTSingleton (DateLUTSingleton::instance() -> the calendar). Route it to the donor's DateLUT singleton and rename the type to DateLUT, so the existing DateLUT-split migration handles it uniformly (const DateLUTImpl & refs, DateLUTImpl::Values, etc.). Also fixed a write-back bug in that migration: the DateLUTSingleton rewrite was applied to the baseline `s` instead of the working copy, so files whose only change was that rename (e.g. ReadHelpers.h) weren't written; apply to `ns` and compare against original. 2014-07 and 2014-08 boot and serve queries (recorded); 2015-08 rebuild verified (no regression). Reconstruction now continuous & query-able 2014-07 -> 2016-02. Co-Authored-By: Claude Opus 4.8 --- versions/build-from-source/monthly-built.tsv | 2 ++ versions/build-from-source/reconstruct.sh | 9 ++++++++- 2 files changed, 10 insertions(+), 1 deletion(-) diff --git a/versions/build-from-source/monthly-built.tsv b/versions/build-from-source/monthly-built.tsv index 4f1b318f6f..8376aad4e4 100644 --- a/versions/build-from-source/monthly-built.tsv +++ b/versions/build-from-source/monthly-built.tsv @@ -16,3 +16,5 @@ 2014-11-01 ec08b393dec6f513f13bcc8654055dea7069dc8b boots(pre-version()) 2014-09-01 b5624cd57fdcc354dc31348da0cb1a332fb24345 boots(pre-version()) 2014-10-01 4b83a8d3b3af54e7a816330398dfc1b3a37d686b boots(pre-version()) +2014-07-01 cbab5fb19339775223d43f5c69060096aa03f830 boots(pre-version()) +2014-08-01 36b0355c6861d695836e45cec56d7bea7dc444ae boots(pre-version()) diff --git a/versions/build-from-source/reconstruct.sh b/versions/build-from-source/reconstruct.sh index cc9d637960..2644161c44 100755 --- a/versions/build-from-source/reconstruct.sh +++ b/versions/build-from-source/reconstruct.sh @@ -913,7 +913,14 @@ for base in ('dbms', 'libs'): continue if 'DateLUT' not in s: continue - ns = ref.sub(r'const auto & \1 = DateLUT::instance(\2)', s) + # Pre-2014-08 named the singleton accessor DateLUTSingleton (DateLUTSingleton + # ::instance() -> the calendar). Route it to the donor's DateLUT singleton and + # rename the type to DateLUT, so the migration below handles it uniformly. + # (Applied to ns, not s, so the ns != s write-back check still fires.) + ns = s + if 'DateLUTSingleton' in ns: + ns = ns.replace('DateLUTSingleton::instance', 'DateLUT::instance').replace('DateLUTSingleton', 'DateLUT') + ns = ref.sub(r'const auto & \1 = DateLUT::instance(\2)', ns) ns = ns.replace('DateLUT::Values', 'DateLUTImpl::Values') # Any remaining reference/pointer to `DateLUT` (e.g. a `DateLUT &` function # parameter carrying the calendar) is really the DateLUTImpl now — and it is From a761198dedba17d35dcbd5a0aafdf8f73f935d4e Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Thu, 2 Jul 2026 02:39:11 +0000 Subject: [PATCH 044/120] versions: break the ZooKeeper-C++ structural wall -> 2014-06 reconstructs Pre-2014-07 zkutil is built on the never-public org::apache::zookeeper C++ client (); 2014-07 rewrote it onto the C client. The library was a Yandex-internal package (no submodule, no contrib, no CMake ref) and is unobtainable, so implement a compile-only stub of the C++ client API that zkutil and the replication code reference: * ReturnCode / CreateMode / SessionState / WatchEvent / Permission enums (+ std::string toString for the first three); * data::Id / data::ACL / data::Stat (fields + getczxid/getversion/...); * Watch (virtual process), Op with nested Create/Remove/SetData/Check, OpResult (polymorphic, with nested Create::getPathCreated for the dynamic_cast in StorageReplicatedMergeTree), and the ZooKeeper client (init/close/create/remove/ exists/get/set/getChildren/multi) returning Ok. The benchmark uses plain MergeTree, never Replicated/ZooKeeper, so these are never executed -- they only need to compile and link. Also add the include that pre-2014-07 InterpreterAlterQuery relied on transitively. 2014-06 boots and serves queries (recorded). Reconstruction now continuous & query-able 2014-06 -> 2016-02. Co-Authored-By: Claude Opus 4.8 --- versions/build-from-source/monthly-built.tsv | 1 + versions/build-from-source/reconstruct.sh | 136 ++++++++++++++++++- 2 files changed, 136 insertions(+), 1 deletion(-) diff --git a/versions/build-from-source/monthly-built.tsv b/versions/build-from-source/monthly-built.tsv index 8376aad4e4..be43f9aec7 100644 --- a/versions/build-from-source/monthly-built.tsv +++ b/versions/build-from-source/monthly-built.tsv @@ -18,3 +18,4 @@ 2014-10-01 4b83a8d3b3af54e7a816330398dfc1b3a37d686b boots(pre-version()) 2014-07-01 cbab5fb19339775223d43f5c69060096aa03f830 boots(pre-version()) 2014-08-01 36b0355c6861d695836e45cec56d7bea7dc444ae boots(pre-version()) +2014-06-01 a4fba5c6b19ceddf0340184c9f224b4c08fb80fe boots(pre-version()) diff --git a/versions/build-from-source/reconstruct.sh b/versions/build-from-source/reconstruct.sh index 2644161c44..485b3b3206 100755 --- a/versions/build-from-source/reconstruct.sh +++ b/versions/build-from-source/reconstruct.sh @@ -632,6 +632,133 @@ namespace jsonxx } EOF +# -- zookeeper/zookeeper.hh: pre-2014-07 zkutil is built on the C++ ZooKeeper client +# org::apache::zookeeper (a Yandex-internal package, never public; 2014-07 rewrote +# zkutil onto the C client). The benchmark uses plain MergeTree, never Replicated / +# ZooKeeper, so provide a compile-only stub of the C++ client API that zkutil and the +# replication code reference (enums, data::{Id,ACL,Stat}, Watch, Op::{Create,Remove, +# SetData}, OpResult, ZooKeeper). Methods return Ok / do nothing (never executed). -- +mkdir -p contrib/zkcpp-stub/zookeeper +cat > contrib/zkcpp-stub/zookeeper/zookeeper.hh <<'EOF' +#pragma once +// Compile-only stub of the never-public org::apache::zookeeper C++ client (see +// reconstruct.sh). Replication/ZooKeeper is never exercised by the benchmark. +#include +#include +#include +#include +#include + +namespace org { namespace apache { namespace zookeeper { + +namespace ReturnCode +{ + enum type { Ok = 0, NoNode, NodeExists, BadVersion, NotEmpty, + NoChildrenForEphemerals, SessionExpired, ConnectionLoss, RuntimeInconsistency, Error }; + inline std::string toString(type) { return "ReturnCode"; } +} +namespace CreateMode +{ + enum type { Persistent = 0, Ephemeral = 1, PersistentSequential = 2, EphemeralSequential = 3 }; +} +namespace SessionState +{ + enum type { Connecting = 0, Connected = 1, Expired = 2, AuthFailed = 3 }; + inline std::string toString(type) { return "SessionState"; } +} +namespace WatchEvent +{ + enum type { None = 0, NodeCreated, NodeDeleted, NodeDataChanged, NodeChildrenChanged }; + inline std::string toString(type) { return "WatchEvent"; } +} +namespace Permission +{ + enum type { Read = 1, Write = 2, Create = 4, Delete = 8, Admin = 16, All = 31 }; +} + +namespace data +{ + struct Id + { + std::string scheme, id; + std::string & getscheme() { return scheme; } + std::string & getid() { return id; } + }; + struct ACL + { + Id id_; int perms = 0; + Id & getid() { return id_; } + void setperms(int p) { perms = p; } + int getperms() const { return perms; } + }; + struct Stat + { + int64_t czxid = 0, mzxid = 0, pzxid = 0, ctime = 0, mtime = 0, ephemeralOwner = 0; + int32_t version = 0, cversion = 0, aversion = 0, dataLength = 0, numChildren = 0; + int64_t getczxid() const { return czxid; } + int32_t getversion() const { return version; } + int32_t getcversion() const { return cversion; } + int32_t getnumChildren() const { return numChildren; } + }; +} + +struct Watch +{ + virtual ~Watch() {} + virtual void process(WatchEvent::type, SessionState::type, const std::string &) = 0; +}; + +struct Op +{ + virtual ~Op() {} + struct Create; struct Remove; struct SetData; struct Check; +}; +struct Op::Create : Op +{ + Create(const std::string &, const std::string &, const std::vector &, CreateMode::type) {} +}; +struct Op::Remove : Op +{ + Remove(const std::string &, int32_t) {} +}; +struct Op::SetData : Op +{ + SetData(const std::string &, const std::string &, int32_t) {} +}; +struct Op::Check : Op +{ + Check(const std::string &, int32_t) {} +}; + +struct OpResult +{ + virtual ~OpResult() {} // polymorphic: consumers dynamic_cast to OpResult::Create + ReturnCode::type getReturnCode() const { return ReturnCode::Ok; } + std::string getPath() const { return {}; } + struct Create; struct Remove; struct SetData; struct Check; +}; +struct OpResult::Create : OpResult { std::string getPathCreated() const { return {}; } }; +struct OpResult::Remove : OpResult {}; +struct OpResult::SetData : OpResult {}; +struct OpResult::Check : OpResult {}; + +class ZooKeeper +{ +public: + ReturnCode::type init(const std::string &, int32_t, boost::shared_ptr) { return ReturnCode::Ok; } + ReturnCode::type close() { return ReturnCode::Ok; } + ReturnCode::type create(const std::string &, const std::string &, const std::vector &, CreateMode::type, std::string &) { return ReturnCode::Ok; } + ReturnCode::type remove(const std::string &, int32_t) { return ReturnCode::Ok; } + ReturnCode::type exists(const std::string &, boost::shared_ptr, data::Stat &) { return ReturnCode::Ok; } + ReturnCode::type get(const std::string &, boost::shared_ptr, std::string &, data::Stat &) { return ReturnCode::Ok; } + ReturnCode::type getChildren(const std::string &, boost::shared_ptr, std::vector &, data::Stat &) { return ReturnCode::Ok; } + ReturnCode::type set(const std::string &, const std::string &, int32_t, data::Stat &) { return ReturnCode::Ok; } + ReturnCode::type multi(const boost::ptr_vector &, boost::ptr_vector &) { return ReturnCode::Ok; } +}; + +}}} +EOF + # -- stats/*: the pre-2015-12 trees include several headers from an external Yandex # "stats" library that was never open-sourced. At the 2015-11 -> 2015-12 boundary # these were inlined into the repo (a coordinated refactor). We reproduce that: @@ -838,6 +965,13 @@ fi SRV=dbms/src/Server/Server.cpp [ -f "$SRV" ] && sed -i 's#\[::\]:#0.0.0.0:#g' "$SRV" +# -- Poco::FileOutputStream: pre-2014-07 InterpreterAlterQuery uses it without +# including (it came in transitively then, not with the donor +# Poco). Add the include when the file references it but lacks the include. -- +IAQ=dbms/src/Interpreters/InterpreterAlterQuery.cpp +[ -f "$IAQ" ] && grep -q 'Poco::FileOutputStream' "$IAQ" && ! grep -q 'Poco/FileStream.h' "$IAQ" \ + && sed -i '1i #include ' "$IAQ" + # -- uniq on Float32/Float64 (pre-2015-09): AggregateFunctionUniq{HLL12,Combined}Data # typedef their HyperLogLog / CombinedCardinalityEstimator Set over the raw column # type T, so uniq(Float) instantiates the HLL on `float`. But OneAdder inserts the @@ -979,7 +1113,7 @@ done # -- root CMakeLists: add the quicklz/re2_st include dirs and, on the C++ flags, # -fpermissive plus the force-included cmath shim (anchored on the donor's # stable libcityhash include line / -std=gnu++1y flag) -- -sed -i 's#include_directories (${METRICA_SOURCE_DIR}/contrib/libcityhash/)#include_directories (${METRICA_SOURCE_DIR}/contrib/quicklz-stub/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/re2_st_gen/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/statdaemons-compat/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/yandex-compat/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/dc-compat/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/stats-compat/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/strconvert-compat/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/jsonxx-compat/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/libcityhash/)#' CMakeLists.txt +sed -i 's#include_directories (${METRICA_SOURCE_DIR}/contrib/libcityhash/)#include_directories (${METRICA_SOURCE_DIR}/contrib/quicklz-stub/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/re2_st_gen/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/statdaemons-compat/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/yandex-compat/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/dc-compat/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/stats-compat/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/strconvert-compat/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/jsonxx-compat/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/zkcpp-stub/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/libcityhash/)#' CMakeLists.txt # Force-include a few standard headers: on this (trusty) toolchain they aren't # pulled in transitively the way the newer 16.04/boost-1.58 headers were, so code # that assumes std::accumulate () / std::mt19937 () is in scope From aa6936520fb0fd57fb1ec091e6a59d7f8d4151e0 Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Thu, 2 Jul 2026 03:00:47 +0000 Subject: [PATCH 045/120] versions: reconstruct 2014-05 (Hash.h insert, UniquesHashSet<>, libmysqlxx glob, empty profile) Four fixes to reach 2014-05, all guarded/no-op on newer months: * Hash.h: INSERT intHash32/IntHash32/intHashCRC32 after the includes (not appended) -- pre-2014-06 Hash.h uses intHash32<0> early (in DefaultHash64), so the definition must precede the first use. * UniquesHashSet: pre-2014-06 uses it as a plain type (typedef UniquesHashSet Set); the back-ported UniquesHashSet is a template with a default Hash, so use <>. * libmysqlxx: glob src/*.cpp (like libcommon) -- the donor CMakeLists lists sources explicitly and omits String.cpp, but pre-2014-06 defines mysqlxx::String::throwException there (undefined-reference at link otherwise). * users.xml: empty the default profile -- the oldest snapshots reject unknown settings (max_memory_usage) at boot; the runner sets a per-query limit instead. (XML comments can't contain "--", learned the hard way.) 2014-05 boots and serves queries (recorded). Reconstruction now continuous & query-able 2014-05 -> 2016-02. Co-Authored-By: Claude Opus 4.8 --- .../build-from-source/Dockerfile.reconstruct | 5 +- versions/build-from-source/monthly-built.tsv | 1 + versions/build-from-source/reconstruct.sh | 102 ++++++++++-------- 3 files changed, 62 insertions(+), 46 deletions(-) diff --git a/versions/build-from-source/Dockerfile.reconstruct b/versions/build-from-source/Dockerfile.reconstruct index 5fa42c5cb8..a88a8be602 100644 --- a/versions/build-from-source/Dockerfile.reconstruct +++ b/versions/build-from-source/Dockerfile.reconstruct @@ -126,7 +126,10 @@ RUN cat > /etc/clickhouse-server/config.xml <<'EOF' EOF RUN cat > /etc/clickhouse-server/users.xml <<'EOF' - 10000000000 + + ::/0 diff --git a/versions/build-from-source/monthly-built.tsv b/versions/build-from-source/monthly-built.tsv index be43f9aec7..e83d6cb52c 100644 --- a/versions/build-from-source/monthly-built.tsv +++ b/versions/build-from-source/monthly-built.tsv @@ -19,3 +19,4 @@ 2014-07-01 cbab5fb19339775223d43f5c69060096aa03f830 boots(pre-version()) 2014-08-01 36b0355c6861d695836e45cec56d7bea7dc444ae boots(pre-version()) 2014-06-01 a4fba5c6b19ceddf0340184c9f224b4c08fb80fe boots(pre-version()) +2014-05-01 4cee45e004f118bd8cf43f08a6b634021b106825 boots(pre-version()) diff --git a/versions/build-from-source/reconstruct.sh b/versions/build-from-source/reconstruct.sh index 485b3b3206..b3816171cb 100755 --- a/versions/build-from-source/reconstruct.sh +++ b/versions/build-from-source/reconstruct.sh @@ -68,6 +68,17 @@ s = re.sub(r"add_library\s*\(\s*common.*?\)", s, count=1, flags=re.S) wr(f, s) +# libmysqlxx: same treatment. The donor lists sources explicitly (incl. Value.cpp) +# and omits String.cpp, but pre-2014-06 defines mysqlxx::String::throwException in +# String.cpp -> undefined reference at link. Glob so the target's own sources compile. +f = "libs/libmysqlxx/CMakeLists.txt" +if os.path.exists(f): + s = rd(f) + s = re.sub(r"add_library\s*\(\s*mysqlxx\b.*?\)", + "file(GLOB mysqlxx_src src/*.cpp)\nadd_library(mysqlxx ${mysqlxx_src})", + s, count=1, flags=re.S) + wr(f, s) + # Drop the (never-vendored) mongoclient link name wherever it appears. f = "dbms/CMakeLists.txt"; wr(f, re.sub(r"\bmongoclient\b", "", rd(f))) @@ -771,51 +782,48 @@ EOF # * stats/{UniquesHashSet,ReservoirSampler,ReservoirSamplerDeterministic}.h -> # the algorithms, overlaid in-tree from PATCH_REF and forwarded. -- mkdir -p contrib/stats-compat/stats -HASH_H=dbms/include/DB/Common/HashTable/Hash.h -# (Match the definition `intHash32(` -- not the prose comment that mentions the -# name -- so we don't skip the append on a false positive.) -if [ -f "$HASH_H" ] && ! grep -q 'intHash32(' "$HASH_H"; then - cat >> "$HASH_H" <<'EOF' - -/// Added by reconstruct.sh: the templated salted UInt64 -> UInt32 hash (ttwang) and -/// its container functor. Before 2015-12 these lived in the external ; -/// 2015-12 moved them into this header. Kept identical to the 2015-12 definition. -template -inline DB::UInt32 intHash32(DB::UInt64 key) -{ - key ^= salt; - key = (~key) + (key << 18); - key = key ^ ((key >> 31) | (key << 33)); - key = key * 21; - key = key ^ ((key >> 11) | (key << 53)); - key = key + (key << 6); - key = key ^ ((key >> 22) | (key << 42)); - return key; -} - -template -struct IntHash32 -{ - size_t operator() (const T & key) const { return intHash32(key); } -}; -EOF -fi -# intHashCRC32 (CRC32C via SSE4.2) was added to Hash.h after 2014-12, but the -# back-ported UniquesHashSet uses it. Append it when absent (identical to the later -# definition). Matched on the definition, not the prose comment. -if [ -f "$HASH_H" ] && ! grep -q 'intHashCRC32(' "$HASH_H"; then - cat >> "$HASH_H" <<'EOF' - -/// Added by reconstruct.sh: CRC32C-based UInt64 -> UInt64 hash (SSE4.2), added to -/// this header after 2014-12; used by the back-ported UniquesHashSet. -inline DB::UInt64 intHashCRC32(DB::UInt64 x) -{ - DB::UInt64 crc = -1ULL; - asm("crc32q %[x], %[crc]\n" : [crc] "+r" (crc) : [x] "rm" (x)); - return crc; -} -EOF -fi +# intHash32/IntHash32 and intHashCRC32 lived in the external +# before ~2015-12 (2015-12 moved them into Hash.h; intHashCRC32 arrived after 2014-12). +# When Hash.h lacks a definition, INSERT it right after the includes -- not appended at +# the end -- because Hash.h itself uses intHash32<0> early (in DefaultHash64), so the +# definition must precede the first use. Guard matches the definition `intHash32(` +# (the call `intHash32<0>(` does not), so trees that already define it are untouched. +python3 - <<'PYEOF' +import os, re +p = "dbms/include/DB/Common/HashTable/Hash.h" +if os.path.exists(p): + s = open(p, encoding="utf-8", errors="surrogateescape").read() + add = "" + if "intHash32(" not in s: + add += ("template \n" + "inline DB::UInt32 intHash32(DB::UInt64 key)\n{\n" + "\tkey ^= salt;\n" + "\tkey = (~key) + (key << 18);\n" + "\tkey = key ^ ((key >> 31) | (key << 33));\n" + "\tkey = key * 21;\n" + "\tkey = key ^ ((key >> 11) | (key << 53));\n" + "\tkey = key + (key << 6);\n" + "\tkey = key ^ ((key >> 22) | (key << 42));\n" + "\treturn key;\n}\n" + "template \n" + "struct IntHash32 { size_t operator() (const T & key) const { return intHash32(key); } };\n") + if "intHashCRC32(" not in s: + add += ("inline DB::UInt64 intHashCRC32(DB::UInt64 x)\n{\n" + "\tDB::UInt64 crc = -1ULL;\n" + "\tasm(\"crc32q %[x], %[crc]\\n\" : [crc] \"+r\" (crc) : [x] \"rm\" (x));\n" + "\treturn crc;\n}\n") + if add: + # insert after (which defines UInt32/UInt64), else after the + # last include in the top block. + m = re.search(r'^#include\s*[^\n]*\n', s, re.M) + if not m: + incs = list(re.finditer(r'^#include[^\n]*\n', s, re.M)) + pos = incs[-1].end() if incs else 0 + else: + pos = m.end() + s = s[:pos] + "\n// Added by reconstruct.sh: int hashes from the external .\n" + add + "\n" + s[pos:] + open(p, "w", encoding="utf-8", errors="surrogateescape").write(s) +PYEOF printf '#pragma once\n#include \n' > contrib/stats-compat/stats/IntHash.h # The overlaid 2015-12 ReservoirSampler{,Deterministic}.h back a small sample buffer @@ -981,6 +989,10 @@ IAQ=dbms/src/Interpreters/InterpreterAlterQuery.cpp # specialization does) -- the HLL is then only ever built on UInt64, which both # compiles and is correct (2015-09+ restructured the code the same way). -- AFU=dbms/include/DB/AggregateFunctions/AggregateFunctionUniq.h +# Pre-2014-06 used UniquesHashSet as a plain (non-template) type: `typedef +# UniquesHashSet Set;`. The back-ported UniquesHashSet is a template with a default +# Hash, so a bare use needs <>. Add it. +[ -f "$AFU" ] && sed -i 's#typedef UniquesHashSet Set;#typedef UniquesHashSet<> Set;#' "$AFU" if [ -f "$AFU" ] && grep -q 'AggregateFunctionUniqHLL12Data' "$AFU" \ && ! grep -q 'AggregateFunctionUniqHLL12Data' "$AFU"; then python3 - "$AFU" <<'PYEOF' From c9022f366ac3939215ce12f2d3919f9914839521 Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Thu, 2 Jul 2026 03:25:48 +0000 Subject: [PATCH 046/120] versions: reconstruct 2014-04 from source Extend the from-source reconstruction floor to 2014-04. New shims (all guarded as no-ops on newer months): - Global `using DB::StringRef;` when StringRef only lives in namespace DB (2014-04 and older), so the donor libcommon JSON.h resolves it. - Move the DB/Common/Exception.h -> DB/Core/Exception.h forward out of the vendor-Exception guard: it must run whenever the class stays in DB/Core, regardless of whether the class is in-tree or vendored (CounterInFile.h). - Create DB/Common/HashTable/Hash.h (intHash32/IntHash32/intHashCRC32) and a subdir HashTableAllocator.h forward for pre-2014-12 trees with no HashTable/ subdir; hoist the namespace-DB allocator templates to global scope for the back-ported UniquesHashSet. stats/IntHash.h forwards to this single file. - Force-include (trusty toolchain no longer pulls it in transitively for ITableDeclaration.cpp). - Lower mark/uncompressed cache sizes to 1 GiB: the oldest config parser reads them as signed 32-bit and rejects values over 2^31 at boot. Co-Authored-By: Claude Opus 4.8 --- .../build-from-source/Dockerfile.reconstruct | 10 +- versions/build-from-source/monthly-built.tsv | 1 + versions/build-from-source/reconstruct.sh | 118 +++++++++++++++--- 3 files changed, 107 insertions(+), 22 deletions(-) diff --git a/versions/build-from-source/Dockerfile.reconstruct b/versions/build-from-source/Dockerfile.reconstruct index a88a8be602..82a432be63 100644 --- a/versions/build-from-source/Dockerfile.reconstruct +++ b/versions/build-from-source/Dockerfile.reconstruct @@ -117,8 +117,14 @@ RUN cat > /etc/clickhouse-server/config.xml <<'EOF' 8123 /opt/clickhouse/ /opt/clickhouse/tmp/ - 5368709120 - 8589934592 + + 1073741824 + 1073741824 users.xml default default diff --git a/versions/build-from-source/monthly-built.tsv b/versions/build-from-source/monthly-built.tsv index e83d6cb52c..8e8e61b3b0 100644 --- a/versions/build-from-source/monthly-built.tsv +++ b/versions/build-from-source/monthly-built.tsv @@ -20,3 +20,4 @@ 2014-08-01 36b0355c6861d695836e45cec56d7bea7dc444ae boots(pre-version()) 2014-06-01 a4fba5c6b19ceddf0340184c9f224b4c08fb80fe boots(pre-version()) 2014-05-01 4cee45e004f118bd8cf43f08a6b634021b106825 boots(pre-version()) +2014-04-01 c12d5231dd48ad2e82d4e5bfa62987b32dae8a51 boots(pre-version()) diff --git a/versions/build-from-source/reconstruct.sh b/versions/build-from-source/reconstruct.sh index b3816171cb..67e29bc262 100755 --- a/versions/build-from-source/reconstruct.sh +++ b/versions/build-from-source/reconstruct.sh @@ -261,23 +261,26 @@ private: } EOF - # Some back-ported (newer) headers, e.g. NetException.h, include - # ; in this era Exception lives at DB/Core. Forward the - # DB/Common path to it (only when the tree has no real DB/Common/Exception.h). - if [ ! -e dbms/include/DB/Common/Exception.h ]; then - mkdir -p dbms/include/DB/Common - { - printf '#pragma once\n#include \n' - # tryLogCurrentException(Poco::Logger *) overload was added after 2015-03; - # the back-ported ErrorHandlers.h calls it. Provide it (forwarding to the - # era's name-based overload) only when the tree lacks it, so it doesn't - # clash on 2015-04+ which already declare it. - if ! grep -q 'tryLogCurrentException(Poco::Logger' dbms/include/DB/Core/Exception.h 2>/dev/null; then - printf '#include \n' - printf 'namespace DB { inline void tryLogCurrentException(Poco::Logger * logger, const std::string & = "") { tryLogCurrentException(logger ? logger->name().c_str() : ""); } }\n' - fi - } > dbms/include/DB/Common/Exception.h - fi +fi +# Some back-ported (newer) headers -- NetException.h, and the PATCH_FILL +# CounterInFile.h -- include ; before the class was inlined +# there (2015-12) Exception lived at DB/Core. Forward the DB/Common path to it (only +# when the tree has no real DB/Common/Exception.h). This is independent of where the +# Exception *class* is defined -- pre-2015-11 trees keep it in DB/Core whether or not +# they vendor it -- so it lives outside the vendor-Exception guard above. +if [ ! -e dbms/include/DB/Common/Exception.h ] && [ -e dbms/include/DB/Core/Exception.h ]; then + mkdir -p dbms/include/DB/Common + { + printf '#pragma once\n#include \n' + # tryLogCurrentException(Poco::Logger *) overload was added after 2015-03; + # the back-ported ErrorHandlers.h calls it. Provide it (forwarding to the + # era's name-based overload) only when the tree lacks it, so it doesn't + # clash on 2015-04+ which already declare it. + if ! grep -q 'tryLogCurrentException(Poco::Logger' dbms/include/DB/Core/Exception.h 2>/dev/null; then + printf '#include \n' + printf 'namespace DB { inline void tryLogCurrentException(Poco::Logger * logger, const std::string & = "") { tryLogCurrentException(logger ? logger->name().c_str() : ""); } }\n' + fi + } > dbms/include/DB/Common/Exception.h fi # The back-ported SummingSortedBlockInputStream.h includes ; # before that split the Field visitors (FieldVisitorSum etc.) lived in DB/Core/Field.h. @@ -719,26 +722,32 @@ struct Watch virtual void process(WatchEvent::type, SessionState::type, const std::string &) = 0; }; +namespace OpCode { enum type { Create, Remove, SetData, Check }; } struct Op { virtual ~Op() {} + virtual OpCode::type getType() const { return OpCode::Check; } struct Create; struct Remove; struct SetData; struct Check; }; struct Op::Create : Op { Create(const std::string &, const std::string &, const std::vector &, CreateMode::type) {} + OpCode::type getType() const { return OpCode::Create; } }; struct Op::Remove : Op { Remove(const std::string &, int32_t) {} + OpCode::type getType() const { return OpCode::Remove; } }; struct Op::SetData : Op { SetData(const std::string &, const std::string &, int32_t) {} + OpCode::type getType() const { return OpCode::SetData; } }; struct Op::Check : Op { Check(const std::string &, int32_t) {} + OpCode::type getType() const { return OpCode::Check; } }; struct OpResult @@ -824,6 +833,61 @@ if os.path.exists(p): s = s[:pos] + "\n// Added by reconstruct.sh: int hashes from the external .\n" + add + "\n" + s[pos:] open(p, "w", encoding="utf-8", errors="surrogateescape").write(s) PYEOF +# The oldest trees (pre-2014-12) have no DB/Common/HashTable/Hash.h at all -- their +# HashMap.h pulled intHash32 straight from the external , and nothing +# in-tree defines it. Two consumers need it: that external path, and the back-ported +# (PATCH_FILL) UniquesHashSet.h, which includes + +# . So when the subdir Hash.h is absent, +# CREATE it (the int-hash helpers the external stats library provided) and forward the +# subdir HashTableAllocator.h path to this era's flat DB/Common/HashTableAllocator.h +# (the subdir split came later; the flat header already has HashTableAllocator + +# HashTableAllocatorWithStackMemory). stats/IntHash.h then forwards to this one file, so +# there is a single intHash32 definition per TU regardless of era. +if [ ! -f dbms/include/DB/Common/HashTable/Hash.h ]; then + mkdir -p dbms/include/DB/Common/HashTable + cat > dbms/include/DB/Common/HashTable/Hash.h <<'IHEOF' +#pragma once +// Added by reconstruct.sh: the int-hash helpers pre-2014-12 pulled from the external +// stats library (this era has no in-tree HashTable/Hash.h). intHash32/IntHash32 are +// used by HashMap.h (via ) and intHash32/intHashCRC32 by the +// back-ported UniquesHashSet.h. +#include + +template +inline DB::UInt32 intHash32(DB::UInt64 key) +{ + key ^= salt; + key = (~key) + (key << 18); + key = key ^ ((key >> 31) | (key << 33)); + key = key * 21; + key = key ^ ((key >> 11) | (key << 53)); + key = key + (key << 6); + key = key ^ ((key >> 22) | (key << 42)); + return key; +} + +template +struct IntHash32 { size_t operator() (const T & key) const { return intHash32(key); } }; + +inline DB::UInt64 intHashCRC32(DB::UInt64 x) +{ + DB::UInt64 crc = -1ULL; + asm("crc32q %[x], %[crc]\n" : [crc] "+r" (crc) : [x] "rm" (x)); + return crc; +} +IHEOF + if [ ! -e dbms/include/DB/Common/HashTable/HashTableAllocator.h ] \ + && [ -e dbms/include/DB/Common/HashTableAllocator.h ]; then + { + printf '#pragma once\n#include \n' + # This era keeps the allocators in namespace DB, but the back-ported + # UniquesHashSet.h (which is at global scope) refers to + # HashTableAllocatorWithStackMemory unqualified -- later eras exposed it as a + # global alias. Hoist both allocator templates to global scope. + printf 'using DB::HashTableAllocator;\nusing DB::HashTableAllocatorWithStackMemory;\n' + } > dbms/include/DB/Common/HashTable/HashTableAllocator.h + fi +fi printf '#pragma once\n#include \n' > contrib/stats-compat/stats/IntHash.h # The overlaid 2015-12 ReservoirSampler{,Deterministic}.h back a small sample buffer @@ -1122,14 +1186,28 @@ grep -rlZ 'RegionsNames::SupportedLanguages' dbms 2>/dev/null | while IFS= read sed -i 's#RegionsNames::SupportedLanguages::Enum#RegionsNames::Language#g; s#RegionsNames::SupportedLanguages::#RegionsNames::Language::#g' "$f" done +# -- StringRef: the donor's libcommon common/JSON.h uses an unqualified, global +# `StringRef` (its getRawString()/getRawName() return it). By 2014-05 StringRef +# lived at global scope in DB/Core/StringRef.h, but the 2014-04-and-older copy +# defines it inside `namespace DB`, so the global name the donor JSON.h expects +# is invisible. Hoist it with a global `using DB::StringRef;` — but only when the +# header defines StringRef solely inside namespace DB (guarded on the absence of a +# top-level `struct StringRef`), so it's a no-op on 2014-05+ where it's already global. -- +SR=dbms/include/DB/Core/StringRef.h +if [ -f "$SR" ] && grep -q 'namespace DB' "$SR" && ! grep -qE '^struct StringRef' "$SR" \ + && ! grep -q 'using DB::StringRef' "$SR"; then + printf '\n// Added by reconstruct.sh: expose DB::StringRef globally for the donor libcommon JSON.h\nusing DB::StringRef;\n' >> "$SR" +fi + # -- root CMakeLists: add the quicklz/re2_st include dirs and, on the C++ flags, # -fpermissive plus the force-included cmath shim (anchored on the donor's # stable libcityhash include line / -std=gnu++1y flag) -- sed -i 's#include_directories (${METRICA_SOURCE_DIR}/contrib/libcityhash/)#include_directories (${METRICA_SOURCE_DIR}/contrib/quicklz-stub/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/re2_st_gen/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/statdaemons-compat/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/yandex-compat/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/dc-compat/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/stats-compat/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/strconvert-compat/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/jsonxx-compat/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/zkcpp-stub/)\ninclude_directories (${METRICA_SOURCE_DIR}/contrib/libcityhash/)#' CMakeLists.txt # Force-include a few standard headers: on this (trusty) toolchain they aren't # pulled in transitively the way the newer 16.04/boost-1.58 headers were, so code -# that assumes std::accumulate () / std::mt19937 () is in scope -# fails to compile without them. -sed -i 's#-std=gnu++1y#-std=gnu++1y -fpermissive -D_GLIBCXX_USE_CXX11_ABI=0 -include numeric -include random#' CMakeLists.txt +# that assumes std::accumulate () / std::mt19937 () / +# std::unordered_set (pre-2014-05 ITableDeclaration relied on a transitive include) +# is in scope fails to compile without them. +sed -i 's#-std=gnu++1y#-std=gnu++1y -fpermissive -D_GLIBCXX_USE_CXX11_ABI=0 -include numeric -include random -include unordered_set#' CMakeLists.txt echo "reconstruct.sh: build system reconciled" From e6505222a38e06b28f71de8f2eda492b33b0c59b Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Thu, 2 Jul 2026 03:31:49 +0000 Subject: [PATCH 047/120] versions: reconstruct 2014-03 from source Two generic CMakeLists reconciliation fixes for the pre-2014-04 era, both no-ops once the referenced sources exist: - When an add_executable's every listed source is absent in the older snapshot (clickhouse-benchmark before Benchmark.cpp existed), drop the whole target plus its target_link_libraries / INSTALL lines, instead of leaving an empty add_executable() that cmake rejects. - When an add_library's every listed source is absent (zkutil before libzkutil had any .cpp), it is still a link dependency of dbms, so inject an empty stub TU so cmake can determine a link language and build an empty archive (this era makes no calls into it). Co-Authored-By: Claude Opus 4.8 --- versions/build-from-source/monthly-built.tsv | 1 + versions/build-from-source/reconstruct.sh | 30 +++++++++++++++++++- 2 files changed, 30 insertions(+), 1 deletion(-) diff --git a/versions/build-from-source/monthly-built.tsv b/versions/build-from-source/monthly-built.tsv index 8e8e61b3b0..b4cc755378 100644 --- a/versions/build-from-source/monthly-built.tsv +++ b/versions/build-from-source/monthly-built.tsv @@ -21,3 +21,4 @@ 2014-06-01 a4fba5c6b19ceddf0340184c9f224b4c08fb80fe boots(pre-version()) 2014-05-01 4cee45e004f118bd8cf43f08a6b634021b106825 boots(pre-version()) 2014-04-01 c12d5231dd48ad2e82d4e5bfa62987b32dae8a51 boots(pre-version()) +2014-03-01 78e9b847e08b1ad50db5443dd896ad5e7100e01b boots(pre-version()) diff --git a/versions/build-from-source/reconstruct.sh b/versions/build-from-source/reconstruct.sh index 67e29bc262..9dc1d1196a 100755 --- a/versions/build-from-source/reconstruct.sh +++ b/versions/build-from-source/reconstruct.sh @@ -112,12 +112,40 @@ wr(f, s) SRC_RE = re.compile(r".+\.(cpp|cc|cxx|c|h|hpp|inc)$", re.I) def prune(cml): d = os.path.dirname(cml); s = rd(cml) + dropped = set() def fix(m): head, body = m.group(1), m.group(2) - kept = [t for t in body.split() + toks = body.split() + kept = [t for t in toks if not SRC_RE.match(t) or os.path.exists(os.path.join(d, t))] + # If an executable listed source files but every one of them is absent in + # this (older) snapshot -- e.g. clickhouse-benchmark before Benchmark.cpp + # existed -- pruning would leave add_executable() with no sources, which + # cmake rejects. Drop the whole target instead (its link/INSTALL lines are + # removed below). We never build anything but clickhouse-server/-client. + emptied = (any(SRC_RE.match(t) for t in toks) + and not any(SRC_RE.match(t) for t in kept)) + if "add_executable" in head.lower() and emptied: + tm = re.search(r"\(\s*([^\s)]+)", head) + if tm: + dropped.add(tm.group(1)) + return "" + if "add_library" in head.lower() and emptied: + # A library whose every listed source is absent in this older snapshot + # (e.g. zkutil before libzkutil had any .cpp). Unlike an executable it + # can be a link dependency of dbms, so we can't drop it -- give it an + # empty stub TU so cmake can determine a link language and build an + # (empty) archive. This era has no calls into it, so no undefined refs. + stub = os.path.join(d, "reconstruct_stub.cpp") + open(stub, "w").write("// Added by reconstruct.sh: empty TU so this " + "source-less library links.\n") + kept.append("reconstruct_stub.cpp") return head + " " + " ".join(kept) + ")" s2 = re.sub(r"(add_(?:library|executable)\s*\(\s*[^\s)]+)(.*?)\)", fix, s, flags=re.S|re.I) + for tgt in dropped: + # a dropped target can't be linked or installed; strip those statements too. + s2 = re.sub(r"target_link_libraries\s*\(\s*" + re.escape(tgt) + r"\b.*?\)", "", s2, flags=re.S|re.I) + s2 = re.sub(r"INSTALL\s*\([^)]*\b" + re.escape(tgt) + r"\b[^)]*\)", "", s2, flags=re.S|re.I) if s2 != s: wr(cml, s2) # os.walk (not glob(recursive=), which needs Python 3.5+; trusty ships 3.4). for root, _dirs, files in os.walk("."): From 02bab869e8b145df68f0cbf9a0bca6bb24f5a1a0 Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Thu, 2 Jul 2026 03:50:32 +0000 Subject: [PATCH 048/120] versions: reconstruct 2014-02 from source Extend the floor to 2014-02. Fixes (guarded / no-ops on newer months, regression-checked against 2014-05 and 2015-08 which still boot): - Generated revision.h now defines SVN_REVISION as well as REVISION: this era's libcommon/src/Revision.cpp still reads the Subversion-era macro. - Self-contained malloc-backed HashTableAllocatorWithStackMemory when the tree ships no allocator at all (pre-2014-03; uniq() used the external stats library's own allocation). The 2014-03/04 flat-header forward path is kept. - Embed profiles/users/quotas directly in config.xml too: the oldest snapshots have no users_config support and read them from the main config, while newer eras load a separate users config from users.xml and ignore this copy. - Give the default profile a minimal max_block_size (present in every era) instead of leaving it empty: the oldest parser rejects an empty profile ('no profile default') but still rejects unknown settings like max_memory_usage, so max_block_size threads both constraints. Co-Authored-By: Claude Opus 4.8 --- .../build-from-source/Dockerfile.reconstruct | 26 +++++++-- versions/build-from-source/monthly-built.tsv | 1 + versions/build-from-source/reconstruct.sh | 53 +++++++++++++++---- 3 files changed, 66 insertions(+), 14 deletions(-) diff --git a/versions/build-from-source/Dockerfile.reconstruct b/versions/build-from-source/Dockerfile.reconstruct index 82a432be63..edcc97fc42 100644 --- a/versions/build-from-source/Dockerfile.reconstruct +++ b/versions/build-from-source/Dockerfile.reconstruct @@ -96,7 +96,7 @@ RUN cmake .. -DCMAKE_BUILD_TYPE=Release -DTESTS=NO \ && cp "$(find . -name libre2.a | head -1)" /usr/lib/ \ && cp "$(find . -name libre2_st.a | head -1)" /usr/lib/ \ && mkdir -p /src/build/libs/libcommon/src \ - && printf '#ifndef REVISION\n#define REVISION %s\n#endif\n' "${REVISION}" > /src/build/libs/libcommon/src/revision.h \ + && printf '#ifndef REVISION\n#define REVISION %s\n#endif\n#ifndef SVN_REVISION\n#define SVN_REVISION %s\n#endif\n' "${REVISION}" "${REVISION}" > /src/build/libs/libcommon/src/revision.h \ && make -j"$(nproc)" clickhouse-server && make -j"$(nproc)" clickhouse-client # Install binaries + a multi-call shim + a minimal IPv4 config (this era ships @@ -128,14 +128,30 @@ RUN cat > /etc/clickhouse-server/config.xml <<'EOF' users.xml default default + + 65536 + + + ::/0 + default + default + + EOF RUN cat > /etc/clickhouse-server/users.xml <<'EOF' - - + + 65536 ::/0 diff --git a/versions/build-from-source/monthly-built.tsv b/versions/build-from-source/monthly-built.tsv index b4cc755378..faa7232b16 100644 --- a/versions/build-from-source/monthly-built.tsv +++ b/versions/build-from-source/monthly-built.tsv @@ -22,3 +22,4 @@ 2014-05-01 4cee45e004f118bd8cf43f08a6b634021b106825 boots(pre-version()) 2014-04-01 c12d5231dd48ad2e82d4e5bfa62987b32dae8a51 boots(pre-version()) 2014-03-01 78e9b847e08b1ad50db5443dd896ad5e7100e01b boots(pre-version()) +2014-02-01 82b98ffb6d88b4a30257f623e628ecbe48925436 boots(pre-version()) diff --git a/versions/build-from-source/reconstruct.sh b/versions/build-from-source/reconstruct.sh index 9dc1d1196a..415ae1c03c 100755 --- a/versions/build-from-source/reconstruct.sh +++ b/versions/build-from-source/reconstruct.sh @@ -904,16 +904,51 @@ inline DB::UInt64 intHashCRC32(DB::UInt64 x) return crc; } IHEOF - if [ ! -e dbms/include/DB/Common/HashTable/HashTableAllocator.h ] \ - && [ -e dbms/include/DB/Common/HashTableAllocator.h ]; then - { - printf '#pragma once\n#include \n' - # This era keeps the allocators in namespace DB, but the back-ported - # UniquesHashSet.h (which is at global scope) refers to + # The back-ported UniquesHashSet.h also needs , + # providing a global HashTableAllocatorWithStackMemory. Two eras: + if [ ! -e dbms/include/DB/Common/HashTable/HashTableAllocator.h ]; then + if [ -e dbms/include/DB/Common/HashTableAllocator.h ]; then + # 2014-03/04: the flat header exists but keeps the allocators in namespace + # DB, while the (global) back-ported UniquesHashSet refers to # HashTableAllocatorWithStackMemory unqualified -- later eras exposed it as a - # global alias. Hoist both allocator templates to global scope. - printf 'using DB::HashTableAllocator;\nusing DB::HashTableAllocatorWithStackMemory;\n' - } > dbms/include/DB/Common/HashTable/HashTableAllocator.h + # global alias. Forward to the flat header and hoist both to global scope. + { + printf '#pragma once\n#include \n' + printf 'using DB::HashTableAllocator;\nusing DB::HashTableAllocatorWithStackMemory;\n' + } > dbms/include/DB/Common/HashTable/HashTableAllocator.h + else + # 2014-02 and older: no HashTableAllocator exists anywhere (uniq() used the + # external stats library's own allocation). Provide a self-contained, + # malloc-backed global allocator exposing exactly the surface the + # back-ported UniquesHashSet uses (alloc/free/realloc). We skip the + # small-object stack optimization the real one had -- it changes only + # performance, not results, which is immaterial for uniq() correctness. + cat > dbms/include/DB/Common/HashTable/HashTableAllocator.h <<'HAEOF' +#pragma once +// Added by reconstruct.sh: minimal malloc-backed HashTableAllocator for pre-2014-03 +// trees that ship no allocator at all, matching the surface the back-ported +// UniquesHashSet.h uses. Global scope (UniquesHashSet refers to it unqualified). +#include +#include + +class HashTableAllocator +{ +public: + void * alloc(size_t size) { return ::calloc(size, 1); } + void free(void * buf, size_t) { ::free(buf); } + void * realloc(void * buf, size_t old_size, size_t new_size) + { + buf = ::realloc(buf, new_size); + if (new_size > old_size) + memset(reinterpret_cast(buf) + old_size, 0, new_size - old_size); + return buf; + } +}; + +template +class HashTableAllocatorWithStackMemory : public HashTableAllocator {}; +HAEOF + fi fi fi printf '#pragma once\n#include \n' > contrib/stats-compat/stats/IntHash.h From 47a276befaefd6e6a87fdf44ff8fdcd828f36069 Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Thu, 2 Jul 2026 03:57:49 +0000 Subject: [PATCH 049/120] versions: reconstruct 2014-01 from source Two more era fixes (guarded / no-ops on newer months): - Prune add_subdirectory(X) when X is not an existing directory: the donor build lists component dirs (TableFunctions) added after this snapshot; cmake errors on the missing subdir and nothing in this era's globbed dbms links what it would have built. Variable-driven forms are left untouched. - Rewrite the pre-C++11 TR1 namespace to its C++11 form across dbms + libs: std::tr1::unordered_set/map -> std::..., and include paths -> <...>, which a modern gcc-5 in -std=gnu++1y mode no longer provides. Co-Authored-By: Claude Opus 4.8 --- versions/build-from-source/monthly-built.tsv | 1 + versions/build-from-source/reconstruct.sh | 19 +++++++++++++++++++ 2 files changed, 20 insertions(+) diff --git a/versions/build-from-source/monthly-built.tsv b/versions/build-from-source/monthly-built.tsv index faa7232b16..16228dfbfd 100644 --- a/versions/build-from-source/monthly-built.tsv +++ b/versions/build-from-source/monthly-built.tsv @@ -23,3 +23,4 @@ 2014-04-01 c12d5231dd48ad2e82d4e5bfa62987b32dae8a51 boots(pre-version()) 2014-03-01 78e9b847e08b1ad50db5443dd896ad5e7100e01b boots(pre-version()) 2014-02-01 82b98ffb6d88b4a30257f623e628ecbe48925436 boots(pre-version()) +2014-01-01 5d7fb8ecce5987e108afba878e77d5364a93d960 boots(pre-version()) diff --git a/versions/build-from-source/reconstruct.sh b/versions/build-from-source/reconstruct.sh index 415ae1c03c..d1af7e924d 100755 --- a/versions/build-from-source/reconstruct.sh +++ b/versions/build-from-source/reconstruct.sh @@ -146,6 +146,17 @@ def prune(cml): # a dropped target can't be linked or installed; strip those statements too. s2 = re.sub(r"target_link_libraries\s*\(\s*" + re.escape(tgt) + r"\b.*?\)", "", s2, flags=re.S|re.I) s2 = re.sub(r"INSTALL\s*\([^)]*\b" + re.escape(tgt) + r"\b[^)]*\)", "", s2, flags=re.S|re.I) + # Drop add_subdirectory(X) when X isn't an existing directory: the donor build + # lists component dirs (e.g. TableFunctions) that an older snapshot doesn't have + # yet. cmake errors on a missing subdir; the code that would have linked its + # library isn't present in this era's globbed dbms sources either, so no dangling + # refs. Skip variable-driven forms -- only prune bare directory-name arguments. + def fix_subdir(m): + arg = m.group(1) + if "$" in arg or "{" in arg: + return m.group(0) + return m.group(0) if os.path.isdir(os.path.join(d, arg)) else "" + s2 = re.sub(r"add_subdirectory\s*\(\s*([^\s)]+)\s*\)", fix_subdir, s2, flags=re.I) if s2 != s: wr(cml, s2) # os.walk (not glob(recursive=), which needs Python 3.5+; trusty ships 3.4). for root, _dirs, files in os.walk("."): @@ -1144,6 +1155,14 @@ open(p, 'w', encoding='utf-8', errors='surrogateescape').write(s) PYEOF fi +# -- std::tr1 -> std (pre-2014-02): the oldest snapshots use the pre-C++11 TR1 +# namespace (std::tr1::unordered_set/map) and include paths, which a +# modern gcc-5 in -std=gnu++1y mode no longer provides. Rewrite both to their C++11 +# forms. Guarded by grep, so it's a no-op on trees that already use std:: directly. -- +grep -rlZ 'tr1' dbms libs 2>/dev/null | while IFS= read -r -d '' f; do + sed -i 's##<\1>#g; s#std::tr1::#std::#g' "$f" +done + # -- HyperLogLog counter template arg order: pre-2015-09 # HyperLogLogWithSmallSetOptimization instantiates the counter as # HyperLogLogCounter (old 3-arg form). The back-ported From a84036f279bfe21a946f2ef5cdc0c7d96068b5af Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Thu, 2 Jul 2026 04:03:06 +0000 Subject: [PATCH 050/120] versions: reconstruct 2013-12 from source Drop libmysqlxx's POST_BUILD patch.sh step when the script is absent. The donor CMakeLists runs libmysqlxx/patch.sh to patch the bundled mysqlclient, and the CMakeLists overlay doesn't bring the script -- newer target trees ship their own copy, but the oldest (pre-2014) don't, so the command failed with 'not found' (Error 127). We link the system libmysqlclient and never use MySQL in the benchmark, so the patch is unnecessary. Guarded on patch.sh existence, so trees that ship it keep patching as before. Co-Authored-By: Claude Opus 4.8 --- versions/build-from-source/monthly-built.tsv | 1 + versions/build-from-source/reconstruct.sh | 9 +++++++++ 2 files changed, 10 insertions(+) diff --git a/versions/build-from-source/monthly-built.tsv b/versions/build-from-source/monthly-built.tsv index 16228dfbfd..d0dd38e68a 100644 --- a/versions/build-from-source/monthly-built.tsv +++ b/versions/build-from-source/monthly-built.tsv @@ -24,3 +24,4 @@ 2014-03-01 78e9b847e08b1ad50db5443dd896ad5e7100e01b boots(pre-version()) 2014-02-01 82b98ffb6d88b4a30257f623e628ecbe48925436 boots(pre-version()) 2014-01-01 5d7fb8ecce5987e108afba878e77d5364a93d960 boots(pre-version()) +2013-12-01 ff7cd145ca21b225b9734e5c08e9984475fb6d68 boots(pre-version()) diff --git a/versions/build-from-source/reconstruct.sh b/versions/build-from-source/reconstruct.sh index d1af7e924d..0059a166e9 100755 --- a/versions/build-from-source/reconstruct.sh +++ b/versions/build-from-source/reconstruct.sh @@ -77,6 +77,15 @@ if os.path.exists(f): s = re.sub(r"add_library\s*\(\s*mysqlxx\b.*?\)", "file(GLOB mysqlxx_src src/*.cpp)\nadd_library(mysqlxx ${mysqlxx_src})", s, count=1, flags=re.S) + # The donor CMakeLists has a POST_BUILD step running libmysqlxx/patch.sh to patch + # the bundled mysqlclient. Newer target trees ship that script, but the oldest + # (pre-2014) don't -- and the overlay only brings CMakeLists/.cmake, not patch.sh, + # so the command fails with "not found" (Error 127). We link the *system* + # libmysqlclient and never touch MySQL in the benchmark, so when the script is + # absent just drop the custom command. Guarded on patch.sh existence -> no-op on + # trees that ship it (they keep patching, as before). + if not os.path.exists("libs/libmysqlxx/patch.sh"): + s = re.sub(r"ADD_CUSTOM_COMMAND\s*\([^)]*patch\.sh[^)]*\)", "", s, flags=re.I|re.S) wr(f, s) # Drop the (never-vendored) mongoclient link name wherever it appears. From 71d2ad19be14cfc7a6a1588bcb583daa94a3dd65 Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Thu, 2 Jul 2026 04:22:33 +0000 Subject: [PATCH 051/120] versions: reset all hits query minimum-version annotations to 0 The 20.5 floor on hits queries 18-26 and 33-41 was not a capability limit but a memory-exhaustion artifact. The actual 20.4.9.110 run log shows Code 241 (MEMORY_LIMIT_EXCEEDED, 'maximum: 27.58 GiB' = max_server_memory_usage on the 32 GB VM), and the failures cascade: a heavy high-cardinality GROUP BY pushes the global memory tracker to the ceiling, and subsequent queries in the block -- even trivial ones like a point filter on UserID -- then fail too, because the runner's drop_caches only drops the host page cache (not ClickHouse's tracked memory) and revive only fires on a crash, not a Code 241 error. A query that succeeded 3 tries then OOM'd 3 more confirms it is cumulative, not per-query capability. Reset to 0 so these queries are re-attempted on every version; older versions may well run them given a clean memory state. The runner's memory-isolation is being addressed separately. Co-Authored-By: Claude Opus 4.8 --- versions/queries/hits.minver | 36 ++++++++++++++++++------------------ 1 file changed, 18 insertions(+), 18 deletions(-) diff --git a/versions/queries/hits.minver b/versions/queries/hits.minver index fff3f3d4f7..e6d6b5f60e 100644 --- a/versions/queries/hits.minver +++ b/versions/queries/hits.minver @@ -15,29 +15,29 @@ 0 0 0 -20.5 -20.5 -20.5 -20.5 -20.5 -20.5 -20.5 -20.5 -20.5 0 0 0 0 0 0 -20.5 -20.5 -20.5 -20.5 -20.5 -20.5 -20.5 -20.5 -20.5 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 +0 0 0 From 6a88763c021b8855ed5c04cd7e542318d42b9662 Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Thu, 2 Jul 2026 04:52:11 +0000 Subject: [PATCH 052/120] versions: add release_date and server-reported version to result JSON The result JSON now carries two more fields: - release_date: resolved from list-versions.sh column 3 (the authoritative version_date.tsv) for published and tagged source builds, falling back to the commit date in monthly.tsv for the reconstructed monthly snapshots. - actual_version (server-reported): SELECT version() where it exists (it returns 0.0. on the pre-release source builds), falling back to 0.0. for the oldest builds that have no version() function -- read from /clickhouse-revision baked into the reconstructed image. The reconstructed image now derives its revision from the snapshot's own source: the maximum DBMS_MIN_REVISION_WITH_* constant in Core/Defines.h. Those are real SVN revisions (the newest feature the snapshot carries landed at that revision), so the reported 0.0. is authentic and era-ordered. It is also always >= the minimum the in-image client enforces at handshake -- a lower, 'more authentic' number such as 0.0.34172 makes the client reject its own server ('Server revision is too old ... at least 34482'). Verified on 2014-06 (reports 0.0.50264). Co-Authored-By: Claude Opus 4.8 --- .../build-from-source/Dockerfile.reconstruct | 17 ++++++++- versions/run-version.sh | 38 +++++++++++++++++-- 2 files changed, 51 insertions(+), 4 deletions(-) diff --git a/versions/build-from-source/Dockerfile.reconstruct b/versions/build-from-source/Dockerfile.reconstruct index edcc97fc42..e06a1e56af 100644 --- a/versions/build-from-source/Dockerfile.reconstruct +++ b/versions/build-from-source/Dockerfile.reconstruct @@ -88,6 +88,17 @@ RUN bash /reconstruct.sh # Configure, then build. re2/re2_st must be built (and put on the linker search # path) before the server links; revision.h is generated directly (the donor's # generator does a git-fetch that hangs on a shallow checkout). +# +# Revision: derive the authentic era revision from the source itself -- the maximum of +# the DBMS_MIN_REVISION_WITH_* feature-gate constants in Core/Defines.h. Those are real +# SVN revisions (the newest feature this snapshot carries landed at that revision, i.e. +# ~= the snapshot's own revision), so it is era-ordered and, being >= every threshold +# the in-image client checks at handshake, keeps client and server compatible (a lower, +# "more authentic" number like 0.0.34172 makes the client reject its own server: +# "Server revision is too old ... at least 34482"). The compiled-in value is what the +# server reports (0.0.); it is also written to /clickhouse-revision so +# run-version.sh can report the same value on the oldest builds, which have no SELECT +# version(). Falls back to the REVISION build-arg if no constants are found. ARG REVISION=53400 WORKDIR /src/build RUN cmake .. -DCMAKE_BUILD_TYPE=Release -DTESTS=NO \ @@ -96,7 +107,11 @@ RUN cmake .. -DCMAKE_BUILD_TYPE=Release -DTESTS=NO \ && cp "$(find . -name libre2.a | head -1)" /usr/lib/ \ && cp "$(find . -name libre2_st.a | head -1)" /usr/lib/ \ && mkdir -p /src/build/libs/libcommon/src \ - && printf '#ifndef REVISION\n#define REVISION %s\n#endif\n#ifndef SVN_REVISION\n#define SVN_REVISION %s\n#endif\n' "${REVISION}" "${REVISION}" > /src/build/libs/libcommon/src/revision.h \ + && { REV=$(grep -hoE 'DBMS_MIN_REVISION_WITH_[A-Z_]+[[:space:]]+[0-9]+' $(find /src -path '*/Core/Defines.h' 2>/dev/null) 2>/dev/null | grep -oE '[0-9]+$' | sort -n | tail -1); \ + REV=${REV:-${REVISION}}; \ + echo "reconstruct: using revision ${REV}"; \ + printf '%s' "${REV}" > /clickhouse-revision; \ + printf '#ifndef REVISION\n#define REVISION %s\n#endif\n#ifndef SVN_REVISION\n#define SVN_REVISION %s\n#endif\n' "${REV}" "${REV}" > /src/build/libs/libcommon/src/revision.h; } \ && make -j"$(nproc)" clickhouse-server && make -j"$(nproc)" clickhouse-client # Install binaries + a multi-call shim + a minimal IPv4 config (this era ships diff --git a/versions/run-version.sh b/versions/run-version.sh index a4639d7034..813323d694 100755 --- a/versions/run-version.sh +++ b/versions/run-version.sh @@ -114,6 +114,9 @@ ensure_built_image() { fi sha="$(awk -F'\t' -v v="${VERSION}" '$1==v{print $2; exit}' "${bfs}/monthly.tsv" 2>/dev/null)" if [ -n "${sha}" ]; then + # The revision is derived from the snapshot's own source (max + # DBMS_MIN_REVISION_WITH_* in Core/Defines.h) inside Dockerfile.reconstruct, so + # each build reports its authentic era revision as 0.0.; nothing to pass here. echo "reconstructing ${IMAGE} from source (commit ${sha})" >&2 sudo docker buildx build --progress=plain --load --build-arg "TAG=${sha}" \ -t "${IMAGE}" -f "${bfs}/Dockerfile.reconstruct" "${bfs}" >&2 @@ -426,15 +429,44 @@ emit_data_size_json() { printf '%s' "${out}" | awk -F'\t' 'BEGIN{printf "{"} NF>=2 && $2!=""{printf "%s\"%s\": %s",(n++?", ":""),$1,$2} END{printf "}"}' } +# Release date of this version, for the result JSON. list-versions.sh already +# resolves it (column 3) from the authoritative version_date.tsv for published and +# tagged source builds; the reconstructed monthly snapshots aren't in that list, so +# fall back to their commit date in monthly.tsv (column 3). +release_date() { + local d + d=$(./list-versions.sh 2>/dev/null | awk -F'\t' -v v="${VERSION}" '$1==v{print $3; exit}') + [ -z "${d}" ] && d=$(awk -F'\t' -v v="${VERSION}" '$1==v{print $3; exit}' "${HERE}/build-from-source/monthly.tsv" 2>/dev/null) + printf '%s' "${d}" +} + +# Version string as reported by the running server. SELECT version() works from +# ~2015-07 on and returns 0.0. for the pre-release source builds (e.g. +# 0.0.53975). The oldest prehistoric builds have no version() function at all, so +# fall back to 0.0. using the revision compiled into the reconstructed +# image (baked at /clickhouse-revision by Dockerfile.reconstruct) -- which is exactly +# what those servers report in their TCP handshake. +server_version() { + local v rev + v=$(client --query "SELECT version()" 2>/dev/null | tr -d '\r') + if [ -z "${v}" ]; then + rev=$(sudo docker exec "${CONTAINER}" cat /clickhouse-revision 2>/dev/null | tr -d '\r\n ') + [ -n "${rev}" ] && v="0.0.${rev}" + fi + printf '%s' "${v}" +} + # Time every query and write results/.json. run_benchmark() { - local ACTUAL ds query FIRST=1 qnum=0 row QDB MINVERS mv lidx - ACTUAL=$(client --query "SELECT version()" 2>/dev/null | tr -d '\r') - echo "benchmarking ${VERSION} (server reports ${ACTUAL})" >&2 + local ACTUAL RELEASE ds query FIRST=1 qnum=0 row QDB MINVERS mv lidx + ACTUAL=$(server_version) + RELEASE=$(release_date) + echo "benchmarking ${VERSION} (server reports ${ACTUAL:-unknown}, released ${RELEASE:-unknown})" >&2 { echo '{' echo " \"version\": \"${VERSION}\"," echo " \"actual_version\": \"${ACTUAL}\"," + echo " \"release_date\": \"${RELEASE}\"," echo " \"load_time\": $(emit_load_time_json)," echo " \"data_size\": $(emit_data_size_json)," echo ' "result":' From 793438837877bcea0ae91ac6b2f9ebb5b40a70ba Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Thu, 2 Jul 2026 05:07:33 +0000 Subject: [PATCH 053/120] versions: assign interpolated per-month revisions from protocol defines The reconstructed monthly snapshots report 0.0., and that revision must be >= the maximum DBMS_MIN_REVISION_WITH_* constant present in the snapshot, since those defines gate the wire protocol (a lower value makes the in-image client reject its own server at handshake). Rather than reporting only that floor -- which is flat across months where no new define landed -- derive a smooth per-month value: - Each DBMS_MIN_REVISION_WITH_* constant is the real SVN revision where that protocol feature landed; git dates when each define first appeared give (date, revision) anchors (28558 @ 2013-02 ... 51903 @ 2015-01 ... 54032 @ 2016-10). - monthly.tsv column 4 is each snapshot's revision, linearly interpolated by commit date between those anchors (e.g. 2014-04 -> 50276, just above its own TEMPORARY_TABLES=50264 define; 2016-02 -> 53166), monotonic across the timeline. - Dockerfile.reconstruct clamps the passed revision up to the snapshot's own protocol floor as a safety net, then compiles it in and writes /clickhouse-revision. Verified on 2014-06: reports 0.0.50653 (protocol floor 50264), handshake OK. Co-Authored-By: Claude Opus 4.8 --- .../build-from-source/Dockerfile.reconstruct | 31 ++--- versions/build-from-source/monthly.tsv | 106 +++++++++--------- versions/run-version.sh | 14 ++- 3 files changed, 78 insertions(+), 73 deletions(-) diff --git a/versions/build-from-source/Dockerfile.reconstruct b/versions/build-from-source/Dockerfile.reconstruct index e06a1e56af..47df1c2e13 100644 --- a/versions/build-from-source/Dockerfile.reconstruct +++ b/versions/build-from-source/Dockerfile.reconstruct @@ -89,17 +89,18 @@ RUN bash /reconstruct.sh # path) before the server links; revision.h is generated directly (the donor's # generator does a git-fetch that hangs on a shallow checkout). # -# Revision: derive the authentic era revision from the source itself -- the maximum of -# the DBMS_MIN_REVISION_WITH_* feature-gate constants in Core/Defines.h. Those are real -# SVN revisions (the newest feature this snapshot carries landed at that revision, i.e. -# ~= the snapshot's own revision), so it is era-ordered and, being >= every threshold -# the in-image client checks at handshake, keeps client and server compatible (a lower, -# "more authentic" number like 0.0.34172 makes the client reject its own server: -# "Server revision is too old ... at least 34482"). The compiled-in value is what the -# server reports (0.0.); it is also written to /clickhouse-revision so -# run-version.sh can report the same value on the oldest builds, which have no SELECT -# version(). Falls back to the REVISION build-arg if no constants are found. -ARG REVISION=53400 +# Revision: the caller passes REVISION -- the per-month value interpolated in +# monthly.tsv between the dates the DBMS_MIN_REVISION_WITH_* protocol defines were +# introduced (those constants are the real SVN revisions where each protocol feature +# landed). We then clamp it up to this snapshot's own protocol FLOOR: the maximum +# DBMS_MIN_REVISION_WITH_* constant in Core/Defines.h. The floor matters because those +# defines control the wire protocol -- the compiled-in revision must be >= every +# threshold the in-image client checks at handshake, or the client rejects its own +# server ("Server revision is too old ... at least 34482"). The resulting value is +# what the server reports (0.0.) and is written to /clickhouse-revision so +# run-version.sh reports the same on the oldest builds, which have no SELECT version(). +# With no REVISION passed it falls back to the floor, then to 53400. +ARG REVISION= WORKDIR /src/build RUN cmake .. -DCMAKE_BUILD_TYPE=Release -DTESTS=NO \ -DCMAKE_C_COMPILER="gcc-${GCC}" -DCMAKE_CXX_COMPILER="g++-${GCC}" \ @@ -107,9 +108,11 @@ RUN cmake .. -DCMAKE_BUILD_TYPE=Release -DTESTS=NO \ && cp "$(find . -name libre2.a | head -1)" /usr/lib/ \ && cp "$(find . -name libre2_st.a | head -1)" /usr/lib/ \ && mkdir -p /src/build/libs/libcommon/src \ - && { REV=$(grep -hoE 'DBMS_MIN_REVISION_WITH_[A-Z_]+[[:space:]]+[0-9]+' $(find /src -path '*/Core/Defines.h' 2>/dev/null) 2>/dev/null | grep -oE '[0-9]+$' | sort -n | tail -1); \ - REV=${REV:-${REVISION}}; \ - echo "reconstruct: using revision ${REV}"; \ + && { FLOOR=$(grep -hoE 'DBMS_MIN_REVISION_WITH_[A-Z_]+[[:space:]]+[0-9]+' $(find /src -path '*/Core/Defines.h' 2>/dev/null) 2>/dev/null | grep -oE '[0-9]+$' | sort -n | tail -1); \ + REV=${REVISION:-${FLOOR}}; \ + if [ -n "${FLOOR}" ] && [ "${REV:-0}" -lt "${FLOOR}" ] 2>/dev/null; then REV=${FLOOR}; fi; \ + REV=${REV:-53400}; \ + echo "reconstruct: using revision ${REV} (protocol floor ${FLOOR:-none})"; \ printf '%s' "${REV}" > /clickhouse-revision; \ printf '#ifndef REVISION\n#define REVISION %s\n#endif\n#ifndef SVN_REVISION\n#define SVN_REVISION %s\n#endif\n' "${REV}" "${REV}" > /src/build/libs/libcommon/src/revision.h; } \ && make -j"$(nproc)" clickhouse-server && make -j"$(nproc)" clickhouse-client diff --git a/versions/build-from-source/monthly.tsv b/versions/build-from-source/monthly.tsv index bd52a1d21f..30b6b7b1a9 100644 --- a/versions/build-from-source/monthly.tsv +++ b/versions/build-from-source/monthly.tsv @@ -1,53 +1,53 @@ -2016-05-01 2b1550105cec9ff8192606560931191d69101397 2016-04-28 -2016-04-01 f41bba57a546430ed2c3d3c5e97a599003a6889d 2016-04-01 -2016-03-01 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7182920cecd3ec7d1e6fffd64ec52679d4e111ef 2011-12-30 28558 diff --git a/versions/run-version.sh b/versions/run-version.sh index 813323d694..66cc24954e 100755 --- a/versions/run-version.sh +++ b/versions/run-version.sh @@ -112,13 +112,15 @@ ensure_built_image() { bash "${bfs}/build.sh" "${VERSION}" "${tag:-v${VERSION}-stable}" "${gcc:-5}" >&2 return $? fi - sha="$(awk -F'\t' -v v="${VERSION}" '$1==v{print $2; exit}' "${bfs}/monthly.tsv" 2>/dev/null)" + local rev + read -r sha rev < <(awk -F'\t' -v v="${VERSION}" '$1==v{print $2, $4; exit}' "${bfs}/monthly.tsv" 2>/dev/null) if [ -n "${sha}" ]; then - # The revision is derived from the snapshot's own source (max - # DBMS_MIN_REVISION_WITH_* in Core/Defines.h) inside Dockerfile.reconstruct, so - # each build reports its authentic era revision as 0.0.; nothing to pass here. - echo "reconstructing ${IMAGE} from source (commit ${sha})" >&2 - sudo docker buildx build --progress=plain --load --build-arg "TAG=${sha}" \ + # monthly.tsv column 4 is the per-month revision, interpolated between the dates + # the DBMS_MIN_REVISION_WITH_* protocol defines appeared; the Dockerfile clamps + # it up to the snapshot's own protocol floor. The server then reports 0.0.. + echo "reconstructing ${IMAGE} from source (commit ${sha}, revision ${rev:-auto})" >&2 + sudo docker buildx build --progress=plain --load \ + --build-arg "TAG=${sha}" ${rev:+--build-arg "REVISION=${rev}"} \ -t "${IMAGE}" -f "${bfs}/Dockerfile.reconstruct" "${bfs}" >&2 return $? fi From fabe5a620828b2db9381bef93b71c22c10daf90c Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Thu, 2 Jul 2026 05:16:18 +0000 Subject: [PATCH 054/120] versions: delete pre-rework scripts/results; fetch results from the sink - Remove the pre-rework apt-based harness (versions/scripts, versions/unified_scripts) and the old 75-query result JSONs, all superseded by the Docker-based pipeline. - Add fetch-results.sh: pull the latest Versions Benchmark result for each version from the sink (sink.data, kind=versions-benchmark), enrich with the release date (list-versions.sh / monthly.tsv), and write results/.json. Uses $CONNECTION_PARAMS like the repo's collect-results.sh. - Regenerate results/ from the sink: 179 versions, each with per-dataset load_time and data_size, release_date, and the 344-query result array. Co-Authored-By: Claude Opus 4.8 --- versions/fetch-results.sh | 55 ++++++++++++++ versions/results/1.1.54019.json | 83 +--------------------- versions/results/1.1.54020.json | 1 + versions/results/1.1.54022.json | 1 + versions/results/1.1.54023.json | 1 + versions/results/1.1.54030.json | 1 + versions/results/1.1.54046.json | 1 + versions/results/1.1.54074.json | 1 + versions/results/1.1.54080.json | 1 + versions/results/1.1.54083.json | 1 + versions/results/1.1.54112.json | 1 + versions/results/1.1.54127.json | 1 + versions/results/1.1.54133.json | 1 + versions/results/1.1.54134.json | 1 + versions/results/1.1.54135.json | 1 + versions/results/1.1.54144.json | 1 + versions/results/1.1.54159.json | 1 + versions/results/1.1.54181.json | 1 + versions/results/1.1.54188.json | 1 + versions/results/1.1.54190.json | 1 + versions/results/1.1.54198.json | 1 + versions/results/1.1.54236.json | 1 + versions/results/1.1.54242.json | 1 + versions/results/1.1.54245.json | 1 + versions/results/1.1.54276.json | 1 + versions/results/1.1.54282.json | 1 + versions/results/1.1.54284.json | 1 + versions/results/1.1.54289.json | 1 + versions/results/1.1.54292.json | 1 + versions/results/1.1.54304.json | 1 + versions/results/1.1.54310.json | 1 + versions/results/1.1.54327.json | 1 + versions/results/1.1.54335.json | 1 + versions/results/1.1.54336.json | 1 + versions/results/1.1.54337.json | 1 + versions/results/1.1.54342.json | 1 + versions/results/1.1.54343.json | 1 + versions/results/1.1.54358.json | 1 + versions/results/1.1.54362.json | 1 + versions/results/1.1.54370.json | 1 + versions/results/1.1.54378.json | 83 +--------------------- versions/results/1.1.54380.json | 82 +-------------------- versions/results/1.1.54381.json | 82 +-------------------- versions/results/1.1.54383.json | 82 +-------------------- versions/results/1.1.54385.json | 82 +-------------------- versions/results/1.1.54388.json | 82 +-------------------- versions/results/1.1.54390.json | 82 +-------------------- versions/results/1.1.54394.json | 82 +-------------------- versions/results/18.1.0.json | 82 +-------------------- versions/results/18.10.3.json | 82 +-------------------- versions/results/18.12.17.json | 82 +-------------------- versions/results/18.14.19.json | 82 +-------------------- versions/results/18.16.1+ds.json | 81 --------------------- versions/results/18.16.1.json | 1 + versions/results/18.4.0.json | 82 +-------------------- versions/results/18.5.1.json | 82 +-------------------- versions/results/18.6.0.json | 82 +-------------------- versions/results/19.1.16.79.json | 1 + versions/results/19.1.16.json | 81 --------------------- versions/results/19.10.1.5.json | 83 +--------------------- versions/results/19.11.14.1.json | 83 +--------------------- versions/results/19.13.7.57.json | 83 +--------------------- versions/results/19.14.13.4.json | 83 +--------------------- versions/results/19.15.7.30.json | 83 +--------------------- versions/results/19.16.19.85.json | 83 +--------------------- versions/results/19.17.10.1.json | 83 +--------------------- versions/results/19.3.9.12.json | 1 + versions/results/19.3.9.json | 81 --------------------- versions/results/19.4.5.35.json | 82 +-------------------- versions/results/19.5.4.22.json | 82 +-------------------- versions/results/19.6.3.18.json | 83 +--------------------- versions/results/19.7.5.29.json | 83 +--------------------- versions/results/19.8.3.8.json | 83 +--------------------- versions/results/19.9.5.36.json | 83 +--------------------- versions/results/20.1.16.120.json | 83 +--------------------- versions/results/20.10.7.4.json | 83 +--------------------- versions/results/20.11.6.6.json | 83 +--------------------- versions/results/20.12.8.5.json | 83 +--------------------- versions/results/20.3.21.2.json | 83 +--------------------- versions/results/20.4.9.110.json | 83 +--------------------- versions/results/20.5.5.74.json | 83 +--------------------- versions/results/20.6.11.1.json | 83 +--------------------- versions/results/20.7.4.11.json | 83 +--------------------- versions/results/20.8.19.4.json | 83 +--------------------- versions/results/20.9.7.11.json | 83 +--------------------- versions/results/21.1.9.41.json | 83 +--------------------- versions/results/21.10.5.3.json | 1 + versions/results/21.10.6.2.json | 82 --------------------- versions/results/21.11.11.1.json | 83 +--------------------- versions/results/21.12.4.1.json | 83 +--------------------- versions/results/21.2.10.48.json | 83 +--------------------- versions/results/21.3.20.1.json | 83 +--------------------- versions/results/21.4.7.3.json | 1 + versions/results/21.5.9.4.json | 83 +--------------------- versions/results/21.6.9.7.json | 83 +--------------------- versions/results/21.7.11.3.json | 83 +--------------------- versions/results/21.8.15.7.json | 83 +--------------------- versions/results/21.9.6.24.json | 83 +--------------------- versions/results/22.1.4.30.json | 1 + versions/results/22.10.7.13.json | 83 +--------------------- versions/results/22.11.6.44.json | 83 +--------------------- versions/results/22.12.6.22.json | 83 +--------------------- versions/results/22.2.3.5.json | 1 + versions/results/22.3.20.29.json | 83 +--------------------- versions/results/22.4.6.53.json | 83 +--------------------- versions/results/22.5.4.19.json | 83 +--------------------- versions/results/22.6.9.11.json | 83 +--------------------- versions/results/22.7.7.24.json | 83 +--------------------- versions/results/22.8.20.11.json | 82 --------------------- versions/results/22.8.21.38.json | 1 + versions/results/22.9.7.34.json | 83 +--------------------- versions/results/23.1.7.30.json | 83 +--------------------- versions/results/23.10.4.25.json | 82 --------------------- versions/results/23.10.6.60.json | 1 + versions/results/23.11.1.2711.json | 82 --------------------- versions/results/23.11.5.29.json | 1 + versions/results/23.12.1.1368.json | 82 --------------------- versions/results/23.12.6.19.json | 1 + versions/results/23.2.7.32.json | 83 +--------------------- versions/results/23.3.22.3.json | 1 + versions/results/23.3.8.21.json | 82 --------------------- versions/results/23.4.6.25.json | 83 +--------------------- versions/results/23.5.4.25.json | 82 --------------------- versions/results/23.5.5.92.json | 1 + versions/results/23.6.2.18.json | 82 --------------------- versions/results/23.6.3.87.json | 1 + versions/results/23.7.5.30_old.json | 81 --------------------- versions/results/23.7.6.111.json | 83 +--------------------- versions/results/23.8.16.40.json | 1 + versions/results/23.8.7.24.json | 82 --------------------- versions/results/23.9.5.29.json | 82 --------------------- versions/results/23.9.6.20.json | 1 + versions/results/24.1.1.2048.json | 82 --------------------- versions/results/24.1.8.22.json | 1 + versions/results/24.10.1.2812.json | 82 --------------------- versions/results/24.10.4.191.json | 1 + versions/results/24.11.1.2557.json | 82 --------------------- versions/results/24.11.5.49.json | 1 + versions/results/24.12.5.81.json | 82 --------------------- versions/results/24.12.6.70.json | 1 + versions/results/24.2.1.2248.json | 82 --------------------- versions/results/24.2.3.70.json | 1 + versions/results/24.3.18.7.json | 1 + versions/results/24.3.3.102.json | 82 --------------------- versions/results/24.4.1.2088.json | 82 --------------------- versions/results/24.4.4.113.json | 1 + versions/results/24.5.3.5.json | 82 --------------------- versions/results/24.5.8.10.json | 1 + versions/results/24.6.1.4392.json | 82 --------------------- versions/results/24.6.6.6.json | 1 + versions/results/24.7.3.42.json | 82 --------------------- versions/results/24.7.6.8.json | 1 + versions/results/24.8.14.39.json | 1 + versions/results/24.8.2.3.json | 82 --------------------- versions/results/24.9.2.42.json | 82 --------------------- versions/results/24.9.3.128.json | 1 + versions/results/25.1.5.31.json | 82 --------------------- versions/results/25.1.8.25.json | 1 + versions/results/25.10.1.3832.json | 82 --------------------- versions/results/25.10.7.6.json | 1 + versions/results/25.11.2.24.json | 82 --------------------- versions/results/25.11.9.34.json | 1 + versions/results/25.12.11.4.json | 1 + versions/results/25.12.5.44.json | 82 --------------------- versions/results/25.2.1.3085.json | 82 --------------------- versions/results/25.2.2.39.json | 1 + versions/results/25.3.14.14.json | 1 + versions/results/25.3.3.42.json | 82 --------------------- versions/results/25.4.1.2934.json | 82 --------------------- versions/results/25.4.13.22.json | 1 + versions/results/25.5.1.2782.json | 82 --------------------- versions/results/25.5.11.15.json | 1 + versions/results/25.6.13.41.json | 1 + versions/results/25.6.2.5.json | 82 --------------------- versions/results/25.7.1.3997.json | 82 --------------------- versions/results/25.7.8.71.json | 1 + versions/results/25.8.1.5101.json | 82 --------------------- versions/results/25.8.24.21.json | 1 + versions/results/25.9.5.21.json | 82 --------------------- versions/results/25.9.7.56.json | 1 + versions/results/26.1.12.23.json | 1 + versions/results/26.1.2.11.json | 82 --------------------- versions/results/26.2.16.4.json | 82 --------------------- versions/results/26.2.19.43.json | 1 + versions/results/26.3.13.31.json | 1 + versions/results/26.3.9.8.json | 82 --------------------- versions/results/26.4.3.37.json | 1 + versions/results/26.5.3.52.json | 1 + versions/results/26.6.1.1193.json | 1 + versions/results/53974.json | 83 +--------------------- versions/results/53975.json | 83 +--------------------- versions/results/53976.json | 83 +--------------------- versions/results/53977.json | 83 +--------------------- versions/results/53978.json | 83 +--------------------- versions/results/53979.json | 83 +--------------------- 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11425 deletions(-) create mode 100755 versions/fetch-results.sh create mode 100644 versions/results/1.1.54020.json create mode 100644 versions/results/1.1.54022.json create mode 100644 versions/results/1.1.54023.json create mode 100644 versions/results/1.1.54030.json create mode 100644 versions/results/1.1.54046.json create mode 100644 versions/results/1.1.54074.json create mode 100644 versions/results/1.1.54080.json create mode 100644 versions/results/1.1.54083.json create mode 100644 versions/results/1.1.54112.json create mode 100644 versions/results/1.1.54127.json create mode 100644 versions/results/1.1.54133.json create mode 100644 versions/results/1.1.54134.json create mode 100644 versions/results/1.1.54135.json create mode 100644 versions/results/1.1.54144.json create mode 100644 versions/results/1.1.54159.json create mode 100644 versions/results/1.1.54181.json create mode 100644 versions/results/1.1.54188.json create mode 100644 versions/results/1.1.54190.json create mode 100644 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versions/unified_scripts/old_versions.list delete mode 100755 versions/unified_scripts/runner.sh delete mode 100644 versions/unified_scripts/versions.list diff --git a/versions/fetch-results.sh b/versions/fetch-results.sh new file mode 100755 index 0000000000..504fc4084f --- /dev/null +++ b/versions/fetch-results.sh @@ -0,0 +1,55 @@ +#!/bin/bash -e + +# Fetch the latest Versions Benchmark result for every version from the sink database +# (sink.data, rows with kind = "versions-benchmark", sent by cloud-init.sh.in) and write +# results/.json, enriched with the release date. The committed result files are +# produced solely by this script -- do not edit them by hand. +# +# Connection settings come from $CONNECTION_PARAMS, as in the repo's collect-results.sh: +# CONNECTION_PARAMS='--user check_benchmark_results --password *** --host play.clickhouse.com --secure' \ +# ./fetch-results.sh +# +# Then regenerate the page data with ./generate-results.sh. + +HERE="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" +cd "${HERE}" +CH() { clickhouse-client ${CONNECTION_PARAMS} "$@"; } + +mkdir -p results + +# Release-date lookup. list-versions.sh resolves it (column 3) for published and tagged +# builds from the authoritative version_date.tsv; the reconstructed monthly snapshots are +# not in that list, so fall back to their commit date in build-from-source/monthly.tsv. +LV="$(./list-versions.sh 2>/dev/null || true)" +reldate() { + local v="$1" d + d="$(awk -F'\t' -v v="$v" '$1==v{print $3; exit}' <<<"${LV}")" + [ -z "${d}" ] && d="$(awk -F'\t' -v v="$v" '$1==v{print $3; exit}' build-from-source/monthly.tsv 2>/dev/null)" + printf '%s' "${d}" +} + +mapfile -t VERSIONS < <(CH --query " + SELECT DISTINCT JSONExtractString(content, 'version') AS v + FROM sink.data + WHERE JSONExtractString(content, 'kind') = 'versions-benchmark' AND v != '' + ORDER BY v + FORMAT TSV") + +echo "fetching ${#VERSIONS[@]} versions from the sink" >&2 +rm -f results/*.json +for v in "${VERSIONS[@]}"; do + [ -z "${v}" ] && continue + # argMax over time keeps the most recent run for this version. + CH --query " + SELECT argMax(content, time) FROM sink.data + WHERE JSONExtractString(content, 'kind') = 'versions-benchmark' + AND JSONExtractString(content, 'version') = '${v}' + FORMAT TSVRaw" > /tmp/vb-content.json + rd="$(reldate "${v}")" + # Keep the recorded fields; add release_date (preferring one already in the payload). + jq -S --arg rd "${rd}" \ + '. + {release_date: (.release_date // (if $rd == "" then null else $rd end))}' \ + /tmp/vb-content.json > "results/${v}.json" + echo " results/${v}.json (released ${rd:-unknown})" >&2 +done +echo "wrote $(ls results/*.json 2>/dev/null | wc -l) result files" >&2 diff --git a/versions/results/1.1.54019.json b/versions/results/1.1.54019.json index d7e7950f1a..7d07d639cf 100644 --- a/versions/results/1.1.54019.json +++ b/versions/results/1.1.54019.json @@ -1,82 +1 @@ -{ - "version": "1.1.54019", - "actual_version": "1.1.54019", - "result": - [ -[null, null, null], -[null, null, null], -[null, null, null], -[null, null, null], -[null, null, null], -[null, null, null], -[0.079, 0.008, 0.008], -[0.081, 0.023, 0.024], -[null, null, null], -[0.134, 0.089, 0.079], -[null, null, null], -[1.178, 0.380, 0.375], -[null, null, null], -[null, null, null], -[null, null, null], -[3.441, 0.208, 0.205], -[null, null, null], -[3.423, 0.255, 0.255], -[57.621, 1.702, 1.684], -[44.238, 1.320, 1.316], -[44.353, 1.309, 1.299], -[53.659, 2.471, 2.475], -[61.644, 2.476, 2.452], -[42.120, 1.821, 1.819], -[null, null, null], -[68.166, 2.124, 2.113], -[20.773, 0.941, 0.961], -[21.461, 0.844, 0.844], -[0.065, 0.012, 0.010], -[0.079, 0.013, 0.014], -[0.075, 0.022, 0.023], -[0.756, 0.039, 0.039], -[0.818, 0.111, 0.109], -[1.789, 0.144, 0.145], -[0.070, 0.016, 0.015], -[0.069, 0.015, 0.014], -[1.385, 0.164, 0.166], -[1.778, 0.186, 0.188], -[0.894, 0.181, 0.174], -[0.946, 0.192, 0.198], -[1.799, 0.280, 0.274], -[3.508, 0.308, 0.306], -[2.054, 0.300, 0.299], -[0.857, 0.341, 0.336], -[3.638, 0.894, 0.792], -[3.836, 0.700, 0.690], -[6.902, 1.030, 0.969], -[0.747, 0.058, 0.056], -[18.092, 0.256, 0.248], -[20.745, 0.344, 0.333], -[38.815, 0.630, 0.622], -[31.769, 0.415, 0.386], -[4.624, 0.168, 0.163], -[1.731, 0.144, 0.148], -[4.625, 0.152, 0.173], -[18.113, 0.377, 0.371], -[15.269, 0.402, 0.401], -[0.738, 0.670, 0.695], -[3.568, 0.327, 0.321], -[9.489, 0.395, 0.379], -[8.129, 2.495, 2.446], -[18.588, 1.378, 1.328], -[18.339, 1.021, 0.844], -[0.744, 0.566, 0.573], -[0.155, 0.076, 0.125], -[0.103, 0.055, 0.055], -[0.112, 0.043, 0.037], -[0.261, 0.142, 0.145], -[0.082, 0.013, 0.013], -[0.070, 0.011, 0.012], -[0.052, 0.004, 0.004], -[76.757, 3.468, 3.500], -[129.489, 3.390, 3.347], -[91.138, 3.978, 3.993], -[151.217, 6.332, 6.324] - ] -} +{"actual_version":"1.1.54019","data_size":{"default":4096,"hits":14212886527,"job":1816841964,"mgbench":1074952778,"ontime":2322016698,"ssb":74342854748,"taxi":23118404107,"tpcds":19012720281,"tpch":18888239027,"uk":722425129},"kind":"versions-benchmark","load_time":{"hits":215,"job":64,"mgbench":26,"ontime":75,"ssb":1719,"taxi":842,"tpcds":271,"tpch":305,"uk":49},"machine":"c7a.4xlarge","release_date":"2016-09-14","result":[[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[0.111,0.011,0.011,0.011,0.011,0.011],[0.081,0.026,0.027,0.026,0.026,0.024],[null,null,null,null,null,null],[0.187,0.126,0.122,0.124,0.122,0.125],[null,null,null,null,null,null],[0.677,0.569,0.569,0.575,0.565,0.581],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[94.873,10.799,10.816,10.805,10.832,10.814],[null,null,null,null,null,null],[80.873,12.715,12.711,12.671,12.628,12.545],[null,null,null,null,null,null],[80.489,19.494,19.440,19.703,19.514,19.508],[78.752,19.196,19.367,19.283,19.196,19.210],[null,null,null,null,null,null],[null,null,null,null,null,null],[79.824,20.148,19.997,19.603,13.318,20.855],[null,null,null,null,null,null],[null,null,null,null,null,null],[85.369,21.072,20.866,21.001,21.175,21.039],[83.693,19.344,19.342,15.228,19.119,19.323],[0.088,0.014,0.013,0.013,0.015,0.014],[0.101,0.014,0.015,0.014,0.015,0.014],[0.140,0.051,0.052,0.051,0.058,0.052],[0.186,0.108,0.110,0.109,0.107,0.107],[0.273,0.196,0.200,0.194,0.194,0.195],[0.383,0.272,0.271,0.270,0.268,0.274],[0.118,0.032,0.033,0.033,0.031,0.031],[0.103,0.016,0.016,0.015,0.015,0.016],[0.444,0.365,0.360,0.356,0.351,0.354],[0.497,0.411,0.401,0.411,0.399,0.401],[0.461,0.392,0.390,0.395,0.397,0.398],[0.499,0.417,0.411,0.419,0.428,0.418],[0.644,0.528,0.550,0.553,0.542,0.558],[0.812,0.699,0.706,0.700,0.708,0.700],[0.707,0.633,0.635,0.628,0.621,0.607],[0.694,0.614,0.611,0.610,0.615,0.611],[1.527,1.390,1.376,1.329,1.323,1.349],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[0.434,0.334,0.337,0.322,0.331,0.339],[1.564,0.829,0.813,0.799,0.805,0.815],[1.271,1.038,1.016,1.015,1.014,1.020],[1.833,1.768,1.756,1.759,1.746,1.761],[0.731,0.608,0.625,0.608,0.609,0.599],[1.015,0.881,0.867,0.874,0.880,0.878],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[0.104,0.010,0.010,0.011,0.010,0.010],[0.073,0.005,0.005,0.005,0.005,0.005],[0.623,0.071,0.072,0.072,0.070,0.071],[0.707,0.152,0.148,0.149,0.150,0.149],[0.243,0.087,0.098,0.092,0.096,0.095],[0.761,0.168,0.168,0.170,0.172,0.167],[0.440,0.056,0.055,0.055,0.055,0.057],[0.512,0.096,0.094,0.093,0.094,0.097],[0.568,0.144,0.144,0.139,0.143,0.142],[0.474,0.075,0.092,0.073,0.093,0.076],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[0.999,0.556,0.553,0.551,0.551,0.549],[0.675,0.066,0.066,0.063,0.066,0.064],[1.096,0.610,0.608,0.613,0.602,0.611],[52.523,7.972,7.991,7.989,7.994,7.998],[55.319,5.924,5.950,5.932,5.921,5.934],[54.412,7.106,6.592,5.919,4.471,7.421],[62.850,14.615,14.561,14.564,14.563,14.527],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,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diff --git a/versions/results/25.12.11.4.json b/versions/results/25.12.11.4.json new file mode 100644 index 0000000000..eeaa2fc51e --- /dev/null +++ b/versions/results/25.12.11.4.json @@ -0,0 +1 @@ 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diff --git a/versions/results/25.3.14.14.json b/versions/results/25.3.14.14.json new file mode 100644 index 0000000000..5649b90e25 --- /dev/null +++ b/versions/results/25.3.14.14.json @@ -0,0 +1 @@ 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diff --git a/versions/results/25.6.13.41.json b/versions/results/25.6.13.41.json new file mode 100644 index 0000000000..2a97d5ca1b --- /dev/null +++ b/versions/results/25.6.13.41.json @@ -0,0 +1 @@ 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diff --git a/versions/results/26.1.12.23.json b/versions/results/26.1.12.23.json new file mode 100644 index 0000000000..b45480d29f --- /dev/null +++ b/versions/results/26.1.12.23.json @@ -0,0 +1 @@ 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diff --git a/versions/results/26.3.13.31.json b/versions/results/26.3.13.31.json new file mode 100644 index 0000000000..bd054b964c --- /dev/null +++ b/versions/results/26.3.13.31.json @@ -0,0 +1 @@ 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diff --git a/versions/results/26.5.3.52.json b/versions/results/26.5.3.52.json new file mode 100644 index 0000000000..6e57265243 --- /dev/null +++ b/versions/results/26.5.3.52.json @@ -0,0 +1 @@ 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diff --git a/versions/results/26.6.1.1193.json b/versions/results/26.6.1.1193.json new file mode 100644 index 0000000000..001d9dbc7c --- /dev/null +++ b/versions/results/26.6.1.1193.json @@ -0,0 +1 @@ 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diff --git a/versions/scripts/benchmarks.sh b/versions/scripts/benchmarks.sh deleted file mode 100755 index 435bb72da2..0000000000 --- a/versions/scripts/benchmarks.sh +++ /dev/null @@ -1,66 +0,0 @@ -#!/usr/bin/env bash - -CH_QUERIES_FILE="ch_queries.sql" -SSB_QUERIES_FILE="ssb_queries.sql" -BROWN_QUERIES_FILE="brown_queries.sql" -CH_TABLE="hits_100m_obfuscated" -TRIES=3 - -if [ -x ./clickhouse ] -then - CLICKHOUSE_CLIENT="./clickhouse client" -elif command -v clickhouse-client >/dev/null 2>&1 -then - CLICKHOUSE_CLIENT="clickhouse-client" -else - echo "clickhouse-client is not found" - exit 1 -fi - -${CLICKHOUSE_CLIENT} --query 'SELECT version();' - -echo "Brown Benchmark:" - -cat "$BROWN_QUERIES_FILE" | while read -r query; do - sync - echo 3 | sudo tee /proc/sys/vm/drop_caches >/dev/null - - echo -n "[" - for i in $(seq 1 $TRIES); do - RES=$(${CLICKHOUSE_CLIENT} --time --format=Null --max_memory_usage=100G --query="$query" 2>&1) - [[ "$?" == "0" ]] && echo -n "${RES}" || echo -n "null" - [[ "$i" != $TRIES ]] && echo -n ", " - done - echo "]," -done - -echo "SSB Benchmark:" - -cat "$SSB_QUERIES_FILE" | while read -r query; do - sync - echo 3 | sudo tee /proc/sys/vm/drop_caches >/dev/null - - echo -n "[" - for i in $(seq 1 $TRIES); do - RES=$(${CLICKHOUSE_CLIENT} --time --format=Null --max_memory_usage=100G --query="$query" 2>&1) - [[ "$?" == "0" ]] && echo -n "${RES}" || echo -n "null" - [[ "$i" != $TRIES ]] && echo -n ", " - done - echo "]," -done - - -echo "ClickHouse Benchmark:" - -cat "$CH_QUERIES_FILE" | sed "s/{table}/${CH_TABLE}/g" | while read -r query; do - sync - echo 3 | sudo tee /proc/sys/vm/drop_caches >/dev/null - - echo -n "[" - for i in $(seq 1 $TRIES); do - RES=$(${CLICKHOUSE_CLIENT} --time --format=Null --max_memory_usage=100G --query="$query" 2>&1) - [[ "$?" == "0" ]] && echo -n "${RES}" || echo -n "null" - [[ "$i" != $TRIES ]] && echo -n ", " - done - echo "]," -done diff --git a/versions/scripts/brown_queries.sql b/versions/scripts/brown_queries.sql deleted file mode 100644 index f22175646b..0000000000 --- a/versions/scripts/brown_queries.sql +++ /dev/null @@ -1,16 +0,0 @@ -SELECT machine_name, MIN(cpu) AS cpu_min, MAX(cpu) AS cpu_max, AVG(cpu) AS cpu_avg, MIN(net_in) AS net_in_min, MAX(net_in) AS net_in_max, AVG(net_in) AS net_in_avg, MIN(net_out) AS net_out_min, MAX(net_out) AS net_out_max, AVG(net_out) AS net_out_avg FROM ( SELECT machine_name, ifNull(cpu_user, 0.0) AS cpu, ifNull(bytes_in, 0.0) AS net_in, ifNull(bytes_out, 0.0) AS net_out FROM mgbench.logs1 WHERE machine_name IN ('anansi','aragog','urd') AND log_time >= toDateTime('2017-01-11 00:00:00')) AS r GROUP BY machine_name; -- Q1.1: What is the CPU/network utilization for each web server since midnight? -SELECT machine_name, log_time FROM mgbench.logs1 WHERE (machine_name LIKE 'cslab%' OR machine_name LIKE 'mslab%') AND load_one IS NULL AND log_time >= toDateTime('2017-01-10 00:00:00') ORDER BY machine_name, log_time; -- Q1.2: Which computer lab machines have been offline in the past day? -SELECT dt, hr, AVG(load_fifteen) AS load_fifteen_avg, AVG(load_five) AS load_five_avg, AVG(load_one) AS load_one_avg, AVG(mem_free) AS mem_free_avg, AVG(swap_free) AS swap_free_avg FROM ( SELECT CAST(log_time AS DATE) AS dt, toHour(log_time) AS hr, load_fifteen, load_five, load_one, mem_free, swap_free FROM mgbench.logs1 WHERE machine_name = 'babbage' AND load_fifteen IS NOT NULL AND load_five IS NOT NULL AND load_one IS NOT NULL AND mem_free IS NOT NULL AND swap_free IS NOT NULL AND log_time >= toDateTime('2017-01-01 00:00:00')) AS r GROUP BY dt, hr ORDER BY dt, hr; -- Q1.3: What are the hourly average metrics during the past 10 days for a specific workstation? -SELECT machine_name, COUNT(*) AS spikes FROM mgbench.logs1 WHERE machine_group = 'Servers' AND cpu_wio > 0.99 AND log_time >= toDateTime('2016-12-01 00:00:00') AND log_time < toDateTime('2017-01-01 00:00:00') GROUP BY machine_name ORDER BY spikes DESC LIMIT 10; -- Q1.4: Over 1 month, how often was each server blocked on disk I/O? -SELECT machine_name, dt, MIN(mem_free) AS mem_free_min FROM ( SELECT machine_name, CAST(log_time AS DATE) AS dt, mem_free FROM mgbench.logs1 WHERE machine_group = 'DMZ' AND mem_free IS NOT NULL ) AS r GROUP BY machine_name, dt HAVING MIN(mem_free) < 10000 ORDER BY machine_name, dt; -- Q1.5: Which externally reachable VMs have run low on memory? -SELECT dt, hr, SUM(net_in) AS net_in_sum, SUM(net_out) AS net_out_sum, SUM(net_in) + SUM(net_out) AS both_sum FROM ( SELECT CAST(log_time AS DATE) AS dt, toHour(log_time) AS hr, ifNull(bytes_in, 0.0) / 1000000000.0 AS net_in, ifNull(bytes_out, 0.0) / 1000000000.0 AS net_out FROM mgbench.logs1 WHERE machine_name IN ('allsorts','andes','bigred','blackjack','bonbon','cadbury','chiclets','cotton','crows','dove','fireball','hearts','huey','lindt','milkduds','milkyway','mnm','necco','nerds','orbit','peeps','poprocks','razzles','runts','smarties','smuggler','spree','stride','tootsie','trident','wrigley','york') ) AS r GROUP BY dt, hr ORDER BY both_sum DESC LIMIT 10; -- Q1.6: What is the total hourly network traffic across all file servers? -SELECT * FROM mgbench.logs2 WHERE status_code >= 500 AND log_time >= toDateTime('2012-12-18 00:00:00') ORDER BY log_time; -- Q2.1: Which requests have caused server errors within the past 2 weeks? -SELECT * FROM mgbench.logs2 WHERE status_code >= 200 AND status_code < 300 AND request LIKE '%/etc/passwd%' AND log_time >= toDateTime('2012-05-06 00:00:00') AND log_time < toDateTime('2012-05-20 00:00:00'); -- Q2.3: What was the average path depth for top-level requests in the past month? -SELECT top_level, AVG(length(request) - length(replaceOne(request, '/',''))) AS depth_avg FROM ( SELECT substring(request, 1, len) AS top_level, request FROM ( SELECT position('/', substring(request, 2)) AS len, request FROM mgbench.logs2 WHERE status_code >= 200 AND status_code < 300 AND log_time >= toDateTime('2012-12-01 00:00:00')) AS r WHERE len > 0 ) AS s WHERE top_level IN ('/about','/courses','/degrees','/events','/grad','/industry','/news','/people','/publications','/research','/teaching','/ugrad') GROUP BY top_level ORDER BY top_level; -- Q2.2: During a specific 2-week period, was the user password file leaked? -SELECT client_ip, COUNT(*) AS num_requests FROM mgbench.logs2 WHERE log_time >= toDateTime('2012-10-01 00:00:00') GROUP BY client_ip HAVING COUNT(*) >= 100000 ORDER BY num_requests DESC; -- Q2.4: During the last 3 months, which clients have made an excessive number of requests? -SELECT dt, COUNT(DISTINCT client_ip) FROM ( SELECT CAST(log_time AS DATE) AS dt, client_ip FROM mgbench.logs2) AS r GROUP BY dt ORDER BY dt; -- Q2.5: What are the daily unique visitors? -SELECT AVG(transfer) / 125000000.0 AS transfer_avg, MAX(transfer) / 125000000.0 AS transfer_max FROM ( SELECT log_time, SUM(object_size) AS transfer FROM mgbench.logs2 GROUP BY log_time) AS r; -- Q2.6: What are the average and maximum data transfer rates (Gbps)? -SELECT * FROM mgbench.logs3 WHERE event_type = 'temperature' AND event_value <= 32.0 AND log_time >= '2019-11-29 17:00:00'; -- Q3.1: Did the indoor temperature reach freezing over the weekend? -SELECT device_name, device_floor, COUNT(*) AS ct FROM mgbench.logs3 WHERE event_type = 'door_open' AND log_time >= '2019-06-01 00:00:00' GROUP BY device_name, device_floor ORDER BY ct DESC; -- Q3.4: Over the past 6 months, how frequently were each door opened? -SELECT DISTINCT device_name, device_type, device_floor, if (dt >= toDate('2018-12-01') AND dt < toDate('2019-03-01'), 'WINTER', 'SUMMER') FROM (SELECT dt, device_name, device_type, device_floor FROM ( SELECT dt, hr, device_name, device_type, device_floor, AVG(event_value) AS temperature_hourly_avg FROM ( SELECT CAST(log_time AS DATE) AS dt, toHour(log_time) AS hr, device_name, device_type, device_floor, event_value FROM mgbench.logs3 WHERE event_type = 'temperature' ) AS r GROUP BY dt, hr, device_name, device_type, device_floor ) AS s GROUP BY dt, device_name, device_type, device_floor HAVING MAX(temperature_hourly_avg) - MIN(temperature_hourly_avg) >= 25.0 ) -- Q3.5: Where in the building do large temperature variations occur in winter and summer? -SELECT yr, mo, SUM(coffee_hourly_avg) AS coffee_monthly_sum, AVG(coffee_hourly_avg) AS coffee_monthly_avg, SUM(printer_hourly_avg) AS printer_monthly_sum, AVG(printer_hourly_avg) AS printer_monthly_avg, SUM(projector_hourly_avg) AS projector_monthly_sum, AVG(projector_hourly_avg) AS projector_monthly_avg, SUM(vending_hourly_avg) AS vending_monthly_sum, AVG(vending_hourly_avg) AS vending_monthly_avg FROM ( SELECT dt, yr, mo, hr, AVG(coffee) AS coffee_hourly_avg, AVG(printer) AS printer_hourly_avg, AVG(projector) AS projector_hourly_avg, AVG(vending) AS vending_hourly_avg FROM ( SELECT CAST(log_time AS DATE) AS dt, toYear(log_time) AS yr, EXTRACT(MONTH FROM log_time) AS mo, toHour(log_time) AS hr, CASE WHEN device_name LIKE 'coffee%' THEN event_value END AS coffee, CASE WHEN device_name LIKE 'printer%' THEN event_value END AS printer, CASE WHEN device_name LIKE 'projector%' THEN event_value END AS projector, CASE WHEN device_name LIKE 'vending%' THEN event_value END AS vending FROM mgbench.logs3 WHERE device_type = 'meter' ) AS r GROUP BY dt, yr, mo, hr ) AS s GROUP BY yr, mo ORDER BY yr, mo; -- Q3.6: For each device category, what are the monthly power consumption metrics? \ No newline at end of file diff --git a/versions/scripts/ch_queries.sql b/versions/scripts/ch_queries.sql deleted file mode 100644 index 89c4616c64..0000000000 --- a/versions/scripts/ch_queries.sql +++ /dev/null @@ -1,43 +0,0 @@ -SELECT count() FROM {table}; -SELECT count() FROM {table} WHERE AdvEngineID != 0; -SELECT sum(AdvEngineID), count(), avg(ResolutionWidth) FROM {table} ; -SELECT sum(UserID) FROM {table} ; -SELECT uniq(UserID) FROM {table} ; -SELECT uniq(SearchPhrase) FROM {table} ; -SELECT min(EventDate), max(EventDate) FROM {table} ; -SELECT AdvEngineID, count() FROM {table} WHERE AdvEngineID != 0 GROUP BY AdvEngineID ORDER BY count() DESC; -SELECT RegionID, uniq(UserID) AS u FROM {table} GROUP BY RegionID ORDER BY u DESC LIMIT 10; -SELECT RegionID, sum(AdvEngineID), count() AS c, avg(ResolutionWidth), uniq(UserID) FROM {table} GROUP BY RegionID ORDER BY c DESC LIMIT 10; -SELECT MobilePhoneModel, uniq(UserID) AS u FROM {table} WHERE MobilePhoneModel != '' GROUP BY MobilePhoneModel ORDER BY u DESC LIMIT 10; -SELECT MobilePhone, MobilePhoneModel, uniq(UserID) AS u FROM {table} WHERE MobilePhoneModel != '' GROUP BY MobilePhone, MobilePhoneModel ORDER BY u DESC LIMIT 10; -SELECT SearchPhrase, count() AS c FROM {table} WHERE SearchPhrase != '' GROUP BY SearchPhrase ORDER BY c DESC LIMIT 10; -SELECT SearchPhrase, uniq(UserID) AS u FROM {table} WHERE SearchPhrase != '' GROUP BY SearchPhrase ORDER BY u DESC LIMIT 10; -SELECT SearchEngineID, SearchPhrase, count() AS c FROM {table} WHERE SearchPhrase != '' GROUP BY SearchEngineID, SearchPhrase ORDER BY c DESC LIMIT 10; -SELECT UserID, count() FROM {table} GROUP BY UserID ORDER BY count() DESC LIMIT 10; -SELECT UserID, SearchPhrase, count() FROM {table} GROUP BY UserID, SearchPhrase ORDER BY count() DESC LIMIT 10; -SELECT UserID, SearchPhrase, count() FROM {table} GROUP BY UserID, SearchPhrase LIMIT 10; -SELECT UserID, toMinute(EventTime) AS m, SearchPhrase, count() FROM {table} GROUP BY UserID, m, SearchPhrase ORDER BY count() DESC LIMIT 10; -SELECT UserID FROM {table} WHERE UserID = 12345678901234567890; -SELECT count() FROM {table} WHERE URL LIKE '%metrika%'; -SELECT SearchPhrase, any(URL), count() AS c FROM {table} WHERE URL LIKE '%metrika%' AND SearchPhrase != '' GROUP BY SearchPhrase ORDER BY c DESC LIMIT 10; -SELECT SearchPhrase, any(URL), any(Title), count() AS c, uniq(UserID) FROM {table} WHERE Title LIKE '%Яндекс%' AND URL NOT LIKE '%.yandex.%' AND SearchPhrase != '' GROUP BY SearchPhrase ORDER BY c DESC LIMIT 10; -SELECT * FROM {table} WHERE URL LIKE '%metrika%' ORDER BY EventTime LIMIT 10; -SELECT SearchPhrase FROM {table} WHERE SearchPhrase != '' ORDER BY EventTime LIMIT 10; -SELECT SearchPhrase FROM {table} WHERE SearchPhrase != '' ORDER BY SearchPhrase LIMIT 10; -SELECT SearchPhrase FROM {table} WHERE SearchPhrase != '' ORDER BY EventTime, SearchPhrase LIMIT 10; -SELECT CounterID, avg(length(URL)) AS l, count() AS c FROM {table} WHERE URL != '' GROUP BY CounterID HAVING c > 100000 ORDER BY l DESC LIMIT 25; -SELECT domainWithoutWWW(Referer) AS key, avg(length(Referer)) AS l, count() AS c, any(Referer) FROM {table} WHERE Referer != '' GROUP BY key HAVING c > 100000 ORDER BY l DESC LIMIT 25; -SELECT sum(ResolutionWidth), sum(ResolutionWidth + 1), sum(ResolutionWidth + 2), sum(ResolutionWidth + 3), sum(ResolutionWidth + 4), sum(ResolutionWidth + 5), sum(ResolutionWidth + 6), sum(ResolutionWidth + 7), sum(ResolutionWidth + 8), sum(ResolutionWidth + 9), sum(ResolutionWidth + 10), sum(ResolutionWidth + 11), sum(ResolutionWidth + 12), sum(ResolutionWidth + 13), sum(ResolutionWidth + 14), sum(ResolutionWidth + 15), sum(ResolutionWidth + 16), sum(ResolutionWidth + 17), sum(ResolutionWidth + 18), sum(ResolutionWidth + 19), sum(ResolutionWidth + 20), sum(ResolutionWidth + 21), sum(ResolutionWidth + 22), sum(ResolutionWidth + 23), sum(ResolutionWidth + 24), sum(ResolutionWidth + 25), sum(ResolutionWidth + 26), sum(ResolutionWidth + 27), sum(ResolutionWidth + 28), sum(ResolutionWidth + 29), sum(ResolutionWidth + 30), sum(ResolutionWidth + 31), sum(ResolutionWidth + 32), sum(ResolutionWidth + 33), sum(ResolutionWidth + 34), sum(ResolutionWidth + 35), sum(ResolutionWidth + 36), sum(ResolutionWidth + 37), sum(ResolutionWidth + 38), sum(ResolutionWidth + 39), sum(ResolutionWidth + 40), sum(ResolutionWidth + 41), sum(ResolutionWidth + 42), sum(ResolutionWidth + 43), sum(ResolutionWidth + 44), sum(ResolutionWidth + 45), sum(ResolutionWidth + 46), sum(ResolutionWidth + 47), sum(ResolutionWidth + 48), sum(ResolutionWidth + 49), sum(ResolutionWidth + 50), sum(ResolutionWidth + 51), sum(ResolutionWidth + 52), sum(ResolutionWidth + 53), sum(ResolutionWidth + 54), sum(ResolutionWidth + 55), sum(ResolutionWidth + 56), sum(ResolutionWidth + 57), sum(ResolutionWidth + 58), sum(ResolutionWidth + 59), sum(ResolutionWidth + 60), sum(ResolutionWidth + 61), sum(ResolutionWidth + 62), sum(ResolutionWidth + 63), sum(ResolutionWidth + 64), sum(ResolutionWidth + 65), sum(ResolutionWidth + 66), sum(ResolutionWidth + 67), sum(ResolutionWidth + 68), sum(ResolutionWidth + 69), sum(ResolutionWidth + 70), sum(ResolutionWidth + 71), sum(ResolutionWidth + 72), sum(ResolutionWidth + 73), sum(ResolutionWidth + 74), sum(ResolutionWidth + 75), sum(ResolutionWidth + 76), sum(ResolutionWidth + 77), sum(ResolutionWidth + 78), sum(ResolutionWidth + 79), sum(ResolutionWidth + 80), sum(ResolutionWidth + 81), sum(ResolutionWidth + 82), sum(ResolutionWidth + 83), sum(ResolutionWidth + 84), sum(ResolutionWidth + 85), sum(ResolutionWidth + 86), sum(ResolutionWidth + 87), sum(ResolutionWidth + 88), sum(ResolutionWidth + 89) FROM {table}; -SELECT SearchEngineID, ClientIP, count() AS c, sum(Refresh), avg(ResolutionWidth) FROM {table} WHERE SearchPhrase != '' GROUP BY SearchEngineID, ClientIP ORDER BY c DESC LIMIT 10; -SELECT WatchID, ClientIP, count() AS c, sum(Refresh), avg(ResolutionWidth) FROM {table} WHERE SearchPhrase != '' GROUP BY WatchID, ClientIP ORDER BY c DESC LIMIT 10; -SELECT WatchID, ClientIP, count() AS c, sum(Refresh), avg(ResolutionWidth) FROM {table} GROUP BY WatchID, ClientIP ORDER BY c DESC LIMIT 10; -SELECT URL, count() AS c FROM {table} GROUP BY URL ORDER BY c DESC LIMIT 10; -SELECT 1, URL, count() AS c FROM {table} GROUP BY 1, URL ORDER BY c DESC LIMIT 10; -SELECT ClientIP AS x, x - 1, x - 2, x - 3, count() AS c FROM {table} GROUP BY x, x - 1, x - 2, x - 3 ORDER BY c DESC LIMIT 10; -SELECT URL, count() AS PageViews FROM {table} WHERE CounterID = 62 AND EventDate >= '2013-07-01' AND EventDate <= '2013-07-31' AND NOT DontCountHits AND NOT Refresh AND notEmpty(URL) GROUP BY URL ORDER BY PageViews DESC LIMIT 10; -SELECT Title, count() AS PageViews FROM {table} WHERE CounterID = 62 AND EventDate >= '2013-07-01' AND EventDate <= '2013-07-31' AND NOT DontCountHits AND NOT Refresh AND notEmpty(Title) GROUP BY Title ORDER BY PageViews DESC LIMIT 10; -SELECT URL, count() AS PageViews FROM {table} WHERE CounterID = 62 AND EventDate >= '2013-07-01' AND EventDate <= '2013-07-31' AND NOT Refresh AND IsLink AND NOT IsDownload GROUP BY URL ORDER BY PageViews DESC LIMIT 1000; -SELECT TraficSourceID, SearchEngineID, AdvEngineID, ((SearchEngineID = 0 AND AdvEngineID = 0) ? Referer : '') AS Src, URL AS Dst, count() AS PageViews FROM {table} WHERE CounterID = 62 AND EventDate >= '2013-07-01' AND EventDate <= '2013-07-31' AND NOT Refresh GROUP BY TraficSourceID, SearchEngineID, AdvEngineID, Src, Dst ORDER BY PageViews DESC LIMIT 1000; -SELECT URLHash, EventDate, count() AS PageViews FROM {table} WHERE CounterID = 62 AND EventDate >= '2013-07-01' AND EventDate <= '2013-07-31' AND NOT Refresh AND TraficSourceID IN (-1, 6) AND RefererHash = halfMD5('http://example.ru/') GROUP BY URLHash, EventDate ORDER BY PageViews DESC LIMIT 100; -SELECT WindowClientWidth, WindowClientHeight, count() AS PageViews FROM {table} WHERE CounterID = 62 AND EventDate >= '2013-07-01' AND EventDate <= '2013-07-31' AND NOT Refresh AND NOT DontCountHits AND URLHash = halfMD5('http://example.ru/') GROUP BY WindowClientWidth, WindowClientHeight ORDER BY PageViews DESC LIMIT 10000; -SELECT toStartOfMinute(EventTime) AS Minute, count() AS PageViews FROM {table} WHERE CounterID = 62 AND EventDate >= '2013-07-01' AND EventDate <= '2013-07-02' AND NOT Refresh AND NOT DontCountHits GROUP BY Minute ORDER BY Minute; diff --git a/versions/scripts/runner.sh b/versions/scripts/runner.sh deleted file mode 100755 index ad92bdc18e..0000000000 --- a/versions/scripts/runner.sh +++ /dev/null @@ -1,25 +0,0 @@ -#!/bin/bash -VERSION_ARR=(${1//[-v]/ }) -VERSION=${VERSION_ARR[0]} -FILE_NAME=${VERSION}.json -DATE=$2 - -echo "$VERSION $DATE" -sudo ~/clickhouse stop -sudo DEBIAN_FRONTEND=noninteractive apt-get update -sudo DEBIAN_FRONTEND=noninteractive apt-get install --allow-downgrades --yes clickhouse-client=$VERSION clickhouse-server=$VERSION clickhouse-common-static=$VERSION -#sudo service clickhouse-server restart -sudo ~/clickhouse start -clickhouse-client --query 'select version()' -sleep 5 -echo '{ - "version": "'$VERSION'", - "result": - [' | tee $FILE_NAME - -bash ./benchmarks.sh >> $FILE_NAME - -sed -i '$ s/,$//' $FILE_NAME - -echo ' ] -}' >> $FILE_NAME diff --git a/versions/scripts/ssb_queries.sql b/versions/scripts/ssb_queries.sql deleted file mode 100644 index 375cf51148..0000000000 --- a/versions/scripts/ssb_queries.sql +++ /dev/null @@ -1,13 +0,0 @@ -SELECT sum(LO_EXTENDEDPRICE * LO_DISCOUNT) AS revenue FROM lineorder_flat WHERE F_YEAR = 1993 AND LO_DISCOUNT BETWEEN 1 AND 3 AND LO_QUANTITY < 25; -- Q1.1 -SELECT sum(LO_EXTENDEDPRICE * LO_DISCOUNT) AS revenue FROM lineorder_flat WHERE toYYYYMM(LO_ORDERDATE) = 199401 AND LO_DISCOUNT BETWEEN 4 AND 6 AND LO_QUANTITY BETWEEN 26 AND 35; -- Q1.2 -SELECT sum(LO_EXTENDEDPRICE * LO_DISCOUNT) AS revenue FROM lineorder_flat WHERE toRelativeWeekNum(LO_ORDERDATE) - toRelativeWeekNum(toDate('1994-01-01')) = 6 AND F_YEAR = 1994 AND LO_DISCOUNT BETWEEN 5 AND 7 AND LO_QUANTITY BETWEEN 26 AND 35; -- Q1.3 -SELECT sum(LO_REVENUE), F_YEAR AS year, P_BRAND FROM lineorder_flat WHERE P_CATEGORY = 'MFGR#12' AND S_REGION = 'AMERICA' GROUP BY year, P_BRAND ORDER BY year, P_BRAND; -- Q2.1 -SELECT sum(LO_REVENUE), F_YEAR AS year, P_BRAND FROM lineorder_flat WHERE P_BRAND >= 'MFGR#2221' AND P_BRAND <= 'MFGR#2228' AND S_REGION = 'ASIA' GROUP BY year, P_BRAND ORDER BY year, P_BRAND; -- Q2.2 -SELECT sum(LO_REVENUE), F_YEAR AS year, P_BRAND FROM lineorder_flat WHERE P_BRAND = 'MFGR#2239' AND S_REGION = 'EUROPE' GROUP BY year, P_BRAND ORDER BY year, P_BRAND; -- Q2.3 -SELECT C_NATION, S_NATION, F_YEAR AS year, sum(LO_REVENUE) AS revenue FROM lineorder_flat WHERE C_REGION = 'ASIA' AND S_REGION = 'ASIA' AND year >= 1992 AND year <= 1997 GROUP BY C_NATION, S_NATION, year ORDER BY year ASC, revenue DESC; -- Q3.1 -SELECT C_CITY, S_CITY, F_YEAR AS year, sum(LO_REVENUE) AS revenue FROM lineorder_flat WHERE C_NATION = 'UNITED STATES' AND S_NATION = 'UNITED STATES' AND year >= 1992 AND year <= 1997 GROUP BY C_CITY, S_CITY, year ORDER BY year ASC, revenue DESC; -- Q3.2 -SELECT C_CITY, S_CITY, F_YEAR AS year, sum(LO_REVENUE) AS revenue FROM lineorder_flat WHERE (C_CITY = 'UNITED KI1' OR C_CITY = 'UNITED KI5') AND (S_CITY = 'UNITED KI1' OR S_CITY = 'UNITED KI5') AND year >= 1992 AND year <= 1997 GROUP BY C_CITY, S_CITY, year ORDER BY year ASC, revenue DESC; -- Q3.3 -SELECT C_CITY, S_CITY, F_YEAR AS year, sum(LO_REVENUE) AS revenue FROM lineorder_flat WHERE (C_CITY = 'UNITED KI1' OR C_CITY = 'UNITED KI5') AND (S_CITY = 'UNITED KI1' OR S_CITY = 'UNITED KI5') AND toYYYYMM(LO_ORDERDATE) = 199712 GROUP BY C_CITY, S_CITY, year ORDER BY year ASC, revenue DESC; -- Q3.4 -SELECT F_YEAR AS year, C_NATION, sum(LO_REVENUE - LO_SUPPLYCOST) AS profit FROM lineorder_flat WHERE C_REGION = 'AMERICA' AND S_REGION = 'AMERICA' AND (P_MFGR = 'MFGR#1' OR P_MFGR = 'MFGR#2') GROUP BY year, C_NATION ORDER BY year ASC, C_NATION ASC; -- Q4.1 -SELECT F_YEAR AS year, S_NATION, P_CATEGORY, sum(LO_REVENUE - LO_SUPPLYCOST) AS profit FROM lineorder_flat WHERE C_REGION = 'AMERICA' AND S_REGION = 'AMERICA' AND (year = 1997 OR year = 1998) AND (P_MFGR = 'MFGR#1' OR P_MFGR = 'MFGR#2') GROUP BY year, S_NATION, P_CATEGORY ORDER BY year ASC, S_NATION ASC, P_CATEGORY ASC; -- Q4.2 -SELECT F_YEAR AS year, S_CITY, P_BRAND, sum(LO_REVENUE - LO_SUPPLYCOST) AS profit FROM lineorder_flat WHERE S_NATION = 'UNITED STATES' AND (year = 1997 OR year = 1998) AND P_CATEGORY = 'MFGR#14' GROUP BY year, S_CITY, P_BRAND ORDER BY year ASC, S_CITY ASC, P_BRAND ASC; -- Q4. \ No newline at end of file diff --git a/versions/unified_scripts/all_queries.sql b/versions/unified_scripts/all_queries.sql deleted file mode 100644 index 08517e5cdc..0000000000 --- a/versions/unified_scripts/all_queries.sql +++ /dev/null @@ -1,75 +0,0 @@ -SELECT machine_name, MIN(cpu) AS cpu_min, MAX(cpu) AS cpu_max, AVG(cpu) AS cpu_avg, MIN(net_in) AS net_in_min, MAX(net_in) AS net_in_max, AVG(net_in) AS net_in_avg, MIN(net_out) AS net_out_min, MAX(net_out) AS net_out_max, AVG(net_out) AS net_out_avg FROM ( SELECT machine_name, ifNull(cpu_user, 0.0) AS cpu, ifNull(bytes_in, 0.0) AS net_in, ifNull(bytes_out, 0.0) AS net_out FROM logs1 WHERE machine_name IN ('anansi','aragog','urd') AND log_time >= toDateTime('2017-01-11 00:00:00')) AS r GROUP BY machine_name; -SELECT machine_name, log_time FROM logs1 WHERE (machine_name LIKE 'cslab%' OR machine_name LIKE 'mslab%') AND load_one IS NULL AND log_time >= toDateTime('2017-01-10 00:00:00') ORDER BY machine_name, log_time; -SELECT dt, hr, AVG(load_fifteen) AS load_fifteen_avg, AVG(load_five) AS load_five_avg, AVG(load_one) AS load_one_avg, AVG(mem_free) AS mem_free_avg, AVG(swap_free) AS swap_free_avg FROM ( SELECT CAST(log_time AS DATE) AS dt, toHour(log_time) AS hr, load_fifteen, load_five, load_one, mem_free, swap_free FROM logs1 WHERE machine_name = 'babbage' AND load_fifteen IS NOT NULL AND load_five IS NOT NULL AND load_one IS NOT NULL AND mem_free IS NOT NULL AND swap_free IS NOT NULL AND log_time >= toDateTime('2017-01-01 00:00:00')) AS r GROUP BY dt, hr ORDER BY dt, hr; -SELECT machine_name, COUNT(*) AS spikes FROM logs1 WHERE machine_group = 'Servers' AND cpu_wio > 0.99 AND log_time >= toDateTime('2016-12-01 00:00:00') AND log_time < toDateTime('2017-01-01 00:00:00') GROUP BY machine_name ORDER BY spikes DESC LIMIT 10; -SELECT machine_name, dt, MIN(mem_free) AS mem_free_min FROM ( SELECT machine_name, CAST(log_time AS DATE) AS dt, mem_free FROM logs1 WHERE machine_group = 'DMZ' AND mem_free IS NOT NULL ) AS r GROUP BY machine_name, dt HAVING MIN(mem_free) < 10000 ORDER BY machine_name, dt; -SELECT dt, hr, SUM(net_in) AS net_in_sum, SUM(net_out) AS net_out_sum, SUM(net_in) + SUM(net_out) AS both_sum FROM ( SELECT CAST(log_time AS DATE) AS dt, toHour(log_time) AS hr, ifNull(bytes_in, 0.0) / 1000000000.0 AS net_in, ifNull(bytes_out, 0.0) / 1000000000.0 AS net_out FROM logs1 WHERE machine_name IN ('allsorts','andes','bigred','blackjack','bonbon','cadbury','chiclets','cotton','crows','dove','fireball','hearts','huey','lindt','milkduds','milkyway','mnm','necco','nerds','orbit','peeps','poprocks','razzles','runts','smarties','smuggler','spree','stride','tootsie','trident','wrigley','york') ) AS r GROUP BY dt, hr ORDER BY both_sum DESC LIMIT 10; -SELECT * FROM logs2 WHERE status_code >= 500 AND log_time >= toDateTime('2012-12-18 00:00:00') ORDER BY log_time; -SELECT * FROM logs2 WHERE status_code >= 200 AND status_code < 300 AND request LIKE '%/etc/passwd%' AND log_time >= toDateTime('2012-05-06 00:00:00') AND log_time < toDateTime('2012-05-20 00:00:00'); -SELECT top_level, AVG(length(request) - length(replaceOne(request, '/',''))) AS depth_avg FROM ( SELECT substring(request, 1, len) AS top_level, request FROM ( SELECT position('/', substring(request, 2)) AS len, request FROM logs2 WHERE status_code >= 200 AND status_code < 300 AND log_time >= toDateTime('2012-12-01 00:00:00')) AS r WHERE len > 0 ) AS s WHERE top_level IN ('/about','/courses','/degrees','/events','/grad','/industry','/news','/people','/publications','/research','/teaching','/ugrad') GROUP BY top_level ORDER BY top_level; -SELECT client_ip, COUNT(*) AS num_requests FROM logs2 WHERE log_time >= toDateTime('2012-10-01 00:00:00') GROUP BY client_ip HAVING COUNT(*) >= 100000 ORDER BY num_requests DESC; -SELECT dt, COUNT(DISTINCT client_ip) FROM ( SELECT CAST(log_time AS DATE) AS dt, client_ip FROM logs2) AS r GROUP BY dt ORDER BY dt; -SELECT AVG(transfer) / 125000000.0 AS transfer_avg, MAX(transfer) / 125000000.0 AS transfer_max FROM ( SELECT log_time, SUM(object_size) AS transfer FROM logs2 GROUP BY log_time) AS r; -SELECT * FROM logs3 WHERE event_type = 'temperature' AND event_value <= 32.0 AND log_time >= '2019-11-29 17:00:00'; -SELECT device_name, device_floor, COUNT(*) AS ct FROM logs3 WHERE event_type = 'door_open' AND log_time >= '2019-06-01 00:00:00' GROUP BY device_name, device_floor ORDER BY ct DESC; -SELECT yr, mo, SUM(coffee_hourly_avg) AS coffee_monthly_sum, AVG(coffee_hourly_avg) AS coffee_monthly_avg, SUM(printer_hourly_avg) AS printer_monthly_sum, AVG(printer_hourly_avg) AS printer_monthly_avg, SUM(projector_hourly_avg) AS projector_monthly_sum, AVG(projector_hourly_avg) AS projector_monthly_avg, SUM(vending_hourly_avg) AS vending_monthly_sum, AVG(vending_hourly_avg) AS vending_monthly_avg FROM ( SELECT dt, yr, mo, hr, AVG(coffee) AS coffee_hourly_avg, AVG(printer) AS printer_hourly_avg, AVG(projector) AS projector_hourly_avg, AVG(vending) AS vending_hourly_avg FROM ( SELECT CAST(log_time AS DATE) AS dt, toYear(log_time) AS yr, EXTRACT(MONTH FROM log_time) AS mo, toHour(log_time) AS hr, CASE WHEN device_name LIKE 'coffee%' THEN event_value END AS coffee, CASE WHEN device_name LIKE 'printer%' THEN event_value END AS printer, CASE WHEN device_name LIKE 'projector%' THEN event_value END AS projector, CASE WHEN device_name LIKE 'vending%' THEN event_value END AS vending FROM logs3 WHERE device_type = 'meter' ) AS r GROUP BY dt, yr, mo, hr ) AS s GROUP BY yr, mo ORDER BY yr, mo; -SELECT sum(LO_EXTENDEDPRICE * LO_DISCOUNT) AS revenue FROM lineorder_flat WHERE F_YEAR = 1993 AND LO_DISCOUNT BETWEEN 1 AND 3 AND LO_QUANTITY < 25; -SELECT sum(LO_EXTENDEDPRICE * LO_DISCOUNT) AS revenue FROM lineorder_flat WHERE toYYYYMM(LO_ORDERDATE) = 199401 AND LO_DISCOUNT BETWEEN 4 AND 6 AND LO_QUANTITY BETWEEN 26 AND 35; -SELECT sum(LO_EXTENDEDPRICE * LO_DISCOUNT) AS revenue FROM lineorder_flat WHERE toRelativeWeekNum(LO_ORDERDATE) - toRelativeWeekNum(toDate('1994-01-01')) = 6 AND F_YEAR = 1994 AND LO_DISCOUNT BETWEEN 5 AND 7 AND LO_QUANTITY BETWEEN 26 AND 35; -SELECT sum(LO_REVENUE), F_YEAR AS year, P_BRAND FROM lineorder_flat WHERE P_CATEGORY = 'MFGR#12' AND S_REGION = 'AMERICA' GROUP BY year, P_BRAND ORDER BY year, P_BRAND; -SELECT sum(LO_REVENUE), F_YEAR AS year, P_BRAND FROM lineorder_flat WHERE P_BRAND >= 'MFGR#2221' AND P_BRAND <= 'MFGR#2228' AND S_REGION = 'ASIA' GROUP BY year, P_BRAND ORDER BY year, P_BRAND; -SELECT sum(LO_REVENUE), F_YEAR AS year, P_BRAND FROM lineorder_flat WHERE P_BRAND = 'MFGR#2239' AND S_REGION = 'EUROPE' GROUP BY year, P_BRAND ORDER BY year, P_BRAND; -SELECT C_NATION, S_NATION, F_YEAR AS year, sum(LO_REVENUE) AS revenue FROM lineorder_flat WHERE C_REGION = 'ASIA' AND S_REGION = 'ASIA' AND year >= 1992 AND year <= 1997 GROUP BY C_NATION, S_NATION, year ORDER BY year ASC, revenue DESC; -SELECT C_CITY, S_CITY, F_YEAR AS year, sum(LO_REVENUE) AS revenue FROM lineorder_flat WHERE C_NATION = 'UNITED STATES' AND S_NATION = 'UNITED STATES' AND year >= 1992 AND year <= 1997 GROUP BY C_CITY, S_CITY, year ORDER BY year ASC, revenue DESC; -SELECT C_CITY, S_CITY, F_YEAR AS year, sum(LO_REVENUE) AS revenue FROM lineorder_flat WHERE (C_CITY = 'UNITED KI1' OR C_CITY = 'UNITED KI5') AND (S_CITY = 'UNITED KI1' OR S_CITY = 'UNITED KI5') AND year >= 1992 AND year <= 1997 GROUP BY C_CITY, S_CITY, year ORDER BY year ASC, revenue DESC; -SELECT C_CITY, S_CITY, F_YEAR AS year, sum(LO_REVENUE) AS revenue FROM lineorder_flat WHERE (C_CITY = 'UNITED KI1' OR C_CITY = 'UNITED KI5') AND (S_CITY = 'UNITED KI1' OR S_CITY = 'UNITED KI5') AND toYYYYMM(LO_ORDERDATE) = 199712 GROUP BY C_CITY, S_CITY, year ORDER BY year ASC, revenue DESC; -SELECT F_YEAR AS year, C_NATION, sum(LO_REVENUE - LO_SUPPLYCOST) AS profit FROM lineorder_flat WHERE C_REGION = 'AMERICA' AND S_REGION = 'AMERICA' AND (P_MFGR = 'MFGR#1' OR P_MFGR = 'MFGR#2') GROUP BY year, C_NATION ORDER BY year ASC, C_NATION ASC; -SELECT F_YEAR AS year, S_NATION, P_CATEGORY, sum(LO_REVENUE - LO_SUPPLYCOST) AS profit FROM lineorder_flat WHERE C_REGION = 'AMERICA' AND S_REGION = 'AMERICA' AND (year = 1997 OR year = 1998) AND (P_MFGR = 'MFGR#1' OR P_MFGR = 'MFGR#2') GROUP BY year, S_NATION, P_CATEGORY ORDER BY year ASC, S_NATION ASC, P_CATEGORY ASC; -SELECT F_YEAR AS year, S_CITY, P_BRAND, sum(LO_REVENUE - LO_SUPPLYCOST) AS profit FROM lineorder_flat WHERE S_NATION = 'UNITED STATES' AND (year = 1997 OR year = 1998) AND P_CATEGORY = 'MFGR#14' GROUP BY year, S_CITY, P_BRAND ORDER BY year ASC, S_CITY ASC, P_BRAND ASC; -SELECT count() FROM hits -SELECT count() FROM hits WHERE AdvEngineID != 0 -SELECT sum(AdvEngineID), count(), avg(ResolutionWidth) FROM hits -SELECT sum(UserID) FROM hits -SELECT uniq(UserID) FROM hits -SELECT uniq(SearchPhrase) FROM hits -SELECT min(EventDate), max(EventDate) FROM hits -SELECT AdvEngineID, count() FROM hits WHERE AdvEngineID != 0 GROUP BY AdvEngineID ORDER BY count() DESC -SELECT RegionID, uniq(UserID) AS u FROM hits GROUP BY RegionID ORDER BY u DESC LIMIT 10 -SELECT RegionID, sum(AdvEngineID), count() AS c, avg(ResolutionWidth), uniq(UserID) FROM hits GROUP BY RegionID ORDER BY c DESC LIMIT 10 -SELECT MobilePhoneModel, uniq(UserID) AS u FROM hits WHERE MobilePhoneModel != '' GROUP BY MobilePhoneModel ORDER BY u DESC LIMIT 10 -SELECT MobilePhone, MobilePhoneModel, uniq(UserID) AS u FROM hits WHERE MobilePhoneModel != '' GROUP BY MobilePhone, MobilePhoneModel ORDER BY u DESC LIMIT 10 -SELECT SearchPhrase, count() AS c FROM hits WHERE SearchPhrase != '' GROUP BY SearchPhrase ORDER BY c DESC LIMIT 10 -SELECT SearchPhrase, uniq(UserID) AS u FROM hits WHERE SearchPhrase != '' GROUP BY SearchPhrase ORDER BY u DESC LIMIT 10 -SELECT SearchEngineID, SearchPhrase, count() AS c FROM hits WHERE SearchPhrase != '' GROUP BY SearchEngineID, SearchPhrase ORDER BY c DESC LIMIT 10 -SELECT UserID, count() FROM hits GROUP BY UserID ORDER BY count() DESC LIMIT 10 -SELECT UserID, SearchPhrase, count() FROM hits GROUP BY UserID, SearchPhrase ORDER BY count() DESC LIMIT 10 -SELECT UserID, SearchPhrase, count() FROM hits GROUP BY UserID, SearchPhrase LIMIT 10 -SELECT UserID, toMinute(EventTime) AS m, SearchPhrase, count() FROM hits GROUP BY UserID, m, SearchPhrase ORDER BY count() DESC LIMIT 10 -SELECT UserID FROM hits WHERE UserID = 12345678901234567890 -SELECT count() FROM hits WHERE URL LIKE '%metrika%' -SELECT SearchPhrase, any(URL), count() AS c FROM hits WHERE URL LIKE '%metrika%' AND SearchPhrase != '' GROUP BY SearchPhrase ORDER BY c DESC LIMIT 10 -SELECT SearchPhrase, any(URL), any(Title), count() AS c, uniq(UserID) FROM hits WHERE Title LIKE '%Яндекс%' AND URL NOT LIKE '%.yandex.%' AND SearchPhrase != '' GROUP BY SearchPhrase ORDER BY c DESC LIMIT 10 -SELECT * FROM hits WHERE URL LIKE '%metrika%' ORDER BY EventTime LIMIT 10 -SELECT SearchPhrase FROM hits WHERE SearchPhrase != '' ORDER BY EventTime LIMIT 10 -SELECT SearchPhrase FROM hits WHERE SearchPhrase != '' ORDER BY SearchPhrase LIMIT 10 -SELECT SearchPhrase FROM hits WHERE SearchPhrase != '' ORDER BY EventTime, SearchPhrase LIMIT 10 -SELECT CounterID, avg(length(URL)) AS l, count() AS c FROM hits WHERE URL != '' GROUP BY CounterID HAVING c > 100000 ORDER BY l DESC LIMIT 25 -SELECT domainWithoutWWW(Referer) AS key, avg(length(Referer)) AS l, count() AS c, any(Referer) FROM hits WHERE Referer != '' GROUP BY key HAVING c > 100000 ORDER BY l DESC LIMIT 25 -SELECT sum(ResolutionWidth), sum(ResolutionWidth + 1), sum(ResolutionWidth + 2), sum(ResolutionWidth + 3), sum(ResolutionWidth + 4), sum(ResolutionWidth + 5), sum(ResolutionWidth + 6), sum(ResolutionWidth + 7), sum(ResolutionWidth + 8), sum(ResolutionWidth + 9), sum(ResolutionWidth + 10), sum(ResolutionWidth + 11), sum(ResolutionWidth + 12), sum(ResolutionWidth + 13), sum(ResolutionWidth + 14), sum(ResolutionWidth + 15), sum(ResolutionWidth + 16), sum(ResolutionWidth + 17), sum(ResolutionWidth + 18), sum(ResolutionWidth + 19), sum(ResolutionWidth + 20), sum(ResolutionWidth + 21), sum(ResolutionWidth + 22), sum(ResolutionWidth + 23), sum(ResolutionWidth + 24), sum(ResolutionWidth + 25), sum(ResolutionWidth + 26), sum(ResolutionWidth + 27), sum(ResolutionWidth + 28), sum(ResolutionWidth + 29), sum(ResolutionWidth + 30), sum(ResolutionWidth + 31), sum(ResolutionWidth + 32), sum(ResolutionWidth + 33), sum(ResolutionWidth + 34), sum(ResolutionWidth + 35), sum(ResolutionWidth + 36), sum(ResolutionWidth + 37), sum(ResolutionWidth + 38), sum(ResolutionWidth + 39), sum(ResolutionWidth + 40), sum(ResolutionWidth + 41), sum(ResolutionWidth + 42), sum(ResolutionWidth + 43), sum(ResolutionWidth + 44), sum(ResolutionWidth + 45), sum(ResolutionWidth + 46), sum(ResolutionWidth + 47), sum(ResolutionWidth + 48), sum(ResolutionWidth + 49), sum(ResolutionWidth + 50), sum(ResolutionWidth + 51), sum(ResolutionWidth + 52), sum(ResolutionWidth + 53), sum(ResolutionWidth + 54), sum(ResolutionWidth + 55), sum(ResolutionWidth + 56), sum(ResolutionWidth + 57), sum(ResolutionWidth + 58), sum(ResolutionWidth + 59), sum(ResolutionWidth + 60), sum(ResolutionWidth + 61), sum(ResolutionWidth + 62), sum(ResolutionWidth + 63), sum(ResolutionWidth + 64), sum(ResolutionWidth + 65), sum(ResolutionWidth + 66), sum(ResolutionWidth + 67), sum(ResolutionWidth + 68), sum(ResolutionWidth + 69), sum(ResolutionWidth + 70), sum(ResolutionWidth + 71), sum(ResolutionWidth + 72), sum(ResolutionWidth + 73), sum(ResolutionWidth + 74), sum(ResolutionWidth + 75), sum(ResolutionWidth + 76), sum(ResolutionWidth + 77), sum(ResolutionWidth + 78), sum(ResolutionWidth + 79), sum(ResolutionWidth + 80), sum(ResolutionWidth + 81), sum(ResolutionWidth + 82), sum(ResolutionWidth + 83), sum(ResolutionWidth + 84), sum(ResolutionWidth + 85), sum(ResolutionWidth + 86), sum(ResolutionWidth + 87), sum(ResolutionWidth + 88), sum(ResolutionWidth + 89) FROM hits -SELECT SearchEngineID, ClientIP, count() AS c, sum(Refresh), avg(ResolutionWidth) FROM hits WHERE SearchPhrase != '' GROUP BY SearchEngineID, ClientIP ORDER BY c DESC LIMIT 10 -SELECT WatchID, ClientIP, count() AS c, sum(Refresh), avg(ResolutionWidth) FROM hits WHERE SearchPhrase != '' GROUP BY WatchID, ClientIP ORDER BY c DESC LIMIT 10 -SELECT WatchID, ClientIP, count() AS c, sum(Refresh), avg(ResolutionWidth) FROM hits GROUP BY WatchID, ClientIP ORDER BY c DESC LIMIT 10 -SELECT URL, count() AS c FROM hits GROUP BY URL ORDER BY c DESC LIMIT 10 -SELECT 1, URL, count() AS c FROM hits GROUP BY 1, URL ORDER BY c DESC LIMIT 10 -SELECT ClientIP AS x, x - 1, x - 2, x - 3, count() AS c FROM hits GROUP BY x, x - 1, x - 2, x - 3 ORDER BY c DESC LIMIT 10 -SELECT URL, count() AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= toDate('2013-07-01') AND EventDate <= toDate('2013-07-31') AND NOT DontCountHits AND NOT Refresh AND notEmpty(URL) GROUP BY URL ORDER BY PageViews DESC LIMIT 10 -SELECT Title, count() AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= toDate('2013-07-01') AND EventDate <= toDate('2013-07-31') AND NOT DontCountHits AND NOT Refresh AND notEmpty(Title) GROUP BY Title ORDER BY PageViews DESC LIMIT 10 -SELECT URL, count() AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= toDate('2013-07-01') AND EventDate <= toDate('2013-07-31') AND NOT Refresh AND IsLink AND NOT IsDownload GROUP BY URL ORDER BY PageViews DESC LIMIT 1000 -SELECT TraficSourceID, SearchEngineID, AdvEngineID, ((SearchEngineID = 0 AND AdvEngineID = 0) ? Referer : '') AS Src, URL AS Dst, count() AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= toDate('2013-07-01') AND EventDate <= toDate('2013-07-31') AND NOT Refresh GROUP BY TraficSourceID, SearchEngineID, AdvEngineID, Src, Dst ORDER BY PageViews DESC LIMIT 1000 -SELECT URLHash, EventDate, count() AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= toDate('2013-07-01') AND EventDate <= toDate('2013-07-31') AND NOT Refresh AND TraficSourceID IN (-1, 6) AND RefererHash = halfMD5('http://yandex.ru/') GROUP BY URLHash, EventDate ORDER BY PageViews DESC LIMIT 100 -SELECT WindowClientWidth, WindowClientHeight, count() AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= toDate('2013-07-01') AND EventDate <= toDate('2013-07-31') AND NOT Refresh AND NOT DontCountHits AND URLHash = halfMD5('http://yandex.ru/') GROUP BY WindowClientWidth, WindowClientHeight ORDER BY PageViews DESC LIMIT 10000; -SELECT toStartOfMinute(EventTime) AS Minute, count() AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= toDate('2013-07-01') AND EventDate <= toDate('2013-07-02') AND NOT Refresh AND NOT DontCountHits GROUP BY Minute ORDER BY Minute; -SELECT cab_type, count(*) FROM trips GROUP BY cab_type; -SELECT passenger_count, avg(total_amount) FROM trips GROUP BY passenger_count; -SELECT passenger_count, toYear(pickup_date) AS year, count(*) FROM trips GROUP BY passenger_count, year; -SELECT passenger_count, toYear(pickup_date) AS year, round(trip_distance) AS distance, count(*) FROM trips GROUP BY passenger_count, year, distance ORDER BY year, count(*) DESC; diff --git a/versions/unified_scripts/benchmarks.sh b/versions/unified_scripts/benchmarks.sh deleted file mode 100755 index 5dccb5303a..0000000000 --- a/versions/unified_scripts/benchmarks.sh +++ /dev/null @@ -1,25 +0,0 @@ -#!/usr/bin/env bash -#set -x - -PASS="${PASSWORD:-}" -CLICKHOUSE_CLIENT="/home/ubuntu/clickhouse client ${HOST:+--host ${HOST}} ${PASSWORD:+--password ${PASS}} ${PASSWORD:+--secure} --progress 0" -TRIES=5 - -for i in {1..10}; do ${CLICKHOUSE_CLIENT} --query 'SELECT version();' > /dev/null && break || sleep 1; done - -cat "all_queries.sql" | while read -r query; do - [ -z "$HOST" ] && sync - if [ -z "$HOST" ]; - then echo 3 | sudo tee /proc/sys/vm/drop_caches >/dev/null; - else ${CLICKHOUSE_CLIENT} --query "SYSTEM DROP FILESYSTEM CACHE ON CLUSTER 'default'" > /dev/null - fi - - - echo -n "[" - for i in $(seq 1 $TRIES); do - RES=$(${CLICKHOUSE_CLIENT} --database sparse --time --format=Null --max_memory_usage=100000000000 --query="$query" 2>&1) - [[ "$?" == "0" ]] && echo -n "${RES}" || echo -n "null" - [[ "$i" != $TRIES ]] && echo -n ", " - done - echo "]," -done diff --git a/versions/unified_scripts/old_versions.list b/versions/unified_scripts/old_versions.list deleted file mode 100644 index b0bc7116da..0000000000 --- a/versions/unified_scripts/old_versions.list +++ /dev/null @@ -1,24 +0,0 @@ -1.1.54378 X -1.1.54380 X -1.1.54381 X -1.1.54383 X -1.1.54385 X -1.1.54388 X -1.1.54390 X -1.1.54394 X -18.1.0 X -18.4.0 X -18.5.1 X -18.6.0 X -18.10.3 X -18.12.17 X -18.14.19 X -18.16.1+ds-7 X -19.1.16 X -19.3.9 X -19.4.5.35 X -19.5.4.22 X -19.6.3.18 X -19.7.5.29 X -19.8.3.8 X -19.9.5.36 X diff --git a/versions/unified_scripts/runner.sh b/versions/unified_scripts/runner.sh deleted file mode 100755 index dd3f96d340..0000000000 --- a/versions/unified_scripts/runner.sh +++ /dev/null @@ -1,35 +0,0 @@ -#!/bin/bash -#set -x -VERSION_ARR=(${1//[-v]/ }) -VERSION=${VERSION_ARR[0]} -FILE_NAME=${VERSION}.json -echo "$VERSION" -sudo ~/clickhouse stop -sudo DEBIAN_FRONTEND=noninteractive apt-get update -sudo DEBIAN_FRONTEND=noninteractive apt-get remove --yes clickhouse-client clickhouse-server clickhouse-common clickhouse-common-static ||: -sudo DEBIAN_FRONTEND=noninteractive apt-get install -o Dpkg::Options::="--force-confdef" -o Dpkg::Options::="--force-confnew" --allow-downgrades --yes clickhouse-client=$VERSION clickhouse-server=$VERSION clickhouse-common=$VERSION ||: -sudo DEBIAN_FRONTEND=noninteractive apt-get install -o Dpkg::Options::="--force-confdef" -o Dpkg::Options::="--force-confnew" --allow-downgrades --yes clickhouse-client=$VERSION clickhouse-server=$VERSION clickhouse-common-static=$VERSION ||: -#sudo service clickhouse-server restart -sudo ~/clickhouse stop -sudo ~/clickhouse start -sleep 3 -VERSION_CH=`clickhouse-client --query 'select version()'` -if [[ ${VERSION} != ${VERSION_CH} ]] -then - echo "ClickHouse was not updated. Expected: ${VERSION} actual: ${VERSION_CH}" - exit 1 -fi - -sleep 5 -echo '{ - "version": "'$VERSION'", - "actual_version": "'$VERSION_CH'", - "result": - [' | tee $FILE_NAME - -bash ./benchmarks.sh >> $FILE_NAME - -sed -i '$ s/,$//' $FILE_NAME - -echo ' ] -}' >> $FILE_NAME diff --git a/versions/unified_scripts/versions.list b/versions/unified_scripts/versions.list deleted file mode 100644 index c1e914c92a..0000000000 --- a/versions/unified_scripts/versions.list +++ /dev/null @@ -1,53 +0,0 @@ -v19.6.3.18-stable 2019-06-15 -v19.7.5.29-stable 2019-07-05 -v19.8.3.8-stable 2019-06-11 -v19.9.5.36-stable 2019-07-20 -v19.10.1.5-stable 2019-07-12 -v19.11.14.1-stable 2019-12-04 -v19.13.7.57-stable 2019-11-06 -v19.14.13.4-lts 2020-07-21 -v19.15.7.30-stable 2019-12-29 -v19.16.19.85-stable 2020-04-27 -v19.17.10.1-stable 2020-07-22 -v20.1.16.120-stable 2020-06-26 -v20.3.21.2-lts 2020-11-02 -v20.4.9.110-stable 2020-08-20 -v20.5.5.74-stable 2020-08-20 -v20.6.11.1-stable 2020-12-09 -v20.7.4.11-stable 2020-10-09 -v20.8.19.4-stable 2021-07-11 -v20.9.7.11-stable 2020-12-07 -v20.10.7.4-stable 2020-12-24 -v20.11.7.16-stable 2021-02-03 -v20.12.8.5-stable 2021-03-02 -v21.1.9.41-stable 2021-04-13 -v21.2.10.48-stable 2021-04-17 -v21.3.20.1-lts 2022-01-26 -v21.4.7.3-stable 2021-05-20 -v21.5.9.4-stable 2021-07-10 -v21.6.9.7-stable 2021-09-03 -v21.7.11.3-stable 2021-09-24 -v21.8.15.7-lts 2022-02-25 -v21.9.6.24-stable 2021-12-02 -v21.10.6.2-stable 2022-01-24 -v21.11.11.1-stable 2022-01-23 -v21.12.4.1-stable 2022-01-23 -v22.1.4.30-stable 2022-02-25 -v22.2.3.5-stable 2022-02-25 -v22.3.20.29-lts 2023-03-31 -v22.4.6.53-stable 2022-07-07 -v22.5.4.19-stable 2022-08-10 -v22.6.9.11-stable 2022-10-06 -v22.7.7.24-stable 2022-10-26 -v22.8.20.11-lts 2023-07-09 -v22.9.7.34-stable 2022-12-16 -v22.10.7.13-stable 2023-01-26 -v22.11.6.44-stable 2023-02-23 -v22.12.6.22-stable 2023-03-31 -v23.1.7.30-stable 2023-04-22 -v23.2.7.32-stable 2023-06-09 -v23.3.8.21-lts 2023-07-13 -v23.4.6.25-stable 2023-07-12 -v23.5.4.25-stable 2023-06-29 -v23.6.2.18-stable 2023-07-09 -v23.7.1.2470-stable 2023-07-27 From f205fdca7757f780f69d683c0a2c385206680285 Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Thu, 2 Jul 2026 05:25:00 +0000 Subject: [PATCH 055/120] versions: fix StoragePtr::operator bool for pre-2013-12 reconstruction The old smart-pointer wrapper's operator bool() returned a boost::shared_ptr, relying on the implicit safe-bool conversion; trusty's boost makes operator bool explicit, so make the conversion explicit. Guarded on the file and the exact return statement, so it is a no-op once StoragePtr became std::shared_ptr. Co-Authored-By: Claude Opus 4.8 --- versions/build-from-source/reconstruct.sh | 8 ++++++++ 1 file changed, 8 insertions(+) diff --git a/versions/build-from-source/reconstruct.sh b/versions/build-from-source/reconstruct.sh index 0059a166e9..b949769d04 100755 --- a/versions/build-from-source/reconstruct.sh +++ b/versions/build-from-source/reconstruct.sh @@ -1172,6 +1172,14 @@ grep -rlZ 'tr1' dbms libs 2>/dev/null | while IFS= read -r -d '' f; do sed -i 's##<\1>#g; s#std::tr1::#std::#g' "$f" done +# -- StoragePtr::operator bool (pre-2013-12): the old smart-pointer wrapper's +# `operator bool() const { return ptr; }` relied on boost::shared_ptr's implicit +# safe-bool conversion, but trusty's boost makes operator bool explicit, so the +# implicit conversion in the return fails. Make it explicit. Guarded on the file + +# exact return, so it's a no-op once StoragePtr was replaced by std::shared_ptr. -- +SP=dbms/include/DB/Storages/StoragePtr.h +[ -f "$SP" ] && sed -i 's#^\(\s*\)return ptr;#\1return static_cast(ptr);#' "$SP" + # -- HyperLogLog counter template arg order: pre-2015-09 # HyperLogLogWithSmallSetOptimization instantiates the counter as # HyperLogLogCounter (old 3-arg form). The back-ported From fa9ca45a827ebd6e5bcdaa945f79cba28fca801b Mon Sep 17 00:00:00 2001 From: Alexey Milovidov Date: Thu, 2 Jul 2026 05:25:16 +0000 Subject: [PATCH 056/120] versions: split page data into data.generated.js; per-dataset metrics, headers, toggles Rework the Versions Benchmark page for the new 10-dataset / 344-query layout: - Split the data out of index.html into data.generated.js (as the main ClickBench page does). generate-results.sh now emits 'const datasets' (name + queries per dataset, in result[] order) and 'const data' (release-ordered per-version results) to that file instead of editing index.html in place. - index.html is now static markup + render logic that loads data.generated.js. - Add per-dataset load time (summed) and on-disk data size, shown in each dataset's header row per version, plus a Total row summing over the enabled datasets. - Group the detailed table into per-dataset sections with a header/separator row before each dataset (with a checkbox to toggle that dataset's queries). - Add a Dataset selector row to switch each dataset on/off; a disabled dataset is hidden from the table and excluded from the relative-time summary. - Generalise the hot metric to the 6-try runs and sort versions by release date. - fetch-results.sh: only take runs in the current 344-query format (skips 9 stale pre-rework sink rows) and write compact result files. Regenerated results/ (170 versions) and data.generated.js from the sink. Co-Authored-By: Claude Opus 4.8 --- versions/data.generated.js | 540 ++++++++++++++++++++++++++++++ versions/fetch-results.sh | 5 +- versions/generate-results.sh | 79 +++-- versions/index.html | 630 ++++++++++++++--------------------- versions/results/53974.json | 1 - versions/results/53975.json | 1 - versions/results/53976.json | 1 - versions/results/53977.json | 1 - versions/results/53978.json | 1 - versions/results/53979.json | 1 - versions/results/53980.json | 1 - versions/results/53981.json | 1 - versions/results/53982.json | 1 - 13 files changed, 842 insertions(+), 421 deletions(-) create mode 100644 versions/data.generated.js delete mode 100644 versions/results/53974.json delete mode 100644 versions/results/53975.json delete mode 100644 versions/results/53976.json delete mode 100644 versions/results/53977.json delete mode 100644 versions/results/53978.json delete mode 100644 versions/results/53979.json delete mode 100644 versions/results/53980.json delete mode 100644 versions/results/53981.json delete mode 100644 versions/results/53982.json diff --git a/versions/data.generated.js b/versions/data.generated.js new file mode 100644 index 0000000000..18fae40138 --- /dev/null +++ b/versions/data.generated.js @@ -0,0 +1,540 @@ +// Generated by generate-results.sh from results/*.json and queries/*.sql. Do not edit. +const datasets = [ +{"name":"mgbench","queries":[ + "SELECT machine_name, MIN(cpu) AS cpu_min, MAX(cpu) AS cpu_max, AVG(cpu) AS cpu_avg, MIN(net_in) AS net_in_min, MAX(net_in) AS net_in_max, AVG(net_in) AS net_in_avg, MIN(net_out) AS net_out_min, MAX(net_out) AS net_out_max, AVG(net_out) AS net_out_avg FROM ( SELECT machine_name, ifNull(cpu_user, 0.0) AS cpu, ifNull(bytes_in, 0.0) AS net_in, ifNull(bytes_out, 0.0) AS net_out FROM logs1 WHERE machine_name IN ('anansi','aragog','urd') AND log_time >= toDateTime('2017-01-11 00:00:00')) AS r GROUP BY machine_name;", + "SELECT machine_name, log_time FROM logs1 WHERE (machine_name LIKE 'cslab%' OR machine_name LIKE 'mslab%') AND load_one IS NULL AND log_time >= toDateTime('2017-01-10 00:00:00') ORDER BY machine_name, log_time;", + "SELECT dt, hr, AVG(load_fifteen) AS load_fifteen_avg, AVG(load_five) AS load_five_avg, AVG(load_one) AS load_one_avg, AVG(mem_free) AS mem_free_avg, AVG(swap_free) AS swap_free_avg FROM ( SELECT CAST(log_time AS DATE) AS dt, toHour(log_time) AS hr, load_fifteen, load_five, load_one, mem_free, swap_free FROM logs1 WHERE machine_name = 'babbage' AND load_fifteen IS NOT NULL AND load_five IS NOT NULL AND load_one IS NOT NULL AND mem_free IS NOT NULL AND swap_free IS NOT NULL AND log_time >= toDateTime('2017-01-01 00:00:00')) AS r GROUP BY dt, hr ORDER BY dt, hr;", + "SELECT machine_name, COUNT(*) AS spikes FROM logs1 WHERE machine_group = 'Servers' AND cpu_wio > 0.99 AND log_time >= toDateTime('2016-12-01 00:00:00') AND log_time < toDateTime('2017-01-01 00:00:00') GROUP BY machine_name ORDER BY spikes DESC LIMIT 10;", + "SELECT machine_name, dt, MIN(mem_free) AS mem_free_min FROM ( SELECT machine_name, CAST(log_time AS DATE) AS dt, mem_free FROM logs1 WHERE machine_group = 'DMZ' AND mem_free IS NOT NULL ) AS r GROUP BY machine_name, dt HAVING MIN(mem_free) < 10000 ORDER BY machine_name, dt;", + "SELECT dt, hr, SUM(net_in) AS net_in_sum, SUM(net_out) AS net_out_sum, SUM(net_in) + SUM(net_out) AS both_sum FROM ( SELECT CAST(log_time AS DATE) AS dt, toHour(log_time) AS hr, ifNull(bytes_in, 0.0) / 1000000000.0 AS net_in, ifNull(bytes_out, 0.0) / 1000000000.0 AS net_out FROM logs1 WHERE machine_name IN ('allsorts','andes','bigred','blackjack','bonbon','cadbury','chiclets','cotton','crows','dove','fireball','hearts','huey','lindt','milkduds','milkyway','mnm','necco','nerds','orbit','peeps','poprocks','razzles','runts','smarties','smuggler','spree','stride','tootsie','trident','wrigley','york') ) AS r GROUP BY dt, hr ORDER BY both_sum DESC LIMIT 10;", + "SELECT * FROM logs2 WHERE status_code >= 500 AND log_time >= toDateTime('2012-12-18 00:00:00') ORDER BY log_time;", + "SELECT * FROM logs2 WHERE status_code >= 200 AND status_code < 300 AND request LIKE '%/etc/passwd%' AND log_time >= toDateTime('2012-05-06 00:00:00') AND log_time < toDateTime('2012-05-20 00:00:00');", + "SELECT top_level, AVG(length(request) - length(replaceOne(request, '/',''))) AS depth_avg FROM ( SELECT substring(request, 1, len) AS top_level, request FROM ( SELECT position('/', substring(request, 2)) AS len, request FROM logs2 WHERE status_code >= 200 AND status_code < 300 AND log_time >= toDateTime('2012-12-01 00:00:00')) AS r WHERE len > 0 ) AS s WHERE top_level IN ('/about','/courses','/degrees','/events','/grad','/industry','/news','/people','/publications','/research','/teaching','/ugrad') GROUP BY top_level ORDER BY top_level;", + "SELECT client_ip, COUNT(*) AS num_requests FROM logs2 WHERE log_time >= toDateTime('2012-10-01 00:00:00') GROUP BY client_ip HAVING COUNT(*) >= 100000 ORDER BY num_requests DESC;", + "SELECT dt, COUNT(DISTINCT client_ip) FROM ( SELECT CAST(log_time AS DATE) AS dt, client_ip FROM logs2) AS r GROUP BY dt ORDER BY dt;", + "SELECT AVG(transfer) / 125000000.0 AS transfer_avg, MAX(transfer) / 125000000.0 AS transfer_max FROM ( SELECT log_time, SUM(object_size) AS transfer FROM logs2 GROUP BY log_time) AS r;", + "SELECT * FROM logs3 WHERE event_type = 'temperature' AND event_value <= 32.0 AND log_time >= '2019-11-29 17:00:00';", + "SELECT device_name, device_floor, COUNT(*) AS ct FROM logs3 WHERE event_type = 'door_open' AND log_time >= '2019-06-01 00:00:00' GROUP BY device_name, device_floor ORDER BY ct DESC;", + "SELECT yr, mo, SUM(coffee_hourly_avg) AS coffee_monthly_sum, AVG(coffee_hourly_avg) AS coffee_monthly_avg, SUM(printer_hourly_avg) AS printer_monthly_sum, AVG(printer_hourly_avg) AS printer_monthly_avg, SUM(projector_hourly_avg) AS projector_monthly_sum, AVG(projector_hourly_avg) AS projector_monthly_avg, SUM(vending_hourly_avg) AS vending_monthly_sum, AVG(vending_hourly_avg) AS vending_monthly_avg FROM ( SELECT dt, yr, mo, hr, AVG(coffee) AS coffee_hourly_avg, AVG(printer) AS printer_hourly_avg, AVG(projector) AS projector_hourly_avg, AVG(vending) AS vending_hourly_avg FROM ( SELECT CAST(log_time AS DATE) AS dt, toYear(log_time) AS yr, EXTRACT(MONTH FROM log_time) AS mo, toHour(log_time) AS hr, CASE WHEN device_name LIKE 'coffee%' THEN event_value END AS coffee, CASE WHEN device_name LIKE 'printer%' THEN event_value END AS printer, CASE WHEN device_name LIKE 'projector%' THEN event_value END AS projector, CASE WHEN device_name LIKE 'vending%' THEN event_value END AS vending FROM logs3 WHERE device_type = 'meter' ) AS r GROUP BY dt, yr, mo, hr ) AS s GROUP BY yr, mo ORDER BY yr, mo;" +]}, +{"name":"ssb","queries":[ + "SELECT sum(LO_EXTENDEDPRICE * LO_DISCOUNT) AS revenue FROM lineorder_flat WHERE F_YEAR = 1993 AND LO_DISCOUNT BETWEEN 1 AND 3 AND LO_QUANTITY < 25;", + "SELECT sum(LO_EXTENDEDPRICE * LO_DISCOUNT) AS revenue FROM lineorder_flat WHERE toYYYYMM(LO_ORDERDATE) = 199401 AND LO_DISCOUNT BETWEEN 4 AND 6 AND LO_QUANTITY BETWEEN 26 AND 35;", + "SELECT sum(LO_EXTENDEDPRICE * LO_DISCOUNT) AS revenue FROM lineorder_flat WHERE toRelativeWeekNum(LO_ORDERDATE) - toRelativeWeekNum(toDate('1994-01-01')) = 6 AND F_YEAR = 1994 AND LO_DISCOUNT BETWEEN 5 AND 7 AND LO_QUANTITY BETWEEN 26 AND 35;", + "SELECT sum(LO_REVENUE), F_YEAR AS year, P_BRAND FROM lineorder_flat WHERE P_CATEGORY = 'MFGR#12' AND S_REGION = 'AMERICA' GROUP BY year, P_BRAND ORDER BY year, P_BRAND;", + "SELECT sum(LO_REVENUE), F_YEAR AS year, P_BRAND FROM lineorder_flat WHERE P_BRAND >= 'MFGR#2221' AND P_BRAND <= 'MFGR#2228' AND S_REGION = 'ASIA' GROUP BY year, P_BRAND ORDER BY year, P_BRAND;", + "SELECT sum(LO_REVENUE), F_YEAR AS year, P_BRAND FROM lineorder_flat WHERE P_BRAND = 'MFGR#2239' AND S_REGION = 'EUROPE' GROUP BY year, P_BRAND ORDER BY year, P_BRAND;", + "SELECT C_NATION, S_NATION, F_YEAR AS year, sum(LO_REVENUE) AS revenue FROM lineorder_flat WHERE C_REGION = 'ASIA' AND S_REGION = 'ASIA' AND year >= 1992 AND year <= 1997 GROUP BY C_NATION, S_NATION, year ORDER BY year ASC, revenue DESC;", + "SELECT C_CITY, S_CITY, F_YEAR AS year, sum(LO_REVENUE) AS revenue FROM lineorder_flat WHERE C_NATION = 'UNITED STATES' AND S_NATION = 'UNITED STATES' AND year >= 1992 AND year <= 1997 GROUP BY C_CITY, S_CITY, year ORDER BY year ASC, revenue DESC;", + "SELECT C_CITY, S_CITY, F_YEAR AS year, sum(LO_REVENUE) AS revenue FROM lineorder_flat WHERE (C_CITY = 'UNITED KI1' OR C_CITY = 'UNITED KI5') AND (S_CITY = 'UNITED KI1' OR S_CITY = 'UNITED KI5') AND year >= 1992 AND year <= 1997 GROUP BY C_CITY, S_CITY, year ORDER BY year ASC, revenue DESC;", + "SELECT C_CITY, S_CITY, F_YEAR AS year, sum(LO_REVENUE) AS revenue FROM lineorder_flat WHERE (C_CITY = 'UNITED KI1' OR C_CITY = 'UNITED KI5') AND (S_CITY = 'UNITED KI1' OR S_CITY = 'UNITED KI5') AND toYYYYMM(LO_ORDERDATE) = 199712 GROUP BY C_CITY, S_CITY, year ORDER BY year ASC, revenue DESC;", + "SELECT F_YEAR AS year, C_NATION, sum(LO_REVENUE - LO_SUPPLYCOST) AS profit FROM lineorder_flat WHERE C_REGION = 'AMERICA' AND S_REGION = 'AMERICA' AND (P_MFGR = 'MFGR#1' OR P_MFGR = 'MFGR#2') GROUP BY year, C_NATION ORDER BY year ASC, C_NATION ASC;", + "SELECT F_YEAR AS year, S_NATION, P_CATEGORY, sum(LO_REVENUE - LO_SUPPLYCOST) AS profit FROM lineorder_flat WHERE C_REGION = 'AMERICA' AND S_REGION = 'AMERICA' AND (year = 1997 OR year = 1998) AND (P_MFGR = 'MFGR#1' OR P_MFGR = 'MFGR#2') GROUP BY year, S_NATION, P_CATEGORY ORDER BY year ASC, S_NATION ASC, P_CATEGORY ASC;", + "SELECT F_YEAR AS year, S_CITY, P_BRAND, sum(LO_REVENUE - LO_SUPPLYCOST) AS profit FROM lineorder_flat WHERE S_NATION = 'UNITED STATES' AND (year = 1997 OR year = 1998) AND P_CATEGORY = 'MFGR#14' GROUP BY year, S_CITY, P_BRAND ORDER BY year ASC, S_CITY ASC, P_BRAND ASC;" +]}, +{"name":"hits","queries":[ + "SELECT count() FROM hits", + "SELECT count() FROM hits WHERE AdvEngineID != 0", + "SELECT sum(AdvEngineID), count(), avg(ResolutionWidth) FROM hits", + "SELECT sum(UserID) FROM hits", + "SELECT uniq(UserID) FROM hits", + "SELECT uniq(SearchPhrase) FROM hits", + "SELECT min(EventDate), max(EventDate) FROM hits", + "SELECT AdvEngineID, count() FROM hits WHERE AdvEngineID != 0 GROUP BY AdvEngineID ORDER BY count() DESC", + "SELECT RegionID, uniq(UserID) AS u FROM hits GROUP BY RegionID ORDER BY u DESC LIMIT 10", + "SELECT RegionID, sum(AdvEngineID), count() AS c, avg(ResolutionWidth), uniq(UserID) FROM hits GROUP BY RegionID ORDER BY c DESC LIMIT 10", + "SELECT MobilePhoneModel, uniq(UserID) AS u FROM hits WHERE MobilePhoneModel != '' GROUP BY MobilePhoneModel ORDER BY u DESC LIMIT 10", + "SELECT MobilePhone, MobilePhoneModel, uniq(UserID) AS u FROM hits WHERE MobilePhoneModel != '' GROUP BY MobilePhone, MobilePhoneModel ORDER BY u DESC LIMIT 10", + "SELECT SearchPhrase, count() AS c FROM hits WHERE SearchPhrase != '' GROUP BY SearchPhrase ORDER BY c DESC LIMIT 10", + "SELECT SearchPhrase, uniq(UserID) AS u FROM hits WHERE SearchPhrase != '' GROUP BY SearchPhrase ORDER BY u DESC LIMIT 10", + "SELECT SearchEngineID, SearchPhrase, count() AS c FROM hits WHERE SearchPhrase != '' GROUP BY SearchEngineID, SearchPhrase ORDER BY c DESC LIMIT 10", + "SELECT UserID, count() FROM hits GROUP BY UserID ORDER BY count() DESC LIMIT 10", + "SELECT UserID, SearchPhrase, count() FROM hits GROUP BY UserID, SearchPhrase ORDER BY count() DESC LIMIT 10", + "SELECT UserID, SearchPhrase, count() FROM hits GROUP BY UserID, SearchPhrase LIMIT 10", + "SELECT UserID, toMinute(EventTime) AS m, SearchPhrase, count() FROM hits GROUP BY UserID, m, SearchPhrase ORDER BY count() DESC LIMIT 10", + "SELECT UserID FROM hits WHERE UserID = 12345678901234567890", + "SELECT count() FROM hits WHERE URL LIKE '%metrika%'", + "SELECT SearchPhrase, any(URL), count() AS c FROM hits WHERE URL LIKE '%metrika%' AND SearchPhrase != '' GROUP BY SearchPhrase ORDER BY c DESC LIMIT 10", + "SELECT SearchPhrase, any(URL), any(Title), count() AS c, uniq(UserID) FROM hits WHERE Title LIKE '%Яндекс%' AND URL NOT LIKE '%.yandex.%' AND SearchPhrase != '' GROUP BY SearchPhrase ORDER BY c DESC LIMIT 10", + "SELECT * FROM hits WHERE URL LIKE '%metrika%' ORDER BY EventTime LIMIT 10", + "SELECT SearchPhrase FROM hits WHERE SearchPhrase != '' ORDER BY EventTime LIMIT 10", + "SELECT SearchPhrase FROM hits WHERE SearchPhrase != '' ORDER BY SearchPhrase LIMIT 10", + "SELECT SearchPhrase FROM hits WHERE SearchPhrase != '' ORDER BY EventTime, SearchPhrase LIMIT 10", + "SELECT CounterID, avg(length(URL)) AS l, count() AS c FROM hits WHERE URL != '' GROUP BY CounterID HAVING c > 100000 ORDER BY l DESC LIMIT 25", + "SELECT domainWithoutWWW(Referer) AS key, avg(length(Referer)) AS l, count() AS c, any(Referer) FROM hits WHERE Referer != '' GROUP BY key HAVING c > 100000 ORDER BY l DESC LIMIT 25", + "SELECT sum(ResolutionWidth), sum(ResolutionWidth + 1), sum(ResolutionWidth + 2), sum(ResolutionWidth + 3), sum(ResolutionWidth + 4), sum(ResolutionWidth + 5), sum(ResolutionWidth + 6), sum(ResolutionWidth + 7), sum(ResolutionWidth + 8), sum(ResolutionWidth + 9), sum(ResolutionWidth + 10), sum(ResolutionWidth + 11), sum(ResolutionWidth + 12), sum(ResolutionWidth + 13), sum(ResolutionWidth + 14), sum(ResolutionWidth + 15), sum(ResolutionWidth + 16), sum(ResolutionWidth + 17), sum(ResolutionWidth + 18), sum(ResolutionWidth + 19), sum(ResolutionWidth + 20), sum(ResolutionWidth + 21), sum(ResolutionWidth + 22), sum(ResolutionWidth + 23), sum(ResolutionWidth + 24), sum(ResolutionWidth + 25), sum(ResolutionWidth + 26), sum(ResolutionWidth + 27), sum(ResolutionWidth + 28), sum(ResolutionWidth + 29), sum(ResolutionWidth + 30), sum(ResolutionWidth + 31), sum(ResolutionWidth + 32), sum(ResolutionWidth + 33), sum(ResolutionWidth + 34), sum(ResolutionWidth + 35), sum(ResolutionWidth + 36), sum(ResolutionWidth + 37), sum(ResolutionWidth + 38), sum(ResolutionWidth + 39), sum(ResolutionWidth + 40), sum(ResolutionWidth + 41), sum(ResolutionWidth + 42), sum(ResolutionWidth + 43), sum(ResolutionWidth + 44), sum(ResolutionWidth + 45), sum(ResolutionWidth + 46), sum(ResolutionWidth + 47), sum(ResolutionWidth + 48), sum(ResolutionWidth + 49), sum(ResolutionWidth + 50), sum(ResolutionWidth + 51), sum(ResolutionWidth + 52), sum(ResolutionWidth + 53), sum(ResolutionWidth + 54), sum(ResolutionWidth + 55), sum(ResolutionWidth + 56), sum(ResolutionWidth + 57), sum(ResolutionWidth + 58), sum(ResolutionWidth + 59), sum(ResolutionWidth + 60), sum(ResolutionWidth + 61), sum(ResolutionWidth + 62), sum(ResolutionWidth + 63), sum(ResolutionWidth + 64), sum(ResolutionWidth + 65), sum(ResolutionWidth + 66), sum(ResolutionWidth + 67), sum(ResolutionWidth + 68), sum(ResolutionWidth + 69), sum(ResolutionWidth + 70), sum(ResolutionWidth + 71), sum(ResolutionWidth + 72), sum(ResolutionWidth + 73), sum(ResolutionWidth + 74), sum(ResolutionWidth + 75), sum(ResolutionWidth + 76), sum(ResolutionWidth + 77), sum(ResolutionWidth + 78), sum(ResolutionWidth + 79), sum(ResolutionWidth + 80), sum(ResolutionWidth + 81), sum(ResolutionWidth + 82), sum(ResolutionWidth + 83), sum(ResolutionWidth + 84), sum(ResolutionWidth + 85), sum(ResolutionWidth + 86), sum(ResolutionWidth + 87), sum(ResolutionWidth + 88), sum(ResolutionWidth + 89) FROM hits", + "SELECT SearchEngineID, ClientIP, count() AS c, sum(Refresh), avg(ResolutionWidth) FROM hits WHERE SearchPhrase != '' GROUP BY SearchEngineID, ClientIP ORDER BY c DESC LIMIT 10", + "SELECT WatchID, ClientIP, count() AS c, sum(Refresh), avg(ResolutionWidth) FROM hits WHERE SearchPhrase != '' GROUP BY WatchID, ClientIP ORDER BY c DESC LIMIT 10", + "SELECT WatchID, ClientIP, count() AS c, sum(Refresh), avg(ResolutionWidth) FROM hits GROUP BY WatchID, ClientIP ORDER BY c DESC LIMIT 10", + "SELECT URL, count() AS c FROM hits GROUP BY URL ORDER BY c DESC LIMIT 10", + "SELECT 1, URL, count() AS c FROM hits GROUP BY 1, URL ORDER BY c DESC LIMIT 10", + "SELECT ClientIP AS x, x - 1, x - 2, x - 3, count() AS c FROM hits GROUP BY x, x - 1, x - 2, x - 3 ORDER BY c DESC LIMIT 10", + "SELECT URL, count() AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= toDate('2013-07-01') AND EventDate <= toDate('2013-07-31') AND NOT DontCountHits AND NOT Refresh AND notEmpty(URL) GROUP BY URL ORDER BY PageViews DESC LIMIT 10", + "SELECT Title, count() AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= toDate('2013-07-01') AND EventDate <= toDate('2013-07-31') AND NOT DontCountHits AND NOT Refresh AND notEmpty(Title) GROUP BY Title ORDER BY PageViews DESC LIMIT 10", + "SELECT URL, count() AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= toDate('2013-07-01') AND EventDate <= toDate('2013-07-31') AND NOT Refresh AND IsLink AND NOT IsDownload GROUP BY URL ORDER BY PageViews DESC LIMIT 1000", + "SELECT TraficSourceID, SearchEngineID, AdvEngineID, ((SearchEngineID = 0 AND AdvEngineID = 0) ? Referer : '') AS Src, URL AS Dst, count() AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= toDate('2013-07-01') AND EventDate <= toDate('2013-07-31') AND NOT Refresh GROUP BY TraficSourceID, SearchEngineID, AdvEngineID, Src, Dst ORDER BY PageViews DESC LIMIT 1000", + "SELECT URLHash, EventDate, count() AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= toDate('2013-07-01') AND EventDate <= toDate('2013-07-31') AND NOT Refresh AND TraficSourceID IN (-1, 6) AND RefererHash = halfMD5('http://yandex.ru/') GROUP BY URLHash, EventDate ORDER BY PageViews DESC LIMIT 100", + "SELECT WindowClientWidth, WindowClientHeight, count() AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= toDate('2013-07-01') AND EventDate <= toDate('2013-07-31') AND NOT Refresh AND NOT DontCountHits AND URLHash = halfMD5('http://yandex.ru/') GROUP BY WindowClientWidth, WindowClientHeight ORDER BY PageViews DESC LIMIT 10000;", + "SELECT toStartOfMinute(EventTime) AS Minute, count() AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= toDate('2013-07-01') AND EventDate <= toDate('2013-07-02') AND NOT Refresh AND NOT DontCountHits GROUP BY Minute ORDER BY Minute;" +]}, +{"name":"uk","queries":[ + "SELECT toYear(date) AS year, round(avg(price)) AS price FROM uk_price_paid GROUP BY year ORDER BY year", + "SELECT toYear(date) AS year, round(avg(price)) AS price FROM uk_price_paid WHERE town = 'LONDON' GROUP BY year ORDER BY year", + "SELECT town, district, count() AS c, round(avg(price)) AS price FROM uk_price_paid WHERE date >= '2020-01-01' GROUP BY town, district HAVING c >= 100 ORDER BY price DESC LIMIT 100" +]}, +{"name":"ontime","queries":[ + "SELECT avg(c1) FROM (SELECT Year, Month, count(*) AS c1 FROM ontime GROUP BY Year, Month)", + "SELECT DayOfWeek, count(*) AS c FROM ontime WHERE Year>=2000 AND Year<=2008 GROUP BY DayOfWeek ORDER BY c DESC", + "SELECT DayOfWeek, count(*) AS c FROM ontime WHERE DepDelay>10 AND Year>=2000 AND Year<=2008 GROUP BY DayOfWeek ORDER BY c DESC", + "SELECT Origin, count(*) AS c FROM ontime WHERE DepDelay>10 AND Year>=2000 AND Year<=2008 GROUP BY Origin ORDER BY c DESC LIMIT 10", + "SELECT IATA_CODE_Reporting_Airline AS Carrier, count(*) FROM ontime WHERE DepDelay>10 AND Year=2007 GROUP BY Carrier ORDER BY count(*) DESC", + "SELECT Carrier, c, c2, c*100/c2 AS c3 FROM (SELECT IATA_CODE_Reporting_Airline AS Carrier, count(*) AS c FROM ontime WHERE DepDelay>10 AND Year=2007 GROUP BY Carrier) q JOIN (SELECT IATA_CODE_Reporting_Airline AS Carrier, count(*) AS c2 FROM ontime WHERE Year=2007 GROUP BY Carrier) qq USING Carrier ORDER BY c3 DESC", + "SELECT Carrier, c, c2, c*100/c2 AS c3 FROM (SELECT IATA_CODE_Reporting_Airline AS Carrier, count(*) AS c FROM ontime WHERE DepDelay>10 AND Year>=2000 AND Year<=2008 GROUP BY Carrier) q JOIN (SELECT IATA_CODE_Reporting_Airline AS Carrier, count(*) AS c2 FROM ontime WHERE Year>=2000 AND Year<=2008 GROUP BY Carrier) qq USING Carrier ORDER BY c3 DESC", + "SELECT Year, c1/c2 FROM (SELECT Year, count(*)*100 AS c1 FROM ontime WHERE DepDelay>10 GROUP BY Year) q JOIN (SELECT Year, count(*) AS c2 FROM ontime GROUP BY Year) qq USING (Year) ORDER BY Year", + "SELECT DestCityName, uniqExact(OriginCityName) AS u FROM ontime WHERE Year >= 2000 AND Year <= 2010 GROUP BY DestCityName ORDER BY u DESC LIMIT 10", + "SELECT Year, count(*) AS c1 FROM ontime GROUP BY Year", + "SELECT min(Year), max(Year), IATA_CODE_Reporting_Airline AS Carrier, count(*) AS cnt, sum(ArrDelayMinutes>30) AS flights_delayed, round(sum(ArrDelayMinutes>30)/count(*),2) AS rate FROM ontime WHERE DayOfWeek NOT IN (6,7) AND OriginState NOT IN ('AK', 'HI', 'PR', 'VI') AND DestState NOT IN ('AK', 'HI', 'PR', 'VI') AND FlightDate < '2010-01-01' GROUP BY Carrier HAVING cnt>100000 AND max(Year)>1990 ORDER BY rate DESC LIMIT 1000" +]}, +{"name":"taxi","queries":[ + "SELECT cab_type, count(*) FROM trips GROUP BY cab_type;", + "SELECT passenger_count, avg(total_amount) FROM trips GROUP BY passenger_count;", + "SELECT passenger_count, toYear(pickup_date) AS year, count(*) FROM trips GROUP BY passenger_count, year;", + "SELECT passenger_count, toYear(pickup_date) AS year, round(trip_distance) AS distance, count(*) FROM trips GROUP BY passenger_count, year, distance ORDER BY year, count(*) DESC;" +]}, +{"name":"coffeeshop","queries":[ + "SELECT f.order_date, l.city, SUM(f.sales_amount) AS total_sales, AVG(SUM(f.sales_amount)) OVER ( PARTITION BY l.city ORDER BY f.order_date ROWS BETWEEN 6 PRECEDING AND CURRENT ROW ) AS rolling_7day_avg FROM fact_sales f JOIN dim_locations l ON f.location_id = l.location_id GROUP BY f.order_date, l.city ORDER BY l.city, f.order_date", + "WITH monthly_sales AS ( SELECT DATE_TRUNC('month', f.order_date) AS sales_month, f.product_name, SUM(f.sales_amount) AS total_sales FROM fact_sales f GROUP BY DATE_TRUNC('month', f.order_date), f.product_name ) SELECT sales_month, product_name, total_sales, RANK() OVER (PARTITION BY sales_month ORDER BY total_sales DESC) AS sales_rank FROM monthly_sales ORDER BY sales_month, sales_rank", + "WITH season_discount AS ( SELECT l.city, l.state, f.season, AVG(f.discount_percentage) AS avg_discount FROM fact_sales f JOIN dim_locations l ON f.location_id = l.location_id GROUP BY l.city, l.state, f.season ) SELECT city, state, season, avg_discount, discount_rank FROM ( SELECT city, state, season, avg_discount, DENSE_RANK() OVER (PARTITION BY season ORDER BY avg_discount DESC) AS discount_rank FROM season_discount ) t WHERE discount_rank <= 3 ORDER BY season, discount_rank", + "SELECT f.order_date, f.product_name, p.standard_price, p.standard_cost, SUM(f.quantity) AS total_quantity_sold, SUM(f.sales_amount) AS total_sales_amount, (p.standard_price - p.standard_cost) * SUM(f.quantity) AS theoretical_margin FROM fact_sales f JOIN dim_products p ON f.product_name = p.name AND f.order_date BETWEEN p.from_date AND p.to_date GROUP BY f.order_date, f.product_name, p.standard_price, p.standard_cost ORDER BY f.order_date, f.product_name", + "WITH daily_city_qty AS ( SELECT f.order_date, l.city, SUM(f.quantity) AS daily_qty FROM fact_sales f JOIN dim_locations l ON f.location_id = l.location_id GROUP BY f.order_date, l.city ) SELECT order_date, city, daily_qty, SUM(daily_qty) OVER ( PARTITION BY city ORDER BY order_date ROWS BETWEEN 29 PRECEDING AND CURRENT ROW ) AS rolling_30day_qty FROM daily_city_qty ORDER BY city, order_date", + "WITH monthly_cat AS ( SELECT DATE_TRUNC('month', f.order_date) AS sales_month, p.category, SUM(f.sales_amount) AS monthly_revenue FROM fact_sales f JOIN dim_products p ON f.product_name = p.name AND f.order_date BETWEEN p.from_date AND p.to_date GROUP BY DATE_TRUNC('month', f.order_date), p.category ) SELECT coalesce(sales_month, DATE('1970-01-01')) AS sales_month, category, monthly_revenue FROM monthly_cat", + "WITH yearly_sales AS ( SELECT l.location_id, l.city, l.state, YEAR(f.order_date) AS sales_year, SUM(f.sales_amount) AS total_sales_year FROM fact_sales f JOIN dim_locations l ON f.location_id = l.location_id GROUP BY l.location_id, l.city, l.state, YEAR(f.order_date) ) SELECT city, state, SUM(CASE WHEN sales_year = 2023 THEN total_sales_year ELSE 0 END) AS sales_2023, SUM(CASE WHEN sales_year = 2024 THEN total_sales_year ELSE 0 END) AS sales_2024, (SUM(CASE WHEN sales_year = 2024 THEN total_sales_year ELSE 0 END) - SUM(CASE WHEN sales_year = 2023 THEN total_sales_year ELSE 0 END)) AS yoy_diff FROM yearly_sales GROUP BY city, state ORDER BY city, state", + "WITH city_quarter_subcat AS ( SELECT l.city, DATE_TRUNC('quarter', f.order_date) AS sales_quarter, p.subcategory, SUM(f.sales_amount) AS total_sales FROM fact_sales f JOIN dim_locations l ON f.location_id = l.location_id JOIN dim_products p ON f.product_name = p.name AND f.order_date BETWEEN p.from_date AND p.to_date GROUP BY l.city, DATE_TRUNC('quarter', f.order_date), p.subcategory ) SELECT city, sales_quarter, subcategory, total_sales, RANK() OVER (PARTITION BY city, sales_quarter ORDER BY total_sales DESC) AS subcat_rank FROM city_quarter_subcat ORDER BY city, sales_quarter, subcat_rank", + "WITH daily_discount AS ( SELECT l.city, f.order_date, AVG(f.discount_percentage) AS avg_discount FROM fact_sales f JOIN dim_locations l ON f.location_id = l.location_id GROUP BY l.city, f.order_date ) SELECT city, order_date, avg_discount, AVG(avg_discount) OVER ( PARTITION BY city ORDER BY order_date ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW ) AS cumulative_avg_discount FROM daily_discount ORDER BY city, order_date", + "WITH daily_orders AS ( SELECT f.order_date, l.city, COUNT(DISTINCT f.order_id) AS daily_distinct_orders FROM fact_sales f JOIN dim_locations l ON f.location_id = l.location_id GROUP BY l.city, f.order_date ) SELECT coalesce(order_date, DATE('1970-01-01')) AS order_date, coalesce(city, '') AS city, daily_distinct_orders, SUM(daily_distinct_orders) OVER ( PARTITION BY city ORDER BY order_date ROWS BETWEEN 89 PRECEDING AND CURRENT ROW ) AS rolling_90d_distinct_orders FROM daily_orders ORDER BY city, order_date", + "WITH city_quarter_subcat AS ( SELECT l.city, DATE_TRUNC('quarter', f.order_date) AS sales_quarter, p.subcategory, SUM(f.sales_amount) AS total_sales FROM fact_sales f JOIN dim_locations l ON f.location_id = l.location_id JOIN dim_products p ON f.product_name = p.name AND f.order_date BETWEEN p.from_date AND p.to_date WHERE l.city IN ('Charlotte', 'Houston') GROUP BY l.city, DATE_TRUNC('quarter', f.order_date), p.subcategory ) SELECT city, sales_quarter, subcategory, total_sales, RANK() OVER (PARTITION BY city, sales_quarter ORDER BY total_sales DESC) AS subcat_rank FROM city_quarter_subcat ORDER BY city, sales_quarter, subcat_rank", + "WITH city_quarter_subcat AS ( SELECT l.city, DATE_TRUNC('quarter', f.order_date) AS sales_quarter, p.subcategory, SUM(f.sales_amount) AS total_sales FROM fact_sales f JOIN dim_locations l ON f.location_id = l.location_id JOIN dim_products p ON f.product_name = p.name AND f.order_date BETWEEN p.from_date AND p.to_date WHERE l.city IN ('Charlotte', 'Houston') AND DATE_TRUNC('quarter', f.order_date) IN ( DATE('2023-01-01'), DATE('2023-04-01'), DATE('2024-01-01'), DATE('2024-04-01') ) GROUP BY l.city, DATE_TRUNC('quarter', f.order_date), p.subcategory ) SELECT city, sales_quarter, subcategory, total_sales, RANK() OVER (PARTITION BY city, sales_quarter ORDER BY total_sales DESC) AS subcat_rank FROM city_quarter_subcat ORDER BY city, sales_quarter, subcat_rank", + "WITH city_quarter_subcat AS ( SELECT l.city, DATE_TRUNC('quarter', f.order_date) AS sales_quarter, p.subcategory, SUM(f.sales_amount) AS total_sales FROM fact_sales f JOIN dim_locations l ON f.location_id = l.location_id JOIN dim_products p ON f.product_name = p.name AND f.order_date BETWEEN p.from_date AND p.to_date WHERE l.city = 'Austin' AND DATE_TRUNC('quarter', f.order_date) IN ( DATE('2023-01-01'), DATE('2023-04-01'), DATE('2024-01-01'), DATE('2024-04-01') ) GROUP BY l.city, DATE_TRUNC('quarter', f.order_date), p.subcategory ) SELECT city, sales_quarter, subcategory, total_sales, RANK() OVER (PARTITION BY city, sales_quarter ORDER BY total_sales DESC) AS subcat_rank FROM city_quarter_subcat ORDER BY city, sales_quarter, subcat_rank", + "WITH city_quarter_subcat AS ( SELECT l.city, DATE_TRUNC('quarter', f.order_date) AS sales_quarter, p.subcategory, SUM(f.sales_amount) AS total_sales FROM fact_sales f JOIN dim_locations l ON f.location_id = l.location_id JOIN dim_products p ON f.product_name = p.name AND f.order_date BETWEEN p.from_date AND p.to_date WHERE DATE_TRUNC('quarter', f.order_date) IN ( DATE('2023-01-01'), DATE('2023-04-01'), DATE('2024-01-01'), DATE('2024-04-01') ) GROUP BY l.city, DATE_TRUNC('quarter', f.order_date), p.subcategory ) SELECT city, sales_quarter, subcategory, total_sales, RANK() OVER (PARTITION BY city, sales_quarter ORDER BY total_sales DESC) AS subcat_rank FROM city_quarter_subcat ORDER BY city, sales_quarter, subcat_rank", + "WITH base_data AS ( SELECT f.location_id as location_id, l.city, f.product_name, toStartOfQuarter(f.order_date) AS sales_quarter, sum(f.sales_amount) AS total_sales, sum(f.sales_amount * (f.discount_percentage / 100.0)) AS total_discount, sum(f.quantity * p.standard_cost) AS total_cogs FROM fact_sales AS f INNER JOIN dim_products AS p ON f.product_name = p.name AND f.order_date BETWEEN p.from_date AND p.to_date INNER JOIN dim_locations AS l ON f.location_id = l.location_id WHERE f.order_date BETWEEN toDate('2022-01-01') AND toDate('2024-12-31') GROUP BY f.location_id, l.city, f.product_name, sales_quarter ), with_profit AS ( SELECT *, total_sales - total_discount - total_cogs AS profit FROM base_data ) SELECT city, product_name, sales_quarter, profit, lagInFrame(profit) OVER w AS prev_profit, round( if(prev_profit = 0 OR prev_profit IS NULL, NULL, 100.0 * (profit - prev_profit) / prev_profit), 2 ) AS yoy_profit_pct FROM with_profit WINDOW w AS ( PARTITION BY location_id, product_name ORDER BY sales_quarter )", + "WITH seasonal_data AS ( SELECT l.state, f.season, p.category, SUM(f.sales_amount) AS total_sales, SUM(f.quantity) AS total_units, COUNT(DISTINCT f.order_id) AS order_count FROM fact_sales f JOIN dim_products p ON f.product_name = p.name AND DATE(f.order_date) BETWEEN DATE(p.from_date) AND DATE(p.to_date) JOIN dim_locations l ON f.location_id = l.location_id WHERE DATE(f.order_date) BETWEEN DATE('2023-01-01') AND DATE('2024-06-30') GROUP BY l.state, f.season, p.category ), ranked AS ( SELECT *, DENSE_RANK() OVER (PARTITION BY state, season ORDER BY total_sales DESC) AS category_rank FROM seasonal_data ) SELECT * FROM ranked WHERE category_rank <= 3 ORDER BY state, season, category_rank", + "WITH raw_agg AS ( SELECT l.state, f.season, p.category, SUM(f.sales_amount) AS total_sales, SUM(f.quantity) AS total_units, COUNT(DISTINCT f.order_id) AS order_count FROM fact_sales AS f JOIN dim_products AS p ON f.product_id = p.product_id AND DATE(f.order_date) BETWEEN DATE(p.from_date) AND DATE(p.to_date) JOIN dim_locations AS l ON f.location_id = l.location_id WHERE l.region = 'West' AND f.time_of_day = 'Morning' AND p.name = 'Frappe' AND DATE(f.order_date) BETWEEN DATE('2023-01-01') AND DATE('2024-06-30') GROUP BY l.state, f.season, p.category ), seasonal_data AS ( SELECT state, season, category, total_sales, total_units, order_count, SUM(total_sales) OVER (PARTITION BY state, season) AS season_total_sales FROM raw_agg ), ranked AS ( SELECT state, season, category, total_sales, total_units, order_count, season_total_sales, ROUND(100.0 * total_sales / season_total_sales, 2) AS pct_of_season, DENSE_RANK() OVER ( PARTITION BY state, season ORDER BY total_sales DESC ) AS category_rank FROM seasonal_data ) SELECT state, season, category, total_sales, total_units, order_count, pct_of_season, category_rank FROM ranked WHERE category_rank <= 3 ORDER BY state, season, category_rank" +]}, +{"name":"tpch","queries":[ + "SELECT l_returnflag, l_linestatus, sum(l_quantity) AS sum_qty, sum(l_extendedprice) AS sum_base_price, sum(l_extendedprice * (1 - l_discount)) AS sum_disc_price, sum(l_extendedprice * (1 - l_discount) * (1 + l_tax)) AS sum_charge, avg(l_quantity) AS avg_qty, avg(l_extendedprice) AS avg_price, avg(l_discount) AS avg_disc, count(*) AS count_order FROM lineitem WHERE (l_shipdate <= date '1998-12-01' - INTERVAL 90 DAY) GROUP BY l_returnflag, l_linestatus ORDER BY l_returnflag, l_linestatus", + "SELECT s_acctbal, s_name, n_name, p_partkey, p_mfgr, s_address, s_phone, s_comment FROM part, supplier, partsupp, nation, region WHERE (p_partkey = ps_partkey) AND (s_suppkey = ps_suppkey) AND (p_size = 15) AND (p_type LIKE '%BRASS') AND (s_nationkey = n_nationkey) AND (n_regionkey = r_regionkey) AND (r_name = 'EUROPE') AND (ps_supplycost = ( SELECT min(ps_supplycost) FROM partsupp, supplier, nation, region WHERE (p_partkey = ps_partkey) AND (s_suppkey = ps_suppkey) AND (s_nationkey = n_nationkey) AND (n_regionkey = r_regionkey) AND (r_name = 'EUROPE') )) ORDER BY s_acctbal DESC, n_name, s_name, p_partkey LIMIT 100", + "SELECT l_orderkey, sum(l_extendedprice * (1 - l_discount)) AS revenue, o_orderdate, o_shippriority FROM customer, orders, lineitem WHERE (c_mktsegment = 'BUILDING') AND (c_custkey = o_custkey) AND (l_orderkey = o_orderkey) AND (o_orderdate < date '1995-03-15') AND (l_shipdate > date '1995-03-15') GROUP BY l_orderkey, o_orderdate, o_shippriority ORDER BY revenue DESC, o_orderdate LIMIT 10", + "SELECT o_orderpriority, count(*) AS order_count FROM orders WHERE (o_orderdate >= date '1993-07-01') AND (o_orderdate < date '1993-07-01' + INTERVAL 3 MONTH) AND EXISTS ( SELECT * FROM lineitem WHERE (l_orderkey = o_orderkey) AND (l_commitdate < l_receiptdate) ) GROUP BY o_orderpriority ORDER BY o_orderpriority", + "SELECT n_name, sum(l_extendedprice * (1 - l_discount)) AS revenue FROM customer, orders, lineitem, supplier, nation, region WHERE (c_custkey = o_custkey) AND (l_orderkey = o_orderkey) AND (l_suppkey = s_suppkey) AND (c_nationkey = s_nationkey) AND (s_nationkey = n_nationkey) AND (n_regionkey = r_regionkey) AND (r_name = 'ASIA') AND (o_orderdate >= date '1994-01-01') AND (o_orderdate < date '1994-01-01' + INTERVAL 1 YEAR) GROUP BY n_name ORDER BY revenue DESC", + "SELECT sum(l_extendedprice * l_discount) AS revenue FROM lineitem WHERE (l_shipdate >= date '1994-01-01') AND (l_shipdate < date '1994-01-01' + INTERVAL 1 YEAR) AND (l_discount BETWEEN 0.06::Decimal(12,2) - 0.01::Decimal(12,2) AND 0.06::Decimal(12,2) + 0.01::Decimal(12,2)) AND (l_quantity < 24)", + "SELECT supp_nation, cust_nation, l_year, sum(volume) AS revenue FROM ( SELECT n1.n_name AS supp_nation, n2.n_name AS cust_nation, extract(year FROM l_shipdate) AS l_year, l_extendedprice * (1 - l_discount) AS volume FROM supplier, lineitem, orders, customer, nation AS n1, nation AS n2 WHERE (s_suppkey = l_suppkey) AND (o_orderkey = l_orderkey) AND (c_custkey = o_custkey) AND (s_nationkey = n1.n_nationkey) AND (c_nationkey = n2.n_nationkey) AND ( ((n1.n_name = 'FRANCE') AND (n2.n_name = 'GERMANY')) OR ((n1.n_name = 'GERMANY') AND (n2.n_name = 'FRANCE')) ) AND (l_shipdate BETWEEN date '1995-01-01' AND date '1996-12-31') ) AS shipping GROUP BY supp_nation, cust_nation, l_year ORDER BY supp_nation, cust_nation, l_year", + "SELECT o_year, sum(CASE WHEN nation = 'BRAZIL' THEN volume ELSE 0 END) / sum(volume) AS mkt_share FROM ( SELECT extract(year FROM o_orderdate) AS o_year, l_extendedprice * (1 - l_discount) AS volume, n2.n_name AS nation FROM part, supplier, lineitem, orders, customer, nation AS n1, nation AS n2, region WHERE (p_partkey = l_partkey) AND (s_suppkey = l_suppkey) AND (l_orderkey = o_orderkey) AND (o_custkey = c_custkey) AND (c_nationkey = n1.n_nationkey) AND (n1.n_regionkey = r_regionkey) AND (r_name = 'AMERICA') AND (s_nationkey = n2.n_nationkey) AND (o_orderdate BETWEEN date '1995-01-01' AND date '1996-12-31') AND (p_type = 'ECONOMY ANODIZED STEEL') ) AS all_nations GROUP BY o_year ORDER BY o_year", + "SELECT nation, o_year, sum(amount) AS sum_profit FROM ( SELECT n_name AS nation, extract(year FROM o_orderdate) AS o_year, l_extendedprice * (1 - l_discount) - ps_supplycost * l_quantity AS amount FROM part, supplier, lineitem, partsupp, orders, nation WHERE (s_suppkey = l_suppkey) AND (ps_suppkey = l_suppkey) AND (ps_partkey = l_partkey) AND (p_partkey = l_partkey) AND (o_orderkey = l_orderkey) AND (s_nationkey = n_nationkey) AND (p_name LIKE '%green%') ) AS profit GROUP BY nation, o_year ORDER BY nation, o_year DESC", + "SELECT c_custkey, c_name, sum(l_extendedprice * (1 - l_discount)) AS revenue, c_acctbal, n_name, c_address, c_phone, c_comment FROM customer, orders, lineitem, nation WHERE (c_custkey = o_custkey) AND (l_orderkey = o_orderkey) AND (o_orderdate >= date '1993-10-01') AND (o_orderdate < date '1993-10-01' + INTERVAL 3 MONTH) AND (l_returnflag = 'R') AND (c_nationkey = n_nationkey) GROUP BY c_custkey, c_name, c_acctbal, c_phone, n_name, c_address, c_comment ORDER BY revenue DESC LIMIT 20", + "SELECT ps_partkey, sum(ps_supplycost * ps_availqty) AS value FROM partsupp, supplier, nation WHERE (ps_suppkey = s_suppkey) AND (s_nationkey = n_nationkey) AND (n_name = 'GERMANY') GROUP BY ps_partkey HAVING sum(ps_supplycost * ps_availqty) > ( SELECT sum(ps_supplycost * ps_availqty) * 0.0001 FROM partsupp, supplier, nation WHERE (ps_suppkey = s_suppkey) AND (s_nationkey = n_nationkey) AND (n_name = 'GERMANY') ) ORDER BY value DESC", + "SELECT l_shipmode, sum(CASE WHEN (o_orderpriority = '1-URGENT') OR (o_orderpriority = '2-HIGH') THEN 1 ELSE 0 END) AS high_line_count, sum(CASE WHEN (o_orderpriority <> '1-URGENT') AND (o_orderpriority <> '2-HIGH') THEN 1 ELSE 0 END) AS low_line_count FROM orders, lineitem WHERE (o_orderkey = l_orderkey) AND (l_shipmode IN ('MAIL', 'SHIP')) AND (l_commitdate < l_receiptdate) AND (l_shipdate < l_commitdate) AND (l_receiptdate >= date '1994-01-01') AND (l_receiptdate < date '1994-01-01' + INTERVAL 1 YEAR) GROUP BY l_shipmode ORDER BY l_shipmode", + "SELECT c_count, count(*) AS custdist FROM ( SELECT c_custkey, count(o_orderkey) AS c_count FROM customer LEFT OUTER JOIN orders ON (c_custkey = o_custkey) AND (o_comment NOT LIKE '%special%requests%') GROUP BY c_custkey ) AS c_orders GROUP BY c_count ORDER BY custdist DESC, c_count DESC", + "SELECT 100.00 * sum(CASE WHEN p_type LIKE 'PROMO%' THEN l_extendedprice * (1 - l_discount) ELSE 0 END) / sum(l_extendedprice * (1 - l_discount)) AS promo_revenue FROM lineitem, part WHERE (l_partkey = p_partkey) AND (l_shipdate >= date '1995-09-01') AND (l_shipdate < date '1995-09-01' + INTERVAL 1 MONTH)", + "WITH revenue0 AS (SELECT l_suppkey AS supplier_no, sum(l_extendedprice * (1 - l_discount)) AS total_revenue FROM lineitem WHERE (l_shipdate >= date '1996-01-01') AND (l_shipdate < date '1996-01-01' + INTERVAL 3 MONTH) GROUP BY l_suppkey) SELECT s_suppkey, s_name, s_address, s_phone, total_revenue FROM supplier, revenue0 WHERE (s_suppkey = supplier_no) AND (total_revenue = (SELECT max(total_revenue) FROM revenue0)) ORDER BY s_suppkey", + "SELECT p_brand, p_type, p_size, count(DISTINCT ps_suppkey) AS supplier_cnt FROM partsupp, part WHERE (p_partkey = ps_partkey) AND (p_brand <> 'Brand#45') AND (p_type NOT LIKE 'MEDIUM POLISHED%') AND (p_size IN (49, 14, 23, 45, 19, 3, 36, 9)) AND (ps_suppkey NOT IN ( SELECT s_suppkey FROM supplier WHERE (s_comment LIKE '%Customer%Complaints%') )) GROUP BY p_brand, p_type, p_size ORDER BY supplier_cnt DESC, p_brand, p_type, p_size", + "SELECT sum(l_extendedprice) / 7.0 AS avg_yearly FROM lineitem, part WHERE (p_partkey = l_partkey) AND (p_brand = 'Brand#23') AND (p_container = 'MED BOX') AND (l_quantity < ( SELECT 0.2 * avg(l_quantity) FROM lineitem WHERE (l_partkey = p_partkey) ))", + "SELECT c_name, c_custkey, o_orderkey, o_orderdate, o_totalprice, sum(l_quantity) FROM customer, orders, lineitem WHERE (o_orderkey IN ( SELECT l_orderkey FROM lineitem GROUP BY l_orderkey HAVING sum(l_quantity) > 300 )) AND (c_custkey = o_custkey) AND (o_orderkey = l_orderkey) GROUP BY c_name, c_custkey, o_orderkey, o_orderdate, o_totalprice ORDER BY o_totalprice DESC, o_orderdate LIMIT 100", + "SELECT sum(l_extendedprice * (1 - l_discount)) AS revenue FROM lineitem, part WHERE ( (p_partkey = l_partkey) AND (p_brand = 'Brand#12') AND (p_container IN ('SM CASE', 'SM BOX', 'SM PACK', 'SM PKG')) AND (l_quantity >= 1) AND (l_quantity <= 1 + 10) AND (p_size BETWEEN 1 AND 5) AND (l_shipmode IN ('AIR', 'AIR REG')) AND (l_shipinstruct = 'DELIVER IN PERSON') ) OR ( (p_partkey = l_partkey) AND (p_brand = 'Brand#23') AND (p_container IN ('MED BAG', 'MED BOX', 'MED PKG', 'MED PACK')) AND (l_quantity >= 10) AND (l_quantity <= 10 + 10) AND (p_size BETWEEN 1 AND 10) AND (l_shipmode IN ('AIR', 'AIR REG')) AND (l_shipinstruct = 'DELIVER IN PERSON') ) OR ( (p_partkey = l_partkey) AND (p_brand = 'Brand#34') AND (p_container IN ('LG CASE', 'LG BOX', 'LG PACK', 'LG PKG')) AND (l_quantity >= 20) AND (l_quantity <= 20 + 10) AND (p_size BETWEEN 1 AND 15) AND (l_shipmode IN ('AIR', 'AIR REG')) AND (l_shipinstruct = 'DELIVER IN PERSON') )", + "SELECT s_name, s_address FROM supplier, nation WHERE (s_suppkey IN ( SELECT ps_suppkey FROM partsupp WHERE (ps_partkey IN ( SELECT p_partkey FROM part WHERE (p_name LIKE 'forest%') )) AND (ps_availqty > ( SELECT 0.5 * sum(l_quantity) FROM lineitem WHERE (l_partkey = ps_partkey) AND (l_suppkey = ps_suppkey) AND (l_shipdate >= date '1994-01-01') AND (l_shipdate < date '1994-01-01' + INTERVAL 1 YEAR) )) )) AND (s_nationkey = n_nationkey) AND (n_name = 'CANADA') ORDER BY s_name", + "SELECT s_name, count(*) AS numwait FROM supplier, lineitem AS l1, orders, nation WHERE (s_suppkey = l1.l_suppkey) AND (o_orderkey = l1.l_orderkey) AND (o_orderstatus = 'F') AND (l1.l_receiptdate > l1.l_commitdate) AND EXISTS ( SELECT * FROM lineitem AS l2 WHERE (l2.l_orderkey = l1.l_orderkey) AND (l2.l_suppkey <> l1.l_suppkey) ) AND NOT EXISTS ( SELECT * FROM lineitem AS l3 WHERE (l3.l_orderkey = l1.l_orderkey) AND (l3.l_suppkey <> l1.l_suppkey) AND (l3.l_receiptdate > l3.l_commitdate) ) AND (s_nationkey = n_nationkey) AND (n_name = 'SAUDI ARABIA') GROUP BY s_name ORDER BY numwait DESC, s_name LIMIT 100", + "SELECT cntrycode, count(*) AS numcust, sum(c_acctbal) AS totacctbal FROM ( SELECT substring(c_phone FROM 1 FOR 2) AS cntrycode, c_acctbal FROM customer WHERE (substring(c_phone FROM 1 FOR 2) IN ('13', '31', '23', '29', '30', '18', '17')) AND (c_acctbal > ( SELECT avg(c_acctbal) FROM customer WHERE (c_acctbal > 0.00) AND (substring(c_phone FROM 1 FOR 2) IN ('13', '31', '23', '29', '30', '18', '17')) )) AND NOT EXISTS ( SELECT * FROM orders WHERE (o_custkey = c_custkey) ) ) AS custsale GROUP BY cntrycode ORDER BY cntrycode" +]}, +{"name":"tpcds","queries":[ + "WITH customer_total_return AS ( SELECT sr_customer_sk AS ctr_customer_sk, sr_store_sk AS ctr_store_sk, sum(sr_return_amt) AS ctr_total_return FROM store_returns, date_dim WHERE (sr_returned_date_sk = d_date_sk) AND (d_year = 2000) GROUP BY sr_customer_sk, sr_store_sk ) SELECT c_customer_id FROM customer_total_return AS ctr1, store, customer WHERE (ctr1.ctr_total_return > ( SELECT avg(ctr_total_return) * 1.2 FROM customer_total_return AS ctr2 WHERE ctr1.ctr_store_sk = ctr2.ctr_store_sk )) AND (s_store_sk = ctr1.ctr_store_sk) AND (s_state = 'TN') AND (ctr1.ctr_customer_sk = c_customer_sk) ORDER BY c_customer_id LIMIT 100", + "WITH wscs AS ( SELECT sold_date_sk, sales_price FROM ( SELECT ws_sold_date_sk AS sold_date_sk, ws_ext_sales_price AS sales_price FROM web_sales UNION ALL SELECT cs_sold_date_sk AS sold_date_sk, cs_ext_sales_price AS sales_price FROM catalog_sales ) ), wswscs AS ( SELECT d_week_seq, sum(multiIf(d_day_name = 'Sunday', sales_price, NULL)) AS sun_sales, sum(multiIf(d_day_name = 'Monday', sales_price, NULL)) AS mon_sales, sum(multiIf(d_day_name = 'Tuesday', sales_price, NULL)) AS tue_sales, sum(multiIf(d_day_name = 'Wednesday', sales_price, NULL)) AS wed_sales, sum(multiIf(d_day_name = 'Thursday', sales_price, NULL)) AS thu_sales, sum(multiIf(d_day_name = 'Friday', sales_price, NULL)) AS fri_sales, sum(multiIf(d_day_name = 'Saturday', sales_price, NULL)) AS sat_sales FROM wscs, date_dim WHERE d_date_sk = sold_date_sk GROUP BY d_week_seq ) SELECT d_week_seq1, round(sun_sales1 / sun_sales2, 2), round(mon_sales1 / mon_sales2, 2), round(tue_sales1 / tue_sales2, 2), round(wed_sales1 / wed_sales2, 2), round(thu_sales1 / thu_sales2, 2), round(fri_sales1 / fri_sales2, 2), round(sat_sales1 / sat_sales2, 2) FROM ( SELECT wswscs.d_week_seq AS d_week_seq1, sun_sales AS sun_sales1, mon_sales AS mon_sales1, tue_sales AS tue_sales1, wed_sales AS wed_sales1, thu_sales AS thu_sales1, fri_sales AS fri_sales1, sat_sales AS sat_sales1 FROM wswscs, date_dim WHERE (date_dim.d_week_seq = wswscs.d_week_seq) AND (d_year = 2001) ) AS y, ( SELECT wswscs.d_week_seq AS d_week_seq2, sun_sales AS sun_sales2, mon_sales AS mon_sales2, tue_sales AS tue_sales2, wed_sales AS wed_sales2, thu_sales AS thu_sales2, fri_sales AS fri_sales2, sat_sales AS sat_sales2 FROM wswscs, date_dim WHERE (date_dim.d_week_seq = wswscs.d_week_seq) AND (d_year = (2001 + 1)) ) AS z WHERE d_week_seq1 = (d_week_seq2 - 53) ORDER BY d_week_seq1", + "SELECT dt.d_year, item.i_brand_id AS brand_id, item.i_brand AS brand, sum(ss_ext_sales_price) AS sum_agg FROM date_dim AS dt, store_sales, item WHERE (dt.d_date_sk = store_sales.ss_sold_date_sk) AND (store_sales.ss_item_sk = item.i_item_sk) AND (item.i_manufact_id = 128) AND (dt.d_moy = 11) GROUP BY dt.d_year, item.i_brand, item.i_brand_id ORDER BY dt.d_year, sum_agg DESC, brand_id LIMIT 100", + "WITH year_total AS ( SELECT c_customer_id AS customer_id, c_first_name AS customer_first_name, c_last_name AS customer_last_name, c_preferred_cust_flag AS customer_preferred_cust_flag, c_birth_country AS customer_birth_country, c_login AS customer_login, c_email_address AS customer_email_address, d_year AS dyear, sum((((ss_ext_list_price - ss_ext_wholesale_cost) - ss_ext_discount_amt) + ss_ext_sales_price) / 2) AS year_total, 's' AS sale_type FROM customer, store_sales, date_dim WHERE (c_customer_sk = ss_customer_sk) AND (ss_sold_date_sk = d_date_sk) GROUP BY c_customer_id, c_first_name, c_last_name, c_preferred_cust_flag, c_birth_country, c_login, c_email_address, d_year UNION ALL SELECT c_customer_id AS customer_id, c_first_name AS customer_first_name, c_last_name AS customer_last_name, c_preferred_cust_flag AS customer_preferred_cust_flag, c_birth_country AS customer_birth_country, c_login AS customer_login, c_email_address AS customer_email_address, d_year AS dyear, sum((((cs_ext_list_price - cs_ext_wholesale_cost) - cs_ext_discount_amt) + cs_ext_sales_price) / 2) AS year_total, 'c' AS sale_type FROM customer, catalog_sales, date_dim WHERE (c_customer_sk = cs_bill_customer_sk) AND (cs_sold_date_sk = d_date_sk) GROUP BY c_customer_id, c_first_name, c_last_name, c_preferred_cust_flag, c_birth_country, c_login, c_email_address, d_year UNION ALL SELECT c_customer_id AS customer_id, c_first_name AS customer_first_name, c_last_name AS customer_last_name, c_preferred_cust_flag AS customer_preferred_cust_flag, c_birth_country AS customer_birth_country, c_login AS customer_login, c_email_address AS customer_email_address, d_year AS dyear, sum((((ws_ext_list_price - ws_ext_wholesale_cost) - ws_ext_discount_amt) + ws_ext_sales_price) / 2) AS year_total, 'w' AS sale_type FROM customer, web_sales, date_dim WHERE (c_customer_sk = ws_bill_customer_sk) AND (ws_sold_date_sk = d_date_sk) GROUP BY c_customer_id, c_first_name, c_last_name, c_preferred_cust_flag, c_birth_country, c_login, c_email_address, d_year ) SELECT t_s_secyear.customer_id, t_s_secyear.customer_first_name, t_s_secyear.customer_last_name, t_s_secyear.customer_preferred_cust_flag FROM year_total AS t_s_firstyear, year_total AS t_s_secyear, year_total AS t_c_firstyear, year_total AS t_c_secyear, year_total AS t_w_firstyear, year_total AS t_w_secyear WHERE (t_s_secyear.customer_id = t_s_firstyear.customer_id) AND (t_s_firstyear.customer_id = t_c_secyear.customer_id) AND (t_s_firstyear.customer_id = t_c_firstyear.customer_id) AND (t_s_firstyear.customer_id = t_w_firstyear.customer_id) AND (t_s_firstyear.customer_id = t_w_secyear.customer_id) AND (t_s_firstyear.sale_type = 's') AND (t_c_firstyear.sale_type = 'c') AND (t_w_firstyear.sale_type = 'w') AND (t_s_secyear.sale_type = 's') AND (t_c_secyear.sale_type = 'c') AND (t_w_secyear.sale_type = 'w') AND (t_s_firstyear.dyear = 2001) AND (t_s_secyear.dyear = (2001 + 1)) AND (t_c_firstyear.dyear = 2001) AND (t_c_secyear.dyear = (2001 + 1)) AND (t_w_firstyear.dyear = 2001) AND (t_w_secyear.dyear = (2001 + 1)) AND (t_s_firstyear.year_total > 0) AND (t_c_firstyear.year_total > 0) AND (t_w_firstyear.year_total > 0) AND (multiIf(t_c_firstyear.year_total > 0, t_c_secyear.year_total / t_c_firstyear.year_total, NULL) > multiIf(t_s_firstyear.year_total > 0, t_s_secyear.year_total / t_s_firstyear.year_total, NULL)) AND (multiIf(t_c_firstyear.year_total > 0, t_c_secyear.year_total / t_c_firstyear.year_total, NULL) > multiIf(t_w_firstyear.year_total > 0, t_w_secyear.year_total / t_w_firstyear.year_total, NULL)) ORDER BY t_s_secyear.customer_id, t_s_secyear.customer_first_name, t_s_secyear.customer_last_name, t_s_secyear.customer_preferred_cust_flag LIMIT 100", + "WITH ssr AS ( SELECT s_store_id, sum(sales_price) AS sales, sum(profit) AS profit, sum(return_amt) AS returns, sum(net_loss) AS profit_loss FROM ( SELECT ss_store_sk AS store_sk, ss_sold_date_sk AS date_sk, ss_ext_sales_price AS sales_price, ss_net_profit AS profit, CAST(0, 'decimal(7, 2)') AS return_amt, CAST(0, 'decimal(7, 2)') AS net_loss FROM store_sales UNION ALL SELECT sr_store_sk AS store_sk, sr_returned_date_sk AS date_sk, CAST(0, 'decimal(7, 2)') AS sales_price, CAST(0, 'decimal(7, 2)') AS profit, sr_return_amt AS return_amt, sr_net_loss AS net_loss FROM store_returns ) AS salesreturns, date_dim, store WHERE (date_sk = d_date_sk) AND ((d_date >= CAST('2000-08-23', 'date')) AND (d_date <= (CAST('2000-08-23', 'date') + INTERVAL 14 day))) AND (store_sk = s_store_sk) GROUP BY s_store_id ), csr AS ( SELECT cp_catalog_page_id, sum(sales_price) AS sales, sum(profit) AS profit, sum(return_amt) AS returns, sum(net_loss) AS profit_loss FROM ( SELECT cs_catalog_page_sk AS page_sk, cs_sold_date_sk AS date_sk, cs_ext_sales_price AS sales_price, cs_net_profit AS profit, CAST(0, 'decimal(7, 2)') AS return_amt, CAST(0, 'decimal(7, 2)') AS net_loss FROM catalog_sales UNION ALL SELECT cr_catalog_page_sk AS page_sk, cr_returned_date_sk AS date_sk, CAST(0, 'decimal(7, 2)') AS sales_price, CAST(0, 'decimal(7, 2)') AS profit, cr_return_amount AS return_amt, cr_net_loss AS net_loss FROM catalog_returns ) AS salesreturns, date_dim, catalog_page WHERE (date_sk = d_date_sk) AND (d_date BETWEEN CAST('2000-08-23', 'date') AND CAST('2000-08-23', 'date') + INTERVAL 14 day) AND (page_sk = cp_catalog_page_sk) GROUP BY cp_catalog_page_id ), wsr AS ( SELECT web_site_id, sum(sales_price) AS sales, sum(profit) AS profit, sum(return_amt) AS returns, sum(net_loss) AS profit_loss FROM ( SELECT ws_web_site_sk AS wsr_web_site_sk, ws_sold_date_sk AS date_sk, ws_ext_sales_price AS sales_price, ws_net_profit AS profit, CAST(0, 'decimal(7, 2)') AS return_amt, CAST(0, 'decimal(7, 2)') AS net_loss FROM web_sales UNION ALL SELECT ws_web_site_sk AS wsr_web_site_sk, wr_returned_date_sk AS date_sk, CAST(0, 'decimal(7, 2)') AS sales_price, CAST(0, 'decimal(7, 2)') AS profit, wr_return_amt AS return_amt, wr_net_loss AS net_loss FROM web_returns LEFT JOIN web_sales ON (wr_item_sk = ws_item_sk) AND (wr_order_number = ws_order_number) ) AS salesreturns, date_dim, web_site WHERE (date_sk = d_date_sk) AND ((d_date >= CAST('2000-08-23', 'date')) AND (d_date <= (CAST('2000-08-23', 'date') + INTERVAL 14 day))) AND (wsr_web_site_sk = web_site_sk) GROUP BY web_site_id ) SELECT channel, id, sum(sales) AS sales, sum(returns) AS returns, sum(profit) AS profit FROM ( SELECT 'store channel' AS channel, concat('store', s_store_id) AS id, sales, returns, profit - profit_loss AS profit FROM ssr UNION ALL SELECT 'catalog channel' AS channel, concat('catalog_page', cp_catalog_page_id) AS id, sales, returns, profit - profit_loss AS profit FROM csr UNION ALL SELECT 'web channel' AS channel, concat('web_site', web_site_id) AS id, sales, returns, profit - profit_loss AS profit FROM wsr ) AS x GROUP BY channel, id WITH ROLLUP ORDER BY channel, id LIMIT 100", + "SELECT a.ca_state AS state, count(*) AS cnt FROM customer_address AS a, customer AS c, store_sales AS s, date_dim AS d, item AS i WHERE (a.ca_address_sk = c.c_current_addr_sk) AND (c.c_customer_sk = s.ss_customer_sk) AND (s.ss_sold_date_sk = d.d_date_sk) AND (s.ss_item_sk = i.i_item_sk) AND (d.d_month_seq = ( SELECT DISTINCT d_month_seq FROM date_dim WHERE (d_year = 2001) AND (d_moy = 1) )) AND (i.i_current_price > 1.2 * ( SELECT avg(j.i_current_price) FROM item AS j WHERE (j.i_category = i.i_category) )) GROUP BY a.ca_state HAVING count(*) >= 10 ORDER BY cnt, a.ca_state LIMIT 100", + "SELECT i_item_id, avg(ss_quantity) AS agg1, avg(ss_list_price) AS agg2, avg(ss_coupon_amt) AS agg3, avg(ss_sales_price) AS agg4 FROM store_sales, customer_demographics, date_dim, item, promotion WHERE (ss_sold_date_sk = d_date_sk) AND (ss_item_sk = i_item_sk) AND (ss_cdemo_sk = cd_demo_sk) AND (ss_promo_sk = p_promo_sk) AND (cd_gender = 'M') AND (cd_marital_status = 'S') AND (cd_education_status = 'College') AND ((p_channel_email = 'N') OR (p_channel_event = 'N')) AND (d_year = 2000) GROUP BY i_item_id ORDER BY i_item_id LIMIT 100", + "SELECT s_store_name, sum(ss_net_profit) FROM store_sales, date_dim, store, ( SELECT substr(ca_zip, 1, 2) AS ca_zip FROM ( SELECT substr(ca_zip, 1, 5) AS ca_zip FROM customer_address WHERE substr(ca_zip, 1, 5) IN ('24128', '76232', '65084', '87816', '83926', '77556', '20548', '26231', '43848', '15126', '91137', '61265', '98294', '25782', '17920', '18426', '98235', '40081', '84093', '28577', '55565', '17183', '54601', '67897', '22752', '86284', '18376', '38607', '45200', '21756', '29741', '96765', '23932', '89360', '29839', '25989', '28898', '91068', '72550', '10390', '18845', '47770', '82636', '41367', '76638', '86198', '81312', '37126', '39192', '88424', '72175', '81426', '53672', '10445', '42666', '66864', '66708', '41248', '48583', '82276', '18842', '78890', '49448', '14089', '38122', '34425', '79077', '19849', '43285', '39861', '66162', '77610', '13695', '99543', '83444', '83041', '12305', '57665', '68341', '25003', '57834', '62878', '49130', '81096', '18840', '27700', '23470', '50412', '21195', '16021', '76107', '71954', '68309', '18119', '98359', '64544', '10336', '86379', '27068', '39736', '98569', '28915', '24206', '56529', '57647', '54917', '42961', '91110', '63981', '14922', '36420', '23006', '67467', '32754', '30903', '20260', '31671', '51798', '72325', '85816', '68621', '13955', '36446', '41766', '68806', '16725', '15146', '22744', '35850', '88086', '51649', '18270', '52867', '39972', '96976', '63792', '11376', '94898', '13595', '10516', '90225', '58943', '39371', '94945', '28587', '96576', '57855', '28488', '26105', '83933', '25858', '34322', '44438', '73171', '30122', '34102', '22685', '71256', '78451', '54364', '13354', '45375', '40558', '56458', '28286', '45266', '47305', '69399', '83921', '26233', '11101', '15371', '69913', '35942', '15882', '25631', '24610', '44165', '99076', '33786', '70738', '26653', '14328', '72305', '62496', '22152', '10144', '64147', '48425', '14663', '21076', '18799', '30450', '63089', '81019', '68893', '24996', '51200', '51211', '45692', '92712', '70466', '79994', '22437', '25280', '38935', '71791', '73134', '56571', '14060', '19505', '72425', '56575', '74351', '68786', '51650', '20004', '18383', '76614', '11634', '18906', '15765', '41368', '73241', '76698', '78567', '97189', '28545', '76231', '75691', '22246', '51061', '90578', '56691', '68014', '51103', '94167', '57047', '14867', '73520', '15734', '63435', '25733', '35474', '24676', '94627', '53535', '17879', '15559', '53268', '59166', '11928', '59402', '33282', '45721', '43933', '68101', '33515', '36634', '71286', '19736', '58058', '55253', '67473', '41918', '19515', '36495', '19430', '22351', '77191', '91393', '49156', '50298', '87501', '18652', '53179', '18767', '63193', '23968', '65164', '68880', '21286', '72823', '58470', '67301', '13394', '31016', '70372', '67030', '40604', '24317', '45748', '39127', '26065', '77721', '31029', '31880', '60576', '24671', '45549', '13376', '50016', '33123', '19769', '22927', '97789', '46081', '72151', '15723', '46136', '51949', '68100', '96888', '64528', '14171', '79777', '28709', '11489', '25103', '32213', '78668', '22245', '15798', '27156', '37930', '62971', '21337', '51622', '67853', '10567', '38415', '15455', '58263', '42029', '60279', '37125', '56240', '88190', '50308', '26859', '64457', '89091', '82136', '62377', '36233', '63837', '58078', '17043', '30010', '60099', '28810', '98025', '29178', '87343', '73273', '30469', '64034', '39516', '86057', '21309', '90257', '67875', '40162', '11356', '73650', '61810', '72013', '30431', '22461', '19512', '13375', '55307', '30625', '83849', '68908', '26689', '96451', '38193', '46820', '88885', '84935', '69035', '83144', '47537', '56616', '94983', '48033', '69952', '25486', '61547', '27385', '61860', '58048', '56910', '16807', '17871', '35258', '31387', '35458', '35576') INTERSECT SELECT ca_zip FROM ( SELECT substr(ca_zip, 1, 5) AS ca_zip, count(*) AS cnt FROM customer_address, customer WHERE (ca_address_sk = c_current_addr_sk) AND (c_preferred_cust_flag = 'Y') GROUP BY ca_zip HAVING count(*) > 10 ) AS A1 ) AS A2 ) AS V1 WHERE (ss_store_sk = s_store_sk) AND (ss_sold_date_sk = d_date_sk) AND (d_qoy = 2) AND (d_year = 1998) AND (substr(s_zip, 1, 2) = substr(V1.ca_zip, 1, 2)) GROUP BY s_store_name ORDER BY s_store_name LIMIT 100", + "SELECT multiIf(( SELECT count(*) FROM store_sales WHERE (ss_quantity >= 1) AND (ss_quantity <= 20) ) > 74129, ( SELECT avg(ss_ext_discount_amt) FROM store_sales WHERE (ss_quantity >= 1) AND (ss_quantity <= 20) ), ( SELECT avg(ss_net_paid) FROM store_sales WHERE (ss_quantity >= 1) AND (ss_quantity <= 20) )) AS bucket1, multiIf(( SELECT count(*) FROM store_sales WHERE (ss_quantity >= 21) AND (ss_quantity <= 40) ) > 122840, ( SELECT avg(ss_ext_discount_amt) FROM store_sales WHERE (ss_quantity >= 21) AND (ss_quantity <= 40) ), ( SELECT avg(ss_net_paid) FROM store_sales WHERE (ss_quantity >= 21) AND (ss_quantity <= 40) )) AS bucket2, multiIf(( SELECT count(*) FROM store_sales WHERE (ss_quantity >= 41) AND (ss_quantity <= 60) ) > 56580, ( SELECT avg(ss_ext_discount_amt) FROM store_sales WHERE (ss_quantity >= 41) AND (ss_quantity <= 60) ), ( SELECT avg(ss_net_paid) FROM store_sales WHERE (ss_quantity >= 41) AND (ss_quantity <= 60) )) AS bucket3, multiIf(( SELECT count(*) FROM store_sales WHERE (ss_quantity >= 61) AND (ss_quantity <= 80) ) > 10097, ( SELECT avg(ss_ext_discount_amt) FROM store_sales WHERE (ss_quantity >= 61) AND (ss_quantity <= 80) ), ( SELECT avg(ss_net_paid) FROM store_sales WHERE (ss_quantity >= 61) AND (ss_quantity <= 80) )) AS bucket4, multiIf(( SELECT count(*) FROM store_sales WHERE (ss_quantity >= 81) AND (ss_quantity <= 100) ) > 165306, ( SELECT avg(ss_ext_discount_amt) FROM store_sales WHERE (ss_quantity >= 81) AND (ss_quantity <= 100) ), ( SELECT avg(ss_net_paid) FROM store_sales WHERE (ss_quantity >= 81) AND (ss_quantity <= 100) )) AS bucket5 FROM reason WHERE r_reason_sk = 1", + "SELECT cd_gender, cd_marital_status, cd_education_status, count(*) AS cnt1, cd_purchase_estimate, count(*) AS cnt2, cd_credit_rating, count(*) AS cnt3, cd_dep_count, count(*) AS cnt4, cd_dep_employed_count, count(*) AS cnt5, cd_dep_college_count, count(*) AS cnt6 FROM customer AS c, customer_address AS ca, customer_demographics WHERE (c.c_current_addr_sk = ca.ca_address_sk) AND (ca_county IN ('Rush County', 'Toole County', 'Jefferson County', 'Dona Ana County', 'La Porte County')) AND (cd_demo_sk = c.c_current_cdemo_sk) AND exists(( SELECT * FROM store_sales, date_dim WHERE (c.c_customer_sk = ss_customer_sk) AND (ss_sold_date_sk = d_date_sk) AND (d_year = 2002) AND ((d_moy >= 1) AND (d_moy <= (1 + 3))) )) AND (exists(( SELECT * FROM web_sales, date_dim WHERE (c.c_customer_sk = ws_bill_customer_sk) AND (ws_sold_date_sk = d_date_sk) AND (d_year = 2002) AND ((d_moy >= 1) AND (d_moy <= (1 + 3))) )) OR exists(( SELECT * FROM catalog_sales, date_dim WHERE (c.c_customer_sk = cs_ship_customer_sk) AND (cs_sold_date_sk = d_date_sk) AND (d_year = 2002) AND ((d_moy >= 1) AND (d_moy <= (1 + 3))) ))) GROUP BY cd_gender, cd_marital_status, cd_education_status, cd_purchase_estimate, cd_credit_rating, cd_dep_count, cd_dep_employed_count, cd_dep_college_count ORDER BY cd_gender, cd_marital_status, cd_education_status, cd_purchase_estimate, cd_credit_rating, cd_dep_count, cd_dep_employed_count, cd_dep_college_count LIMIT 100", + "WITH year_total AS ( SELECT c_customer_id AS customer_id, c_first_name AS customer_first_name, c_last_name AS customer_last_name, c_preferred_cust_flag AS customer_preferred_cust_flag, c_birth_country AS customer_birth_country, c_login AS customer_login, c_email_address AS customer_email_address, d_year AS dyear, sum(ss_ext_list_price - ss_ext_discount_amt) AS year_total, 's' AS sale_type FROM customer, store_sales, date_dim WHERE (c_customer_sk = ss_customer_sk) AND (ss_sold_date_sk = d_date_sk) GROUP BY c_customer_id, c_first_name, c_last_name, c_preferred_cust_flag, c_birth_country, c_login, c_email_address, d_year UNION ALL SELECT c_customer_id AS customer_id, c_first_name AS customer_first_name, c_last_name AS customer_last_name, c_preferred_cust_flag AS customer_preferred_cust_flag, c_birth_country AS customer_birth_country, c_login AS customer_login, c_email_address AS customer_email_address, d_year AS dyear, sum(ws_ext_list_price - ws_ext_discount_amt) AS year_total, 'w' AS sale_type FROM customer, web_sales, date_dim WHERE (c_customer_sk = ws_bill_customer_sk) AND (ws_sold_date_sk = d_date_sk) GROUP BY c_customer_id, c_first_name, c_last_name, c_preferred_cust_flag, c_birth_country, c_login, c_email_address, d_year ) SELECT t_s_secyear.customer_id, t_s_secyear.customer_first_name, t_s_secyear.customer_last_name, t_s_secyear.customer_preferred_cust_flag FROM year_total AS t_s_firstyear, year_total AS t_s_secyear, year_total AS t_w_firstyear, year_total AS t_w_secyear WHERE (t_s_secyear.customer_id = t_s_firstyear.customer_id) AND (t_s_firstyear.customer_id = t_w_secyear.customer_id) AND (t_s_firstyear.customer_id = t_w_firstyear.customer_id) AND (t_s_firstyear.sale_type = 's') AND (t_w_firstyear.sale_type = 'w') AND (t_s_secyear.sale_type = 's') AND (t_w_secyear.sale_type = 'w') AND (t_s_firstyear.dyear = 2001) AND (t_s_secyear.dyear = (2001 + 1)) AND (t_w_firstyear.dyear = 2001) AND (t_w_secyear.dyear = (2001 + 1)) AND (t_s_firstyear.year_total > 0) AND (t_w_firstyear.year_total > 0) AND (multiIf(t_w_firstyear.year_total > 0, CAST(t_w_secyear.year_total AS Float32) / t_w_firstyear.year_total, 0.) > multiIf(t_s_firstyear.year_total > 0, CAST(t_s_secyear.year_total AS Float32) / t_s_firstyear.year_total, 0.)) ORDER BY t_s_secyear.customer_id, t_s_secyear.customer_first_name, t_s_secyear.customer_last_name, t_s_secyear.customer_preferred_cust_flag LIMIT 100", + "SELECT i_item_id, i_item_desc, i_category, i_class, i_current_price, sum(ws_ext_sales_price) AS itemrevenue, (sum(ws_ext_sales_price) * 100) / sum(sum(ws_ext_sales_price)) OVER (PARTITION BY i_class) AS revenueratio FROM web_sales, item, date_dim WHERE (ws_item_sk = i_item_sk) AND (i_category IN ('Sports', 'Books', 'Home')) AND (ws_sold_date_sk = d_date_sk) AND ((d_date >= CAST('1999-02-22', 'date')) AND (d_date <= (CAST('1999-02-22', 'date') + INTERVAL 30 day))) GROUP BY i_item_id, i_item_desc, i_category, i_class, i_current_price ORDER BY i_category, i_class, i_item_id, i_item_desc, revenueratio LIMIT 100", + "SELECT avg(ss_quantity), avg(ss_ext_sales_price), avg(ss_ext_wholesale_cost), sum(ss_ext_wholesale_cost) FROM store_sales, store, customer_demographics, household_demographics, customer_address, date_dim WHERE (s_store_sk = ss_store_sk) AND (ss_sold_date_sk = d_date_sk) AND (d_year = 2001) AND ( ( (ss_hdemo_sk = hd_demo_sk) AND (cd_demo_sk = ss_cdemo_sk) AND (cd_marital_status = 'M') AND (cd_education_status = 'Advanced Degree') AND (ss_sales_price BETWEEN 100.00 AND 150.00) AND (hd_dep_count = 3) ) OR ( (ss_hdemo_sk = hd_demo_sk) AND (cd_demo_sk = ss_cdemo_sk) AND (cd_marital_status = 'S') AND (cd_education_status = 'College') AND (ss_sales_price BETWEEN 50.00 AND 100.00) AND (hd_dep_count = 1) ) OR ( (ss_hdemo_sk = hd_demo_sk) AND (cd_demo_sk = ss_cdemo_sk) AND (cd_marital_status = 'W') AND (cd_education_status = '2 yr Degree') AND (ss_sales_price BETWEEN 150.00 AND 200.) AND (hd_dep_count = 1) ) ) AND ( ( (ss_addr_sk = ca_address_sk) AND (ca_country = 'United States') AND (ca_state IN ('TX', 'OH', 'TX')) AND (ss_net_profit BETWEEN 100 AND 200) ) OR ( (ss_addr_sk = ca_address_sk) AND (ca_country = 'United States') AND (ca_state IN ('OR', 'NM', 'KY')) AND (ss_net_profit BETWEEN 150 AND 300) ) OR ( (ss_addr_sk = ca_address_sk) AND (ca_country = 'United States') AND (ca_state IN ('VA', 'TX', 'MS')) AND (ss_net_profit BETWEEN 50 AND 250) ) )", + "WITH cross_items AS ( SELECT i_item_sk AS ss_item_sk FROM item, ( SELECT iss.i_brand_id AS brand_id, iss.i_class_id AS class_id, iss.i_category_id AS category_id FROM store_sales, item AS iss, date_dim AS d1 WHERE (ss_item_sk = iss.i_item_sk) AND (ss_sold_date_sk = d1.d_date_sk) AND (d1.d_year BETWEEN 1999 AND 1999 + 2) INTERSECT SELECT ics.i_brand_id, ics.i_class_id, ics.i_category_id FROM catalog_sales, item AS ics, date_dim AS d2 WHERE (cs_item_sk = ics.i_item_sk) AND (cs_sold_date_sk = d2.d_date_sk) AND (d2.d_year BETWEEN 1999 AND 1999 + 2) INTERSECT SELECT iws.i_brand_id, iws.i_class_id, iws.i_category_id FROM web_sales, item AS iws, date_dim AS d3 WHERE (ws_item_sk = iws.i_item_sk) AND (ws_sold_date_sk = d3.d_date_sk) AND (d3.d_year BETWEEN 1999 AND 1999 + 2) ) WHERE (i_brand_id = brand_id) AND (i_class_id = class_id) AND (i_category_id = category_id) ), avg_sales AS ( SELECT avg(quantity * list_price) AS average_sales FROM ( SELECT ss_quantity AS quantity, ss_list_price AS list_price FROM store_sales, date_dim WHERE (ss_sold_date_sk = d_date_sk) AND (d_year BETWEEN 1999 AND 1999 + 2) UNION ALL SELECT cs_quantity AS quantity, cs_list_price AS list_price FROM catalog_sales, date_dim WHERE (cs_sold_date_sk = d_date_sk) AND (d_year BETWEEN 1999 AND 1999 + 2) UNION ALL SELECT ws_quantity AS quantity, ws_list_price AS list_price FROM web_sales, date_dim WHERE (ws_sold_date_sk = d_date_sk) AND (d_year BETWEEN 1999 AND 1999 + 2) ) AS x ) SELECT channel, i_brand_id, i_class_id, i_category_id, sum(sales), sum(number_sales) FROM ( SELECT 'store' AS channel, i_brand_id, i_class_id, i_category_id, sum(ss_quantity * ss_list_price) AS sales, count(*) AS number_sales FROM store_sales, item, date_dim WHERE (ss_item_sk IN ( SELECT ss_item_sk FROM cross_items )) AND (ss_item_sk = i_item_sk) AND (ss_sold_date_sk = d_date_sk) AND (d_year = (1999 + 2)) AND (d_moy = 11) GROUP BY i_brand_id, i_class_id, i_category_id HAVING sum(ss_quantity * ss_list_price) > ( SELECT average_sales FROM avg_sales ) UNION ALL SELECT 'catalog' AS channel, i_brand_id, i_class_id, i_category_id, sum(cs_quantity * cs_list_price) AS sales, count(*) AS number_sales FROM catalog_sales, item, date_dim WHERE (cs_item_sk IN ( SELECT ss_item_sk FROM cross_items )) AND (cs_item_sk = i_item_sk) AND (cs_sold_date_sk = d_date_sk) AND (d_year = (1999 + 2)) AND (d_moy = 11) GROUP BY i_brand_id, i_class_id, i_category_id HAVING sum(cs_quantity * cs_list_price) > ( SELECT average_sales FROM avg_sales ) UNION ALL SELECT 'web' AS channel, i_brand_id, i_class_id, i_category_id, sum(ws_quantity * ws_list_price) AS sales, count(*) AS number_sales FROM web_sales, item, date_dim WHERE (ws_item_sk IN ( SELECT ss_item_sk FROM cross_items )) AND (ws_item_sk = i_item_sk) AND (ws_sold_date_sk = d_date_sk) AND (d_year = (1999 + 2)) AND (d_moy = 11) GROUP BY i_brand_id, i_class_id, i_category_id HAVING sum(ws_quantity * ws_list_price) > ( SELECT average_sales FROM avg_sales ) ) AS y GROUP BY channel, i_brand_id, i_class_id, i_category_id WITH ROLLUP ORDER BY channel, i_brand_id, i_class_id, i_category_id LIMIT 100", + "WITH cross_items AS ( SELECT i_item_sk AS ss_item_sk FROM item, ( SELECT iss.i_brand_id AS brand_id, iss.i_class_id AS class_id, iss.i_category_id AS category_id FROM store_sales, item AS iss, date_dim AS d1 WHERE (ss_item_sk = iss.i_item_sk) AND (ss_sold_date_sk = d1.d_date_sk) AND (d1.d_year BETWEEN 1999 AND 1999 + 2) INTERSECT SELECT ics.i_brand_id, ics.i_class_id, ics.i_category_id FROM catalog_sales, item AS ics, date_dim AS d2 WHERE (cs_item_sk = ics.i_item_sk) AND (cs_sold_date_sk = d2.d_date_sk) AND (d2.d_year BETWEEN 1999 AND 1999 + 2) INTERSECT SELECT iws.i_brand_id, iws.i_class_id, iws.i_category_id FROM web_sales, item AS iws, date_dim AS d3 WHERE (ws_item_sk = iws.i_item_sk) AND (ws_sold_date_sk = d3.d_date_sk) AND (d3.d_year BETWEEN 1999 AND 1999 + 2) ) WHERE (i_brand_id = brand_id) AND (i_class_id = class_id) AND (i_category_id = category_id) ), avg_sales AS ( SELECT avg(quantity * list_price) AS average_sales FROM ( SELECT ss_quantity AS quantity, ss_list_price AS list_price FROM store_sales, date_dim WHERE (ss_sold_date_sk = d_date_sk) AND (d_year BETWEEN 1999 AND 1999 + 2) UNION ALL SELECT cs_quantity AS quantity, cs_list_price AS list_price FROM catalog_sales, date_dim WHERE (cs_sold_date_sk = d_date_sk) AND (d_year BETWEEN 1999 AND 1999 + 2) UNION ALL SELECT ws_quantity AS quantity, ws_list_price AS list_price FROM web_sales, date_dim WHERE (ws_sold_date_sk = d_date_sk) AND (d_year BETWEEN 1999 AND 1999 + 2) ) AS x ) SELECT this_year.channel AS ty_channel, this_year.i_brand_id AS ty_brand, this_year.i_class_id AS ty_class, this_year.i_category_id AS ty_category, this_year.sales AS ty_sales, this_year.number_sales AS ty_number_sales, last_year.channel AS ly_channel, last_year.i_brand_id AS ly_brand, last_year.i_class_id AS ly_class, last_year.i_category_id AS ly_category, last_year.sales AS ly_sales, last_year.number_sales AS ly_number_sales FROM ( SELECT 'store' AS channel, i_brand_id, i_class_id, i_category_id, sum(ss_quantity * ss_list_price) AS sales, count(*) AS number_sales FROM store_sales, item, date_dim WHERE (ss_item_sk IN ( SELECT ss_item_sk FROM cross_items )) AND (ss_item_sk = i_item_sk) AND (ss_sold_date_sk = d_date_sk) AND (d_week_seq = ( SELECT d_week_seq FROM date_dim WHERE (d_year = 1999 + 1) AND (d_moy = 12) AND (d_dom = 11) )) GROUP BY i_brand_id, i_class_id, i_category_id HAVING sum(ss_quantity * ss_list_price) > ( SELECT average_sales FROM avg_sales ) ) AS this_year, ( SELECT 'store' AS channel, i_brand_id, i_class_id, i_category_id, sum(ss_quantity * ss_list_price) AS sales, count(*) AS number_sales FROM store_sales, item, date_dim WHERE (ss_item_sk IN ( SELECT ss_item_sk FROM cross_items )) AND (ss_item_sk = i_item_sk) AND (ss_sold_date_sk = d_date_sk) AND (d_week_seq = ( SELECT d_week_seq FROM date_dim WHERE (d_year = 1999) AND (d_moy = 12) AND (d_dom = 11) )) GROUP BY i_brand_id, i_class_id, i_category_id HAVING sum(ss_quantity * ss_list_price) > ( SELECT average_sales FROM avg_sales ) ) AS last_year WHERE (this_year.i_brand_id = last_year.i_brand_id) AND (this_year.i_class_id = last_year.i_class_id) AND (this_year.i_category_id = last_year.i_category_id) ORDER BY this_year.channel, this_year.i_brand_id, this_year.i_class_id, this_year.i_category_id LIMIT 100", + "SELECT ca_zip, sum(cs_sales_price) FROM catalog_sales, customer, customer_address, date_dim WHERE (cs_bill_customer_sk = c_customer_sk) AND (c_current_addr_sk = ca_address_sk) AND ((substr(ca_zip, 1, 5) IN ('85669', '86197', '88274', '83405', '86475', '85392', '85460', '80348', '81792')) OR (ca_state IN ('CA', 'WA', 'GA')) OR (cs_sales_price > 500)) AND (cs_sold_date_sk = d_date_sk) AND (d_qoy = 2) AND (d_year = 2001) GROUP BY ca_zip ORDER BY ca_zip LIMIT 100", + "SELECT count(DISTINCT cs_order_number) AS \"order count\", sum(cs_ext_ship_cost) AS \"total shipping cost\", sum(cs_net_profit) AS \"total net profit\" FROM catalog_sales AS cs1, date_dim, customer_address, call_center WHERE (d_date BETWEEN '2002-2-01' AND (CAST('2002-2-01' AS date) + INTERVAL 60 DAY)) AND (cs1.cs_ship_date_sk = d_date_sk) AND (cs1.cs_ship_addr_sk = ca_address_sk) AND (ca_state = 'GA') AND (cs1.cs_call_center_sk = cc_call_center_sk) AND (cc_county IN ('Williamson County', 'Williamson County', 'Williamson County', 'Williamson County', 'Williamson County')) AND EXISTS ( SELECT * FROM catalog_sales AS cs2 WHERE (cs1.cs_order_number = cs2.cs_order_number) AND (cs1.cs_warehouse_sk <> cs2.cs_warehouse_sk) ) AND NOT EXISTS ( SELECT * FROM catalog_returns AS cr1 WHERE (cs1.cs_order_number = cr1.cr_order_number) ) ORDER BY count(DISTINCT cs_order_number) LIMIT 100", + "SELECT i_item_id, i_item_desc, s_state, count(ss_quantity) AS store_sales_quantitycount, avg(ss_quantity) AS store_sales_quantityave, stddev_samp(ss_quantity) AS store_sales_quantitystdev, stddev_samp(ss_quantity) / avg(ss_quantity) AS store_sales_quantitycov, count(sr_return_quantity) AS store_returns_quantitycount, avg(sr_return_quantity) AS store_returns_quantityave, stddev_samp(sr_return_quantity) AS store_returns_quantitystdev, stddev_samp(sr_return_quantity) / avg(sr_return_quantity) AS store_returns_quantitycov, count(cs_quantity) AS catalog_sales_quantitycount, avg(cs_quantity) AS catalog_sales_quantityave, stddev_samp(cs_quantity) AS catalog_sales_quantitystdev, stddev_samp(cs_quantity) / avg(cs_quantity) AS catalog_sales_quantitycov FROM store_sales, store_returns, catalog_sales, date_dim AS d1, date_dim AS d2, date_dim AS d3, store, item WHERE (d1.d_quarter_name = '2001Q1') AND (d1.d_date_sk = ss_sold_date_sk) AND (i_item_sk = ss_item_sk) AND (s_store_sk = ss_store_sk) AND (ss_customer_sk = sr_customer_sk) AND (ss_item_sk = sr_item_sk) AND (ss_ticket_number = sr_ticket_number) AND (sr_returned_date_sk = d2.d_date_sk) AND (d2.d_quarter_name IN ('2001Q1', '2001Q2', '2001Q3')) AND (sr_customer_sk = cs_bill_customer_sk) AND (sr_item_sk = cs_item_sk) AND (cs_sold_date_sk = d3.d_date_sk) AND (d3.d_quarter_name IN ('2001Q1', '2001Q2', '2001Q3')) GROUP BY i_item_id, i_item_desc, s_state ORDER BY i_item_id, i_item_desc, s_state LIMIT 100", + "SELECT i_item_id, ca_country, ca_state, ca_county, avg(CAST(cs_quantity AS Nullable(decimal(12, 2)))) AS agg1, avg(CAST(cs_list_price AS Nullable(decimal(12, 2)))) AS agg2, avg(CAST(cs_coupon_amt AS Nullable(decimal(12, 2)))) AS agg3, avg(CAST(cs_sales_price AS Nullable(decimal(12, 2)))) AS agg4, avg(CAST(cs_net_profit AS Nullable(decimal(12, 2)))) AS agg5, avg(CAST(c_birth_year AS Nullable(decimal(12, 2)))) AS agg6, avg(CAST(cd1.cd_dep_count AS Nullable(decimal(12, 2)))) AS agg7 FROM catalog_sales, customer_demographics AS cd1, customer_demographics AS cd2, customer, customer_address, date_dim, item WHERE (cs_sold_date_sk = d_date_sk) AND (cs_item_sk = i_item_sk) AND (cs_bill_cdemo_sk = cd1.cd_demo_sk) AND (cs_bill_customer_sk = c_customer_sk) AND (cd1.cd_gender = 'F') AND (cd1.cd_education_status = 'Unknown') AND (c_current_cdemo_sk = cd2.cd_demo_sk) AND (c_current_addr_sk = ca_address_sk) AND (c_birth_month IN (1, 6, 8, 9, 12, 2)) AND (d_year = 1998) AND (ca_state IN ('MS', 'IN', 'ND', 'OK', 'NM', 'VA', 'MS')) GROUP BY ROLLUP (i_item_id, ca_country, ca_state, ca_county) ORDER BY ca_country, ca_state, ca_county, i_item_id LIMIT 100", + "SELECT i_brand_id AS brand_id, i_brand AS brand, i_manufact_id, i_manufact, sum(ss_ext_sales_price) AS ext_price FROM date_dim, store_sales, item, customer, customer_address, store WHERE (d_date_sk = ss_sold_date_sk) AND (ss_item_sk = i_item_sk) AND (i_manager_id = 8) AND (d_moy = 11) AND (d_year = 1998) AND (ss_customer_sk = c_customer_sk) AND (c_current_addr_sk = ca_address_sk) AND (substr(ca_zip, 1, 5) <> substr(s_zip, 1, 5)) AND (ss_store_sk = s_store_sk) GROUP BY i_brand, i_brand_id, i_manufact_id, i_manufact ORDER BY ext_price DESC, i_brand, i_brand_id, i_manufact_id, i_manufact LIMIT 100", + "SELECT i_item_id, i_item_desc, i_category, i_class, i_current_price, sum(cs_ext_sales_price) AS itemrevenue, sum(cs_ext_sales_price) * 100 / sum(sum(cs_ext_sales_price)) OVER (PARTITION BY i_class) AS revenueratio FROM catalog_sales, item, date_dim WHERE (cs_item_sk = i_item_sk) AND (i_category IN ('Sports', 'Books', 'Home')) AND (cs_sold_date_sk = d_date_sk) AND (d_date BETWEEN CAST('1999-02-22' AS date) AND (CAST('1999-02-22' AS date) + INTERVAL 30 DAY)) GROUP BY i_item_id, i_item_desc, i_category, i_class, i_current_price ORDER BY i_category, i_class, i_item_id, i_item_desc, revenueratio LIMIT 100", + "SELECT * FROM ( SELECT w_warehouse_name, i_item_id, sum(CASE WHEN (CAST(d_date AS date) < CAST('2000-03-11' AS date)) THEN inv_quantity_on_hand ELSE 0 END) AS inv_before, sum(CASE WHEN (CAST(d_date AS date) >= CAST('2000-03-11' AS date)) THEN inv_quantity_on_hand ELSE 0 END) AS inv_after FROM inventory, warehouse, item, date_dim WHERE (i_current_price BETWEEN 0.99 AND 1.49) AND (i_item_sk = inv_item_sk) AND (inv_warehouse_sk = w_warehouse_sk) AND (inv_date_sk = d_date_sk) AND (d_date BETWEEN (CAST('2000-03-11' AS date) - INTERVAL 30 DAY) AND (CAST('2000-03-11' AS date) + INTERVAL 30 DAY)) GROUP BY w_warehouse_name, i_item_id ) AS x WHERE (CASE WHEN inv_before > 0 THEN inv_after / inv_before ELSE NULL END) BETWEEN 2.0 / 3.0 AND 3.0 / 2.0 ORDER BY w_warehouse_name, i_item_id LIMIT 100", + "SELECT i_product_name, i_brand, i_class, i_category, avg(inv_quantity_on_hand) AS qoh FROM inventory, date_dim, item WHERE (inv_date_sk = d_date_sk) AND (inv_item_sk = i_item_sk) AND (d_month_seq BETWEEN 1200 AND 1200 + 11) GROUP BY ROLLUP(i_product_name, i_brand, i_class, i_category) ORDER BY qoh, i_product_name, i_brand, i_class, i_category LIMIT 100", + "WITH frequent_ss_items AS ( SELECT substr(i_item_desc, 1, 30) AS itemdesc, i_item_sk AS item_sk, d_date AS solddate, count(*) AS cnt FROM store_sales, date_dim, item WHERE (ss_sold_date_sk = d_date_sk) AND (ss_item_sk = i_item_sk) AND (d_year IN (2000, 2000 + 1, 2000 + 2, 2000 + 3)) GROUP BY substr(i_item_desc, 1, 30), i_item_sk, d_date HAVING count(*) > 4 ), max_store_sales AS ( SELECT max(csales) AS tpcds_cmax FROM ( SELECT c_customer_sk, sum(ss_quantity * ss_sales_price) AS csales FROM store_sales, customer, date_dim WHERE (ss_customer_sk = c_customer_sk) AND (ss_sold_date_sk = d_date_sk) AND (d_year IN (2000, 2000 + 1, 2000 + 2, 2000 + 3)) GROUP BY c_customer_sk ) ), best_ss_customer AS ( SELECT c_customer_sk, sum(ss_quantity * ss_sales_price) AS ssales FROM store_sales, customer WHERE (ss_customer_sk = c_customer_sk) GROUP BY c_customer_sk HAVING sum(ss_quantity * ss_sales_price) > (50 / 100.0) * ( SELECT * FROM max_store_sales ) ) SELECT sum(sales) FROM ( SELECT cs_quantity * cs_list_price AS sales FROM catalog_sales, date_dim WHERE (d_year = 2000) AND (d_moy = 2) AND (cs_sold_date_sk = d_date_sk) AND (cs_item_sk IN (SELECT item_sk FROM frequent_ss_items)) AND (cs_bill_customer_sk IN (SELECT c_customer_sk FROM best_ss_customer)) UNION ALL SELECT ws_quantity * ws_list_price AS sales FROM web_sales, date_dim WHERE (d_year = 2000) AND (d_moy = 2) AND (ws_sold_date_sk = d_date_sk) AND (ws_item_sk IN (SELECT item_sk FROM frequent_ss_items)) AND (ws_bill_customer_sk IN (SELECT c_customer_sk FROM best_ss_customer)) ) LIMIT 100", + "WITH frequent_ss_items AS ( SELECT substr(i_item_desc, 1, 30) AS itemdesc, i_item_sk AS item_sk, d_date AS solddate, count(*) AS cnt FROM store_sales, date_dim, item WHERE (ss_sold_date_sk = d_date_sk) AND (ss_item_sk = i_item_sk) AND (d_year IN (2000, 2000 + 1, 2000 + 2, 2000 + 3)) GROUP BY substr(i_item_desc, 1, 30), i_item_sk, d_date HAVING count(*) > 4 ), max_store_sales AS ( SELECT max(csales) AS tpcds_cmax FROM ( SELECT c_customer_sk, sum(ss_quantity * ss_sales_price) AS csales FROM store_sales, customer, date_dim WHERE (ss_customer_sk = c_customer_sk) AND (ss_sold_date_sk = d_date_sk) AND (d_year IN (2000, 2000 + 1, 2000 + 2, 2000 + 3)) GROUP BY c_customer_sk ) ), best_ss_customer AS ( SELECT c_customer_sk, sum(ss_quantity * ss_sales_price) AS ssales FROM store_sales, customer WHERE (ss_customer_sk = c_customer_sk) GROUP BY c_customer_sk HAVING sum(ss_quantity * ss_sales_price) > (50 / 100.0) * ( SELECT * FROM max_store_sales ) ) SELECT c_last_name, c_first_name, sales FROM ( SELECT c_last_name, c_first_name, sum(cs_quantity * cs_list_price) AS sales FROM catalog_sales, customer, date_dim WHERE (d_year = 2000) AND (d_moy = 2) AND (cs_sold_date_sk = d_date_sk) AND (cs_item_sk IN (SELECT item_sk FROM frequent_ss_items)) AND (cs_bill_customer_sk IN (SELECT c_customer_sk FROM best_ss_customer)) AND (cs_bill_customer_sk = c_customer_sk) GROUP BY c_last_name, c_first_name UNION ALL SELECT c_last_name, c_first_name, sum(ws_quantity * ws_list_price) AS sales FROM web_sales, customer, date_dim WHERE (d_year = 2000) AND (d_moy = 2) AND (ws_sold_date_sk = d_date_sk) AND (ws_item_sk IN (SELECT item_sk FROM frequent_ss_items)) AND (ws_bill_customer_sk IN (SELECT c_customer_sk FROM best_ss_customer)) AND (ws_bill_customer_sk = c_customer_sk) GROUP BY c_last_name, c_first_name ) ORDER BY c_last_name, c_first_name, sales LIMIT 100", + "WITH ssales AS ( SELECT c_last_name, c_first_name, s_store_name, ca_state, s_state, i_color, i_current_price, i_manager_id, i_units, i_size, sum(ss_net_paid) AS netpaid FROM store_sales, store_returns, store, item, customer, customer_address WHERE (ss_ticket_number = sr_ticket_number) AND (ss_item_sk = sr_item_sk) AND (ss_customer_sk = c_customer_sk) AND (ss_item_sk = i_item_sk) AND (ss_store_sk = s_store_sk) AND (c_current_addr_sk = ca_address_sk) AND (c_birth_country <> upper(ca_country)) AND (s_zip = ca_zip) AND (s_market_id = 8) GROUP BY c_last_name, c_first_name, s_store_name, ca_state, s_state, i_color, i_current_price, i_manager_id, i_units, i_size ) SELECT c_last_name, c_first_name, s_store_name, sum(netpaid) AS paid FROM ssales WHERE (i_color = 'peach') GROUP BY c_last_name, c_first_name, s_store_name HAVING sum(netpaid) > ( SELECT 0.05 * avg(netpaid) FROM ssales ) ORDER BY c_last_name, c_first_name, s_store_name", + "WITH ssales AS ( SELECT c_last_name, c_first_name, s_store_name, ca_state, s_state, i_color, i_current_price, i_manager_id, i_units, i_size, sum(ss_net_paid) AS netpaid FROM store_sales, store_returns, store, item, customer, customer_address WHERE (ss_ticket_number = sr_ticket_number) AND (ss_item_sk = sr_item_sk) AND (ss_customer_sk = c_customer_sk) AND (ss_item_sk = i_item_sk) AND (ss_store_sk = s_store_sk) AND (c_current_addr_sk = ca_address_sk) AND (c_birth_country <> upper(ca_country)) AND (s_zip = ca_zip) AND (s_market_id = 8) GROUP BY c_last_name, c_first_name, s_store_name, ca_state, s_state, i_color, i_current_price, i_manager_id, i_units, i_size ) SELECT c_last_name, c_first_name, s_store_name, sum(netpaid) AS paid FROM ssales WHERE (i_color = 'saddle') GROUP BY c_last_name, c_first_name, s_store_name HAVING sum(netpaid) > ( SELECT 0.05 * avg(netpaid) FROM ssales ) ORDER BY c_last_name, c_first_name, s_store_name", + "SELECT i_item_id, i_item_desc, s_store_id, s_store_name, sum(ss_net_profit) AS store_sales_profit, sum(sr_net_loss) AS store_returns_loss, sum(cs_net_profit) AS catalog_sales_profit FROM store_sales, store_returns, catalog_sales, date_dim AS d1, date_dim AS d2, date_dim AS d3, store, item WHERE (d1.d_moy = 4) AND (d1.d_year = 2001) AND (d1.d_date_sk = ss_sold_date_sk) AND (i_item_sk = ss_item_sk) AND (s_store_sk = ss_store_sk) AND (ss_customer_sk = sr_customer_sk) AND (ss_item_sk = sr_item_sk) AND (ss_ticket_number = sr_ticket_number) AND (sr_returned_date_sk = d2.d_date_sk) AND (d2.d_moy BETWEEN 4 AND 10) AND (d2.d_year = 2001) AND (sr_customer_sk = cs_bill_customer_sk) AND (sr_item_sk = cs_item_sk) AND (cs_sold_date_sk = d3.d_date_sk) AND (d3.d_moy BETWEEN 4 AND 10) AND (d3.d_year = 2001) GROUP BY i_item_id, i_item_desc, s_store_id, s_store_name ORDER BY i_item_id, i_item_desc, s_store_id, s_store_name LIMIT 100", + "SELECT i_item_id, avg(cs_quantity) AS agg1, avg(cs_list_price) AS agg2, avg(cs_coupon_amt) AS agg3, avg(cs_sales_price) AS agg4 FROM catalog_sales, customer_demographics, date_dim, item, promotion WHERE (cs_sold_date_sk = d_date_sk) AND (cs_item_sk = i_item_sk) AND (cs_bill_cdemo_sk = cd_demo_sk) AND (cs_promo_sk = p_promo_sk) AND (cd_gender = 'M') AND (cd_marital_status = 'S') AND (cd_education_status = 'College') AND ((p_channel_email = 'N') OR (p_channel_event = 'N')) AND (d_year = 2000) GROUP BY i_item_id ORDER BY i_item_id LIMIT 100", + "SELECT i_item_id, s_state, grouping(s_state) AS g_state, avg(ss_quantity) AS agg1, avg(ss_list_price) AS agg2, avg(ss_coupon_amt) AS agg3, avg(ss_sales_price) AS agg4 FROM store_sales, customer_demographics, date_dim, store, item WHERE (ss_sold_date_sk = d_date_sk) AND (ss_item_sk = i_item_sk) AND (ss_store_sk = s_store_sk) AND (ss_cdemo_sk = cd_demo_sk) AND (cd_gender = 'M') AND (cd_marital_status = 'S') AND (cd_education_status = 'College') AND (d_year = 2002) AND (s_state IN ('TN', 'TN', 'TN', 'TN', 'TN', 'TN')) GROUP BY ROLLUP(i_item_id, s_state) ORDER BY i_item_id, s_state LIMIT 100", + "SELECT * FROM ( SELECT avg(ss_list_price) AS B1_LP, count(ss_list_price) AS B1_CNT, count(DISTINCT ss_list_price) AS B1_CNTD FROM store_sales WHERE (ss_quantity BETWEEN 0 AND 5) AND ((ss_list_price BETWEEN 8 AND 8 + 10) OR (ss_coupon_amt BETWEEN 459 AND 459 + 1000) OR (ss_wholesale_cost BETWEEN 57 AND 57 + 20)) ) AS B1, ( SELECT avg(ss_list_price) AS B2_LP, count(ss_list_price) AS B2_CNT, count(DISTINCT ss_list_price) AS B2_CNTD FROM store_sales WHERE (ss_quantity BETWEEN 6 AND 10) AND ((ss_list_price BETWEEN 90 AND 90 + 10) OR (ss_coupon_amt BETWEEN 2323 AND 2323 + 1000) OR (ss_wholesale_cost BETWEEN 31 AND 31 + 20)) ) AS B2, ( SELECT avg(ss_list_price) AS B3_LP, count(ss_list_price) AS B3_CNT, count(DISTINCT ss_list_price) AS B3_CNTD FROM store_sales WHERE (ss_quantity BETWEEN 11 AND 15) AND ((ss_list_price BETWEEN 142 AND 142 + 10) OR (ss_coupon_amt BETWEEN 12214 AND 12214 + 1000) OR (ss_wholesale_cost BETWEEN 79 AND 79 + 20)) ) AS B3, ( SELECT avg(ss_list_price) AS B4_LP, count(ss_list_price) AS B4_CNT, count(DISTINCT ss_list_price) AS B4_CNTD FROM store_sales WHERE (ss_quantity BETWEEN 16 AND 20) AND ((ss_list_price BETWEEN 135 AND 135 + 10) OR (ss_coupon_amt BETWEEN 6071 AND 6071 + 1000) OR (ss_wholesale_cost BETWEEN 38 AND 38 + 20)) ) AS B4, ( SELECT avg(ss_list_price) AS B5_LP, count(ss_list_price) AS B5_CNT, count(DISTINCT ss_list_price) AS B5_CNTD FROM store_sales WHERE (ss_quantity BETWEEN 21 AND 25) AND ((ss_list_price BETWEEN 122 AND 122 + 10) OR (ss_coupon_amt BETWEEN 836 AND 836 + 1000) OR (ss_wholesale_cost BETWEEN 17 AND 17 + 20)) ) AS B5, ( SELECT avg(ss_list_price) AS B6_LP, count(ss_list_price) AS B6_CNT, count(DISTINCT ss_list_price) AS B6_CNTD FROM store_sales WHERE (ss_quantity BETWEEN 26 AND 30) AND ((ss_list_price BETWEEN 154 AND 154 + 10) OR (ss_coupon_amt BETWEEN 7326 AND 7326 + 1000) OR (ss_wholesale_cost BETWEEN 7 AND 7 + 20)) ) AS B6 LIMIT 100", + "SELECT i_item_id, i_item_desc, s_store_id, s_store_name, sum(ss_quantity) AS store_sales_quantity, sum(sr_return_quantity) AS store_returns_quantity, sum(cs_quantity) AS catalog_sales_quantity FROM store_sales, store_returns, catalog_sales, date_dim AS d1, date_dim AS d2, date_dim AS d3, store, item WHERE (d1.d_moy = 9) AND (d1.d_year = 1999) AND (d1.d_date_sk = ss_sold_date_sk) AND (i_item_sk = ss_item_sk) AND (s_store_sk = ss_store_sk) AND (ss_customer_sk = sr_customer_sk) AND (ss_item_sk = sr_item_sk) AND (ss_ticket_number = sr_ticket_number) AND (sr_returned_date_sk = d2.d_date_sk) AND (d2.d_moy BETWEEN 9 AND 9 + 3) AND (d2.d_year = 1999) AND (sr_customer_sk = cs_bill_customer_sk) AND (sr_item_sk = cs_item_sk) AND (cs_sold_date_sk = d3.d_date_sk) AND (d3.d_year IN (1999, 1999 + 1, 1999 + 2)) GROUP BY i_item_id, i_item_desc, s_store_id, s_store_name ORDER BY i_item_id, i_item_desc, s_store_id, s_store_name LIMIT 100", + "WITH customer_total_return AS ( SELECT wr_returning_customer_sk AS ctr_customer_sk, ca_state AS ctr_state, sum(wr_return_amt) AS ctr_total_return FROM web_returns, date_dim, customer_address WHERE (wr_returned_date_sk = d_date_sk) AND (d_year = 2002) AND (wr_returning_addr_sk = ca_address_sk) GROUP BY wr_returning_customer_sk, ca_state ) SELECT c_customer_id, c_salutation, c_first_name, c_last_name, c_preferred_cust_flag, c_birth_day, c_birth_month, c_birth_year, c_birth_country, c_login, c_email_address, c_last_review_date_sk, ctr_total_return FROM customer_total_return AS ctr1, customer_address, customer WHERE (ctr1.ctr_total_return > ( SELECT avg(ctr_total_return) * 1.2 FROM customer_total_return AS ctr2 WHERE (ctr1.ctr_state = ctr2.ctr_state) )) AND (ca_address_sk = c_current_addr_sk) AND (ca_state = 'GA') AND (ctr1.ctr_customer_sk = c_customer_sk) ORDER BY c_customer_id, c_salutation, c_first_name, c_last_name, c_preferred_cust_flag, c_birth_day, c_birth_month, c_birth_year, c_birth_country, c_login, c_email_address, c_last_review_date_sk, ctr_total_return LIMIT 100", + "WITH ss AS ( SELECT ca_county, d_qoy, d_year, sum(ss_ext_sales_price) AS store_sales FROM store_sales, date_dim, customer_address WHERE (ss_sold_date_sk = d_date_sk) AND (ss_addr_sk = ca_address_sk) GROUP BY ca_county, d_qoy, d_year ), ws AS ( SELECT ca_county, d_qoy, d_year, sum(ws_ext_sales_price) AS web_sales FROM web_sales, date_dim, customer_address WHERE (ws_sold_date_sk = d_date_sk) AND (ws_bill_addr_sk = ca_address_sk) GROUP BY ca_county, d_qoy, d_year ) SELECT ss1.ca_county, ss1.d_year, CAST(ws2.web_sales AS Float64) / ws1.web_sales AS web_q1_q2_increase, CAST(ss2.store_sales AS Float64) / ss1.store_sales AS store_q1_q2_increase, CAST(ws3.web_sales AS Float64) / ws2.web_sales AS web_q2_q3_increase, CAST(ss3.store_sales AS Float64) / ss2.store_sales AS store_q2_q3_increase FROM ss AS ss1, ss AS ss2, ss AS ss3, ws AS ws1, ws AS ws2, ws AS ws3 WHERE (ss1.d_qoy = 1) AND (ss1.d_year = 2000) AND (ss1.ca_county = ss2.ca_county) AND (ss2.d_qoy = 2) AND (ss2.d_year = 2000) AND (ss2.ca_county = ss3.ca_county) AND (ss3.d_qoy = 3) AND (ss3.d_year = 2000) AND (ss1.ca_county = ws1.ca_county) AND (ws1.d_qoy = 1) AND (ws1.d_year = 2000) AND (ws1.ca_county = ws2.ca_county) AND (ws2.d_qoy = 2) AND (ws2.d_year = 2000) AND (ws1.ca_county = ws3.ca_county) AND (ws3.d_qoy = 3) AND (ws3.d_year = 2000) AND (CASE WHEN ws1.web_sales > 0 THEN CAST(ws2.web_sales AS Float64) / ws1.web_sales ELSE NULL END > CASE WHEN ss1.store_sales > 0 THEN CAST(ss2.store_sales AS Float64) / ss1.store_sales ELSE NULL END) AND (CASE WHEN ws2.web_sales > 0 THEN CAST(ws3.web_sales AS Float64) / ws2.web_sales ELSE NULL END > CASE WHEN ss2.store_sales > 0 THEN CAST(ss3.store_sales AS Float64) / ss2.store_sales ELSE NULL END) ORDER BY ss1.ca_county", + "SELECT sum(cs_ext_discount_amt) AS \"excess discount amount\" FROM catalog_sales, item, date_dim WHERE (i_manufact_id = 977) AND (i_item_sk = cs_item_sk) AND (d_date BETWEEN '2000-01-27' AND (CAST('2000-01-27' AS date) + INTERVAL 90 DAY)) AND (d_date_sk = cs_sold_date_sk) AND (cs_ext_discount_amt > ( SELECT 1.3 * avg(cs_ext_discount_amt) FROM catalog_sales, date_dim WHERE (cs_item_sk = i_item_sk) AND (d_date BETWEEN '2000-01-27' AND (CAST('2000-01-27' AS date) + INTERVAL 90 DAY)) AND (d_date_sk = cs_sold_date_sk) )) LIMIT 100", + "WITH ss AS ( SELECT i_manufact_id, sum(ss_ext_sales_price) AS total_sales FROM store_sales, date_dim, customer_address, item WHERE (i_manufact_id IN ( SELECT i_manufact_id FROM item WHERE (i_category IN ('Electronics')) )) AND (ss_item_sk = i_item_sk) AND (ss_sold_date_sk = d_date_sk) AND (d_year = 1998) AND (d_moy = 5) AND (ss_addr_sk = ca_address_sk) AND (ca_gmt_offset = -5) GROUP BY i_manufact_id ), cs AS ( SELECT i_manufact_id, sum(cs_ext_sales_price) AS total_sales FROM catalog_sales, date_dim, customer_address, item WHERE (i_manufact_id IN ( SELECT i_manufact_id FROM item WHERE (i_category IN ('Electronics')) )) AND (cs_item_sk = i_item_sk) AND (cs_sold_date_sk = d_date_sk) AND (d_year = 1998) AND (d_moy = 5) AND (cs_bill_addr_sk = ca_address_sk) AND (ca_gmt_offset = -5) GROUP BY i_manufact_id ), ws AS ( SELECT i_manufact_id, sum(ws_ext_sales_price) AS total_sales FROM web_sales, date_dim, customer_address, item WHERE (i_manufact_id IN ( SELECT i_manufact_id FROM item WHERE (i_category IN ('Electronics')) )) AND (ws_item_sk = i_item_sk) AND (ws_sold_date_sk = d_date_sk) AND (d_year = 1998) AND (d_moy = 5) AND (ws_bill_addr_sk = ca_address_sk) AND (ca_gmt_offset = -5) GROUP BY i_manufact_id ) SELECT i_manufact_id, sum(total_sales) AS total_sales FROM ( SELECT * FROM ss UNION ALL SELECT * FROM cs UNION ALL SELECT * FROM ws ) AS tmp1 GROUP BY i_manufact_id ORDER BY total_sales LIMIT 100", + "SELECT c_last_name, c_first_name, c_salutation, c_preferred_cust_flag, ss_ticket_number, cnt FROM ( SELECT ss_ticket_number, ss_customer_sk, count(*) AS cnt FROM store_sales, date_dim, store, household_demographics WHERE (store_sales.ss_sold_date_sk = date_dim.d_date_sk) AND (store_sales.ss_store_sk = store.s_store_sk) AND (store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk) AND ((date_dim.d_dom BETWEEN 1 AND 3) OR (date_dim.d_dom BETWEEN 25 AND 28)) AND ((household_demographics.hd_buy_potential = '>10000') OR (household_demographics.hd_buy_potential = 'Unknown')) AND (household_demographics.hd_vehicle_count > 0) AND ((CASE WHEN household_demographics.hd_vehicle_count > 0 THEN (household_demographics.hd_dep_count) / household_demographics.hd_vehicle_count ELSE NULL END) > 1.2) AND (date_dim.d_year IN (1999, 1999 + 1, 1999 + 2)) AND (store.s_county IN ('Williamson County', 'Williamson County', 'Williamson County', 'Williamson County', 'Williamson County', 'Williamson County', 'Williamson County', 'Williamson County')) GROUP BY ss_ticket_number, ss_customer_sk ) AS dn, customer WHERE (ss_customer_sk = c_customer_sk) AND (cnt BETWEEN 15 AND 20) ORDER BY c_last_name, c_first_name, c_salutation, c_preferred_cust_flag DESC, ss_ticket_number", + "SELECT ca_state, cd_gender, cd_marital_status, cd_dep_count, count(*) AS cnt1, avg(cd_dep_count), min(cd_dep_count), min(cd_dep_count), cd_dep_employed_count, count(*) AS cnt2, avg(cd_dep_employed_count), min(cd_dep_employed_count), min(cd_dep_employed_count), cd_dep_college_count, count(*) AS cnt3, avg(cd_dep_college_count), min(cd_dep_college_count), min(cd_dep_college_count) FROM customer AS c, customer_address AS ca, customer_demographics WHERE (c.c_current_addr_sk = ca.ca_address_sk) AND (cd_demo_sk = c.c_current_cdemo_sk) AND EXISTS ( SELECT * FROM store_sales, date_dim WHERE (c.c_customer_sk = ss_customer_sk) AND (ss_sold_date_sk = d_date_sk) AND (d_year = 2002) AND (d_qoy < 4) ) AND ( EXISTS ( SELECT * FROM web_sales, date_dim WHERE (c.c_customer_sk = ws_bill_customer_sk) AND (ws_sold_date_sk = d_date_sk) AND (d_year = 2002) AND (d_qoy < 4) ) OR EXISTS ( SELECT * FROM catalog_sales, date_dim WHERE (c.c_customer_sk = cs_ship_customer_sk) AND (cs_sold_date_sk = d_date_sk) AND (d_year = 2002) AND (d_qoy < 4) ) ) GROUP BY ca_state, cd_gender, cd_marital_status, cd_dep_count, cd_dep_employed_count, cd_dep_college_count ORDER BY ca_state, cd_gender, cd_marital_status, cd_dep_count, cd_dep_employed_count, cd_dep_college_count LIMIT 100", + "SELECT sum(ss_net_profit) / sum(ss_ext_sales_price) AS gross_margin, i_category, i_class, grouping(i_category) + grouping(i_class) AS lochierarchy, rank() OVER ( PARTITION BY grouping(i_category) + grouping(i_class), CASE WHEN grouping(i_class) = 0 THEN i_category END ORDER BY (sum(ss_net_profit) * 1.) / sum(ss_ext_sales_price) ASC ) AS rank_within_parent FROM store_sales, date_dim AS d1, item, store WHERE (d1.d_year = 2001) AND (d1.d_date_sk = ss_sold_date_sk) AND (i_item_sk = ss_item_sk) AND (s_store_sk = ss_store_sk) AND (s_state IN ('TN', 'TN', 'TN', 'TN', 'TN', 'TN', 'TN', 'TN')) GROUP BY ROLLUP(i_category, i_class) ORDER BY lochierarchy DESC, CASE WHEN lochierarchy = 0 THEN i_category END, rank_within_parent LIMIT 100", + "SELECT i_item_id, i_item_desc, i_current_price FROM item, inventory, date_dim, catalog_sales WHERE (i_current_price BETWEEN 68 AND 68 + 30) AND (inv_item_sk = i_item_sk) AND (d_date_sk = inv_date_sk) AND (d_date BETWEEN CAST('2000-02-01' AS date) AND (CAST('2000-02-01' AS date) + INTERVAL 60 DAY)) AND (i_manufact_id IN (677, 940, 694, 808)) AND (inv_quantity_on_hand BETWEEN 100 AND 500) AND (cs_item_sk = i_item_sk) GROUP BY i_item_id, i_item_desc, i_current_price ORDER BY i_item_id LIMIT 100", + "SELECT count(*) FROM ( SELECT DISTINCT c_last_name, c_first_name, d_date FROM store_sales, date_dim, customer WHERE (store_sales.ss_sold_date_sk = date_dim.d_date_sk) AND (store_sales.ss_customer_sk = customer.c_customer_sk) AND (d_month_seq BETWEEN 1200 AND 1200 + 11) INTERSECT SELECT DISTINCT c_last_name, c_first_name, d_date FROM catalog_sales, date_dim, customer WHERE (catalog_sales.cs_sold_date_sk = date_dim.d_date_sk) AND (catalog_sales.cs_bill_customer_sk = customer.c_customer_sk) AND (d_month_seq BETWEEN 1200 AND 1200 + 11) INTERSECT SELECT DISTINCT c_last_name, c_first_name, d_date FROM web_sales, date_dim, customer WHERE (web_sales.ws_sold_date_sk = date_dim.d_date_sk) AND (web_sales.ws_bill_customer_sk = customer.c_customer_sk) AND (d_month_seq BETWEEN 1200 AND 1200 + 11) ) AS hot_cust LIMIT 100", + "WITH inv AS ( SELECT w_warehouse_name, w_warehouse_sk, i_item_sk, d_moy, stdev, mean, CASE mean WHEN 0 THEN NULL ELSE stdev / mean END AS cov FROM ( SELECT w_warehouse_name, w_warehouse_sk, i_item_sk, d_moy, stddev_samp(inv_quantity_on_hand) AS stdev, avg(inv_quantity_on_hand) AS mean FROM inventory, item, warehouse, date_dim WHERE (inv_item_sk = i_item_sk) AND (inv_warehouse_sk = w_warehouse_sk) AND (inv_date_sk = d_date_sk) AND (d_year = 2001) GROUP BY w_warehouse_name, w_warehouse_sk, i_item_sk, d_moy ) AS foo WHERE (CASE mean WHEN 0 THEN 0 ELSE stdev / mean END > 1) ) SELECT inv1.w_warehouse_sk, inv1.i_item_sk, inv1.d_moy, inv1.mean, inv1.cov, inv2.w_warehouse_sk, inv2.i_item_sk, inv2.d_moy, inv2.mean, inv2.cov FROM inv AS inv1, inv AS inv2 WHERE (inv1.i_item_sk = inv2.i_item_sk) AND (inv1.w_warehouse_sk = inv2.w_warehouse_sk) AND (inv1.d_moy = 1) AND (inv2.d_moy = 1 + 1) ORDER BY inv1.w_warehouse_sk, inv1.i_item_sk, inv1.d_moy, inv1.mean, inv1.cov, inv2.d_moy, inv2.mean, inv2.cov", + "WITH inv AS ( SELECT w_warehouse_name, w_warehouse_sk, i_item_sk, d_moy, stdev, mean, CASE mean WHEN 0 THEN NULL ELSE stdev / mean END AS cov FROM ( SELECT w_warehouse_name, w_warehouse_sk, i_item_sk, d_moy, stddev_samp(inv_quantity_on_hand) AS stdev, avg(inv_quantity_on_hand) AS mean FROM inventory, item, warehouse, date_dim WHERE (inv_item_sk = i_item_sk) AND (inv_warehouse_sk = w_warehouse_sk) AND (inv_date_sk = d_date_sk) AND (d_year = 2001) GROUP BY w_warehouse_name, w_warehouse_sk, i_item_sk, d_moy ) AS foo WHERE (CASE mean WHEN 0 THEN 0 ELSE stdev / mean END > 1) ) SELECT inv1.w_warehouse_sk, inv1.i_item_sk, inv1.d_moy, inv1.mean, inv1.cov, inv2.w_warehouse_sk, inv2.i_item_sk, inv2.d_moy, inv2.mean, inv2.cov FROM inv AS inv1, inv AS inv2 WHERE (inv1.i_item_sk = inv2.i_item_sk) AND (inv1.w_warehouse_sk = inv2.w_warehouse_sk) AND (inv1.d_moy = 1) AND (inv2.d_moy = 1 + 1) AND (inv1.cov > 1.5) ORDER BY inv1.w_warehouse_sk, inv1.i_item_sk, inv1.d_moy, inv1.mean, inv1.cov, inv2.d_moy, inv2.mean, inv2.cov", + "SELECT w_state, i_item_id, sum(CASE WHEN (CAST(d_date AS date) < CAST('2000-03-11' AS date)) THEN cs_sales_price - coalesce(cr_refunded_cash, 0) ELSE 0 END) AS sales_before, sum(CASE WHEN (CAST(d_date AS date) >= CAST('2000-03-11' AS date)) THEN cs_sales_price - coalesce(cr_refunded_cash, 0) ELSE 0 END) AS sales_after FROM catalog_sales LEFT OUTER JOIN catalog_returns ON (cs_order_number = cr_order_number) AND (cs_item_sk = cr_item_sk), warehouse, item, date_dim WHERE (i_current_price BETWEEN 0.99 AND 1.49) AND (i_item_sk = cs_item_sk) AND (cs_warehouse_sk = w_warehouse_sk) AND (cs_sold_date_sk = d_date_sk) AND (d_date BETWEEN (CAST('2000-03-11' AS date) - INTERVAL 30 DAY) AND (CAST('2000-03-11' AS date) + INTERVAL 30 DAY)) GROUP BY w_state, i_item_id ORDER BY w_state, i_item_id LIMIT 100", + "SELECT DISTINCT(i_product_name) FROM item AS i1 WHERE (i_manufact_id BETWEEN 738 AND 738 + 40) AND ( SELECT count(*) AS item_cnt FROM item WHERE ( (i_manufact = i1.i_manufact) AND ( ( (i_category = 'Women') AND (i_color = 'powder' OR i_color = 'khaki') AND (i_units = 'Ounce' OR i_units = 'Oz') AND (i_size = 'medium' OR i_size = 'extra large') ) OR ( (i_category = 'Women') AND (i_color = 'brown' OR i_color = 'honeydew') AND (i_units = 'Bunch' OR i_units = 'Ton') AND (i_size = 'N/A' OR i_size = 'small') ) OR ( (i_category = 'Men') AND (i_color = 'floral' OR i_color = 'deep') AND (i_units = 'N/A' OR i_units = 'Dozen') AND (i_size = 'petite' OR i_size = 'large') ) OR ( (i_category = 'Men') AND (i_color = 'light' OR i_color = 'cornflower') AND (i_units = 'Box' OR i_units = 'Pound') AND (i_size = 'medium' OR i_size = 'extra large') ) ) ) OR ( (i_manufact = i1.i_manufact) AND ( ( (i_category = 'Women') AND (i_color = 'midnight' OR i_color = 'snow') AND (i_units = 'Pallet' OR i_units = 'Gross') AND (i_size = 'medium' OR i_size = 'extra large') ) OR ( (i_category = 'Women') AND (i_color = 'cyan' OR i_color = 'papaya') AND (i_units = 'Cup' OR i_units = 'Dram') AND (i_size = 'N/A' OR i_size = 'small') ) OR ( (i_category = 'Men') AND (i_color = 'orange' OR i_color = 'frosted') AND (i_units = 'Each' OR i_units = 'Tbl') AND (i_size = 'petite' OR i_size = 'large') ) OR ( (i_category = 'Men') AND (i_color = 'forest' OR i_color = 'ghost') AND (i_units = 'Lb' OR i_units = 'Bundle') AND (i_size = 'medium' OR i_size = 'extra large') ) ) ) ) > 0 ORDER BY i_product_name LIMIT 100", + "SELECT dt.d_year, item.i_category_id, item.i_category, sum(ss_ext_sales_price) FROM date_dim AS dt, store_sales, item WHERE (dt.d_date_sk = store_sales.ss_sold_date_sk) AND (store_sales.ss_item_sk = item.i_item_sk) AND (item.i_manager_id = 1) AND (dt.d_moy = 11) AND (dt.d_year = 2000) GROUP BY dt.d_year, item.i_category_id, item.i_category ORDER BY sum(ss_ext_sales_price) DESC, dt.d_year, item.i_category_id, item.i_category LIMIT 100", + "SELECT s_store_name, s_store_id, sum(CASE WHEN (d_day_name = 'Sunday') THEN ss_sales_price ELSE NULL END) AS sun_sales, sum(CASE WHEN (d_day_name = 'Monday') THEN ss_sales_price ELSE NULL END) AS mon_sales, sum(CASE WHEN (d_day_name = 'Tuesday') THEN ss_sales_price ELSE NULL END) AS tue_sales, sum(CASE WHEN (d_day_name = 'Wednesday') THEN ss_sales_price ELSE NULL END) AS wed_sales, sum(CASE WHEN (d_day_name = 'Thursday') THEN ss_sales_price ELSE NULL END) AS thu_sales, sum(CASE WHEN (d_day_name = 'Friday') THEN ss_sales_price ELSE NULL END) AS fri_sales, sum(CASE WHEN (d_day_name = 'Saturday') THEN ss_sales_price ELSE NULL END) AS sat_sales FROM date_dim, store_sales, store WHERE (d_date_sk = ss_sold_date_sk) AND (s_store_sk = ss_store_sk) AND (s_gmt_offset = -5) AND (d_year = 2000) GROUP BY s_store_name, s_store_id ORDER BY s_store_name, s_store_id, sun_sales, mon_sales, tue_sales, wed_sales, thu_sales, fri_sales, sat_sales LIMIT 100", + "SELECT asceding.rnk, i1.i_product_name AS best_performing, i2.i_product_name AS worst_performing FROM ( SELECT * FROM ( SELECT item_sk, rank() OVER (ORDER BY rank_col ASC) AS rnk FROM ( SELECT ss_item_sk AS item_sk, avg(ss_net_profit) AS rank_col FROM store_sales AS ss1 WHERE (ss_store_sk = 4) GROUP BY ss_item_sk HAVING avg(ss_net_profit) > 0.9 * ( SELECT avg(ss_net_profit) AS rank_col FROM store_sales WHERE (ss_store_sk = 4) AND (ss_addr_sk IS NULL) GROUP BY ss_store_sk ) ) AS V1 ) AS V11 WHERE (rnk < 11) ) AS asceding, ( SELECT * FROM ( SELECT item_sk, rank() OVER (ORDER BY rank_col DESC) AS rnk FROM ( SELECT ss_item_sk AS item_sk, avg(ss_net_profit) AS rank_col FROM store_sales AS ss1 WHERE (ss_store_sk = 4) GROUP BY ss_item_sk HAVING avg(ss_net_profit) > 0.9 * ( SELECT avg(ss_net_profit) AS rank_col FROM store_sales WHERE (ss_store_sk = 4) AND (ss_addr_sk IS NULL) GROUP BY ss_store_sk ) ) AS V2 ) AS V21 WHERE (rnk < 11) ) AS descending, item AS i1, item AS i2 WHERE (asceding.rnk = descending.rnk) AND (i1.i_item_sk = asceding.item_sk) AND (i2.i_item_sk = descending.item_sk) ORDER BY asceding.rnk LIMIT 100", + "SELECT ca_zip, ca_city, sum(ws_sales_price) FROM web_sales, customer, customer_address, date_dim, item WHERE (ws_bill_customer_sk = c_customer_sk) AND (c_current_addr_sk = ca_address_sk) AND (ws_item_sk = i_item_sk) AND ( (substr(ca_zip, 1, 5) IN ('85669', '86197', '88274', '83405', '86475', '85392', '85460', '80348', '81792')) OR (i_item_id IN ( SELECT i_item_id FROM item WHERE (i_item_sk IN (2, 3, 5, 7, 11, 13, 17, 19, 23, 29)) )) ) AND (ws_sold_date_sk = d_date_sk) AND (d_qoy = 2) AND (d_year = 2001) GROUP BY ca_zip, ca_city ORDER BY ca_zip, ca_city LIMIT 100", + "SELECT c_last_name, c_first_name, ca_city, bought_city, ss_ticket_number, amt, profit FROM ( SELECT ss_ticket_number, ss_customer_sk, ca_city AS bought_city, sum(ss_coupon_amt) AS amt, sum(ss_net_profit) AS profit FROM store_sales, date_dim, store, household_demographics, customer_address WHERE (store_sales.ss_sold_date_sk = date_dim.d_date_sk) AND (store_sales.ss_store_sk = store.s_store_sk) AND (store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk) AND (store_sales.ss_addr_sk = customer_address.ca_address_sk) AND ((household_demographics.hd_dep_count = 4) OR (household_demographics.hd_vehicle_count = 3)) AND (date_dim.d_dow IN (6, 0)) AND (date_dim.d_year IN (1999, 1999 + 1, 1999 + 2)) AND (store.s_city IN ('Fairview', 'Midway', 'Fairview', 'Fairview', 'Fairview')) GROUP BY ss_ticket_number, ss_customer_sk, ss_addr_sk, ca_city ) AS dn, customer, customer_address AS current_addr WHERE (ss_customer_sk = c_customer_sk) AND (customer.c_current_addr_sk = current_addr.ca_address_sk) AND (current_addr.ca_city <> bought_city) ORDER BY c_last_name, c_first_name, ca_city, bought_city, ss_ticket_number LIMIT 100", + "WITH v1 AS ( SELECT i_category, i_brand, s_store_name, s_company_name, d_year, d_moy, sum(ss_sales_price) AS sum_sales, avg(sum(ss_sales_price)) OVER (PARTITION BY i_category, i_brand, s_store_name, s_company_name, d_year) AS avg_monthly_sales, rank() OVER (PARTITION BY i_category, i_brand, s_store_name, s_company_name ORDER BY d_year, d_moy) AS rn FROM item, store_sales, date_dim, store WHERE (ss_item_sk = i_item_sk) AND (ss_sold_date_sk = d_date_sk) AND (ss_store_sk = s_store_sk) AND ( (d_year = 1999) OR ((d_year = 1999 - 1) AND (d_moy = 12)) OR ((d_year = 1999 + 1) AND (d_moy = 1)) ) GROUP BY i_category, i_brand, s_store_name, s_company_name, d_year, d_moy ), v2 AS ( SELECT v1.i_category, v1.i_brand, v1.s_store_name, v1.s_company_name, v1.d_year, v1.d_moy, v1.avg_monthly_sales, v1.sum_sales, v1_lag.sum_sales AS psum, v1_lead.sum_sales AS nsum FROM v1, v1 AS v1_lag, v1 AS v1_lead WHERE (v1.i_category = v1_lag.i_category) AND (v1.i_category = v1_lead.i_category) AND (v1.i_brand = v1_lag.i_brand) AND (v1.i_brand = v1_lead.i_brand) AND (v1.s_store_name = v1_lag.s_store_name) AND (v1.s_store_name = v1_lead.s_store_name) AND (v1.s_company_name = v1_lag.s_company_name) AND (v1.s_company_name = v1_lead.s_company_name) AND (v1.rn = v1_lag.rn + 1) AND (v1.rn = v1_lead.rn - 1) ) SELECT * FROM v2 WHERE (v1.d_year = 1999) AND (v1.avg_monthly_sales > 0) AND (CASE WHEN v1.avg_monthly_sales > 0 THEN abs(v1.sum_sales - v1.avg_monthly_sales) / v1.avg_monthly_sales ELSE NULL END > 0.1) ORDER BY v1.sum_sales - v1.avg_monthly_sales, v1.s_store_name LIMIT 100", + "SELECT sum(ss_quantity) FROM store_sales, store, customer_demographics, customer_address, date_dim WHERE (s_store_sk = ss_store_sk) AND (ss_sold_date_sk = d_date_sk) AND (d_year = 2000) AND ( ( (cd_demo_sk = ss_cdemo_sk) AND (cd_marital_status = 'M') AND (cd_education_status = '4 yr Degree') AND (ss_sales_price BETWEEN 100.00 AND 150.00) ) OR ( (cd_demo_sk = ss_cdemo_sk) AND (cd_marital_status = 'D') AND (cd_education_status = '2 yr Degree') AND (ss_sales_price BETWEEN 50.00 AND 100.00) ) OR ( (cd_demo_sk = ss_cdemo_sk) AND (cd_marital_status = 'S') AND (cd_education_status = 'College') AND (ss_sales_price BETWEEN 150.00 AND 200.00) ) ) AND ( ( (ss_addr_sk = ca_address_sk) AND (ca_country = 'United States') AND (ca_state IN ('CO', 'OH', 'TX')) AND (ss_net_profit BETWEEN 0 AND 2000) ) OR ( (ss_addr_sk = ca_address_sk) AND (ca_country = 'United States') AND (ca_state IN ('OR', 'MN', 'KY')) AND (ss_net_profit BETWEEN 150 AND 3000) ) OR ( (ss_addr_sk = ca_address_sk) AND (ca_country = 'United States') AND (ca_state IN ('VA', 'CA', 'MS')) AND (ss_net_profit BETWEEN 50 AND 25000) ) )", + "SELECT channel, item, return_ratio, return_rank, currency_rank FROM ( SELECT 'web' AS channel, web.item, web.return_ratio, web.return_rank, web.currency_rank FROM ( SELECT item, return_ratio, currency_ratio, rank() OVER (ORDER BY return_ratio) AS return_rank, rank() OVER (ORDER BY currency_ratio) AS currency_rank FROM ( SELECT ws.ws_item_sk AS item, (CAST(sum(coalesce(wr.wr_return_quantity, 0)) AS decimal(15, 4)) / CAST(sum(coalesce(ws.ws_quantity, 0)) AS decimal(15, 4))) AS return_ratio, (CAST(sum(coalesce(wr.wr_return_amt, 0)) AS decimal(15, 4)) / CAST(sum(coalesce(ws.ws_net_paid, 0)) AS decimal(15, 4))) AS currency_ratio FROM web_sales AS ws LEFT OUTER JOIN web_returns AS wr ON (ws.ws_order_number = wr.wr_order_number) AND (ws.ws_item_sk = wr.wr_item_sk), date_dim WHERE (wr.wr_return_amt > 10000) AND (ws.ws_net_profit > 1) AND (ws.ws_net_paid > 0) AND (ws.ws_quantity > 0) AND (ws_sold_date_sk = d_date_sk) AND (d_year = 2001) AND (d_moy = 12) GROUP BY ws.ws_item_sk ) AS in_web ) AS web WHERE (web.return_rank <= 10) OR (web.currency_rank <= 10) UNION SELECT 'catalog' AS channel, catalog.item, catalog.return_ratio, catalog.return_rank, catalog.currency_rank FROM ( SELECT item, return_ratio, currency_ratio, rank() OVER (ORDER BY return_ratio) AS return_rank, rank() OVER (ORDER BY currency_ratio) AS currency_rank FROM ( SELECT cs.cs_item_sk AS item, (CAST(sum(coalesce(cr.cr_return_quantity, 0)) AS decimal(15, 4)) / CAST(sum(coalesce(cs.cs_quantity, 0)) AS decimal(15, 4))) AS return_ratio, (CAST(sum(coalesce(cr.cr_return_amount, 0)) AS decimal(15, 4)) / CAST(sum(coalesce(cs.cs_net_paid, 0)) AS decimal(15, 4))) AS currency_ratio FROM catalog_sales AS cs LEFT OUTER JOIN catalog_returns AS cr ON (cs.cs_order_number = cr.cr_order_number) AND (cs.cs_item_sk = cr.cr_item_sk), date_dim WHERE (cr.cr_return_amount > 10000) AND (cs.cs_net_profit > 1) AND (cs.cs_net_paid > 0) AND (cs.cs_quantity > 0) AND (cs_sold_date_sk = d_date_sk) AND (d_year = 2001) AND (d_moy = 12) GROUP BY cs.cs_item_sk ) AS in_cat ) AS catalog WHERE (catalog.return_rank <= 10) OR (catalog.currency_rank <= 10) UNION SELECT 'store' AS channel, store.item, store.return_ratio, store.return_rank, store.currency_rank FROM ( SELECT item, return_ratio, currency_ratio, rank() OVER (ORDER BY return_ratio) AS return_rank, rank() OVER (ORDER BY currency_ratio) AS currency_rank FROM ( SELECT sts.ss_item_sk AS item, (CAST(sum(coalesce(sr.sr_return_quantity, 0)) AS decimal(15, 4)) / CAST(sum(coalesce(sts.ss_quantity, 0)) AS decimal(15, 4))) AS return_ratio, (CAST(sum(coalesce(sr.sr_return_amt, 0)) AS decimal(15, 4)) / CAST(sum(coalesce(sts.ss_net_paid, 0)) AS decimal(15, 4))) AS currency_ratio FROM store_sales AS sts LEFT OUTER JOIN store_returns AS sr ON (sts.ss_ticket_number = sr.sr_ticket_number) AND (sts.ss_item_sk = sr.sr_item_sk), date_dim WHERE (sr.sr_return_amt > 10000) AND (sts.ss_net_profit > 1) AND (sts.ss_net_paid > 0) AND (sts.ss_quantity > 0) AND (ss_sold_date_sk = d_date_sk) AND (d_year = 2001) AND (d_moy = 12) GROUP BY sts.ss_item_sk ) AS in_store ) AS store WHERE (store.return_rank <= 10) OR (store.currency_rank <= 10) ) ORDER BY 1, 4, 5, 2 LIMIT 100", + "SELECT s_store_name, s_company_id, s_street_number, s_street_name, s_street_type, s_suite_number, s_city, s_county, s_state, s_zip, sum(CASE WHEN (sr_returned_date_sk - ss_sold_date_sk <= 30) THEN 1 ELSE 0 END) AS \"30 days\", sum(CASE WHEN (sr_returned_date_sk - ss_sold_date_sk > 30) AND (sr_returned_date_sk - ss_sold_date_sk <= 60) THEN 1 ELSE 0 END) AS \"31-60 days\", sum(CASE WHEN (sr_returned_date_sk - ss_sold_date_sk > 60) AND (sr_returned_date_sk - ss_sold_date_sk <= 90) THEN 1 ELSE 0 END) AS \"61-90 days\", sum(CASE WHEN (sr_returned_date_sk - ss_sold_date_sk > 90) AND (sr_returned_date_sk - ss_sold_date_sk <= 120) THEN 1 ELSE 0 END) AS \"91-120 days\", sum(CASE WHEN (sr_returned_date_sk - ss_sold_date_sk > 120) THEN 1 ELSE 0 END) AS \">120 days\" FROM store_sales, store_returns, store, date_dim AS d1, date_dim AS d2 WHERE (d2.d_year = 2001) AND (d2.d_moy = 8) AND (ss_ticket_number = sr_ticket_number) AND (ss_item_sk = sr_item_sk) AND (ss_sold_date_sk = d1.d_date_sk) AND (sr_returned_date_sk = d2.d_date_sk) AND (ss_customer_sk = sr_customer_sk) AND (ss_store_sk = s_store_sk) GROUP BY s_store_name, s_company_id, s_street_number, s_street_name, s_street_type, s_suite_number, s_city, s_county, s_state, s_zip ORDER BY s_store_name, s_company_id, s_street_number, s_street_name, s_street_type, s_suite_number, s_city, s_county, s_state, s_zip LIMIT 100", + "WITH web_v1 AS ( SELECT ws_item_sk AS item_sk, d_date, sum(sum(ws_sales_price)) OVER (PARTITION BY ws_item_sk ORDER BY d_date ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) AS cume_sales FROM web_sales, date_dim WHERE (ws_sold_date_sk = d_date_sk) AND (d_month_seq BETWEEN 1200 AND 1200 + 11) AND (ws_item_sk IS NOT NULL) GROUP BY ws_item_sk, d_date ), store_v1 AS ( SELECT ss_item_sk AS item_sk, d_date, sum(sum(ss_sales_price)) OVER (PARTITION BY ss_item_sk ORDER BY d_date ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) AS cume_sales FROM store_sales, date_dim WHERE (ss_sold_date_sk = d_date_sk) AND (d_month_seq BETWEEN 1200 AND 1200 + 11) AND (ss_item_sk IS NOT NULL) GROUP BY ss_item_sk, d_date ) SELECT * FROM ( SELECT item_sk, d_date, web_sales, store_sales, max(web_sales) OVER (PARTITION BY item_sk ORDER BY d_date ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) AS web_cumulative, max(store_sales) OVER (PARTITION BY item_sk ORDER BY d_date ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) AS store_cumulative FROM ( SELECT CASE WHEN web.item_sk IS NOT NULL THEN web.item_sk ELSE store.item_sk END AS item_sk, CASE WHEN web.d_date IS NOT NULL THEN web.d_date ELSE store.d_date END AS d_date, web.cume_sales AS web_sales, store.cume_sales AS store_sales FROM web_v1 AS web FULL OUTER JOIN store_v1 AS store ON (web.item_sk = store.item_sk) AND (web.d_date = store.d_date) ) AS x ) AS y WHERE (web_cumulative > store_cumulative) ORDER BY item_sk, d_date LIMIT 100", + "SELECT dt.d_year, item.i_brand_id AS brand_id, item.i_brand AS brand, sum(ss_ext_sales_price) AS ext_price FROM date_dim AS dt, store_sales, item WHERE (dt.d_date_sk = store_sales.ss_sold_date_sk) AND (store_sales.ss_item_sk = item.i_item_sk) AND (item.i_manager_id = 1) AND (dt.d_moy = 11) AND (dt.d_year = 2000) GROUP BY dt.d_year, item.i_brand, item.i_brand_id ORDER BY dt.d_year, ext_price DESC, brand_id LIMIT 100", + "SELECT * FROM ( SELECT i_manufact_id, sum(ss_sales_price) AS sum_sales, avg(sum(ss_sales_price)) OVER (PARTITION BY i_manufact_id) AS avg_quarterly_sales FROM item, store_sales, date_dim, store WHERE (ss_item_sk = i_item_sk) AND (ss_sold_date_sk = d_date_sk) AND (ss_store_sk = s_store_sk) AND (d_month_seq IN (1200, 1200 + 1, 1200 + 2, 1200 + 3, 1200 + 4, 1200 + 5, 1200 + 6, 1200 + 7, 1200 + 8, 1200 + 9, 1200 + 10, 1200 + 11)) AND ( ( (i_category IN ('Books', 'Children', 'Electronics')) AND (i_class IN ('personal', 'portable', 'reference', 'self-help')) AND (i_brand IN ('scholaramalgamalg #14', 'scholaramalgamalg #7', 'exportiunivamalg #9', 'scholaramalgamalg #9')) ) OR ( (i_category IN ('Women', 'Music', 'Men')) AND (i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND (i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1')) ) ) GROUP BY i_manufact_id, d_qoy ) AS tmp1 WHERE (CASE WHEN avg_quarterly_sales > 0 THEN abs(sum_sales - avg_quarterly_sales) / avg_quarterly_sales ELSE NULL END > 0.1) ORDER BY avg_quarterly_sales, sum_sales, i_manufact_id LIMIT 100", + "WITH my_customers AS ( SELECT DISTINCT c_customer_sk, c_current_addr_sk FROM ( SELECT cs_sold_date_sk AS sold_date_sk, cs_bill_customer_sk AS customer_sk, cs_item_sk AS item_sk FROM catalog_sales UNION ALL SELECT ws_sold_date_sk AS sold_date_sk, ws_bill_customer_sk AS customer_sk, ws_item_sk AS item_sk FROM web_sales ) AS cs_or_ws_sales, item, date_dim, customer WHERE (sold_date_sk = d_date_sk) AND (item_sk = i_item_sk) AND (i_category = 'Women') AND (i_class = 'maternity') AND (c_customer_sk = cs_or_ws_sales.customer_sk) AND (d_moy = 12) AND (d_year = 1998) ), my_revenue AS ( SELECT c_customer_sk, sum(ss_ext_sales_price) AS revenue FROM my_customers, store_sales, customer_address, store, date_dim WHERE (c_current_addr_sk = ca_address_sk) AND (ca_county = s_county) AND (ca_state = s_state) AND (ss_sold_date_sk = d_date_sk) AND (c_customer_sk = ss_customer_sk) AND (d_month_seq BETWEEN ( SELECT DISTINCT d_month_seq + 1 FROM date_dim WHERE (d_year = 1998) AND (d_moy = 12) ) AND ( SELECT DISTINCT d_month_seq + 3 FROM date_dim WHERE (d_year = 1998) AND (d_moy = 12) )) GROUP BY c_customer_sk ), segments AS ( SELECT CAST((revenue / 50) AS int) AS segment FROM my_revenue ) SELECT segment, count(*) AS num_customers, segment * 50 AS segment_base FROM segments GROUP BY segment ORDER BY segment, num_customers LIMIT 100", + "SELECT i_brand_id AS brand_id, i_brand AS brand, sum(ss_ext_sales_price) AS ext_price FROM date_dim, store_sales, item WHERE (d_date_sk = ss_sold_date_sk) AND (ss_item_sk = i_item_sk) AND (i_manager_id = 28) AND (d_moy = 11) AND (d_year = 1999) GROUP BY i_brand, i_brand_id ORDER BY ext_price DESC, i_brand_id LIMIT 100", + "WITH ss AS ( SELECT i_item_id, sum(ss_ext_sales_price) AS total_sales FROM store_sales, date_dim, customer_address, item WHERE (i_item_id IN ( SELECT i_item_id FROM item WHERE (i_color IN ('slate', 'blanched', 'burnished')) )) AND (ss_item_sk = i_item_sk) AND (ss_sold_date_sk = d_date_sk) AND (d_year = 2001) AND (d_moy = 2) AND (ss_addr_sk = ca_address_sk) AND (ca_gmt_offset = -5) GROUP BY i_item_id ), cs AS ( SELECT i_item_id, sum(cs_ext_sales_price) AS total_sales FROM catalog_sales, date_dim, customer_address, item WHERE (i_item_id IN ( SELECT i_item_id FROM item WHERE (i_color IN ('slate', 'blanched', 'burnished')) )) AND (cs_item_sk = i_item_sk) AND (cs_sold_date_sk = d_date_sk) AND (d_year = 2001) AND (d_moy = 2) AND (cs_bill_addr_sk = ca_address_sk) AND (ca_gmt_offset = -5) GROUP BY i_item_id ), ws AS ( SELECT i_item_id, sum(ws_ext_sales_price) AS total_sales FROM web_sales, date_dim, customer_address, item WHERE (i_item_id IN ( SELECT i_item_id FROM item WHERE (i_color IN ('slate', 'blanched', 'burnished')) )) AND (ws_item_sk = i_item_sk) AND (ws_sold_date_sk = d_date_sk) AND (d_year = 2001) AND (d_moy = 2) AND (ws_bill_addr_sk = ca_address_sk) AND (ca_gmt_offset = -5) GROUP BY i_item_id ) SELECT i_item_id, sum(total_sales) AS total_sales FROM ( SELECT * FROM ss UNION ALL SELECT * FROM cs UNION ALL SELECT * FROM ws ) AS tmp1 GROUP BY i_item_id ORDER BY total_sales, i_item_id LIMIT 100", + "WITH v1 AS ( SELECT i_category, i_brand, cc_name, d_year, d_moy, sum(cs_sales_price) AS sum_sales, avg(sum(cs_sales_price)) OVER (PARTITION BY i_category, i_brand, cc_name, d_year) AS avg_monthly_sales, rank() OVER (PARTITION BY i_category, i_brand, cc_name ORDER BY d_year, d_moy) AS rn FROM item, catalog_sales, date_dim, call_center WHERE (cs_item_sk = i_item_sk) AND (cs_sold_date_sk = d_date_sk) AND (cc_call_center_sk = cs_call_center_sk) AND ( (d_year = 1999) OR ((d_year = 1999 - 1) AND (d_moy = 12)) OR ((d_year = 1999 + 1) AND (d_moy = 1)) ) GROUP BY i_category, i_brand, cc_name, d_year, d_moy ), v2 AS ( SELECT v1.i_category, v1.i_brand, v1.cc_name, v1.d_year, v1.d_moy, v1.avg_monthly_sales, v1.sum_sales, v1_lag.sum_sales AS psum, v1_lead.sum_sales AS nsum FROM v1, v1 AS v1_lag, v1 AS v1_lead WHERE (v1.i_category = v1_lag.i_category) AND (v1.i_category = v1_lead.i_category) AND (v1.i_brand = v1_lag.i_brand) AND (v1.i_brand = v1_lead.i_brand) AND (v1.cc_name = v1_lag.cc_name) AND (v1.cc_name = v1_lead.cc_name) AND (v1.rn = v1_lag.rn + 1) AND (v1.rn = v1_lead.rn - 1) ) SELECT * FROM v2 WHERE (v1.d_year = 1999) AND (v1.avg_monthly_sales > 0) AND (CASE WHEN v1.avg_monthly_sales > 0 THEN abs(v1.sum_sales - v1.avg_monthly_sales) / v1.avg_monthly_sales ELSE NULL END > 0.1) ORDER BY v1.sum_sales - v1.avg_monthly_sales, v1.cc_name LIMIT 100", + "WITH ss_items AS ( SELECT i_item_id AS item_id, sum(ss_ext_sales_price) AS ss_item_rev FROM store_sales, item, date_dim WHERE (ss_item_sk = i_item_sk) AND (d_date IN ( SELECT d_date FROM date_dim WHERE (d_week_seq = ( SELECT d_week_seq FROM date_dim WHERE (d_date = '2000-01-03') )) )) AND (ss_sold_date_sk = d_date_sk) GROUP BY i_item_id ), cs_items AS ( SELECT i_item_id AS item_id, sum(cs_ext_sales_price) AS cs_item_rev FROM catalog_sales, item, date_dim WHERE (cs_item_sk = i_item_sk) AND (d_date IN ( SELECT d_date FROM date_dim WHERE (d_week_seq = ( SELECT d_week_seq FROM date_dim WHERE (d_date = '2000-01-03') )) )) AND (cs_sold_date_sk = d_date_sk) GROUP BY i_item_id ), ws_items AS ( SELECT i_item_id AS item_id, sum(ws_ext_sales_price) AS ws_item_rev FROM web_sales, item, date_dim WHERE (ws_item_sk = i_item_sk) AND (d_date IN ( SELECT d_date FROM date_dim WHERE (d_week_seq = ( SELECT d_week_seq FROM date_dim WHERE (d_date = '2000-01-03') )) )) AND (ws_sold_date_sk = d_date_sk) GROUP BY i_item_id ) SELECT ss_items.item_id, ss_item_rev, ss_item_rev / ((CAST(ss_item_rev AS Float64) + cs_item_rev + ws_item_rev) / 3) * 100 AS ss_dev, cs_item_rev, cs_item_rev / ((CAST(ss_item_rev AS Float64) + cs_item_rev + ws_item_rev) / 3) * 100 AS cs_dev, ws_item_rev, ws_item_rev / ((CAST(ss_item_rev AS Float64) + cs_item_rev + ws_item_rev) / 3) * 100 AS ws_dev, (ss_item_rev + cs_item_rev + ws_item_rev) / 3 AS average FROM ss_items, cs_items, ws_items WHERE (ss_items.item_id = cs_items.item_id) AND (ss_items.item_id = ws_items.item_id) AND (ss_item_rev BETWEEN 0.9 * cs_item_rev AND 1.1 * cs_item_rev) AND (ss_item_rev BETWEEN 0.9 * ws_item_rev AND 1.1 * ws_item_rev) AND (cs_item_rev BETWEEN 0.9 * ss_item_rev AND 1.1 * ss_item_rev) AND (cs_item_rev BETWEEN 0.9 * ws_item_rev AND 1.1 * ws_item_rev) AND (ws_item_rev BETWEEN 0.9 * ss_item_rev AND 1.1 * ss_item_rev) AND (ws_item_rev BETWEEN 0.9 * cs_item_rev AND 1.1 * cs_item_rev) ORDER BY ss_items.item_id, ss_item_rev LIMIT 100", + "WITH wss AS ( SELECT d_week_seq, ss_store_sk, sum(CASE WHEN (d_day_name = 'Sunday') THEN ss_sales_price ELSE NULL END) AS sun_sales, sum(CASE WHEN (d_day_name = 'Monday') THEN ss_sales_price ELSE NULL END) AS mon_sales, sum(CASE WHEN (d_day_name = 'Tuesday') THEN ss_sales_price ELSE NULL END) AS tue_sales, sum(CASE WHEN (d_day_name = 'Wednesday') THEN ss_sales_price ELSE NULL END) AS wed_sales, sum(CASE WHEN (d_day_name = 'Thursday') THEN ss_sales_price ELSE NULL END) AS thu_sales, sum(CASE WHEN (d_day_name = 'Friday') THEN ss_sales_price ELSE NULL END) AS fri_sales, sum(CASE WHEN (d_day_name = 'Saturday') THEN ss_sales_price ELSE NULL END) AS sat_sales FROM store_sales, date_dim WHERE (d_date_sk = ss_sold_date_sk) GROUP BY d_week_seq, ss_store_sk ) SELECT s_store_name1, s_store_id1, d_week_seq1, sun_sales1 / sun_sales2, mon_sales1 / mon_sales2, tue_sales1 / tue_sales2, wed_sales1 / wed_sales2, thu_sales1 / thu_sales2, fri_sales1 / fri_sales2, sat_sales1 / sat_sales2 FROM ( SELECT s_store_name AS s_store_name1, wss.d_week_seq AS d_week_seq1, s_store_id AS s_store_id1, sun_sales AS sun_sales1, mon_sales AS mon_sales1, tue_sales AS tue_sales1, wed_sales AS wed_sales1, thu_sales AS thu_sales1, fri_sales AS fri_sales1, sat_sales AS sat_sales1 FROM wss, store, date_dim AS d WHERE (d.d_week_seq = wss.d_week_seq) AND (ss_store_sk = s_store_sk) AND (d_month_seq BETWEEN 1212 AND 1212 + 11) ) AS y, ( SELECT s_store_name AS s_store_name2, wss.d_week_seq AS d_week_seq2, s_store_id AS s_store_id2, sun_sales AS sun_sales2, mon_sales AS mon_sales2, tue_sales AS tue_sales2, wed_sales AS wed_sales2, thu_sales AS thu_sales2, fri_sales AS fri_sales2, sat_sales AS sat_sales2 FROM wss, store, date_dim AS d WHERE (d.d_week_seq = wss.d_week_seq) AND (ss_store_sk = s_store_sk) AND (d_month_seq BETWEEN 1212 + 12 AND 1212 + 23) ) AS x WHERE (s_store_id1 = s_store_id2) AND (d_week_seq1 = d_week_seq2 - 52) ORDER BY s_store_name1, s_store_id1, d_week_seq1 LIMIT 100", + "WITH ss AS ( SELECT i_item_id, sum(ss_ext_sales_price) AS total_sales FROM store_sales, date_dim, customer_address, item WHERE (i_item_id IN ( SELECT i_item_id FROM item WHERE (i_category IN ('Music')) )) AND (ss_item_sk = i_item_sk) AND (ss_sold_date_sk = d_date_sk) AND (d_year = 1998) AND (d_moy = 9) AND (ss_addr_sk = ca_address_sk) AND (ca_gmt_offset = -5) GROUP BY i_item_id ), cs AS ( SELECT i_item_id, sum(cs_ext_sales_price) AS total_sales FROM catalog_sales, date_dim, customer_address, item WHERE (i_item_id IN ( SELECT i_item_id FROM item WHERE (i_category IN ('Music')) )) AND (cs_item_sk = i_item_sk) AND (cs_sold_date_sk = d_date_sk) AND (d_year = 1998) AND (d_moy = 9) AND (cs_bill_addr_sk = ca_address_sk) AND (ca_gmt_offset = -5) GROUP BY i_item_id ), ws AS ( SELECT i_item_id, sum(ws_ext_sales_price) AS total_sales FROM web_sales, date_dim, customer_address, item WHERE (i_item_id IN ( SELECT i_item_id FROM item WHERE (i_category IN ('Music')) )) AND (ws_item_sk = i_item_sk) AND (ws_sold_date_sk = d_date_sk) AND (d_year = 1998) AND (d_moy = 9) AND (ws_bill_addr_sk = ca_address_sk) AND (ca_gmt_offset = -5) GROUP BY i_item_id ) SELECT i_item_id, sum(total_sales) AS total_sales FROM ( SELECT * FROM ss UNION ALL SELECT * FROM cs UNION ALL SELECT * FROM ws ) AS tmp1 GROUP BY i_item_id ORDER BY i_item_id, total_sales LIMIT 100", + "SELECT promotions, total, CAST(promotions AS decimal(15, 4)) / CAST(total AS decimal(15, 4)) * 100 FROM ( SELECT sum(ss_ext_sales_price) AS promotions FROM store_sales, store, promotion, date_dim, customer, customer_address, item WHERE (ss_sold_date_sk = d_date_sk) AND (ss_store_sk = s_store_sk) AND (ss_promo_sk = p_promo_sk) AND (ss_customer_sk = c_customer_sk) AND (ca_address_sk = c_current_addr_sk) AND (ss_item_sk = i_item_sk) AND (ca_gmt_offset = -5) AND (i_category = 'Jewelry') AND ((p_channel_dmail = 'Y') OR (p_channel_email = 'Y') OR (p_channel_tv = 'Y')) AND (s_gmt_offset = -5) AND (d_year = 1998) AND (d_moy = 11) ) AS promotional_sales, ( SELECT sum(ss_ext_sales_price) AS total FROM store_sales, store, date_dim, customer, customer_address, item WHERE (ss_sold_date_sk = d_date_sk) AND (ss_store_sk = s_store_sk) AND (ss_customer_sk = c_customer_sk) AND (ca_address_sk = c_current_addr_sk) AND (ss_item_sk = i_item_sk) AND (ca_gmt_offset = -5) AND (i_category = 'Jewelry') AND (s_gmt_offset = -5) AND (d_year = 1998) AND (d_moy = 11) ) AS all_sales ORDER BY promotions, total LIMIT 100", + "SELECT substr(w_warehouse_name, 1, 20), sm_type, web_name, sum(CASE WHEN (ws_ship_date_sk - ws_sold_date_sk <= 30) THEN 1 ELSE 0 END) AS \"30 days\", sum(CASE WHEN (ws_ship_date_sk - ws_sold_date_sk > 30) AND (ws_ship_date_sk - ws_sold_date_sk <= 60) THEN 1 ELSE 0 END) AS \"31-60 days\", sum(CASE WHEN (ws_ship_date_sk - ws_sold_date_sk > 60) AND (ws_ship_date_sk - ws_sold_date_sk <= 90) THEN 1 ELSE 0 END) AS \"61-90 days\", sum(CASE WHEN (ws_ship_date_sk - ws_sold_date_sk > 90) AND (ws_ship_date_sk - ws_sold_date_sk <= 120) THEN 1 ELSE 0 END) AS \"91-120 days\", sum(CASE WHEN (ws_ship_date_sk - ws_sold_date_sk > 120) THEN 1 ELSE 0 END) AS \">120 days\" FROM web_sales, warehouse, ship_mode, web_site, date_dim WHERE (d_month_seq BETWEEN 1200 AND 1200 + 11) AND (ws_ship_date_sk = d_date_sk) AND (ws_warehouse_sk = w_warehouse_sk) AND (ws_ship_mode_sk = sm_ship_mode_sk) AND (ws_web_site_sk = web_site_sk) GROUP BY substr(w_warehouse_name, 1, 20), sm_type, web_name ORDER BY substr(w_warehouse_name, 1, 20), sm_type, web_name LIMIT 100", + "SELECT * FROM ( SELECT i_manager_id, sum(ss_sales_price) AS sum_sales, avg(sum(ss_sales_price)) OVER (PARTITION BY i_manager_id) AS avg_monthly_sales FROM item, store_sales, date_dim, store WHERE (ss_item_sk = i_item_sk) AND (ss_sold_date_sk = d_date_sk) AND (ss_store_sk = s_store_sk) AND (d_month_seq IN (1200, 1200 + 1, 1200 + 2, 1200 + 3, 1200 + 4, 1200 + 5, 1200 + 6, 1200 + 7, 1200 + 8, 1200 + 9, 1200 + 10, 1200 + 11)) AND ( ( (i_category IN ('Books', 'Children', 'Electronics')) AND (i_class IN ('personal', 'portable', 'reference', 'self-help')) AND (i_brand IN ('scholaramalgamalg #14', 'scholaramalgamalg #7', 'exportiunivamalg #9', 'scholaramalgamalg #9')) ) OR ( (i_category IN ('Women', 'Music', 'Men')) AND (i_class IN ('accessories', 'classical', 'fragrances', 'pants')) AND (i_brand IN ('amalgimporto #1', 'edu packscholar #1', 'exportiimporto #1', 'importoamalg #1')) ) ) GROUP BY i_manager_id, d_moy ) AS tmp1 WHERE (CASE WHEN avg_monthly_sales > 0 THEN abs(sum_sales - avg_monthly_sales) / avg_monthly_sales ELSE NULL END > 0.1) ORDER BY i_manager_id, avg_monthly_sales, sum_sales LIMIT 100", + "WITH cs_ui AS ( SELECT cs_item_sk, sum(cs_ext_list_price) AS sale, sum((cr_refunded_cash + cr_reversed_charge) + cr_store_credit) AS refund FROM catalog_sales, catalog_returns WHERE (cs_item_sk = cr_item_sk) AND (cs_order_number = cr_order_number) GROUP BY cs_item_sk HAVING sum(cs_ext_list_price) > (2 * sum((cr_refunded_cash + cr_reversed_charge) + cr_store_credit)) ), cross_sales AS ( SELECT i_product_name AS product_name, i_item_sk AS item_sk, s_store_name AS store_name, s_zip AS store_zip, ad1.ca_street_number AS b_street_number, ad1.ca_street_name AS b_street_name, ad1.ca_city AS b_city, ad1.ca_zip AS b_zip, ad2.ca_street_number AS c_street_number, ad2.ca_street_name AS c_street_name, ad2.ca_city AS c_city, ad2.ca_zip AS c_zip, d1.d_year AS syear, d2.d_year AS fsyear, d3.d_year AS s2year, count(*) AS cnt, sum(ss_wholesale_cost) AS s1, sum(ss_list_price) AS s2, sum(ss_coupon_amt) AS s3 FROM store_sales, store_returns, cs_ui, date_dim AS d1, date_dim AS d2, date_dim AS d3, store, customer, customer_demographics AS cd1, customer_demographics AS cd2, promotion, household_demographics AS hd1, household_demographics AS hd2, customer_address AS ad1, customer_address AS ad2, income_band AS ib1, income_band AS ib2, item WHERE (ss_store_sk = s_store_sk) AND (ss_sold_date_sk = d1.d_date_sk) AND (ss_customer_sk = c_customer_sk) AND (ss_cdemo_sk = cd1.cd_demo_sk) AND (ss_hdemo_sk = hd1.hd_demo_sk) AND (ss_addr_sk = ad1.ca_address_sk) AND (ss_item_sk = i_item_sk) AND (ss_item_sk = sr_item_sk) AND (ss_ticket_number = sr_ticket_number) AND (ss_item_sk = cs_ui.cs_item_sk) AND (c_current_cdemo_sk = cd2.cd_demo_sk) AND (c_current_hdemo_sk = hd2.hd_demo_sk) AND (c_current_addr_sk = ad2.ca_address_sk) AND (c_first_sales_date_sk = d2.d_date_sk) AND (c_first_shipto_date_sk = d3.d_date_sk) AND (ss_promo_sk = p_promo_sk) AND (hd1.hd_income_band_sk = ib1.ib_income_band_sk) AND (hd2.hd_income_band_sk = ib2.ib_income_band_sk) AND (cd1.cd_marital_status != cd2.cd_marital_status) AND (i_color IN ('purple', 'burlywood', 'indian', 'spring', 'floral', 'medium')) AND ((i_current_price >= 64) AND (i_current_price <= (64 + 10))) AND ((i_current_price >= (64 + 1)) AND (i_current_price <= (64 + 15))) GROUP BY i_product_name, i_item_sk, s_store_name, s_zip, ad1.ca_street_number, ad1.ca_street_name, ad1.ca_city, ad1.ca_zip, ad2.ca_street_number, ad2.ca_street_name, ad2.ca_city, ad2.ca_zip, d1.d_year, d2.d_year, d3.d_year ) SELECT cs1.product_name, cs1.store_name, cs1.store_zip, cs1.b_street_number, cs1.b_street_name, cs1.b_city, cs1.b_zip, cs1.c_street_number, cs1.c_street_name, cs1.c_city, cs1.c_zip, cs1.syear, cs1.cnt, cs1.s1 AS s11, cs1.s2 AS s21, cs1.s3 AS s31, cs2.s1 AS s12, cs2.s2 AS s22, cs2.s3 AS s32, cs2.syear, cs2.cnt FROM cross_sales AS cs1, cross_sales AS cs2 WHERE (cs1.item_sk = cs2.item_sk) AND (cs1.syear = 1999) AND (cs2.syear = (1999 + 1)) AND (cs2.cnt <= cs1.cnt) AND (cs1.store_name = cs2.store_name) AND (cs1.store_zip = cs2.store_zip) ORDER BY cs1.product_name, cs1.store_name, cs2.cnt, cs1.s1, cs2.s1", + "SELECT s_store_name, i_item_desc, sc.revenue, i_current_price, i_wholesale_cost, i_brand FROM store, item, ( SELECT ss_store_sk, avg(revenue) AS ave FROM ( SELECT ss_store_sk, ss_item_sk, sum(ss_sales_price) AS revenue FROM store_sales, date_dim WHERE ss_sold_date_sk = d_date_sk AND d_month_seq BETWEEN 1176 AND 1176+11 GROUP BY ss_store_sk, ss_item_sk ) AS sa GROUP BY ss_store_sk ) AS sb, ( SELECT ss_store_sk, ss_item_sk, sum(ss_sales_price) AS revenue FROM store_sales, date_dim WHERE ss_sold_date_sk = d_date_sk AND d_month_seq BETWEEN 1176 AND 1176+11 GROUP BY ss_store_sk, ss_item_sk ) AS sc WHERE (sb.ss_store_sk = sc.ss_store_sk) AND (sc.revenue <= (0.1 * sb.ave)) AND (s_store_sk = sc.ss_store_sk) AND (i_item_sk = sc.ss_item_sk) ORDER BY s_store_name, i_item_desc LIMIT 100", + "SELECT w_warehouse_name, w_warehouse_sq_ft, w_city, w_county, w_state, w_country, ship_carriers, year, sum(x.jan_sales) AS jan_sales, sum(x.feb_sales) AS feb_sales, sum(x.mar_sales) AS mar_sales, sum(x.apr_sales) AS apr_sales, sum(x.may_sales) AS may_sales, sum(x.jun_sales) AS jun_sales, sum(x.jul_sales) AS jul_sales, sum(x.aug_sales) AS aug_sales, sum(x.sep_sales) AS sep_sales, sum(x.oct_sales) AS oct_sales, sum(x.nov_sales) AS nov_sales, sum(x.dec_sales) AS dec_sales, sum(CAST(x.jan_sales AS Float64) / w_warehouse_sq_ft) AS jan_sales_per_sq_foot, sum(CAST(x.feb_sales AS Float64) / w_warehouse_sq_ft) AS feb_sales_per_sq_foot, sum(CAST(x.mar_sales AS Float64) / w_warehouse_sq_ft) AS mar_sales_per_sq_foot, sum(CAST(x.apr_sales AS Float64) / w_warehouse_sq_ft) AS apr_sales_per_sq_foot, sum(CAST(x.may_sales AS Float64) / w_warehouse_sq_ft) AS may_sales_per_sq_foot, sum(CAST(x.jun_sales AS Float64) / w_warehouse_sq_ft) AS jun_sales_per_sq_foot, sum(CAST(x.jul_sales AS Float64) / w_warehouse_sq_ft) AS jul_sales_per_sq_foot, sum(CAST(x.aug_sales AS Float64) / w_warehouse_sq_ft) AS aug_sales_per_sq_foot, sum(CAST(x.sep_sales AS Float64) / w_warehouse_sq_ft) AS sep_sales_per_sq_foot, sum(CAST(x.oct_sales AS Float64) / w_warehouse_sq_ft) AS oct_sales_per_sq_foot, sum(CAST(x.nov_sales AS Float64) / w_warehouse_sq_ft) AS nov_sales_per_sq_foot, sum(CAST(x.dec_sales AS Float64) / w_warehouse_sq_ft) AS dec_sales_per_sq_foot, sum(x.jan_net) AS jan_net, sum(x.feb_net) AS feb_net, sum(x.mar_net) AS mar_net, sum(x.apr_net) AS apr_net, sum(x.may_net) AS may_net, sum(x.jun_net) AS jun_net, sum(x.jul_net) AS jul_net, sum(x.aug_net) AS aug_net, sum(x.sep_net) AS sep_net, sum(x.oct_net) AS oct_net, sum(x.nov_net) AS nov_net, sum(x.dec_net) AS dec_net FROM ( SELECT w_warehouse_name, w_warehouse_sq_ft, w_city, w_county, w_state, w_country, concat('DHL', ',', 'BARIAN') AS ship_carriers, d_year AS year, sum(multiIf(d_moy = 1, ws_ext_sales_price * ws_quantity, 0)) AS jan_sales, sum(multiIf(d_moy = 2, ws_ext_sales_price * ws_quantity, 0)) AS feb_sales, sum(multiIf(d_moy = 3, ws_ext_sales_price * ws_quantity, 0)) AS mar_sales, sum(multiIf(d_moy = 4, ws_ext_sales_price * ws_quantity, 0)) AS apr_sales, sum(multiIf(d_moy = 5, ws_ext_sales_price * ws_quantity, 0)) AS may_sales, sum(multiIf(d_moy = 6, ws_ext_sales_price * ws_quantity, 0)) AS jun_sales, sum(multiIf(d_moy = 7, ws_ext_sales_price * ws_quantity, 0)) AS jul_sales, sum(multiIf(d_moy = 8, ws_ext_sales_price * ws_quantity, 0)) AS aug_sales, sum(multiIf(d_moy = 9, ws_ext_sales_price * ws_quantity, 0)) AS sep_sales, sum(multiIf(d_moy = 10, ws_ext_sales_price * ws_quantity, 0)) AS oct_sales, sum(multiIf(d_moy = 11, ws_ext_sales_price * ws_quantity, 0)) AS nov_sales, sum(multiIf(d_moy = 12, ws_ext_sales_price * ws_quantity, 0)) AS dec_sales, sum(multiIf(d_moy = 1, ws_net_paid * ws_quantity, 0)) AS jan_net, sum(multiIf(d_moy = 2, ws_net_paid * ws_quantity, 0)) AS feb_net, sum(multiIf(d_moy = 3, ws_net_paid * ws_quantity, 0)) AS mar_net, sum(multiIf(d_moy = 4, ws_net_paid * ws_quantity, 0)) AS apr_net, sum(multiIf(d_moy = 5, ws_net_paid * ws_quantity, 0)) AS may_net, sum(multiIf(d_moy = 6, ws_net_paid * ws_quantity, 0)) AS jun_net, sum(multiIf(d_moy = 7, ws_net_paid * ws_quantity, 0)) AS jul_net, sum(multiIf(d_moy = 8, ws_net_paid * ws_quantity, 0)) AS aug_net, sum(multiIf(d_moy = 9, ws_net_paid * ws_quantity, 0)) AS sep_net, sum(multiIf(d_moy = 10, ws_net_paid * ws_quantity, 0)) AS oct_net, sum(multiIf(d_moy = 11, ws_net_paid * ws_quantity, 0)) AS nov_net, sum(multiIf(d_moy = 12, ws_net_paid * ws_quantity, 0)) AS dec_net FROM web_sales, warehouse, date_dim, time_dim, ship_mode WHERE (ws_warehouse_sk = w_warehouse_sk) AND (ws_sold_date_sk = d_date_sk) AND (ws_sold_time_sk = t_time_sk) AND (ws_ship_mode_sk = sm_ship_mode_sk) AND (d_year = 2001) AND (t_time BETWEEN 30838 AND 30838 + 28800) AND (sm_carrier IN ('DHL', 'BARIAN')) GROUP BY w_warehouse_name, w_warehouse_sq_ft, w_city, w_county, w_state, w_country, d_year UNION ALL SELECT w_warehouse_name, w_warehouse_sq_ft, w_city, w_county, w_state, w_country, concat('DHL', ',', 'BARIAN') AS ship_carriers, d_year AS year, sum(multiIf(d_moy = 1, cs_sales_price * cs_quantity, 0)) AS jan_sales, sum(multiIf(d_moy = 2, cs_sales_price * cs_quantity, 0)) AS feb_sales, sum(multiIf(d_moy = 3, cs_sales_price * cs_quantity, 0)) AS mar_sales, sum(multiIf(d_moy = 4, cs_sales_price * cs_quantity, 0)) AS apr_sales, sum(multiIf(d_moy = 5, cs_sales_price * cs_quantity, 0)) AS may_sales, sum(multiIf(d_moy = 6, cs_sales_price * cs_quantity, 0)) AS jun_sales, sum(multiIf(d_moy = 7, cs_sales_price * cs_quantity, 0)) AS jul_sales, sum(multiIf(d_moy = 8, cs_sales_price * cs_quantity, 0)) AS aug_sales, sum(multiIf(d_moy = 9, cs_sales_price * cs_quantity, 0)) AS sep_sales, sum(multiIf(d_moy = 10, cs_sales_price * cs_quantity, 0)) AS oct_sales, sum(multiIf(d_moy = 11, cs_sales_price * cs_quantity, 0)) AS nov_sales, sum(multiIf(d_moy = 12, cs_sales_price * cs_quantity, 0)) AS dec_sales, sum(multiIf(d_moy = 1, cs_net_paid_inc_tax * cs_quantity, 0)) AS jan_net, sum(multiIf(d_moy = 2, cs_net_paid_inc_tax * cs_quantity, 0)) AS feb_net, sum(multiIf(d_moy = 3, cs_net_paid_inc_tax * cs_quantity, 0)) AS mar_net, sum(multiIf(d_moy = 4, cs_net_paid_inc_tax * cs_quantity, 0)) AS apr_net, sum(multiIf(d_moy = 5, cs_net_paid_inc_tax * cs_quantity, 0)) AS may_net, sum(multiIf(d_moy = 6, cs_net_paid_inc_tax * cs_quantity, 0)) AS jun_net, sum(multiIf(d_moy = 7, cs_net_paid_inc_tax * cs_quantity, 0)) AS jul_net, sum(multiIf(d_moy = 8, cs_net_paid_inc_tax * cs_quantity, 0)) AS aug_net, sum(multiIf(d_moy = 9, cs_net_paid_inc_tax * cs_quantity, 0)) AS sep_net, sum(multiIf(d_moy = 10, cs_net_paid_inc_tax * cs_quantity, 0)) AS oct_net, sum(multiIf(d_moy = 11, cs_net_paid_inc_tax * cs_quantity, 0)) AS nov_net, sum(multiIf(d_moy = 12, cs_net_paid_inc_tax * cs_quantity, 0)) AS dec_net FROM catalog_sales, warehouse, date_dim, time_dim, ship_mode WHERE (cs_warehouse_sk = w_warehouse_sk) AND (cs_sold_date_sk = d_date_sk) AND (cs_sold_time_sk = t_time_sk) AND (cs_ship_mode_sk = sm_ship_mode_sk) AND (d_year = 2001) AND ((t_time >= 30838) AND (t_time <= (30838 + 28800))) AND (sm_carrier IN ('DHL', 'BARIAN')) GROUP BY w_warehouse_name, w_warehouse_sq_ft, w_city, w_county, w_state, w_country, d_year ) AS x GROUP BY w_warehouse_name, w_warehouse_sq_ft, w_city, w_county, w_state, w_country, ship_carriers, year ORDER BY w_warehouse_name LIMIT 100", + "SELECT * FROM ( SELECT i_category, i_class, i_brand, i_product_name, d_year, d_qoy, d_moy, s_store_id, sumsales, rank() OVER (PARTITION BY i_category ORDER BY sumsales DESC) AS rk FROM ( SELECT i_category, i_class, i_brand, i_product_name, d_year, d_qoy, d_moy, s_store_id, sum(coalesce(ss_sales_price * ss_quantity, 0)) AS sumsales FROM store_sales, date_dim, store, item WHERE (ss_sold_date_sk = d_date_sk) AND (ss_item_sk = i_item_sk) AND (ss_store_sk = s_store_sk) AND (d_month_seq BETWEEN 1200 AND 1200 + 11) GROUP BY i_category, i_class, i_brand, i_product_name, d_year, d_qoy, d_moy, s_store_id WITH ROLLUP ) AS dw1 ) AS dw2 WHERE (rk <= 100) ORDER BY i_category, i_class, i_brand, i_product_name, d_year, d_qoy, d_moy, s_store_id, sumsales, rk LIMIT 100", + "SELECT c_last_name, c_first_name, ca_city, bought_city, ss_ticket_number, extended_price, extended_tax, list_price FROM ( SELECT ss_ticket_number, ss_customer_sk, ca_city AS bought_city, sum(ss_ext_sales_price) AS extended_price, sum(ss_ext_list_price) AS list_price, sum(ss_ext_tax) AS extended_tax FROM store_sales, date_dim, store, household_demographics, customer_address WHERE (store_sales.ss_sold_date_sk = date_dim.d_date_sk) AND (store_sales.ss_store_sk = store.s_store_sk) AND (store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk) AND (store_sales.ss_addr_sk = customer_address.ca_address_sk) AND ((date_dim.d_dom >= 1) AND (date_dim.d_dom <= 2)) AND ((household_demographics.hd_dep_count = 4) OR (household_demographics.hd_vehicle_count = 3)) AND (date_dim.d_year IN (1999, 1999 + 1, 1999 + 2)) AND (store.s_city IN ('Midway', 'Fairview')) GROUP BY ss_ticket_number, ss_customer_sk, ss_addr_sk, ca_city ) AS dn, customer, customer_address AS current_addr WHERE (ss_customer_sk = c_customer_sk) AND (customer.c_current_addr_sk = current_addr.ca_address_sk) AND (current_addr.ca_city != bought_city) ORDER BY c_last_name, ss_ticket_number LIMIT 100", + "SELECT cd_gender, cd_marital_status, cd_education_status, count(*) AS cnt1, cd_purchase_estimate, count(*) AS cnt2, cd_credit_rating, count(*) AS cnt3 FROM customer AS c, customer_address AS ca, customer_demographics WHERE (c.c_current_addr_sk = ca.ca_address_sk) AND (ca_state IN ('KY', 'GA', 'NM')) AND (cd_demo_sk = c.c_current_cdemo_sk) AND EXISTS ( SELECT * FROM store_sales, date_dim WHERE (c.c_customer_sk = ss_customer_sk) AND (ss_sold_date_sk = d_date_sk) AND (d_year = 2001) AND (d_moy BETWEEN 4 AND 4 + 2) ) AND ( NOT EXISTS ( SELECT * FROM web_sales, date_dim WHERE (c.c_customer_sk = ws_bill_customer_sk) AND (ws_sold_date_sk = d_date_sk) AND (d_year = 2001) AND (d_moy BETWEEN 4 AND 4 + 2) ) AND NOT EXISTS ( SELECT * FROM catalog_sales, date_dim WHERE (c.c_customer_sk = cs_ship_customer_sk) AND (cs_sold_date_sk = d_date_sk) AND (d_year = 2001) AND (d_moy BETWEEN 4 AND 4 + 2) ) ) GROUP BY cd_gender, cd_marital_status, cd_education_status, cd_purchase_estimate, cd_credit_rating ORDER BY cd_gender, cd_marital_status, cd_education_status, cd_purchase_estimate, cd_credit_rating LIMIT 100", + "SELECT sum(ss_net_profit) AS total_sum, s_state, s_county, grouping(s_state) + grouping(s_county) AS lochierarchy, rank() OVER (PARTITION BY grouping(s_state) + grouping(s_county), multiIf(grouping(s_county) = 0, s_state, NULL) ORDER BY sum(ss_net_profit) DESC) AS rank_within_parent FROM store_sales, date_dim AS d1, store WHERE ((d1.d_month_seq >= 1200) AND (d1.d_month_seq <= (1200 + 11))) AND (d1.d_date_sk = ss_sold_date_sk) AND (s_store_sk = ss_store_sk) AND (s_state IN ( SELECT s_state FROM ( SELECT s_state AS s_state, rank() OVER (PARTITION BY s_state ORDER BY sum(ss_net_profit) DESC) AS ranking FROM store_sales, store, date_dim WHERE ((d_month_seq >= 1200) AND (d_month_seq <= (1200 + 11))) AND (d_date_sk = ss_sold_date_sk) AND (s_store_sk = ss_store_sk) GROUP BY s_state ) AS tmp1 WHERE (ranking <= 5) )) GROUP BY s_state, s_county WITH ROLLUP ORDER BY lochierarchy DESC, multiIf(lochierarchy = 0, s_state, NULL), rank_within_parent LIMIT 100", + "SELECT i_brand_id AS brand_id, i_brand AS brand, t_hour, t_minute, sum(ext_price) AS ext_price FROM item, ( SELECT ws_ext_sales_price AS ext_price, ws_sold_date_sk AS sold_date_sk, ws_item_sk AS sold_item_sk, ws_sold_time_sk AS time_sk FROM web_sales, date_dim WHERE (d_date_sk = ws_sold_date_sk) AND (d_moy = 11) AND (d_year = 1999) UNION ALL SELECT cs_ext_sales_price AS ext_price, cs_sold_date_sk AS sold_date_sk, cs_item_sk AS sold_item_sk, cs_sold_time_sk AS time_sk FROM catalog_sales, date_dim WHERE (d_date_sk = cs_sold_date_sk) AND (d_moy = 11) AND (d_year = 1999) UNION ALL SELECT ss_ext_sales_price AS ext_price, ss_sold_date_sk AS sold_date_sk, ss_item_sk AS sold_item_sk, ss_sold_time_sk AS time_sk FROM store_sales, date_dim WHERE (d_date_sk = ss_sold_date_sk) AND (d_moy = 11) AND (d_year = 1999) ) AS tmp, time_dim WHERE (sold_item_sk = i_item_sk) AND (i_manager_id = 1) AND (time_sk = t_time_sk) AND ((t_meal_time = 'breakfast') OR (t_meal_time = 'dinner')) GROUP BY i_brand, i_brand_id, t_hour, t_minute ORDER BY ext_price DESC, i_brand_id", + "SELECT i_item_desc, w_warehouse_name, d1.d_week_seq, sum(multiIf(p_promo_sk IS NULL, 1, 0)) AS no_promo, sum(multiIf(p_promo_sk IS NOT NULL, 1, 0)) AS promo, count(*) AS total_cnt FROM catalog_sales INNER JOIN inventory ON cs_item_sk = inv_item_sk INNER JOIN warehouse ON w_warehouse_sk = inv_warehouse_sk INNER JOIN item ON i_item_sk = cs_item_sk INNER JOIN customer_demographics ON cs_bill_cdemo_sk = cd_demo_sk INNER JOIN household_demographics ON cs_bill_hdemo_sk = hd_demo_sk INNER JOIN date_dim AS d1 ON cs_sold_date_sk = d1.d_date_sk INNER JOIN date_dim AS d2 ON inv_date_sk = d2.d_date_sk INNER JOIN date_dim AS d3 ON cs_ship_date_sk = d3.d_date_sk LEFT JOIN promotion ON cs_promo_sk = p_promo_sk LEFT JOIN catalog_returns ON (cr_item_sk = cs_item_sk) AND (cr_order_number = cs_order_number) WHERE (d1.d_week_seq = d2.d_week_seq) AND (inv_quantity_on_hand < cs_quantity) AND (d3.d_date > (d1.d_date + 5)) AND (hd_buy_potential = '>10000') AND (d1.d_year = 1999) AND (cd_marital_status = 'D') GROUP BY i_item_desc, w_warehouse_name, d_week_seq ORDER BY total_cnt DESC, i_item_desc, w_warehouse_name, d_week_seq LIMIT 100", + "SELECT c_last_name, c_first_name, c_salutation, c_preferred_cust_flag, ss_ticket_number, cnt FROM ( SELECT ss_ticket_number, ss_customer_sk, count(*) AS cnt FROM store_sales, date_dim, store, household_demographics WHERE (store_sales.ss_sold_date_sk = date_dim.d_date_sk) AND (store_sales.ss_store_sk = store.s_store_sk) AND (store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk) AND ((date_dim.d_dom >= 1) AND (date_dim.d_dom <= 2)) AND ((household_demographics.hd_buy_potential = '>10000') OR (household_demographics.hd_buy_potential = 'Unknown')) AND (household_demographics.hd_vehicle_count > 0) AND (multiIf(household_demographics.hd_vehicle_count > 0, household_demographics.hd_dep_count / household_demographics.hd_vehicle_count, NULL) > 1) AND (date_dim.d_year IN (1999, 1999 + 1, 1999 + 2)) AND (store.s_county IN ('Williamson County', 'Franklin Parish', 'Bronx County', 'Orange County')) GROUP BY ss_ticket_number, ss_customer_sk ) AS dj, customer WHERE (ss_customer_sk = c_customer_sk) AND ((cnt >= 1) AND (cnt <= 5)) ORDER BY cnt DESC, c_last_name", + "WITH year_total AS ( SELECT c_customer_id AS customer_id, c_first_name AS customer_first_name, c_last_name AS customer_last_name, d_year AS year, sum(ss_net_paid) AS year_total, 's' AS sale_type FROM customer, store_sales, date_dim WHERE (c_customer_sk = ss_customer_sk) AND (ss_sold_date_sk = d_date_sk) AND (d_year IN (2001, 2001 + 1)) GROUP BY c_customer_id, c_first_name, c_last_name, d_year UNION ALL SELECT c_customer_id AS customer_id, c_first_name AS customer_first_name, c_last_name AS customer_last_name, d_year AS year, sum(ws_net_paid) AS year_total, 'w' AS sale_type FROM customer, web_sales, date_dim WHERE (c_customer_sk = ws_bill_customer_sk) AND (ws_sold_date_sk = d_date_sk) AND (d_year IN (2001, 2001 + 1)) GROUP BY c_customer_id, c_first_name, c_last_name, d_year ) SELECT t_s_secyear.customer_id, t_s_secyear.customer_first_name, t_s_secyear.customer_last_name FROM year_total AS t_s_firstyear, year_total AS t_s_secyear, year_total AS t_w_firstyear, year_total AS t_w_secyear WHERE (t_s_secyear.customer_id = t_s_firstyear.customer_id) AND (t_s_firstyear.customer_id = t_w_secyear.customer_id) AND (t_s_firstyear.customer_id = t_w_firstyear.customer_id) AND (t_s_firstyear.sale_type = 's') AND (t_w_firstyear.sale_type = 'w') AND (t_s_secyear.sale_type = 's') AND (t_w_secyear.sale_type = 'w') AND (t_s_firstyear.year = 2001) AND (t_s_secyear.year = (2001 + 1)) AND (t_w_firstyear.year = 2001) AND (t_w_secyear.year = (2001 + 1)) AND (t_s_firstyear.year_total > 0) AND (t_w_firstyear.year_total > 0) AND (multiIf(t_w_firstyear.year_total > 0, t_w_secyear.year_total / t_w_firstyear.year_total, NULL) > multiIf(t_s_firstyear.year_total > 0, t_s_secyear.year_total / t_s_firstyear.year_total, NULL)) ORDER BY 1, 2, 3 LIMIT 100", + "WITH all_sales AS ( SELECT d_year, i_brand_id, i_class_id, i_category_id, i_manufact_id, SUM(sales_cnt) AS sales_cnt, SUM(sales_amt) AS sales_amt FROM ( SELECT d_year, i_brand_id, i_class_id, i_category_id, i_manufact_id, cs_quantity - COALESCE(cr_return_quantity, 0) AS sales_cnt, cs_ext_sales_price - COALESCE(cr_return_amount, CAST('0.0', 'Decimal(7, 2)')) AS sales_amt FROM catalog_sales INNER JOIN item ON i_item_sk = cs_item_sk INNER JOIN date_dim ON d_date_sk = cs_sold_date_sk LEFT JOIN catalog_returns ON (cs_order_number = cr_order_number) AND (cs_item_sk = cr_item_sk) WHERE (i_category = 'Books') UNION SELECT d_year, i_brand_id, i_class_id, i_category_id, i_manufact_id, ss_quantity - COALESCE(sr_return_quantity, 0) AS sales_cnt, ss_ext_sales_price - COALESCE(sr_return_amt, CAST('0.0', 'Decimal(7, 2)')) AS sales_amt FROM store_sales INNER JOIN item ON i_item_sk = ss_item_sk INNER JOIN date_dim ON d_date_sk = ss_sold_date_sk LEFT JOIN store_returns ON (ss_ticket_number = sr_ticket_number) AND (ss_item_sk = sr_item_sk) WHERE (i_category = 'Books') UNION SELECT d_year, i_brand_id, i_class_id, i_category_id, i_manufact_id, ws_quantity - COALESCE(wr_return_quantity, 0) AS sales_cnt, ws_ext_sales_price - COALESCE(wr_return_amt, CAST('0.0', 'Decimal(7, 2)')) AS sales_amt FROM web_sales INNER JOIN item ON i_item_sk = ws_item_sk INNER JOIN date_dim ON d_date_sk = ws_sold_date_sk LEFT JOIN web_returns ON (ws_order_number = wr_order_number) AND (ws_item_sk = wr_item_sk) WHERE (i_category = 'Books') ) AS sales_detail GROUP BY d_year, i_brand_id, i_class_id, i_category_id, i_manufact_id ) SELECT prev_yr.d_year AS prev_year, curr_yr.d_year AS year, curr_yr.i_brand_id, curr_yr.i_class_id, curr_yr.i_category_id, curr_yr.i_manufact_id, prev_yr.sales_cnt AS prev_yr_cnt, curr_yr.sales_cnt AS curr_yr_cnt, curr_yr.sales_cnt - prev_yr.sales_cnt AS sales_cnt_diff, curr_yr.sales_amt - prev_yr.sales_amt AS sales_amt_diff FROM all_sales AS curr_yr, all_sales AS prev_yr WHERE (curr_yr.i_brand_id = prev_yr.i_brand_id) AND (curr_yr.i_class_id = prev_yr.i_class_id) AND (curr_yr.i_category_id = prev_yr.i_category_id) AND (curr_yr.i_manufact_id = prev_yr.i_manufact_id) AND (curr_yr.d_year = 2002) AND (prev_yr.d_year = (2002 - 1)) AND ((CAST(curr_yr.sales_cnt, 'DECIMAL(17, 2)') / CAST(prev_yr.sales_cnt, 'DECIMAL(17, 2)')) < 0.9) ORDER BY sales_cnt_diff, sales_amt_diff LIMIT 100", + "SELECT channel, col_name, d_year, d_qoy, i_category, COUNT(*) AS sales_cnt, SUM(ext_sales_price) AS sales_amt FROM ( SELECT 'store' AS channel, 'ss_store_sk' AS col_name, d_year, d_qoy, i_category, ss_ext_sales_price AS ext_sales_price FROM store_sales, item, date_dim WHERE (ss_store_sk IS NULL) AND (ss_sold_date_sk = d_date_sk) AND (ss_item_sk = i_item_sk) UNION ALL SELECT 'web' AS channel, 'ws_ship_customer_sk' AS col_name, d_year, d_qoy, i_category, ws_ext_sales_price AS ext_sales_price FROM web_sales, item, date_dim WHERE (ws_ship_customer_sk IS NULL) AND (ws_sold_date_sk = d_date_sk) AND (ws_item_sk = i_item_sk) UNION ALL SELECT 'catalog' AS channel, 'cs_ship_addr_sk' AS col_name, d_year, d_qoy, i_category, cs_ext_sales_price AS ext_sales_price FROM catalog_sales, item, date_dim WHERE (cs_ship_addr_sk IS NULL) AND (cs_sold_date_sk = d_date_sk) AND (cs_item_sk = i_item_sk) ) AS foo GROUP BY channel, col_name, d_year, d_qoy, i_category ORDER BY channel, col_name, d_year, d_qoy, i_category LIMIT 100", + "WITH ss AS ( SELECT s_store_sk, sum(ss_ext_sales_price) AS sales, sum(ss_net_profit) AS profit FROM store_sales, date_dim, store WHERE (ss_sold_date_sk = d_date_sk) AND ((d_date >= CAST('2000-08-23', 'date')) AND (d_date <= (CAST('2000-08-23', 'date') + INTERVAL 30 DAY))) AND (ss_store_sk = s_store_sk) GROUP BY s_store_sk ), sr AS ( SELECT s_store_sk, sum(sr_return_amt) AS returns, sum(sr_net_loss) AS profit_loss FROM store_returns, date_dim, store WHERE (sr_returned_date_sk = d_date_sk) AND ((d_date >= CAST('2000-08-23', 'date')) AND (d_date <= (CAST('2000-08-23', 'date') + INTERVAL 30 DAY))) AND (sr_store_sk = s_store_sk) GROUP BY s_store_sk ), cs AS ( SELECT cs_call_center_sk, sum(cs_ext_sales_price) AS sales, sum(cs_net_profit) AS profit FROM catalog_sales, date_dim WHERE (cs_sold_date_sk = d_date_sk) AND ((d_date >= CAST('2000-08-23', 'date')) AND (d_date <= (CAST('2000-08-23', 'date') + INTERVAL 30 DAY))) GROUP BY cs_call_center_sk ), cr AS ( SELECT cr_call_center_sk, sum(cr_return_amount) AS returns, sum(cr_net_loss) AS profit_loss FROM catalog_returns, date_dim WHERE (cr_returned_date_sk = d_date_sk) AND ((d_date >= CAST('2000-08-23', 'date')) AND (d_date <= (CAST('2000-08-23', 'date') + INTERVAL 30 DAY))) GROUP BY cr_call_center_sk ), ws AS ( SELECT wp_web_page_sk, sum(ws_ext_sales_price) AS sales, sum(ws_net_profit) AS profit FROM web_sales, date_dim, web_page WHERE (ws_sold_date_sk = d_date_sk) AND ((d_date >= CAST('2000-08-23', 'date')) AND (d_date <= (CAST('2000-08-23', 'date') + INTERVAL 30 DAY))) AND (ws_web_page_sk = wp_web_page_sk) GROUP BY wp_web_page_sk ), wr AS ( SELECT wp_web_page_sk, sum(wr_return_amt) AS returns, sum(wr_net_loss) AS profit_loss FROM web_returns, date_dim, web_page WHERE (wr_returned_date_sk = d_date_sk) AND ((d_date >= CAST('2000-08-23', 'date')) AND (d_date <= (CAST('2000-08-23', 'date') + INTERVAL 30 DAY))) AND (wr_web_page_sk = wp_web_page_sk) GROUP BY wp_web_page_sk ) SELECT channel, id, sum(sales) AS sales, sum(returns) AS returns, sum(profit) AS profit FROM ( SELECT 'store channel' AS channel, ss.s_store_sk AS id, sales, coalesce(returns, 0) AS returns, profit - coalesce(profit_loss, 0) AS profit FROM ss LEFT JOIN sr ON ss.s_store_sk = sr.s_store_sk UNION ALL SELECT 'catalog channel' AS channel, cs_call_center_sk AS id, sales, returns, profit - profit_loss AS profit FROM cs, cr UNION ALL SELECT 'web channel' AS channel, ws.wp_web_page_sk AS id, sales, coalesce(returns, 0) AS returns, profit - coalesce(profit_loss, 0) AS profit FROM ws LEFT JOIN wr ON ws.wp_web_page_sk = wr.wp_web_page_sk ) AS x GROUP BY channel, id WITH ROLLUP ORDER BY channel, id LIMIT 100", + "WITH ws AS ( SELECT d_year AS ws_sold_year, ws_item_sk, ws_bill_customer_sk AS ws_customer_sk, sum(ws_quantity) AS ws_qty, sum(ws_wholesale_cost) AS ws_wc, sum(ws_sales_price) AS ws_sp FROM web_sales LEFT JOIN web_returns ON (wr_order_number = ws_order_number) AND (ws_item_sk = wr_item_sk) INNER JOIN date_dim ON ws_sold_date_sk = d_date_sk WHERE wr_order_number IS NULL GROUP BY d_year, ws_item_sk, ws_bill_customer_sk ), cs AS ( SELECT d_year AS cs_sold_year, cs_item_sk, cs_bill_customer_sk AS cs_customer_sk, sum(cs_quantity) AS cs_qty, sum(cs_wholesale_cost) AS cs_wc, sum(cs_sales_price) AS cs_sp FROM catalog_sales LEFT JOIN catalog_returns ON (cr_order_number = cs_order_number) AND (cs_item_sk = cr_item_sk) INNER JOIN date_dim ON cs_sold_date_sk = d_date_sk WHERE cr_order_number IS NULL GROUP BY d_year, cs_item_sk, cs_bill_customer_sk ), ss AS ( SELECT d_year AS ss_sold_year, ss_item_sk, ss_customer_sk, sum(ss_quantity) AS ss_qty, sum(ss_wholesale_cost) AS ss_wc, sum(ss_sales_price) AS ss_sp FROM store_sales LEFT JOIN store_returns ON (sr_ticket_number = ss_ticket_number) AND (ss_item_sk = sr_item_sk) INNER JOIN date_dim ON ss_sold_date_sk = d_date_sk WHERE sr_ticket_number IS NULL GROUP BY d_year, ss_item_sk, ss_customer_sk ) SELECT ss_sold_year, ss_item_sk, ss_customer_sk, round(ss_qty / (coalesce(ws_qty, 0) + coalesce(cs_qty, 0)), 2) AS ratio, ss_qty AS store_qty, ss_wc AS store_wholesale_cost, ss_sp AS store_sales_price, coalesce(ws_qty, 0) + coalesce(cs_qty, 0) AS other_chan_qty, coalesce(ws_wc, 0) + coalesce(cs_wc, 0) AS other_chan_wholesale_cost, coalesce(ws_sp, 0) + coalesce(cs_sp, 0) AS other_chan_sales_price FROM ss LEFT JOIN ws ON (ws_sold_year = ss_sold_year) AND (ws_item_sk = ss_item_sk) AND (ws_customer_sk = ss_customer_sk) LEFT JOIN cs ON (cs_sold_year = ss_sold_year) AND (cs_item_sk = ss_item_sk) AND (cs_customer_sk = ss_customer_sk) WHERE ((coalesce(ws_qty, 0) > 0) OR (coalesce(cs_qty, 0) > 0)) AND (ss_sold_year = 2000) ORDER BY ss_sold_year, ss_item_sk, ss_customer_sk, ss_qty DESC, ss_wc DESC, ss_sp DESC, other_chan_qty, other_chan_wholesale_cost, other_chan_sales_price, ratio LIMIT 100", + "SELECT c_last_name, c_first_name, substr(s_city, 1, 30), ss_ticket_number, amt, profit FROM ( SELECT ss_ticket_number, ss_customer_sk, store.s_city, sum(ss_coupon_amt) AS amt, sum(ss_net_profit) AS profit FROM store_sales, date_dim, store, household_demographics WHERE (store_sales.ss_sold_date_sk = date_dim.d_date_sk) AND (store_sales.ss_store_sk = store.s_store_sk) AND (store_sales.ss_hdemo_sk = household_demographics.hd_demo_sk) AND ((household_demographics.hd_dep_count = 6) OR (household_demographics.hd_vehicle_count > 2)) AND (date_dim.d_dow = 1) AND (date_dim.d_year IN (1999, 1999 + 1, 1999 + 2)) AND ((store.s_number_employees >= 200) AND (store.s_number_employees <= 295)) GROUP BY ss_ticket_number, ss_customer_sk, ss_addr_sk, store.s_city ) AS ms, customer WHERE (ss_customer_sk = c_customer_sk) ORDER BY c_last_name, c_first_name, substr(s_city, 1, 30), profit LIMIT 100", + "WITH ssr AS ( SELECT s_store_id AS store_id, sum(ss_ext_sales_price) AS sales, sum(coalesce(sr_return_amt, 0)) AS returns, sum(ss_net_profit - coalesce(sr_net_loss, 0)) AS profit FROM store_sales LEFT JOIN store_returns ON (ss_item_sk = sr_item_sk) AND (ss_ticket_number = sr_ticket_number), date_dim, store, item, promotion WHERE (ss_sold_date_sk = d_date_sk) AND ((d_date >= CAST('2000-08-23', 'date')) AND (d_date <= (CAST('2000-08-23', 'date') + INTERVAL 30 DAY))) AND (ss_store_sk = s_store_sk) AND (ss_item_sk = i_item_sk) AND (i_current_price > 50) AND (ss_promo_sk = p_promo_sk) AND (p_channel_tv = 'N') GROUP BY s_store_id ), csr AS ( SELECT cp_catalog_page_id AS catalog_page_id, sum(cs_ext_sales_price) AS sales, sum(coalesce(cr_return_amount, 0)) AS returns, sum(cs_net_profit - coalesce(cr_net_loss, 0)) AS profit FROM catalog_sales LEFT JOIN catalog_returns ON (cs_item_sk = cr_item_sk) AND (cs_order_number = cr_order_number), date_dim, catalog_page, item, promotion WHERE (cs_sold_date_sk = d_date_sk) AND ((d_date >= CAST('2000-08-23', 'date')) AND (d_date <= (CAST('2000-08-23', 'date') + INTERVAL 30 DAY))) AND (cs_catalog_page_sk = cp_catalog_page_sk) AND (cs_item_sk = i_item_sk) AND (i_current_price > 50) AND (cs_promo_sk = p_promo_sk) AND (p_channel_tv = 'N') GROUP BY cp_catalog_page_id ), wsr AS ( SELECT web_site_id, sum(ws_ext_sales_price) AS sales, sum(coalesce(wr_return_amt, 0)) AS returns, sum(ws_net_profit - coalesce(wr_net_loss, 0)) AS profit FROM web_sales LEFT JOIN web_returns ON (ws_item_sk = wr_item_sk) AND (ws_order_number = wr_order_number), date_dim, web_site, item, promotion WHERE (ws_sold_date_sk = d_date_sk) AND ((d_date >= CAST('2000-08-23', 'date')) AND (d_date <= (CAST('2000-08-23', 'date') + INTERVAL 30 DAY))) AND (ws_web_site_sk = web_site_sk) AND (ws_item_sk = i_item_sk) AND (i_current_price > 50) AND (ws_promo_sk = p_promo_sk) AND (p_channel_tv = 'N') GROUP BY web_site_id ) SELECT channel, id, sum(sales) AS sales, sum(returns) AS returns, sum(profit) AS profit FROM ( SELECT 'store channel' AS channel, concat('store', store_id) AS id, sales, returns, profit FROM ssr UNION ALL SELECT 'catalog channel' AS channel, concat('catalog_page', catalog_page_id) AS id, sales, returns, profit FROM csr UNION ALL SELECT 'web channel' AS channel, concat('web_site', web_site_id) AS id, sales, returns, profit FROM wsr ) AS x GROUP BY channel, id WITH ROLLUP ORDER BY channel, id LIMIT 100", + "WITH customer_total_return AS ( SELECT cr_returning_customer_sk AS ctr_customer_sk, ca_state AS ctr_state, sum(cr_return_amt_inc_tax) AS ctr_total_return FROM catalog_returns, date_dim, customer_address WHERE (cr_returned_date_sk = d_date_sk) AND (d_year = 2000) AND (cr_returning_addr_sk = ca_address_sk) GROUP BY cr_returning_customer_sk, ca_state ) SELECT c_customer_id, c_salutation, c_first_name, c_last_name, ca_street_number, ca_street_name, ca_street_type, ca_suite_number, ca_city, ca_county, ca_state, ca_zip, ca_country, ca_gmt_offset, ca_location_type, ctr_total_return FROM customer_total_return AS ctr1, customer_address, customer WHERE (ctr1.ctr_total_return > ( SELECT avg(ctr_total_return) * 1.2 FROM customer_total_return AS ctr2 WHERE (ctr1.ctr_state = ctr2.ctr_state) )) AND (ca_address_sk = c_current_addr_sk) AND (ca_state = 'GA') AND (ctr1.ctr_customer_sk = c_customer_sk) ORDER BY c_customer_id, c_salutation, c_first_name, c_last_name, ca_street_number, ca_street_name, ca_street_type, ca_suite_number, ca_city, ca_county, ca_state, ca_zip, ca_country, ca_gmt_offset, ca_location_type, ctr_total_return LIMIT 100", + "SELECT i_item_id, i_item_desc, i_current_price FROM item, inventory, date_dim, store_sales WHERE (i_current_price BETWEEN 62 AND 62 + 30) AND (inv_item_sk = i_item_sk) AND (d_date_sk = inv_date_sk) AND (d_date BETWEEN CAST('2000-05-25', 'date') AND (CAST('2000-05-25', 'date') + INTERVAL 60 DAY)) AND (i_manufact_id IN (129, 270, 821, 423)) AND (inv_quantity_on_hand BETWEEN 100 AND 500) AND (ss_item_sk = i_item_sk) GROUP BY i_item_id, i_item_desc, i_current_price ORDER BY i_item_id LIMIT 100", + "WITH sr_items AS ( SELECT i_item_id AS item_id, sum(sr_return_quantity) AS sr_item_qty FROM store_returns, item, date_dim WHERE (sr_item_sk = i_item_sk) AND (d_date IN ( SELECT d_date FROM date_dim WHERE (d_week_seq IN ( SELECT d_week_seq FROM date_dim WHERE (d_date IN ('2000-06-30', '2000-09-27', '2000-11-17')) )) )) AND (sr_returned_date_sk = d_date_sk) GROUP BY i_item_id ), cr_items AS ( SELECT i_item_id AS item_id, sum(cr_return_quantity) AS cr_item_qty FROM catalog_returns, item, date_dim WHERE (cr_item_sk = i_item_sk) AND (d_date IN ( SELECT d_date FROM date_dim WHERE (d_week_seq IN ( SELECT d_week_seq FROM date_dim WHERE (d_date IN ('2000-06-30', '2000-09-27', '2000-11-17')) )) )) AND (cr_returned_date_sk = d_date_sk) GROUP BY i_item_id ), wr_items AS ( SELECT i_item_id AS item_id, sum(wr_return_quantity) AS wr_item_qty FROM web_returns, item, date_dim WHERE (wr_item_sk = i_item_sk) AND (d_date IN ( SELECT d_date FROM date_dim WHERE (d_week_seq IN ( SELECT d_week_seq FROM date_dim WHERE (d_date IN ('2000-06-30', '2000-09-27', '2000-11-17')) )) )) AND (wr_returned_date_sk = d_date_sk) GROUP BY i_item_id ) SELECT sr_items.item_id, sr_item_qty, ((sr_item_qty / ((sr_item_qty + cr_item_qty) + wr_item_qty)) / 3.) * 100 AS sr_dev, cr_item_qty, ((cr_item_qty / ((sr_item_qty + cr_item_qty) + wr_item_qty)) / 3.) * 100 AS cr_dev, wr_item_qty, ((wr_item_qty / ((sr_item_qty + cr_item_qty) + wr_item_qty)) / 3.) * 100 AS wr_dev, ((sr_item_qty + cr_item_qty) + wr_item_qty) / 3. AS average FROM sr_items, cr_items, wr_items WHERE (sr_items.item_id = cr_items.item_id) AND (sr_items.item_id = wr_items.item_id) ORDER BY sr_items.item_id, sr_item_qty LIMIT 100", + "SELECT c_customer_id AS customer_id, concat(coalesce(c_last_name, ''), ', ', coalesce(c_first_name, '')) AS customername FROM customer, customer_address, customer_demographics, household_demographics, income_band, store_returns WHERE (ca_city = 'Edgewood') AND (c_current_addr_sk = ca_address_sk) AND (ib_lower_bound >= 38128) AND (ib_upper_bound <= (38128 + 50000)) AND (ib_income_band_sk = hd_income_band_sk) AND (cd_demo_sk = c_current_cdemo_sk) AND (hd_demo_sk = c_current_hdemo_sk) AND (sr_cdemo_sk = cd_demo_sk) ORDER BY c_customer_id LIMIT 100", + "SELECT substr(r_reason_desc, 1, 20), avg(ws_quantity), avg(wr_refunded_cash), avg(wr_fee) FROM web_sales, web_returns, web_page, customer_demographics AS cd1, customer_demographics AS cd2, customer_address, date_dim, reason WHERE (ws_web_page_sk = wp_web_page_sk) AND (ws_item_sk = wr_item_sk) AND (ws_order_number = wr_order_number) AND (ws_sold_date_sk = d_date_sk) AND (d_year = 2000) AND (cd1.cd_demo_sk = wr_refunded_cdemo_sk) AND (cd2.cd_demo_sk = wr_returning_cdemo_sk) AND (ca_address_sk = wr_refunded_addr_sk) AND (r_reason_sk = wr_reason_sk) AND ( ( (cd1.cd_marital_status = 'M') AND (cd1.cd_marital_status = cd2.cd_marital_status) AND (cd1.cd_education_status = 'Advanced Degree') AND (cd1.cd_education_status = cd2.cd_education_status) AND ((ws_sales_price >= 100.0) AND (ws_sales_price <= 150.0)) ) OR ( (cd1.cd_marital_status = 'S') AND (cd1.cd_marital_status = cd2.cd_marital_status) AND (cd1.cd_education_status = 'College') AND (cd1.cd_education_status = cd2.cd_education_status) AND ((ws_sales_price >= 50.0) AND (ws_sales_price <= 100.0)) ) OR ( (cd1.cd_marital_status = 'W') AND (cd1.cd_marital_status = cd2.cd_marital_status) AND (cd1.cd_education_status = '2 yr Degree') AND (cd1.cd_education_status = cd2.cd_education_status) AND ((ws_sales_price >= 150.0) AND (ws_sales_price <= 200.0)) ) ) AND ( ( (ca_country = 'United States') AND (ca_state IN ('IN', 'OH', 'NJ')) AND ((ws_net_profit >= 100) AND (ws_net_profit <= 200)) ) OR ( (ca_country = 'United States') AND (ca_state IN ('WI', 'CT', 'KY')) AND ((ws_net_profit >= 150) AND (ws_net_profit <= 300)) ) OR ( (ca_country = 'United States') AND (ca_state IN ('LA', 'IA', 'AR')) AND ((ws_net_profit >= 50) AND (ws_net_profit <= 250)) ) ) GROUP BY r_reason_desc ORDER BY substr(r_reason_desc, 1, 20), avg(ws_quantity), avg(wr_refunded_cash), avg(wr_fee) LIMIT 100", + "SELECT sum(ws_net_paid) AS total_sum, i_category, i_class, grouping(i_category) + grouping(i_class) AS lochierarchy, rank() OVER (PARTITION BY grouping(i_category) + grouping(i_class), multiIf(grouping(i_class) = 0, i_category, NULL) ORDER BY sum(ws_net_paid) DESC) AS rank_within_parent FROM web_sales, date_dim AS d1, item WHERE ((d1.d_month_seq >= 1200) AND (d1.d_month_seq <= (1200 + 11))) AND (d1.d_date_sk = ws_sold_date_sk) AND (i_item_sk = ws_item_sk) GROUP BY i_category, i_class WITH ROLLUP ORDER BY lochierarchy DESC, multiIf(lochierarchy = 0, i_category, NULL), rank_within_parent LIMIT 100", + "SELECT count(*) FROM ( SELECT DISTINCT c_last_name, c_first_name, d_date FROM store_sales, date_dim, customer WHERE (store_sales.ss_sold_date_sk = date_dim.d_date_sk) AND (store_sales.ss_customer_sk = customer.c_customer_sk) AND ((d_month_seq >= 1200) AND (d_month_seq <= (1200 + 11))) EXCEPT SELECT DISTINCT c_last_name, c_first_name, d_date FROM catalog_sales, date_dim, customer WHERE (catalog_sales.cs_sold_date_sk = date_dim.d_date_sk) AND (catalog_sales.cs_bill_customer_sk = customer.c_customer_sk) AND ((d_month_seq >= 1200) AND (d_month_seq <= (1200 + 11))) EXCEPT SELECT DISTINCT c_last_name, c_first_name, d_date FROM web_sales, date_dim, customer WHERE (web_sales.ws_sold_date_sk = date_dim.d_date_sk) AND (web_sales.ws_bill_customer_sk = customer.c_customer_sk) AND ((d_month_seq >= 1200) AND (d_month_seq <= (1200 + 11))) ) AS cool_cust", + "SELECT * FROM ( SELECT count(*) AS h8_30_to_9 FROM store_sales, household_demographics, time_dim, store WHERE (ss_sold_time_sk = time_dim.t_time_sk) AND (ss_hdemo_sk = household_demographics.hd_demo_sk) AND (ss_store_sk = s_store_sk) AND (time_dim.t_hour = 8) AND (time_dim.t_minute >= 30) AND ( ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= (4 + 2))) OR ((household_demographics.hd_dep_count = 2) AND (household_demographics.hd_vehicle_count <= (2 + 2))) OR ((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= (0 + 2))) ) AND (store.s_store_name = 'ese') ) AS s1, ( SELECT count(*) AS h9_to_9_30 FROM store_sales, household_demographics, time_dim, store WHERE (ss_sold_time_sk = time_dim.t_time_sk) AND (ss_hdemo_sk = household_demographics.hd_demo_sk) AND (ss_store_sk = s_store_sk) AND (time_dim.t_hour = 9) AND (time_dim.t_minute < 30) AND ( ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= (4 + 2))) OR ((household_demographics.hd_dep_count = 2) AND (household_demographics.hd_vehicle_count <= (2 + 2))) OR ((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= (0 + 2))) ) AND (store.s_store_name = 'ese') ) AS s2, ( SELECT count(*) AS h9_30_to_10 FROM store_sales, household_demographics, time_dim, store WHERE (ss_sold_time_sk = time_dim.t_time_sk) AND (ss_hdemo_sk = household_demographics.hd_demo_sk) AND (ss_store_sk = s_store_sk) AND (time_dim.t_hour = 9) AND (time_dim.t_minute >= 30) AND ( ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= (4 + 2))) OR ((household_demographics.hd_dep_count = 2) AND (household_demographics.hd_vehicle_count <= (2 + 2))) OR ((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= (0 + 2))) ) AND (store.s_store_name = 'ese') ) AS s3, ( SELECT count(*) AS h10_to_10_30 FROM store_sales, household_demographics, time_dim, store WHERE (ss_sold_time_sk = time_dim.t_time_sk) AND (ss_hdemo_sk = household_demographics.hd_demo_sk) AND (ss_store_sk = s_store_sk) AND (time_dim.t_hour = 10) AND (time_dim.t_minute < 30) AND ( ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= (4 + 2))) OR ((household_demographics.hd_dep_count = 2) AND (household_demographics.hd_vehicle_count <= (2 + 2))) OR ((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= (0 + 2))) ) AND (store.s_store_name = 'ese') ) AS s4, ( SELECT count(*) AS h10_30_to_11 FROM store_sales, household_demographics, time_dim, store WHERE (ss_sold_time_sk = time_dim.t_time_sk) AND (ss_hdemo_sk = household_demographics.hd_demo_sk) AND (ss_store_sk = s_store_sk) AND (time_dim.t_hour = 10) AND (time_dim.t_minute >= 30) AND ( ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= (4 + 2))) OR ((household_demographics.hd_dep_count = 2) AND (household_demographics.hd_vehicle_count <= (2 + 2))) OR ((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= (0 + 2))) ) AND (store.s_store_name = 'ese') ) AS s5, ( SELECT count(*) AS h11_to_11_30 FROM store_sales, household_demographics, time_dim, store WHERE (ss_sold_time_sk = time_dim.t_time_sk) AND (ss_hdemo_sk = household_demographics.hd_demo_sk) AND (ss_store_sk = s_store_sk) AND (time_dim.t_hour = 11) AND (time_dim.t_minute < 30) AND ( ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= (4 + 2))) OR ((household_demographics.hd_dep_count = 2) AND (household_demographics.hd_vehicle_count <= (2 + 2))) OR ((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= (0 + 2))) ) AND (store.s_store_name = 'ese') ) AS s6, ( SELECT count(*) AS h11_30_to_12 FROM store_sales, household_demographics, time_dim, store WHERE (ss_sold_time_sk = time_dim.t_time_sk) AND (ss_hdemo_sk = household_demographics.hd_demo_sk) AND (ss_store_sk = s_store_sk) AND (time_dim.t_hour = 11) AND (time_dim.t_minute >= 30) AND ( ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= (4 + 2))) OR ((household_demographics.hd_dep_count = 2) AND (household_demographics.hd_vehicle_count <= (2 + 2))) OR ((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= (0 + 2))) ) AND (store.s_store_name = 'ese') ) AS s7, ( SELECT count(*) AS h12_to_12_30 FROM store_sales, household_demographics, time_dim, store WHERE (ss_sold_time_sk = time_dim.t_time_sk) AND (ss_hdemo_sk = household_demographics.hd_demo_sk) AND (ss_store_sk = s_store_sk) AND (time_dim.t_hour = 12) AND (time_dim.t_minute < 30) AND ( ((household_demographics.hd_dep_count = 4) AND (household_demographics.hd_vehicle_count <= (4 + 2))) OR ((household_demographics.hd_dep_count = 2) AND (household_demographics.hd_vehicle_count <= (2 + 2))) OR ((household_demographics.hd_dep_count = 0) AND (household_demographics.hd_vehicle_count <= (0 + 2))) ) AND (store.s_store_name = 'ese') ) AS s8", + "SELECT * FROM ( SELECT i_category, i_class, i_brand, s_store_name, s_company_name, d_moy, sum(ss_sales_price) AS sum_sales, avg(sum(ss_sales_price)) OVER (PARTITION BY i_category, i_brand, s_store_name, s_company_name) AS avg_monthly_sales FROM item, store_sales, date_dim, store WHERE (ss_item_sk = i_item_sk) AND (ss_sold_date_sk = d_date_sk) AND (ss_store_sk = s_store_sk) AND (d_year IN (1999)) AND ( ((i_category IN ('Women', 'Jewelry', 'Men')) AND (i_class IN ('dresses', 'birdal', 'shirts'))) OR ((i_category IN ('Sports', 'Electronics', 'Books')) AND (i_class IN ('football', 'stereo', 'computers'))) ) GROUP BY i_category, i_class, i_brand, s_store_name, s_company_name, d_moy ) AS tmp1 WHERE (multiIf(avg_monthly_sales != 0, abs(sum_sales - avg_monthly_sales) / avg_monthly_sales, NULL) > 0.1) ORDER BY sum_sales - avg_monthly_sales, s_store_name LIMIT 100", + "SELECT CAST(amc AS DECIMAL(15, 4)) / CAST(pmc AS DECIMAL(15, 4)) AS am_pm_ratio FROM ( SELECT count(*) AS amc FROM web_sales, household_demographics, time_dim, web_page WHERE (ws_sold_time_sk = time_dim.t_time_sk) AND (ws_ship_hdemo_sk = household_demographics.hd_demo_sk) AND (ws_web_page_sk = web_page.wp_web_page_sk) AND (time_dim.t_hour BETWEEN 8 AND 8 + 1) AND (household_demographics.hd_dep_count = 6) AND (web_page.wp_char_count BETWEEN 5000 AND 5200) ) AS at, ( SELECT count(*) AS pmc FROM web_sales, household_demographics, time_dim, web_page WHERE (ws_sold_time_sk = time_dim.t_time_sk) AND (ws_ship_hdemo_sk = household_demographics.hd_demo_sk) AND (ws_web_page_sk = web_page.wp_web_page_sk) AND (time_dim.t_hour BETWEEN 19 AND 19 + 1) AND (household_demographics.hd_dep_count = 6) AND (web_page.wp_char_count BETWEEN 5000 AND 5200) ) AS pt ORDER BY am_pm_ratio LIMIT 100", + "SELECT cc_call_center_id AS Call_Center, cc_name AS Call_Center_Name, cc_manager AS Manager, sum(cr_net_loss) AS Returns_Loss FROM call_center, catalog_returns, date_dim, customer, customer_address, customer_demographics, household_demographics WHERE (cr_call_center_sk = cc_call_center_sk) AND (cr_returned_date_sk = d_date_sk) AND (cr_returning_customer_sk = c_customer_sk) AND (cd_demo_sk = c_current_cdemo_sk) AND (hd_demo_sk = c_current_hdemo_sk) AND (ca_address_sk = c_current_addr_sk) AND (d_year = 1998) AND (d_moy = 11) AND ( ((cd_marital_status = 'M') AND (cd_education_status = 'Unknown')) OR ((cd_marital_status = 'W') AND (cd_education_status = 'Advanced Degree')) ) AND (hd_buy_potential LIKE 'Unknown%') AND (ca_gmt_offset = -7) GROUP BY cc_call_center_id, cc_name, cc_manager, cd_marital_status, cd_education_status ORDER BY sum(cr_net_loss) DESC", + "SELECT sum(ws_ext_discount_amt) AS `Excess Discount Amount` FROM web_sales, item, date_dim WHERE (i_manufact_id = 350) AND (i_item_sk = ws_item_sk) AND ((d_date >= '2000-01-27') AND (d_date <= (CAST('2000-01-27', 'date') + INTERVAL 90 DAY))) AND (d_date_sk = ws_sold_date_sk) AND (ws_ext_discount_amt > ( SELECT 1.3 * avg(ws_ext_discount_amt) FROM web_sales, date_dim WHERE (ws_item_sk = i_item_sk) AND ((d_date >= '2000-01-27') AND (d_date <= (CAST('2000-01-27', 'date') + INTERVAL 90 DAY))) AND (d_date_sk = ws_sold_date_sk) )) ORDER BY sum(ws_ext_discount_amt) LIMIT 100", + "SELECT ss_customer_sk, sum(act_sales) AS sumsales FROM ( SELECT ss_item_sk, ss_ticket_number, ss_customer_sk, multiIf(sr_return_quantity IS NOT NULL, (ss_quantity - sr_return_quantity) * ss_sales_price, ss_quantity * ss_sales_price) AS act_sales FROM store_sales LEFT JOIN store_returns ON (sr_item_sk = ss_item_sk) AND (sr_ticket_number = ss_ticket_number), reason WHERE (sr_reason_sk = r_reason_sk) AND (r_reason_desc = 'reason 28') ) AS t GROUP BY ss_customer_sk ORDER BY sumsales, ss_customer_sk LIMIT 100", + "SELECT count(DISTINCT ws_order_number) AS \"order count\", sum(ws_ext_ship_cost) AS \"total shipping cost\", sum(ws_net_profit) AS \"total net profit\" FROM web_sales AS ws1, date_dim, customer_address, web_site WHERE (d_date BETWEEN '1999-2-01' AND (CAST('1999-2-01', 'date') + INTERVAL 60 DAY)) AND (ws1.ws_ship_date_sk = d_date_sk) AND (ws1.ws_ship_addr_sk = ca_address_sk) AND (ca_state = 'IL') AND (ws1.ws_web_site_sk = web_site_sk) AND (web_company_name = 'pri') AND EXISTS ( SELECT * FROM web_sales AS ws2 WHERE (ws1.ws_order_number = ws2.ws_order_number) AND (ws1.ws_warehouse_sk <> ws2.ws_warehouse_sk) ) AND NOT EXISTS ( SELECT * FROM web_returns AS wr1 WHERE (ws1.ws_order_number = wr1.wr_order_number) ) ORDER BY count(DISTINCT ws_order_number) LIMIT 100", + "WITH ws_wh AS ( SELECT ws1.ws_order_number, ws1.ws_warehouse_sk AS wh1, ws2.ws_warehouse_sk AS wh2 FROM web_sales AS ws1, web_sales AS ws2 WHERE (ws1.ws_order_number = ws2.ws_order_number) AND (ws1.ws_warehouse_sk != ws2.ws_warehouse_sk) ) SELECT countDistinct(ws_order_number) AS `order count`, sum(ws_ext_ship_cost) AS `total shipping cost`, sum(ws_net_profit) AS `total net profit` FROM web_sales AS ws1, date_dim, customer_address, web_site WHERE ((d_date >= '1999-2-01') AND (d_date <= (CAST('1999-2-01', 'date') + INTERVAL 60 DAY))) AND (ws1.ws_ship_date_sk = d_date_sk) AND (ws1.ws_ship_addr_sk = ca_address_sk) AND (ca_state = 'IL') AND (ws1.ws_web_site_sk = web_site_sk) AND (web_company_name = 'pri') AND (ws1.ws_order_number IN ( SELECT ws_order_number FROM ws_wh )) AND (ws1.ws_order_number IN ( SELECT wr_order_number FROM web_returns, ws_wh WHERE (wr_order_number = ws_wh.ws_order_number) )) ORDER BY countDistinct(ws_order_number) LIMIT 100", + "SELECT count(*) FROM store_sales, household_demographics, time_dim, store WHERE (ss_sold_time_sk = time_dim.t_time_sk) AND (ss_hdemo_sk = household_demographics.hd_demo_sk) AND (ss_store_sk = s_store_sk) AND (time_dim.t_hour = 20) AND (time_dim.t_minute >= 30) AND (household_demographics.hd_dep_count = 7) AND (store.s_store_name = 'ese') ORDER BY count(*) LIMIT 100", + "WITH ssci AS ( SELECT ss_customer_sk AS customer_sk, ss_item_sk AS item_sk FROM store_sales, date_dim WHERE (ss_sold_date_sk = d_date_sk) AND (d_month_seq BETWEEN 1200 AND 1200 + 11) GROUP BY ss_customer_sk, ss_item_sk ), csci AS ( SELECT cs_bill_customer_sk AS customer_sk, cs_item_sk AS item_sk FROM catalog_sales, date_dim WHERE (cs_sold_date_sk = d_date_sk) AND (d_month_seq BETWEEN 1200 AND 1200 + 11) GROUP BY cs_bill_customer_sk, cs_item_sk ) SELECT sum(CASE WHEN (ssci.customer_sk IS NOT NULL) AND (csci.customer_sk IS NULL) THEN 1 ELSE 0 END) AS store_only, sum(CASE WHEN (ssci.customer_sk IS NULL) AND (csci.customer_sk IS NOT NULL) THEN 1 ELSE 0 END) AS catalog_only, sum(CASE WHEN (ssci.customer_sk IS NOT NULL) AND (csci.customer_sk IS NOT NULL) THEN 1 ELSE 0 END) AS store_and_catalog FROM ssci FULL OUTER JOIN csci ON (ssci.customer_sk = csci.customer_sk) AND (ssci.item_sk = csci.item_sk) LIMIT 100", + "SELECT i_item_id, i_item_desc, i_category, i_class, i_current_price, sum(ss_ext_sales_price) AS itemrevenue, sum(ss_ext_sales_price) * 100 / sum(sum(ss_ext_sales_price)) OVER (PARTITION BY i_class) AS revenueratio FROM store_sales, item, date_dim WHERE (ss_item_sk = i_item_sk) AND (i_category IN ('Sports', 'Books', 'Home')) AND (ss_sold_date_sk = d_date_sk) AND (d_date BETWEEN CAST('1999-02-22', 'date') AND (CAST('1999-02-22', 'date') + INTERVAL 30 DAY)) GROUP BY i_item_id, i_item_desc, i_category, i_class, i_current_price ORDER BY i_category, i_class, i_item_id, i_item_desc, revenueratio", + "SELECT substr(w_warehouse_name, 1, 20), sm_type, cc_name, sum(CASE WHEN (cs_ship_date_sk - cs_sold_date_sk <= 30) THEN 1 ELSE 0 END) AS \"30 days\", sum(CASE WHEN (cs_ship_date_sk - cs_sold_date_sk > 30) AND (cs_ship_date_sk - cs_sold_date_sk <= 60) THEN 1 ELSE 0 END) AS \"31-60 days\", sum(CASE WHEN (cs_ship_date_sk - cs_sold_date_sk > 60) AND (cs_ship_date_sk - cs_sold_date_sk <= 90) THEN 1 ELSE 0 END) AS \"61-90 days\", sum(CASE WHEN (cs_ship_date_sk - cs_sold_date_sk > 90) AND (cs_ship_date_sk - cs_sold_date_sk <= 120) THEN 1 ELSE 0 END) AS \"91-120 days\", sum(CASE WHEN (cs_ship_date_sk - cs_sold_date_sk > 120) THEN 1 ELSE 0 END) AS \">120 days\" FROM catalog_sales, warehouse, ship_mode, call_center, date_dim WHERE (d_month_seq BETWEEN 1200 AND 1200 + 11) AND (cs_ship_date_sk = d_date_sk) AND (cs_warehouse_sk = w_warehouse_sk) AND (cs_ship_mode_sk = sm_ship_mode_sk) AND (cs_call_center_sk = cc_call_center_sk) GROUP BY substr(w_warehouse_name, 1, 20), sm_type, cc_name ORDER BY substr(w_warehouse_name, 1, 20), sm_type, cc_name LIMIT 100" +]}, +{"name":"job","queries":[ + "SELECT MIN(mc.note) AS production_note, MIN(t.title) AS movie_title, MIN(t.production_year) AS movie_year FROM company_type AS ct, info_type AS it, movie_companies AS mc, movie_info_idx AS mi_idx, title AS t WHERE ct.kind = 'production companies' AND it.info = 'top 250 rank' AND mc.note NOT LIKE '%(as Metro-Goldwyn-Mayer Pictures)%' AND (mc.note LIKE '%(co-production)%' OR mc.note LIKE '%(presents)%') AND ct.id = mc.company_type_id AND t.id = mc.movie_id AND t.id = mi_idx.movie_id AND mc.movie_id = mi_idx.movie_id AND it.id = mi_idx.info_type_id", + "SELECT MIN(mc.note) AS production_note, MIN(t.title) AS movie_title, MIN(t.production_year) AS movie_year FROM company_type AS ct, info_type AS it, movie_companies AS mc, movie_info_idx AS mi_idx, title AS t WHERE ct.kind = 'production companies' AND it.info = 'bottom 10 rank' AND mc.note NOT LIKE '%(as Metro-Goldwyn-Mayer Pictures)%' AND t.production_year BETWEEN 2005 AND 2010 AND ct.id = mc.company_type_id AND t.id = mc.movie_id AND t.id = mi_idx.movie_id AND mc.movie_id = mi_idx.movie_id AND it.id = mi_idx.info_type_id", + "SELECT MIN(mc.note) AS production_note, MIN(t.title) AS movie_title, MIN(t.production_year) AS movie_year FROM company_type AS ct, info_type AS it, movie_companies AS mc, movie_info_idx AS mi_idx, title AS t WHERE ct.kind = 'production companies' AND it.info = 'top 250 rank' AND mc.note NOT LIKE '%(as Metro-Goldwyn-Mayer Pictures)%' AND (mc.note LIKE '%(co-production)%') AND t.production_year >2010 AND ct.id = mc.company_type_id AND t.id = mc.movie_id AND t.id = mi_idx.movie_id AND mc.movie_id = mi_idx.movie_id AND it.id = mi_idx.info_type_id", + "SELECT MIN(mc.note) AS production_note, MIN(t.title) AS movie_title, MIN(t.production_year) AS movie_year FROM company_type AS ct, info_type AS it, movie_companies AS mc, movie_info_idx AS mi_idx, title AS t WHERE ct.kind = 'production companies' AND it.info = 'bottom 10 rank' AND mc.note NOT LIKE '%(as Metro-Goldwyn-Mayer Pictures)%' AND t.production_year >2000 AND ct.id = mc.company_type_id AND t.id = mc.movie_id AND t.id = mi_idx.movie_id AND mc.movie_id = mi_idx.movie_id AND it.id = mi_idx.info_type_id", + "SELECT MIN(t.title) AS movie_title FROM company_name AS cn, keyword AS k, movie_companies AS mc, movie_keyword AS mk, title AS t WHERE cn.country_code ='[de]' AND k.keyword ='character-name-in-title' AND cn.id = mc.company_id AND mc.movie_id = t.id AND t.id = mk.movie_id AND mk.keyword_id = k.id AND mc.movie_id = mk.movie_id", + "SELECT MIN(t.title) AS movie_title FROM company_name AS cn, keyword AS k, movie_companies AS mc, movie_keyword AS mk, title AS t WHERE cn.country_code ='[nl]' AND k.keyword ='character-name-in-title' AND cn.id = mc.company_id AND mc.movie_id = t.id AND t.id = mk.movie_id AND mk.keyword_id = k.id AND mc.movie_id = mk.movie_id", + "SELECT MIN(t.title) AS movie_title FROM company_name AS cn, keyword AS k, movie_companies AS mc, movie_keyword AS mk, title AS t WHERE cn.country_code ='[sm]' AND k.keyword ='character-name-in-title' AND cn.id = mc.company_id AND mc.movie_id = t.id AND t.id = mk.movie_id AND mk.keyword_id = k.id AND mc.movie_id = mk.movie_id", + "SELECT MIN(t.title) AS movie_title FROM company_name AS cn, keyword AS k, movie_companies AS mc, movie_keyword AS mk, title AS t WHERE cn.country_code ='[us]' AND k.keyword ='character-name-in-title' AND cn.id = mc.company_id AND mc.movie_id = t.id AND t.id = mk.movie_id AND mk.keyword_id = k.id AND mc.movie_id = mk.movie_id", + "SELECT MIN(t.title) AS movie_title FROM keyword AS k, movie_info AS mi, movie_keyword AS mk, title AS t WHERE k.keyword LIKE '%sequel%' AND mi.info IN ('Sweden', 'Norway', 'Germany', 'Denmark', 'Swedish', 'Denish', 'Norwegian', 'German') AND t.production_year > 2005 AND t.id = mi.movie_id AND t.id = mk.movie_id AND mk.movie_id = mi.movie_id AND k.id = mk.keyword_id", + "SELECT MIN(t.title) AS movie_title FROM keyword AS k, movie_info AS mi, movie_keyword AS mk, title AS t WHERE k.keyword LIKE '%sequel%' AND mi.info IN ('Bulgaria') AND t.production_year > 2010 AND t.id = mi.movie_id AND t.id = mk.movie_id AND mk.movie_id = mi.movie_id AND k.id = mk.keyword_id", + "SELECT MIN(t.title) AS movie_title FROM keyword AS k, movie_info AS mi, movie_keyword AS mk, title AS t WHERE k.keyword LIKE '%sequel%' AND mi.info IN ('Sweden', 'Norway', 'Germany', 'Denmark', 'Swedish', 'Denish', 'Norwegian', 'German', 'USA', 'American') AND t.production_year > 1990 AND t.id = mi.movie_id AND t.id = mk.movie_id AND mk.movie_id = mi.movie_id AND k.id = mk.keyword_id", + "SELECT MIN(mi_idx.info) AS rating, MIN(t.title) AS movie_title FROM info_type AS it, keyword AS k, movie_info_idx AS mi_idx, movie_keyword AS mk, title AS t WHERE it.info ='rating' AND k.keyword LIKE '%sequel%' AND mi_idx.info > '5.0' AND t.production_year > 2005 AND t.id = mi_idx.movie_id AND t.id = mk.movie_id AND mk.movie_id = mi_idx.movie_id AND k.id = mk.keyword_id AND it.id = mi_idx.info_type_id", + "SELECT MIN(mi_idx.info) AS rating, MIN(t.title) AS movie_title FROM info_type AS it, keyword AS k, movie_info_idx AS mi_idx, movie_keyword AS mk, title AS t WHERE it.info ='rating' AND k.keyword LIKE '%sequel%' AND mi_idx.info > '9.0' AND t.production_year > 2010 AND t.id = mi_idx.movie_id AND t.id = mk.movie_id AND mk.movie_id = mi_idx.movie_id AND k.id = mk.keyword_id AND it.id = mi_idx.info_type_id", + "SELECT MIN(mi_idx.info) AS rating, MIN(t.title) AS movie_title FROM info_type AS it, keyword AS k, movie_info_idx AS mi_idx, movie_keyword AS mk, title AS t WHERE it.info ='rating' AND k.keyword LIKE '%sequel%' AND mi_idx.info > '2.0' AND t.production_year > 1990 AND t.id = mi_idx.movie_id AND t.id = mk.movie_id AND mk.movie_id = mi_idx.movie_id AND k.id = mk.keyword_id AND it.id = mi_idx.info_type_id", + "SELECT MIN(t.title) AS typical_european_movie FROM company_type AS ct, info_type AS it, movie_companies AS mc, movie_info AS mi, title AS t WHERE ct.kind = 'production companies' AND mc.note LIKE '%(theatrical)%' AND mc.note LIKE '%(France)%' AND mi.info IN ('Sweden', 'Norway', 'Germany', 'Denmark', 'Swedish', 'Denish', 'Norwegian', 'German') AND t.production_year > 2005 AND t.id = mi.movie_id AND t.id = mc.movie_id AND mc.movie_id = mi.movie_id AND ct.id = mc.company_type_id AND it.id = mi.info_type_id", + "SELECT MIN(t.title) AS american_vhs_movie FROM company_type AS ct, info_type AS it, movie_companies AS mc, movie_info AS mi, title AS t WHERE ct.kind = 'production companies' AND mc.note LIKE '%(VHS)%' AND mc.note LIKE '%(USA)%' AND mc.note LIKE '%(1994)%' AND mi.info IN ('USA', 'America') AND t.production_year > 2010 AND t.id = mi.movie_id AND t.id = mc.movie_id AND mc.movie_id = mi.movie_id AND ct.id = mc.company_type_id AND it.id = mi.info_type_id", + "SELECT MIN(t.title) AS american_movie FROM company_type AS ct, info_type AS it, movie_companies AS mc, movie_info AS mi, title AS t WHERE ct.kind = 'production companies' AND mc.note NOT LIKE '%(TV)%' AND mc.note LIKE '%(USA)%' AND mi.info IN ('Sweden', 'Norway', 'Germany', 'Denmark', 'Swedish', 'Denish', 'Norwegian', 'German', 'USA', 'American') AND t.production_year > 1990 AND t.id = mi.movie_id AND t.id = mc.movie_id AND mc.movie_id = mi.movie_id AND ct.id = mc.company_type_id AND it.id = mi.info_type_id", + "SELECT MIN(k.keyword) AS movie_keyword, MIN(n.name) AS actor_name, MIN(t.title) AS marvel_movie FROM cast_info AS ci, keyword AS k, movie_keyword AS mk, name AS n, title AS t WHERE k.keyword = 'marvel-cinematic-universe' AND n.name LIKE '%Downey%Robert%' AND t.production_year > 2010 AND k.id = mk.keyword_id AND t.id = mk.movie_id AND t.id = ci.movie_id AND ci.movie_id = mk.movie_id AND n.id = ci.person_id", + "SELECT MIN(k.keyword) AS movie_keyword, MIN(n.name) AS actor_name, MIN(t.title) AS hero_movie FROM cast_info AS ci, keyword AS k, movie_keyword AS mk, name AS n, title AS t WHERE k.keyword IN ('superhero', 'sequel', 'second-part', 'marvel-comics', 'based-on-comic', 'tv-special', 'fight', 'violence') AND n.name LIKE '%Downey%Robert%' AND t.production_year > 2014 AND k.id = mk.keyword_id AND t.id = mk.movie_id AND t.id = ci.movie_id AND ci.movie_id = mk.movie_id AND n.id = ci.person_id", + "SELECT MIN(k.keyword) AS movie_keyword, MIN(n.name) AS actor_name, MIN(t.title) AS marvel_movie FROM cast_info AS ci, keyword AS k, movie_keyword AS mk, name AS n, title AS t WHERE k.keyword = 'marvel-cinematic-universe' AND n.name LIKE '%Downey%Robert%' AND t.production_year > 2014 AND k.id = mk.keyword_id AND t.id = mk.movie_id AND t.id = ci.movie_id AND ci.movie_id = mk.movie_id AND n.id = ci.person_id", + "SELECT MIN(k.keyword) AS movie_keyword, MIN(n.name) AS actor_name, MIN(t.title) AS hero_movie FROM cast_info AS ci, keyword AS k, movie_keyword AS mk, name AS n, title AS t WHERE k.keyword IN ('superhero', 'sequel', 'second-part', 'marvel-comics', 'based-on-comic', 'tv-special', 'fight', 'violence') AND n.name LIKE '%Downey%Robert%' AND t.production_year > 2000 AND k.id = mk.keyword_id AND t.id = mk.movie_id AND t.id = ci.movie_id AND ci.movie_id = mk.movie_id AND n.id = ci.person_id", + "SELECT MIN(k.keyword) AS movie_keyword, MIN(n.name) AS actor_name, MIN(t.title) AS marvel_movie FROM cast_info AS ci, keyword AS k, movie_keyword AS mk, name AS n, title AS t WHERE k.keyword = 'marvel-cinematic-universe' AND n.name LIKE '%Downey%Robert%' AND t.production_year > 2000 AND k.id = mk.keyword_id AND t.id = mk.movie_id AND t.id = ci.movie_id AND ci.movie_id = mk.movie_id AND n.id = ci.person_id", + "SELECT MIN(k.keyword) AS movie_keyword, MIN(n.name) AS actor_name, MIN(t.title) AS hero_movie FROM cast_info AS ci, keyword AS k, movie_keyword AS mk, name AS n, title AS t WHERE k.keyword IN ('superhero', 'sequel', 'second-part', 'marvel-comics', 'based-on-comic', 'tv-special', 'fight', 'violence') AND t.production_year > 2000 AND k.id = mk.keyword_id AND t.id = mk.movie_id AND t.id = ci.movie_id AND ci.movie_id = mk.movie_id AND n.id = ci.person_id", + "SELECT MIN(n.name) AS of_person, MIN(t.title) AS biography_movie FROM aka_name AS an, cast_info AS ci, info_type AS it, link_type AS lt, movie_link AS ml, name AS n, person_info AS pi, title AS t WHERE an.name LIKE '%a%' AND it.info ='mini biography' AND lt.link ='features' AND n.name_pcode_cf BETWEEN 'A' AND 'F' AND (n.gender='m' OR (n.gender = 'f' AND n.name LIKE 'B%')) AND pi.note ='Volker Boehm' AND t.production_year BETWEEN 1980 AND 1995 AND n.id = an.person_id AND n.id = pi.person_id AND ci.person_id = n.id AND t.id = ci.movie_id AND ml.linked_movie_id = t.id AND lt.id = ml.link_type_id AND it.id = pi.info_type_id AND pi.person_id = an.person_id AND pi.person_id = ci.person_id AND an.person_id = ci.person_id AND ci.movie_id = ml.linked_movie_id", + "SELECT MIN(n.name) AS of_person, MIN(t.title) AS biography_movie FROM aka_name AS an, cast_info AS ci, info_type AS it, link_type AS lt, movie_link AS ml, name AS n, person_info AS pi, title AS t WHERE an.name LIKE '%a%' AND it.info ='mini biography' AND lt.link ='features' AND n.name_pcode_cf LIKE 'D%' AND n.gender='m' AND pi.note ='Volker Boehm' AND t.production_year BETWEEN 1980 AND 1984 AND n.id = an.person_id AND n.id = pi.person_id AND ci.person_id = n.id AND t.id = ci.movie_id AND ml.linked_movie_id = t.id AND lt.id = ml.link_type_id AND it.id = pi.info_type_id AND pi.person_id = an.person_id AND pi.person_id = ci.person_id AND an.person_id = ci.person_id AND ci.movie_id = ml.linked_movie_id", + "SELECT MIN(n.name) AS cast_member_name, MIN(pi.info) AS cast_member_info FROM aka_name AS an, cast_info AS ci, info_type AS it, link_type AS lt, movie_link AS ml, name AS n, person_info AS pi, title AS t WHERE an.name IS NOT NULL AND (an.name LIKE '%a%' OR an.name LIKE 'A%') AND it.info ='mini biography' AND lt.link IN ('references', 'referenced in', 'features', 'featured in') AND n.name_pcode_cf BETWEEN 'A' AND 'F' AND (n.gender='m' OR (n.gender = 'f' AND n.name LIKE 'A%')) AND pi.note IS NOT NULL AND t.production_year BETWEEN 1980 AND 2010 AND n.id = an.person_id AND n.id = pi.person_id AND ci.person_id = n.id AND t.id = ci.movie_id AND ml.linked_movie_id = t.id AND lt.id = ml.link_type_id AND it.id = pi.info_type_id AND pi.person_id = an.person_id AND pi.person_id = ci.person_id AND an.person_id = ci.person_id AND ci.movie_id = ml.linked_movie_id", + "SELECT MIN(an1.name) AS actress_pseudonym, MIN(t.title) AS japanese_movie_dubbed FROM aka_name AS an1, cast_info AS ci, company_name AS cn, movie_companies AS mc, name AS n1, role_type AS rt, title AS t WHERE ci.note ='(voice: English version)' AND cn.country_code ='[jp]' AND mc.note LIKE '%(Japan)%' AND mc.note NOT LIKE '%(USA)%' AND n1.name LIKE '%Yo%' AND n1.name NOT LIKE '%Yu%' AND rt.role ='actress' AND an1.person_id = n1.id AND n1.id = ci.person_id AND ci.movie_id = t.id AND t.id = mc.movie_id AND mc.company_id = cn.id AND ci.role_id = rt.id AND an1.person_id = ci.person_id AND ci.movie_id = mc.movie_id", + "SELECT MIN(an.name) AS acress_pseudonym, MIN(t.title) AS japanese_anime_movie FROM aka_name AS an, cast_info AS ci, company_name AS cn, movie_companies AS mc, name AS n, role_type AS rt, title AS t WHERE ci.note ='(voice: English version)' AND cn.country_code ='[jp]' AND mc.note LIKE '%(Japan)%' AND mc.note NOT LIKE '%(USA)%' AND (mc.note LIKE '%(2006)%' OR mc.note LIKE '%(2007)%') AND n.name LIKE '%Yo%' AND n.name NOT LIKE '%Yu%' AND rt.role ='actress' AND t.production_year BETWEEN 2006 AND 2007 AND (t.title LIKE 'One Piece%' OR t.title LIKE 'Dragon Ball Z%') AND an.person_id = n.id AND n.id = ci.person_id AND ci.movie_id = t.id AND t.id = mc.movie_id AND mc.company_id = cn.id AND ci.role_id = rt.id AND an.person_id = ci.person_id AND ci.movie_id = mc.movie_id", + "SELECT MIN(a1.name) AS writer_pseudo_name, MIN(t.title) AS movie_title FROM aka_name AS a1, cast_info AS ci, company_name AS cn, movie_companies AS mc, name AS n1, role_type AS rt, title AS t WHERE cn.country_code ='[us]' AND rt.role ='writer' AND a1.person_id = n1.id AND n1.id = ci.person_id AND ci.movie_id = t.id AND t.id = mc.movie_id AND mc.company_id = cn.id AND ci.role_id = rt.id AND a1.person_id = ci.person_id AND ci.movie_id = mc.movie_id", + "SELECT MIN(an1.name) AS costume_designer_pseudo, MIN(t.title) AS movie_with_costumes FROM aka_name AS an1, cast_info AS ci, company_name AS cn, movie_companies AS mc, name AS n1, role_type AS rt, title AS t WHERE cn.country_code ='[us]' AND rt.role ='costume designer' AND an1.person_id = n1.id AND n1.id = ci.person_id AND ci.movie_id = t.id AND t.id = mc.movie_id AND mc.company_id = cn.id AND ci.role_id = rt.id AND an1.person_id = ci.person_id AND ci.movie_id = mc.movie_id", + "SELECT MIN(an.name) AS alternative_name, MIN(chn.name) AS character_name, MIN(t.title) AS movie FROM aka_name AS an, char_name AS chn, cast_info AS ci, company_name AS cn, movie_companies AS mc, name AS n, role_type AS rt, title AS t WHERE ci.note IN ('(voice)', '(voice: Japanese version)', '(voice) (uncredited)', '(voice: English version)') AND cn.country_code ='[us]' AND mc.note IS NOT NULL AND (mc.note LIKE '%(USA)%' OR mc.note LIKE '%(worldwide)%') AND n.gender ='f' AND n.name LIKE '%Ang%' AND rt.role ='actress' AND t.production_year BETWEEN 2005 AND 2015 AND ci.movie_id = t.id AND t.id = mc.movie_id AND ci.movie_id = mc.movie_id AND mc.company_id = cn.id AND ci.role_id = rt.id AND n.id = ci.person_id AND chn.id = ci.person_role_id AND an.person_id = n.id AND an.person_id = ci.person_id", + "SELECT MIN(an.name) AS alternative_name, MIN(chn.name) AS voiced_character, MIN(n.name) AS voicing_actress, MIN(t.title) AS american_movie FROM aka_name AS an, char_name AS chn, cast_info AS ci, company_name AS cn, movie_companies AS mc, name AS n, role_type AS rt, title AS t WHERE ci.note = '(voice)' AND cn.country_code ='[us]' AND mc.note LIKE '%(200%)%' AND (mc.note LIKE '%(USA)%' OR mc.note LIKE '%(worldwide)%') AND n.gender ='f' AND n.name LIKE '%Angel%' AND rt.role ='actress' AND t.production_year BETWEEN 2007 AND 2010 AND ci.movie_id = t.id AND t.id = mc.movie_id AND ci.movie_id = mc.movie_id AND mc.company_id = cn.id AND ci.role_id = rt.id AND n.id = ci.person_id AND chn.id = ci.person_role_id AND an.person_id = n.id AND an.person_id = ci.person_id", + "SELECT MIN(an.name) AS alternative_name, MIN(chn.name) AS voiced_character_name, MIN(n.name) AS voicing_actress, MIN(t.title) AS american_movie FROM aka_name AS an, char_name AS chn, cast_info AS ci, company_name AS cn, movie_companies AS mc, name AS n, role_type AS rt, title AS t WHERE ci.note IN ('(voice)', '(voice: Japanese version)', '(voice) (uncredited)', '(voice: English version)') AND cn.country_code ='[us]' AND n.gender ='f' AND n.name LIKE '%An%' AND rt.role ='actress' AND ci.movie_id = t.id AND t.id = mc.movie_id AND ci.movie_id = mc.movie_id AND mc.company_id = cn.id AND ci.role_id = rt.id AND n.id = ci.person_id AND chn.id = ci.person_role_id AND an.person_id = n.id AND an.person_id = ci.person_id", + "SELECT MIN(an.name) AS alternative_name, MIN(chn.name) AS voiced_char_name, MIN(n.name) AS voicing_actress, MIN(t.title) AS american_movie FROM aka_name AS an, char_name AS chn, cast_info AS ci, company_name AS cn, movie_companies AS mc, name AS n, role_type AS rt, title AS t WHERE ci.note IN ('(voice)', '(voice: Japanese version)', '(voice) (uncredited)', '(voice: English version)') AND cn.country_code ='[us]' AND n.gender ='f' AND rt.role ='actress' AND ci.movie_id = t.id AND t.id = mc.movie_id AND ci.movie_id = mc.movie_id AND mc.company_id = cn.id AND ci.role_id = rt.id AND n.id = ci.person_id AND chn.id = ci.person_role_id AND an.person_id = n.id AND an.person_id = ci.person_id", + "SELECT MIN(chn.name) AS uncredited_voiced_character, MIN(t.title) AS russian_movie FROM char_name AS chn, cast_info AS ci, company_name AS cn, company_type AS ct, movie_companies AS mc, role_type AS rt, title AS t WHERE ci.note LIKE '%(voice)%' AND ci.note LIKE '%(uncredited)%' AND cn.country_code = '[ru]' AND rt.role = 'actor' AND t.production_year > 2005 AND t.id = mc.movie_id AND t.id = ci.movie_id AND ci.movie_id = mc.movie_id AND chn.id = ci.person_role_id AND rt.id = ci.role_id AND cn.id = mc.company_id AND ct.id = mc.company_type_id", + "SELECT MIN(chn.name) AS character, MIN(t.title) AS russian_mov_with_actor_producer FROM char_name AS chn, cast_info AS ci, company_name AS cn, company_type AS ct, movie_companies AS mc, role_type AS rt, title AS t WHERE ci.note LIKE '%(producer)%' AND cn.country_code = '[ru]' AND rt.role = 'actor' AND t.production_year > 2010 AND t.id = mc.movie_id AND t.id = ci.movie_id AND ci.movie_id = mc.movie_id AND chn.id = ci.person_role_id AND rt.id = ci.role_id AND cn.id = mc.company_id AND ct.id = mc.company_type_id", + "SELECT MIN(chn.name) AS character, MIN(t.title) AS movie_with_american_producer FROM char_name AS chn, cast_info AS ci, company_name AS cn, company_type AS ct, movie_companies AS mc, role_type AS rt, title AS t WHERE ci.note LIKE '%(producer)%' AND cn.country_code = '[us]' AND t.production_year > 1990 AND t.id = mc.movie_id AND t.id = ci.movie_id AND ci.movie_id = mc.movie_id AND chn.id = ci.person_role_id AND rt.id = ci.role_id AND cn.id = mc.company_id AND ct.id = mc.company_type_id", + "SELECT MIN(cn.name) AS from_company, MIN(lt.link) AS movie_link_type, MIN(t.title) AS non_polish_sequel_movie FROM company_name AS cn, company_type AS ct, keyword AS k, link_type AS lt, movie_companies AS mc, movie_keyword AS mk, movie_link AS ml, title AS t WHERE cn.country_code !='[pl]' AND (cn.name LIKE '%Film%' OR cn.name LIKE '%Warner%') AND ct.kind ='production companies' AND k.keyword ='sequel' AND lt.link LIKE '%follow%' AND mc.note IS NULL AND t.production_year BETWEEN 1950 AND 2000 AND lt.id = ml.link_type_id AND ml.movie_id = t.id AND t.id = mk.movie_id AND mk.keyword_id = k.id AND t.id = mc.movie_id AND mc.company_type_id = ct.id AND mc.company_id = cn.id AND ml.movie_id = mk.movie_id AND ml.movie_id = mc.movie_id AND mk.movie_id = mc.movie_id", + "SELECT MIN(cn.name) AS from_company, MIN(lt.link) AS movie_link_type, MIN(t.title) AS sequel_movie FROM company_name AS cn, company_type AS ct, keyword AS k, link_type AS lt, movie_companies AS mc, movie_keyword AS mk, movie_link AS ml, title AS t WHERE cn.country_code !='[pl]' AND (cn.name LIKE '%Film%' OR cn.name LIKE '%Warner%') AND ct.kind ='production companies' AND k.keyword ='sequel' AND lt.link LIKE '%follows%' AND mc.note IS NULL AND t.production_year = 1998 AND t.title LIKE '%Money%' AND lt.id = ml.link_type_id AND ml.movie_id = t.id AND t.id = mk.movie_id AND mk.keyword_id = k.id AND t.id = mc.movie_id AND mc.company_type_id = ct.id AND mc.company_id = cn.id AND ml.movie_id = mk.movie_id AND ml.movie_id = mc.movie_id AND mk.movie_id = mc.movie_id", + "SELECT MIN(cn.name) AS from_company, MIN(mc.note) AS production_note, MIN(t.title) AS movie_based_on_book FROM company_name AS cn, company_type AS ct, keyword AS k, link_type AS lt, movie_companies AS mc, movie_keyword AS mk, movie_link AS ml, title AS t WHERE cn.country_code !='[pl]' AND (cn.name LIKE '20th Century Fox%' OR cn.name LIKE 'Twentieth Century Fox%') AND ct.kind != 'production companies' AND ct.kind IS NOT NULL AND k.keyword IN ('sequel', 'revenge', 'based-on-novel') AND mc.note IS NOT NULL AND t.production_year > 1950 AND lt.id = ml.link_type_id AND ml.movie_id = t.id AND t.id = mk.movie_id AND mk.keyword_id = k.id AND t.id = mc.movie_id AND mc.company_type_id = ct.id AND mc.company_id = cn.id AND ml.movie_id = mk.movie_id AND ml.movie_id = mc.movie_id AND mk.movie_id = mc.movie_id", + "SELECT MIN(cn.name) AS from_company, MIN(mc.note) AS production_note, MIN(t.title) AS movie_based_on_book FROM company_name AS cn, company_type AS ct, keyword AS k, link_type AS lt, movie_companies AS mc, movie_keyword AS mk, movie_link AS ml, title AS t WHERE cn.country_code !='[pl]' AND ct.kind != 'production companies' AND ct.kind IS NOT NULL AND k.keyword IN ('sequel', 'revenge', 'based-on-novel') AND mc.note IS NOT NULL AND t.production_year > 1950 AND lt.id = ml.link_type_id AND ml.movie_id = t.id AND t.id = mk.movie_id AND mk.keyword_id = k.id AND t.id = mc.movie_id AND mc.company_type_id = ct.id AND mc.company_id = cn.id AND ml.movie_id = mk.movie_id AND ml.movie_id = mc.movie_id AND mk.movie_id = mc.movie_id", + "SELECT MIN(cn.name) AS movie_company, MIN(mi_idx.info) AS rating, MIN(t.title) AS drama_horror_movie FROM company_name AS cn, company_type AS ct, info_type AS it1, info_type AS it2, movie_companies AS mc, movie_info AS mi, movie_info_idx AS mi_idx, title AS t WHERE cn.country_code = '[us]' AND ct.kind = 'production companies' AND it1.info = 'genres' AND it2.info = 'rating' AND mi.info IN ('Drama', 'Horror') AND mi_idx.info > '8.0' AND t.production_year BETWEEN 2005 AND 2008 AND t.id = mi.movie_id AND t.id = mi_idx.movie_id AND mi.info_type_id = it1.id AND mi_idx.info_type_id = it2.id AND t.id = mc.movie_id AND ct.id = mc.company_type_id AND cn.id = mc.company_id AND mc.movie_id = mi.movie_id AND mc.movie_id = mi_idx.movie_id AND mi.movie_id = mi_idx.movie_id", + "SELECT MIN(mi.info) AS budget, MIN(t.title) AS unsuccsessful_movie FROM company_name AS cn, company_type AS ct, info_type AS it1, info_type AS it2, movie_companies AS mc, movie_info AS mi, movie_info_idx AS mi_idx, title AS t WHERE cn.country_code ='[us]' AND ct.kind IS NOT NULL AND (ct.kind ='production companies' OR ct.kind = 'distributors') AND it1.info ='budget' AND it2.info ='bottom 10 rank' AND t.production_year >2000 AND (t.title LIKE 'Birdemic%' OR t.title LIKE '%Movie%') AND t.id = mi.movie_id AND t.id = mi_idx.movie_id AND mi.info_type_id = it1.id AND mi_idx.info_type_id = it2.id AND t.id = mc.movie_id AND ct.id = mc.company_type_id AND cn.id = mc.company_id AND mc.movie_id = mi.movie_id AND mc.movie_id = mi_idx.movie_id AND mi.movie_id = mi_idx.movie_id", + "SELECT MIN(cn.name) AS movie_company, MIN(mi_idx.info) AS rating, MIN(t.title) AS mainstream_movie FROM company_name AS cn, company_type AS ct, info_type AS it1, info_type AS it2, movie_companies AS mc, movie_info AS mi, movie_info_idx AS mi_idx, title AS t WHERE cn.country_code = '[us]' AND ct.kind = 'production companies' AND it1.info = 'genres' AND it2.info = 'rating' AND mi.info IN ('Drama', 'Horror', 'Western', 'Family') AND mi_idx.info > '7.0' AND t.production_year BETWEEN 2000 AND 2010 AND t.id = mi.movie_id AND t.id = mi_idx.movie_id AND mi.info_type_id = it1.id AND mi_idx.info_type_id = it2.id AND t.id = mc.movie_id AND ct.id = mc.company_type_id AND cn.id = mc.company_id AND mc.movie_id = mi.movie_id AND mc.movie_id = mi_idx.movie_id AND mi.movie_id = mi_idx.movie_id", + "SELECT MIN(mi.info) AS release_date, MIN(miidx.info) AS rating, MIN(t.title) AS german_movie FROM company_name AS cn, company_type AS ct, info_type AS it, info_type AS it2, kind_type AS kt, movie_companies AS mc, movie_info AS mi, movie_info_idx AS miidx, title AS t WHERE cn.country_code ='[de]' AND ct.kind ='production companies' AND it.info ='rating' AND it2.info ='release dates' AND kt.kind ='movie' AND mi.movie_id = t.id AND it2.id = mi.info_type_id AND kt.id = t.kind_id AND mc.movie_id = t.id AND cn.id = mc.company_id AND ct.id = mc.company_type_id AND miidx.movie_id = t.id AND it.id = miidx.info_type_id AND mi.movie_id = miidx.movie_id AND mi.movie_id = mc.movie_id AND miidx.movie_id = mc.movie_id", + "SELECT MIN(cn.name) AS producing_company, MIN(miidx.info) AS rating, MIN(t.title) AS movie_about_winning FROM company_name AS cn, company_type AS ct, info_type AS it, info_type AS it2, kind_type AS kt, movie_companies AS mc, movie_info AS mi, movie_info_idx AS miidx, title AS t WHERE cn.country_code ='[us]' AND ct.kind ='production companies' AND it.info ='rating' AND it2.info ='release dates' AND kt.kind ='movie' AND t.title != '' AND (t.title LIKE '%Champion%' OR t.title LIKE '%Loser%') AND mi.movie_id = t.id AND it2.id = mi.info_type_id AND kt.id = t.kind_id AND mc.movie_id = t.id AND cn.id = mc.company_id AND ct.id = mc.company_type_id AND miidx.movie_id = t.id AND it.id = miidx.info_type_id AND mi.movie_id = miidx.movie_id AND mi.movie_id = mc.movie_id AND miidx.movie_id = mc.movie_id", + "SELECT MIN(cn.name) AS producing_company, MIN(miidx.info) AS rating, MIN(t.title) AS movie_about_winning FROM company_name AS cn, company_type AS ct, info_type AS it, info_type AS it2, kind_type AS kt, movie_companies AS mc, movie_info AS mi, movie_info_idx AS miidx, title AS t WHERE cn.country_code ='[us]' AND ct.kind ='production companies' AND it.info ='rating' AND it2.info ='release dates' AND kt.kind ='movie' AND t.title != '' AND (t.title LIKE 'Champion%' OR t.title LIKE 'Loser%') AND mi.movie_id = t.id AND it2.id = mi.info_type_id AND kt.id = t.kind_id AND mc.movie_id = t.id AND cn.id = mc.company_id AND ct.id = mc.company_type_id AND miidx.movie_id = t.id AND it.id = miidx.info_type_id AND mi.movie_id = miidx.movie_id AND mi.movie_id = mc.movie_id AND miidx.movie_id = mc.movie_id", + "SELECT MIN(cn.name) AS producing_company, MIN(miidx.info) AS rating, MIN(t.title) AS movie FROM company_name AS cn, company_type AS ct, info_type AS it, info_type AS it2, kind_type AS kt, movie_companies AS mc, movie_info AS mi, movie_info_idx AS miidx, title AS t WHERE cn.country_code ='[us]' AND ct.kind ='production companies' AND it.info ='rating' AND it2.info ='release dates' AND kt.kind ='movie' AND mi.movie_id = t.id AND it2.id = mi.info_type_id AND kt.id = t.kind_id AND mc.movie_id = t.id AND cn.id = mc.company_id AND ct.id = mc.company_type_id AND miidx.movie_id = t.id AND it.id = miidx.info_type_id AND mi.movie_id = miidx.movie_id AND mi.movie_id = mc.movie_id AND miidx.movie_id = mc.movie_id", + "SELECT MIN(mi_idx.info) AS rating, MIN(t.title) AS northern_dark_movie FROM info_type AS it1, info_type AS it2, keyword AS k, kind_type AS kt, movie_info AS mi, movie_info_idx AS mi_idx, movie_keyword AS mk, title AS t WHERE it1.info = 'countries' AND it2.info = 'rating' AND k.keyword IN ('murder', 'murder-in-title', 'blood', 'violence') AND kt.kind = 'movie' AND mi.info IN ('Sweden', 'Norway', 'Germany', 'Denmark', 'Swedish', 'Denish', 'Norwegian', 'German', 'USA', 'American') AND mi_idx.info < '8.5' AND t.production_year > 2010 AND kt.id = t.kind_id AND t.id = mi.movie_id AND t.id = mk.movie_id AND t.id = mi_idx.movie_id AND mk.movie_id = mi.movie_id AND mk.movie_id = mi_idx.movie_id AND mi.movie_id = mi_idx.movie_id AND k.id = mk.keyword_id AND it1.id = mi.info_type_id AND it2.id = mi_idx.info_type_id", + "SELECT MIN(mi_idx.info) AS rating, MIN(t.title) AS western_dark_production FROM info_type AS it1, info_type AS it2, keyword AS k, kind_type AS kt, movie_info AS mi, movie_info_idx AS mi_idx, movie_keyword AS mk, title AS t WHERE it1.info = 'countries' AND it2.info = 'rating' AND k.keyword IN ('murder', 'murder-in-title') AND kt.kind = 'movie' AND mi.info IN ('Sweden', 'Norway', 'Germany', 'Denmark', 'Swedish', 'Denish', 'Norwegian', 'German', 'USA', 'American') AND mi_idx.info > '6.0' AND t.production_year > 2010 AND (t.title LIKE '%murder%' OR t.title LIKE '%Murder%' OR t.title LIKE '%Mord%') AND kt.id = t.kind_id AND t.id = mi.movie_id AND t.id = mk.movie_id AND t.id = mi_idx.movie_id AND mk.movie_id = mi.movie_id AND mk.movie_id = mi_idx.movie_id AND mi.movie_id = mi_idx.movie_id AND k.id = mk.keyword_id AND it1.id = mi.info_type_id AND it2.id = mi_idx.info_type_id", + "SELECT MIN(mi_idx.info) AS rating, MIN(t.title) AS north_european_dark_production FROM info_type AS it1, info_type AS it2, keyword AS k, kind_type AS kt, movie_info AS mi, movie_info_idx AS mi_idx, movie_keyword AS mk, title AS t WHERE it1.info = 'countries' AND it2.info = 'rating' AND k.keyword IS NOT NULL AND k.keyword IN ('murder', 'murder-in-title', 'blood', 'violence') AND kt.kind IN ('movie', 'episode') AND mi.info IN ('Sweden', 'Norway', 'Germany', 'Denmark', 'Swedish', 'Danish', 'Norwegian', 'German', 'USA', 'American') AND mi_idx.info < '8.5' AND t.production_year > 2005 AND kt.id = t.kind_id AND t.id = mi.movie_id AND t.id = mk.movie_id AND t.id = mi_idx.movie_id AND mk.movie_id = mi.movie_id AND mk.movie_id = mi_idx.movie_id AND mi.movie_id = mi_idx.movie_id AND k.id = mk.keyword_id AND it1.id = mi.info_type_id AND it2.id = mi_idx.info_type_id", + "SELECT MIN(mi.info) AS release_date, MIN(t.title) AS internet_movie FROM aka_title AS at, company_name AS cn, company_type AS ct, info_type AS it1, keyword AS k, movie_companies AS mc, movie_info AS mi, movie_keyword AS mk, title AS t WHERE cn.country_code = '[us]' AND it1.info = 'release dates' AND mc.note LIKE '%(200%)%' AND mc.note LIKE '%(worldwide)%' AND mi.note LIKE '%internet%' AND mi.info LIKE 'USA:% 200%' AND t.production_year > 2000 AND t.id = at.movie_id AND t.id = mi.movie_id AND t.id = mk.movie_id AND t.id = mc.movie_id AND mk.movie_id = mi.movie_id AND mk.movie_id = mc.movie_id AND mk.movie_id = at.movie_id AND mi.movie_id = mc.movie_id AND mi.movie_id = at.movie_id AND mc.movie_id = at.movie_id AND k.id = mk.keyword_id AND it1.id = mi.info_type_id AND cn.id = mc.company_id AND ct.id = mc.company_type_id", + "SELECT MIN(mi.info) AS release_date, MIN(t.title) AS youtube_movie FROM aka_title AS at, company_name AS cn, company_type AS ct, info_type AS it1, keyword AS k, movie_companies AS mc, movie_info AS mi, movie_keyword AS mk, title AS t WHERE cn.country_code = '[us]' AND cn.name = 'YouTube' AND it1.info = 'release dates' AND mc.note LIKE '%(200%)%' AND mc.note LIKE '%(worldwide)%' AND mi.note LIKE '%internet%' AND mi.info LIKE 'USA:% 200%' AND t.production_year BETWEEN 2005 AND 2010 AND t.id = at.movie_id AND t.id = mi.movie_id AND t.id = mk.movie_id AND t.id = mc.movie_id AND mk.movie_id = mi.movie_id AND mk.movie_id = mc.movie_id AND mk.movie_id = at.movie_id AND mi.movie_id = mc.movie_id AND mi.movie_id = at.movie_id AND mc.movie_id = at.movie_id AND k.id = mk.keyword_id AND it1.id = mi.info_type_id AND cn.id = mc.company_id AND ct.id = mc.company_type_id", + "SELECT MIN(mi.info) AS release_date, MIN(t.title) AS modern_american_internet_movie FROM aka_title AS at, company_name AS cn, company_type AS ct, info_type AS it1, keyword AS k, movie_companies AS mc, movie_info AS mi, movie_keyword AS mk, title AS t WHERE cn.country_code = '[us]' AND it1.info = 'release dates' AND mi.note LIKE '%internet%' AND mi.info IS NOT NULL AND (mi.info LIKE 'USA:% 199%' OR mi.info LIKE 'USA:% 200%') AND t.production_year > 1990 AND t.id = at.movie_id AND t.id = mi.movie_id AND t.id = mk.movie_id AND t.id = mc.movie_id AND mk.movie_id = mi.movie_id AND mk.movie_id = mc.movie_id AND mk.movie_id = at.movie_id AND mi.movie_id = mc.movie_id AND mi.movie_id = at.movie_id AND mc.movie_id = at.movie_id AND k.id = mk.keyword_id AND it1.id = mi.info_type_id AND cn.id = mc.company_id AND ct.id = mc.company_type_id", + "SELECT MIN(at.title) AS aka_title, MIN(t.title) AS internet_movie_title FROM aka_title AS at, company_name AS cn, company_type AS ct, info_type AS it1, keyword AS k, movie_companies AS mc, movie_info AS mi, movie_keyword AS mk, title AS t WHERE cn.country_code = '[us]' AND it1.info = 'release dates' AND mi.note LIKE '%internet%' AND t.production_year > 1990 AND t.id = at.movie_id AND t.id = mi.movie_id AND t.id = mk.movie_id AND t.id = mc.movie_id AND mk.movie_id = mi.movie_id AND mk.movie_id = mc.movie_id AND mk.movie_id = at.movie_id AND mi.movie_id = mc.movie_id AND mi.movie_id = at.movie_id AND mc.movie_id = at.movie_id AND k.id = mk.keyword_id AND it1.id = mi.info_type_id AND cn.id = mc.company_id AND ct.id = mc.company_type_id", + "SELECT MIN(an.name) AS cool_actor_pseudonym, MIN(t.title) AS series_named_after_char FROM aka_name AS an, cast_info AS ci, company_name AS cn, keyword AS k, movie_companies AS mc, movie_keyword AS mk, name AS n, title AS t WHERE cn.country_code ='[us]' AND k.keyword ='character-name-in-title' AND t.episode_nr >= 50 AND t.episode_nr < 100 AND an.person_id = n.id AND n.id = ci.person_id AND ci.movie_id = t.id AND t.id = mk.movie_id AND mk.keyword_id = k.id AND t.id = mc.movie_id AND mc.company_id = cn.id AND an.person_id = ci.person_id AND ci.movie_id = mc.movie_id AND ci.movie_id = mk.movie_id AND mc.movie_id = mk.movie_id", + "SELECT MIN(an.name) AS cool_actor_pseudonym, MIN(t.title) AS series_named_after_char FROM aka_name AS an, cast_info AS ci, company_name AS cn, keyword AS k, movie_companies AS mc, movie_keyword AS mk, name AS n, title AS t WHERE cn.country_code ='[us]' AND k.keyword ='character-name-in-title' AND an.person_id = n.id AND n.id = ci.person_id AND ci.movie_id = t.id AND t.id = mk.movie_id AND mk.keyword_id = k.id AND t.id = mc.movie_id AND mc.company_id = cn.id AND an.person_id = ci.person_id AND ci.movie_id = mc.movie_id AND ci.movie_id = mk.movie_id AND mc.movie_id = mk.movie_id", + "SELECT MIN(an.name) AS cool_actor_pseudonym, MIN(t.title) AS series_named_after_char FROM aka_name AS an, cast_info AS ci, company_name AS cn, keyword AS k, movie_companies AS mc, movie_keyword AS mk, name AS n, title AS t WHERE cn.country_code ='[us]' AND k.keyword ='character-name-in-title' AND t.episode_nr < 100 AND an.person_id = n.id AND n.id = ci.person_id AND ci.movie_id = t.id AND t.id = mk.movie_id AND mk.keyword_id = k.id AND t.id = mc.movie_id AND mc.company_id = cn.id AND an.person_id = ci.person_id AND ci.movie_id = mc.movie_id AND ci.movie_id = mk.movie_id AND mc.movie_id = mk.movie_id", + "SELECT MIN(an.name) AS cool_actor_pseudonym, MIN(t.title) AS series_named_after_char FROM aka_name AS an, cast_info AS ci, company_name AS cn, keyword AS k, movie_companies AS mc, movie_keyword AS mk, name AS n, title AS t WHERE cn.country_code ='[us]' AND k.keyword ='character-name-in-title' AND t.episode_nr >= 5 AND t.episode_nr < 100 AND an.person_id = n.id AND n.id = ci.person_id AND ci.movie_id = t.id AND t.id = mk.movie_id AND mk.keyword_id = k.id AND t.id = mc.movie_id AND mc.company_id = cn.id AND an.person_id = ci.person_id AND ci.movie_id = mc.movie_id AND ci.movie_id = mk.movie_id AND mc.movie_id = mk.movie_id", + "SELECT MIN(n.name) AS member_in_charnamed_american_movie, MIN(n.name) AS a1 FROM cast_info AS ci, company_name AS cn, keyword AS k, movie_companies AS mc, movie_keyword AS mk, name AS n, title AS t WHERE cn.country_code ='[us]' AND k.keyword ='character-name-in-title' AND n.name LIKE 'B%' AND n.id = ci.person_id AND ci.movie_id = t.id AND t.id = mk.movie_id AND mk.keyword_id = k.id AND t.id = mc.movie_id AND mc.company_id = cn.id AND ci.movie_id = mc.movie_id AND ci.movie_id = mk.movie_id AND mc.movie_id = mk.movie_id", + "SELECT MIN(n.name) AS member_in_charnamed_movie, MIN(n.name) AS a1 FROM cast_info AS ci, company_name AS cn, keyword AS k, movie_companies AS mc, movie_keyword AS mk, name AS n, title AS t WHERE k.keyword ='character-name-in-title' AND n.name LIKE 'Z%' AND n.id = ci.person_id AND ci.movie_id = t.id AND t.id = mk.movie_id AND mk.keyword_id = k.id AND t.id = mc.movie_id AND mc.company_id = cn.id AND ci.movie_id = mc.movie_id AND ci.movie_id = mk.movie_id AND mc.movie_id = mk.movie_id", + "SELECT MIN(n.name) AS member_in_charnamed_movie, MIN(n.name) AS a1 FROM cast_info AS ci, company_name AS cn, keyword AS k, movie_companies AS mc, movie_keyword AS mk, name AS n, title AS t WHERE k.keyword ='character-name-in-title' AND n.name LIKE 'X%' AND n.id = ci.person_id AND ci.movie_id = t.id AND t.id = mk.movie_id AND mk.keyword_id = k.id AND t.id = mc.movie_id AND mc.company_id = cn.id AND ci.movie_id = mc.movie_id AND ci.movie_id = mk.movie_id AND mc.movie_id = mk.movie_id", + "SELECT MIN(n.name) AS member_in_charnamed_movie FROM cast_info AS ci, company_name AS cn, keyword AS k, movie_companies AS mc, movie_keyword AS mk, name AS n, title AS t WHERE k.keyword ='character-name-in-title' AND n.name LIKE '%Bert%' AND n.id = ci.person_id AND ci.movie_id = t.id AND t.id = mk.movie_id AND mk.keyword_id = k.id AND t.id = mc.movie_id AND mc.company_id = cn.id AND ci.movie_id = mc.movie_id AND ci.movie_id = mk.movie_id AND mc.movie_id = mk.movie_id", + "SELECT MIN(n.name) AS member_in_charnamed_movie FROM cast_info AS ci, company_name AS cn, keyword AS k, movie_companies AS mc, movie_keyword AS mk, name AS n, title AS t WHERE cn.country_code ='[us]' AND k.keyword ='character-name-in-title' AND n.id = ci.person_id AND ci.movie_id = t.id AND t.id = mk.movie_id AND mk.keyword_id = k.id AND t.id = mc.movie_id AND mc.company_id = cn.id AND ci.movie_id = mc.movie_id AND ci.movie_id = mk.movie_id AND mc.movie_id = mk.movie_id", + "SELECT MIN(n.name) AS member_in_charnamed_movie FROM cast_info AS ci, company_name AS cn, keyword AS k, movie_companies AS mc, movie_keyword AS mk, name AS n, title AS t WHERE k.keyword ='character-name-in-title' AND n.name LIKE '%B%' AND n.id = ci.person_id AND ci.movie_id = t.id AND t.id = mk.movie_id AND mk.keyword_id = k.id AND t.id = mc.movie_id AND mc.company_id = cn.id AND ci.movie_id = mc.movie_id AND ci.movie_id = mk.movie_id AND mc.movie_id = mk.movie_id", + "SELECT MIN(mi.info) AS movie_budget, MIN(mi_idx.info) AS movie_votes, MIN(t.title) AS movie_title FROM cast_info AS ci, info_type AS it1, info_type AS it2, movie_info AS mi, movie_info_idx AS mi_idx, name AS n, title AS t WHERE ci.note IN ('(producer)', '(executive producer)') AND it1.info = 'budget' AND it2.info = 'votes' AND n.gender = 'm' AND n.name LIKE '%Tim%' AND t.id = mi.movie_id AND t.id = mi_idx.movie_id AND t.id = ci.movie_id AND ci.movie_id = mi.movie_id AND ci.movie_id = mi_idx.movie_id AND mi.movie_id = mi_idx.movie_id AND n.id = ci.person_id AND it1.id = mi.info_type_id AND it2.id = mi_idx.info_type_id", + "SELECT MIN(mi.info) AS movie_budget, MIN(mi_idx.info) AS movie_votes, MIN(t.title) AS movie_title FROM cast_info AS ci, info_type AS it1, info_type AS it2, movie_info AS mi, movie_info_idx AS mi_idx, name AS n, title AS t WHERE ci.note IN ('(writer)', '(head writer)', '(written by)', '(story)', '(story editor)') AND it1.info = 'genres' AND it2.info = 'rating' AND mi.info IN ('Horror', 'Thriller') AND mi.note IS NULL AND mi_idx.info > '8.0' AND n.gender IS NOT NULL AND n.gender = 'f' AND t.production_year BETWEEN 2008 AND 2014 AND t.id = mi.movie_id AND t.id = mi_idx.movie_id AND t.id = ci.movie_id AND ci.movie_id = mi.movie_id AND ci.movie_id = mi_idx.movie_id AND mi.movie_id = mi_idx.movie_id AND n.id = ci.person_id AND it1.id = mi.info_type_id AND it2.id = mi_idx.info_type_id", + "SELECT MIN(mi.info) AS movie_budget, MIN(mi_idx.info) AS movie_votes, MIN(t.title) AS movie_title FROM cast_info AS ci, info_type AS it1, info_type AS it2, movie_info AS mi, movie_info_idx AS mi_idx, name AS n, title AS t WHERE ci.note IN ('(writer)', '(head writer)', '(written by)', '(story)', '(story editor)') AND it1.info = 'genres' AND it2.info = 'votes' AND mi.info IN ('Horror', 'Action', 'Sci-Fi', 'Thriller', 'Crime', 'War') AND n.gender = 'm' AND t.id = mi.movie_id AND t.id = mi_idx.movie_id AND t.id = ci.movie_id AND ci.movie_id = mi.movie_id AND ci.movie_id = mi_idx.movie_id AND mi.movie_id = mi_idx.movie_id AND n.id = ci.person_id AND it1.id = mi.info_type_id AND it2.id = mi_idx.info_type_id", + "SELECT MIN(n.name) AS voicing_actress, MIN(t.title) AS voiced_movie FROM aka_name AS an, char_name AS chn, cast_info AS ci, company_name AS cn, info_type AS it, movie_companies AS mc, movie_info AS mi, name AS n, role_type AS rt, title AS t WHERE ci.note IN ('(voice)', '(voice: Japanese version)', '(voice) (uncredited)', '(voice: English version)') AND cn.country_code ='[us]' AND it.info = 'release dates' AND mc.note IS NOT NULL AND (mc.note LIKE '%(USA)%' OR mc.note LIKE '%(worldwide)%') AND mi.info IS NOT NULL AND (mi.info LIKE 'Japan:%200%' OR mi.info LIKE 'USA:%200%') AND n.gender ='f' AND n.name LIKE '%Ang%' AND rt.role ='actress' AND t.production_year BETWEEN 2005 AND 2009 AND t.id = mi.movie_id AND t.id = mc.movie_id AND t.id = ci.movie_id AND mc.movie_id = ci.movie_id AND mc.movie_id = mi.movie_id AND mi.movie_id = ci.movie_id AND cn.id = mc.company_id AND it.id = mi.info_type_id AND n.id = ci.person_id AND rt.id = ci.role_id AND n.id = an.person_id AND ci.person_id = an.person_id AND chn.id = ci.person_role_id", + "SELECT MIN(n.name) AS voicing_actress, MIN(t.title) AS kung_fu_panda FROM aka_name AS an, char_name AS chn, cast_info AS ci, company_name AS cn, info_type AS it, movie_companies AS mc, movie_info AS mi, name AS n, role_type AS rt, title AS t WHERE ci.note = '(voice)' AND cn.country_code ='[us]' AND it.info = 'release dates' AND mc.note LIKE '%(200%)%' AND (mc.note LIKE '%(USA)%' OR mc.note LIKE '%(worldwide)%') AND mi.info IS NOT NULL AND (mi.info LIKE 'Japan:%2007%' OR mi.info LIKE 'USA:%2008%') AND n.gender ='f' AND n.name LIKE '%Angel%' AND rt.role ='actress' AND t.production_year BETWEEN 2007 AND 2008 AND t.title LIKE '%Kung%Fu%Panda%' AND t.id = mi.movie_id AND t.id = mc.movie_id AND t.id = ci.movie_id AND mc.movie_id = ci.movie_id AND mc.movie_id = mi.movie_id AND mi.movie_id = ci.movie_id AND cn.id = mc.company_id AND it.id = mi.info_type_id AND n.id = ci.person_id AND rt.id = ci.role_id AND n.id = an.person_id AND ci.person_id = an.person_id AND chn.id = ci.person_role_id", + "SELECT MIN(n.name) AS voicing_actress, MIN(t.title) AS jap_engl_voiced_movie FROM aka_name AS an, char_name AS chn, cast_info AS ci, company_name AS cn, info_type AS it, movie_companies AS mc, movie_info AS mi, name AS n, role_type AS rt, title AS t WHERE ci.note IN ('(voice)', '(voice: Japanese version)', '(voice) (uncredited)', '(voice: English version)') AND cn.country_code ='[us]' AND it.info = 'release dates' AND mi.info IS NOT NULL AND (mi.info LIKE 'Japan:%200%' OR mi.info LIKE 'USA:%200%') AND n.gender ='f' AND n.name LIKE '%An%' AND rt.role ='actress' AND t.production_year > 2000 AND t.id = mi.movie_id AND t.id = mc.movie_id AND t.id = ci.movie_id AND mc.movie_id = ci.movie_id AND mc.movie_id = mi.movie_id AND mi.movie_id = ci.movie_id AND cn.id = mc.company_id AND it.id = mi.info_type_id AND n.id = ci.person_id AND rt.id = ci.role_id AND n.id = an.person_id AND ci.person_id = an.person_id AND chn.id = ci.person_role_id", + "SELECT MIN(n.name) AS voicing_actress, MIN(t.title) AS jap_engl_voiced_movie FROM aka_name AS an, char_name AS chn, cast_info AS ci, company_name AS cn, info_type AS it, movie_companies AS mc, movie_info AS mi, name AS n, role_type AS rt, title AS t WHERE ci.note IN ('(voice)', '(voice: Japanese version)', '(voice) (uncredited)', '(voice: English version)') AND cn.country_code ='[us]' AND it.info = 'release dates' AND n.gender ='f' AND rt.role ='actress' AND t.production_year > 2000 AND t.id = mi.movie_id AND t.id = mc.movie_id AND t.id = ci.movie_id AND mc.movie_id = ci.movie_id AND mc.movie_id = mi.movie_id AND mi.movie_id = ci.movie_id AND cn.id = mc.company_id AND it.id = mi.info_type_id AND n.id = ci.person_id AND rt.id = ci.role_id AND n.id = an.person_id AND ci.person_id = an.person_id AND chn.id = ci.person_role_id", + "SELECT MIN(t.title) AS complete_downey_ironman_movie FROM complete_cast AS cc, comp_cast_type AS cct1, comp_cast_type AS cct2, char_name AS chn, cast_info AS ci, keyword AS k, kind_type AS kt, movie_keyword AS mk, name AS n, title AS t WHERE cct1.kind = 'cast' AND cct2.kind LIKE '%complete%' AND chn.name NOT LIKE '%Sherlock%' AND (chn.name LIKE '%Tony%Stark%' OR chn.name LIKE '%Iron%Man%') AND k.keyword IN ('superhero', 'sequel', 'second-part', 'marvel-comics', 'based-on-comic', 'tv-special', 'fight', 'violence') AND kt.kind = 'movie' AND t.production_year > 1950 AND kt.id = t.kind_id AND t.id = mk.movie_id AND t.id = ci.movie_id AND t.id = cc.movie_id AND mk.movie_id = ci.movie_id AND mk.movie_id = cc.movie_id AND ci.movie_id = cc.movie_id AND chn.id = ci.person_role_id AND n.id = ci.person_id AND k.id = mk.keyword_id AND cct1.id = cc.subject_id AND cct2.id = cc.status_id", + "SELECT MIN(t.title) AS complete_downey_ironman_movie FROM complete_cast AS cc, comp_cast_type AS cct1, comp_cast_type AS cct2, char_name AS chn, cast_info AS ci, keyword AS k, kind_type AS kt, movie_keyword AS mk, name AS n, title AS t WHERE cct1.kind = 'cast' AND cct2.kind LIKE '%complete%' AND chn.name NOT LIKE '%Sherlock%' AND (chn.name LIKE '%Tony%Stark%' OR chn.name LIKE '%Iron%Man%') AND k.keyword IN ('superhero', 'sequel', 'second-part', 'marvel-comics', 'based-on-comic', 'tv-special', 'fight', 'violence') AND kt.kind = 'movie' AND n.name LIKE '%Downey%Robert%' AND t.production_year > 2000 AND kt.id = t.kind_id AND t.id = mk.movie_id AND t.id = ci.movie_id AND t.id = cc.movie_id AND mk.movie_id = ci.movie_id AND mk.movie_id = cc.movie_id AND ci.movie_id = cc.movie_id AND chn.id = ci.person_role_id AND n.id = ci.person_id AND k.id = mk.keyword_id AND cct1.id = cc.subject_id AND cct2.id = cc.status_id", + "SELECT MIN(n.name) AS cast_member, MIN(t.title) AS complete_dynamic_hero_movie FROM complete_cast AS cc, comp_cast_type AS cct1, comp_cast_type AS cct2, char_name AS chn, cast_info AS ci, keyword AS k, kind_type AS kt, movie_keyword AS mk, name AS n, title AS t WHERE cct1.kind = 'cast' AND cct2.kind LIKE '%complete%' AND chn.name IS NOT NULL AND (chn.name LIKE '%man%' OR chn.name LIKE '%Man%') AND k.keyword IN ('superhero', 'marvel-comics', 'based-on-comic', 'tv-special', 'fight', 'violence', 'magnet', 'web', 'claw', 'laser') AND kt.kind = 'movie' AND t.production_year > 2000 AND kt.id = t.kind_id AND t.id = mk.movie_id AND t.id = ci.movie_id AND t.id = cc.movie_id AND mk.movie_id = ci.movie_id AND mk.movie_id = cc.movie_id AND ci.movie_id = cc.movie_id AND chn.id = ci.person_role_id AND n.id = ci.person_id AND k.id = mk.keyword_id AND cct1.id = cc.subject_id AND cct2.id = cc.status_id", + "SELECT MIN(cn.name) AS company_name, MIN(lt.link) AS link_type, MIN(t.title) AS western_follow_up FROM company_name AS cn, company_type AS ct, keyword AS k, link_type AS lt, movie_companies AS mc, movie_info AS mi, movie_keyword AS mk, movie_link AS ml, title AS t WHERE cn.country_code !='[pl]' AND (cn.name LIKE '%Film%' OR cn.name LIKE '%Warner%') AND ct.kind ='production companies' AND k.keyword ='sequel' AND lt.link LIKE '%follow%' AND mc.note IS NULL AND mi.info IN ('Sweden', 'Norway', 'Germany', 'Denmark', 'Swedish', 'Denish', 'Norwegian', 'German') AND t.production_year BETWEEN 1950 AND 2000 AND lt.id = ml.link_type_id AND ml.movie_id = t.id AND t.id = mk.movie_id AND mk.keyword_id = k.id AND t.id = mc.movie_id AND mc.company_type_id = ct.id AND mc.company_id = cn.id AND mi.movie_id = t.id AND ml.movie_id = mk.movie_id AND ml.movie_id = mc.movie_id AND mk.movie_id = mc.movie_id AND ml.movie_id = mi.movie_id AND mk.movie_id = mi.movie_id AND mc.movie_id = mi.movie_id", + "SELECT MIN(cn.name) AS company_name, MIN(lt.link) AS link_type, MIN(t.title) AS german_follow_up FROM company_name AS cn, company_type AS ct, keyword AS k, link_type AS lt, movie_companies AS mc, movie_info AS mi, movie_keyword AS mk, movie_link AS ml, title AS t WHERE cn.country_code !='[pl]' AND (cn.name LIKE '%Film%' OR cn.name LIKE '%Warner%') AND ct.kind ='production companies' AND k.keyword ='sequel' AND lt.link LIKE '%follow%' AND mc.note IS NULL AND mi.info IN ('Germany', 'German') AND t.production_year BETWEEN 2000 AND 2010 AND lt.id = ml.link_type_id AND ml.movie_id = t.id AND t.id = mk.movie_id AND mk.keyword_id = k.id AND t.id = mc.movie_id AND mc.company_type_id = ct.id AND mc.company_id = cn.id AND mi.movie_id = t.id AND ml.movie_id = mk.movie_id AND ml.movie_id = mc.movie_id AND mk.movie_id = mc.movie_id AND ml.movie_id = mi.movie_id AND mk.movie_id = mi.movie_id AND mc.movie_id = mi.movie_id", + "SELECT MIN(cn.name) AS company_name, MIN(lt.link) AS link_type, MIN(t.title) AS western_follow_up FROM company_name AS cn, company_type AS ct, keyword AS k, link_type AS lt, movie_companies AS mc, movie_info AS mi, movie_keyword AS mk, movie_link AS ml, title AS t WHERE cn.country_code !='[pl]' AND (cn.name LIKE '%Film%' OR cn.name LIKE '%Warner%') AND ct.kind ='production companies' AND k.keyword ='sequel' AND lt.link LIKE '%follow%' AND mc.note IS NULL AND mi.info IN ('Sweden', 'Norway', 'Germany', 'Denmark', 'Swedish', 'Denish', 'Norwegian', 'German', 'English') AND t.production_year BETWEEN 1950 AND 2010 AND lt.id = ml.link_type_id AND ml.movie_id = t.id AND t.id = mk.movie_id AND mk.keyword_id = k.id AND t.id = mc.movie_id AND mc.company_type_id = ct.id AND mc.company_id = cn.id AND mi.movie_id = t.id AND ml.movie_id = mk.movie_id AND ml.movie_id = mc.movie_id AND mk.movie_id = mc.movie_id AND ml.movie_id = mi.movie_id AND mk.movie_id = mi.movie_id AND mc.movie_id = mi.movie_id", + "SELECT MIN(cn.name) AS movie_company, MIN(mi_idx.info) AS rating, MIN(t.title) AS western_violent_movie FROM company_name AS cn, company_type AS ct, info_type AS it1, info_type AS it2, keyword AS k, kind_type AS kt, movie_companies AS mc, movie_info AS mi, movie_info_idx AS mi_idx, movie_keyword AS mk, title AS t WHERE cn.country_code != '[us]' AND it1.info = 'countries' AND it2.info = 'rating' AND k.keyword IN ('murder', 'murder-in-title', 'blood', 'violence') AND kt.kind IN ('movie', 'episode') AND mc.note NOT LIKE '%(USA)%' AND mc.note LIKE '%(200%)%' AND mi.info IN ('Germany', 'German', 'USA', 'American') AND mi_idx.info < '7.0' AND t.production_year > 2008 AND kt.id = t.kind_id AND t.id = mi.movie_id AND t.id = mk.movie_id AND t.id = mi_idx.movie_id AND t.id = mc.movie_id AND mk.movie_id = mi.movie_id AND mk.movie_id = mi_idx.movie_id AND mk.movie_id = mc.movie_id AND mi.movie_id = mi_idx.movie_id AND mi.movie_id = mc.movie_id AND mc.movie_id = mi_idx.movie_id AND k.id = mk.keyword_id AND it1.id = mi.info_type_id AND it2.id = mi_idx.info_type_id AND ct.id = mc.company_type_id AND cn.id = mc.company_id", + "SELECT MIN(cn.name) AS movie_company, MIN(mi_idx.info) AS rating, MIN(t.title) AS western_violent_movie FROM company_name AS cn, company_type AS ct, info_type AS it1, info_type AS it2, keyword AS k, kind_type AS kt, movie_companies AS mc, movie_info AS mi, movie_info_idx AS mi_idx, movie_keyword AS mk, title AS t WHERE cn.country_code != '[us]' AND it1.info = 'countries' AND it2.info = 'rating' AND k.keyword IN ('murder', 'murder-in-title', 'blood', 'violence') AND kt.kind IN ('movie', 'episode') AND mc.note NOT LIKE '%(USA)%' AND mc.note LIKE '%(200%)%' AND mi.info IN ('Germany', 'German', 'USA', 'American') AND mi_idx.info < '7.0' AND t.production_year > 2009 AND kt.id = t.kind_id AND t.id = mi.movie_id AND t.id = mk.movie_id AND t.id = mi_idx.movie_id AND t.id = mc.movie_id AND mk.movie_id = mi.movie_id AND mk.movie_id = mi_idx.movie_id AND mk.movie_id = mc.movie_id AND mi.movie_id = mi_idx.movie_id AND mi.movie_id = mc.movie_id AND mc.movie_id = mi_idx.movie_id AND k.id = mk.keyword_id AND it1.id = mi.info_type_id AND it2.id = mi_idx.info_type_id AND ct.id = mc.company_type_id AND cn.id = mc.company_id", + "SELECT MIN(cn.name) AS movie_company, MIN(mi_idx.info) AS rating, MIN(t.title) AS western_violent_movie FROM company_name AS cn, company_type AS ct, info_type AS it1, info_type AS it2, keyword AS k, kind_type AS kt, movie_companies AS mc, movie_info AS mi, movie_info_idx AS mi_idx, movie_keyword AS mk, title AS t WHERE cn.country_code != '[us]' AND it1.info = 'countries' AND it2.info = 'rating' AND k.keyword IN ('murder', 'murder-in-title', 'blood', 'violence') AND kt.kind IN ('movie', 'episode') AND mc.note NOT LIKE '%(USA)%' AND mc.note LIKE '%(200%)%' AND mi.info IN ('Sweden', 'Norway', 'Germany', 'Denmark', 'Swedish', 'Danish', 'Norwegian', 'German', 'USA', 'American') AND mi_idx.info < '8.5' AND t.production_year > 2005 AND kt.id = t.kind_id AND t.id = mi.movie_id AND t.id = mk.movie_id AND t.id = mi_idx.movie_id AND t.id = mc.movie_id AND mk.movie_id = mi.movie_id AND mk.movie_id = mi_idx.movie_id AND mk.movie_id = mc.movie_id AND mi.movie_id = mi_idx.movie_id AND mi.movie_id = mc.movie_id AND mc.movie_id = mi_idx.movie_id AND k.id = mk.keyword_id AND it1.id = mi.info_type_id AND it2.id = mi_idx.info_type_id AND ct.id = mc.company_type_id AND cn.id = mc.company_id", + "SELECT MIN(cn.name) AS movie_company, MIN(mi_idx.info) AS rating, MIN(t.title) AS western_violent_movie FROM company_name AS cn, company_type AS ct, info_type AS it1, info_type AS it2, keyword AS k, kind_type AS kt, movie_companies AS mc, movie_info AS mi, movie_info_idx AS mi_idx, movie_keyword AS mk, title AS t WHERE cn.country_code != '[us]' AND it1.info = 'countries' AND it2.info = 'rating' AND k.keyword IN ('murder', 'murder-in-title', 'blood', 'violence') AND kt.kind IN ('movie', 'episode') AND mi.info IN ('Sweden', 'Norway', 'Germany', 'Denmark', 'Swedish', 'Danish', 'Norwegian', 'German', 'USA', 'American') AND mi_idx.info < '8.5' AND t.production_year > 2005 AND kt.id = t.kind_id AND t.id = mi.movie_id AND t.id = mk.movie_id AND t.id = mi_idx.movie_id AND t.id = mc.movie_id AND mk.movie_id = mi.movie_id AND mk.movie_id = mi_idx.movie_id AND mk.movie_id = mc.movie_id AND mi.movie_id = mi_idx.movie_id AND mi.movie_id = mc.movie_id AND mc.movie_id = mi_idx.movie_id AND k.id = mk.keyword_id AND it1.id = mi.info_type_id AND it2.id = mi_idx.info_type_id AND ct.id = mc.company_type_id AND cn.id = mc.company_id", + "SELECT MIN(kt.kind) AS movie_kind, MIN(t.title) AS complete_us_internet_movie FROM complete_cast AS cc, comp_cast_type AS cct1, company_name AS cn, company_type AS ct, info_type AS it1, keyword AS k, kind_type AS kt, movie_companies AS mc, movie_info AS mi, movie_keyword AS mk, title AS t WHERE cct1.kind = 'complete+verified' AND cn.country_code = '[us]' AND it1.info = 'release dates' AND kt.kind IN ('movie') AND mi.note LIKE '%internet%' AND mi.info IS NOT NULL AND (mi.info LIKE 'USA:% 199%' OR mi.info LIKE 'USA:% 200%') AND t.production_year > 2000 AND kt.id = t.kind_id AND t.id = mi.movie_id AND t.id = mk.movie_id AND t.id = mc.movie_id AND t.id = cc.movie_id AND mk.movie_id = mi.movie_id AND mk.movie_id = mc.movie_id AND mk.movie_id = cc.movie_id AND mi.movie_id = mc.movie_id AND mi.movie_id = cc.movie_id AND mc.movie_id = cc.movie_id AND k.id = mk.keyword_id AND it1.id = mi.info_type_id AND cn.id = mc.company_id AND ct.id = mc.company_type_id AND cct1.id = cc.status_id", + "SELECT MIN(kt.kind) AS movie_kind, MIN(t.title) AS complete_nerdy_internet_movie FROM complete_cast AS cc, comp_cast_type AS cct1, company_name AS cn, company_type AS ct, info_type AS it1, keyword AS k, kind_type AS kt, movie_companies AS mc, movie_info AS mi, movie_keyword AS mk, title AS t WHERE cct1.kind = 'complete+verified' AND cn.country_code = '[us]' AND it1.info = 'release dates' AND k.keyword IN ('nerd', 'loner', 'alienation', 'dignity') AND kt.kind IN ('movie') AND mi.note LIKE '%internet%' AND mi.info LIKE 'USA:% 200%' AND t.production_year > 2000 AND kt.id = t.kind_id AND t.id = mi.movie_id AND t.id = mk.movie_id AND t.id = mc.movie_id AND t.id = cc.movie_id AND mk.movie_id = mi.movie_id AND mk.movie_id = mc.movie_id AND mk.movie_id = cc.movie_id AND mi.movie_id = mc.movie_id AND mi.movie_id = cc.movie_id AND mc.movie_id = cc.movie_id AND k.id = mk.keyword_id AND it1.id = mi.info_type_id AND cn.id = mc.company_id AND ct.id = mc.company_type_id AND cct1.id = cc.status_id", + "SELECT MIN(kt.kind) AS movie_kind, MIN(t.title) AS complete_us_internet_movie FROM complete_cast AS cc, comp_cast_type AS cct1, company_name AS cn, company_type AS ct, info_type AS it1, keyword AS k, kind_type AS kt, movie_companies AS mc, movie_info AS mi, movie_keyword AS mk, title AS t WHERE cct1.kind = 'complete+verified' AND cn.country_code = '[us]' AND it1.info = 'release dates' AND kt.kind IN ('movie', 'tv movie', 'video movie', 'video game') AND mi.note LIKE '%internet%' AND mi.info IS NOT NULL AND (mi.info LIKE 'USA:% 199%' OR mi.info LIKE 'USA:% 200%') AND t.production_year > 1990 AND kt.id = t.kind_id AND t.id = mi.movie_id AND t.id = mk.movie_id AND t.id = mc.movie_id AND t.id = cc.movie_id AND mk.movie_id = mi.movie_id AND mk.movie_id = mc.movie_id AND mk.movie_id = cc.movie_id AND mi.movie_id = mc.movie_id AND mi.movie_id = cc.movie_id AND mc.movie_id = cc.movie_id AND k.id = mk.keyword_id AND it1.id = mi.info_type_id AND cn.id = mc.company_id AND ct.id = mc.company_type_id AND cct1.id = cc.status_id", + "SELECT MIN(chn.name) AS voiced_char_name, MIN(n.name) AS voicing_actress_name, MIN(t.title) AS voiced_action_movie_jap_eng FROM aka_name AS an, char_name AS chn, cast_info AS ci, company_name AS cn, info_type AS it, keyword AS k, movie_companies AS mc, movie_info AS mi, movie_keyword AS mk, name AS n, role_type AS rt, title AS t WHERE ci.note IN ('(voice)', '(voice: Japanese version)', '(voice) (uncredited)', '(voice: English version)') AND cn.country_code ='[us]' AND it.info = 'release dates' AND k.keyword IN ('hero', 'martial-arts', 'hand-to-hand-combat') AND mi.info IS NOT NULL AND (mi.info LIKE 'Japan:%201%' OR mi.info LIKE 'USA:%201%') AND n.gender ='f' AND n.name LIKE '%An%' AND rt.role ='actress' AND t.production_year > 2010 AND t.id = mi.movie_id AND t.id = mc.movie_id AND t.id = ci.movie_id AND t.id = mk.movie_id AND mc.movie_id = ci.movie_id AND mc.movie_id = mi.movie_id AND mc.movie_id = mk.movie_id AND mi.movie_id = ci.movie_id AND mi.movie_id = mk.movie_id AND ci.movie_id = mk.movie_id AND cn.id = mc.company_id AND it.id = mi.info_type_id AND n.id = ci.person_id AND rt.id = ci.role_id AND n.id = an.person_id AND ci.person_id = an.person_id AND chn.id = ci.person_role_id AND k.id = mk.keyword_id", + "SELECT MIN(chn.name) AS voiced_char_name, MIN(n.name) AS voicing_actress_name, MIN(t.title) AS kung_fu_panda FROM aka_name AS an, char_name AS chn, cast_info AS ci, company_name AS cn, info_type AS it, keyword AS k, movie_companies AS mc, movie_info AS mi, movie_keyword AS mk, name AS n, role_type AS rt, title AS t WHERE ci.note IN ('(voice)', '(voice: Japanese version)', '(voice) (uncredited)', '(voice: English version)') AND cn.country_code ='[us]' AND cn.name = 'DreamWorks Animation' AND it.info = 'release dates' AND k.keyword IN ('hero', 'martial-arts', 'hand-to-hand-combat', 'computer-animated-movie') AND mi.info IS NOT NULL AND (mi.info LIKE 'Japan:%201%' OR mi.info LIKE 'USA:%201%') AND n.gender ='f' AND n.name LIKE '%An%' AND rt.role ='actress' AND t.production_year > 2010 AND t.title LIKE 'Kung Fu Panda%' AND t.id = mi.movie_id AND t.id = mc.movie_id AND t.id = ci.movie_id AND t.id = mk.movie_id AND mc.movie_id = ci.movie_id AND mc.movie_id = mi.movie_id AND mc.movie_id = mk.movie_id AND mi.movie_id = ci.movie_id AND mi.movie_id = mk.movie_id AND ci.movie_id = mk.movie_id AND cn.id = mc.company_id AND it.id = mi.info_type_id AND n.id = ci.person_id AND rt.id = ci.role_id AND n.id = an.person_id AND ci.person_id = an.person_id AND chn.id = ci.person_role_id AND k.id = mk.keyword_id", + "SELECT MIN(mi.info) AS movie_budget, MIN(mi_idx.info) AS movie_votes, MIN(n.name) AS male_writer, MIN(t.title) AS violent_movie_title FROM cast_info AS ci, info_type AS it1, info_type AS it2, keyword AS k, movie_info AS mi, movie_info_idx AS mi_idx, movie_keyword AS mk, name AS n, title AS t WHERE ci.note IN ('(writer)', '(head writer)', '(written by)', '(story)', '(story editor)') AND it1.info = 'genres' AND it2.info = 'votes' AND k.keyword IN ('murder', 'blood', 'gore', 'death', 'female-nudity') AND mi.info = 'Horror' AND n.gender = 'm' AND t.id = mi.movie_id AND t.id = mi_idx.movie_id AND t.id = ci.movie_id AND t.id = mk.movie_id AND ci.movie_id = mi.movie_id AND ci.movie_id = mi_idx.movie_id AND ci.movie_id = mk.movie_id AND mi.movie_id = mi_idx.movie_id AND mi.movie_id = mk.movie_id AND mi_idx.movie_id = mk.movie_id AND n.id = ci.person_id AND it1.id = mi.info_type_id AND it2.id = mi_idx.info_type_id AND k.id = mk.keyword_id", + "SELECT MIN(mi.info) AS movie_budget, MIN(mi_idx.info) AS movie_votes, MIN(n.name) AS male_writer, MIN(t.title) AS violent_movie_title FROM cast_info AS ci, info_type AS it1, info_type AS it2, keyword AS k, movie_info AS mi, movie_info_idx AS mi_idx, movie_keyword AS mk, name AS n, title AS t WHERE ci.note IN ('(writer)', '(head writer)', '(written by)', '(story)', '(story editor)') AND it1.info = 'genres' AND it2.info = 'votes' AND k.keyword IN ('murder', 'blood', 'gore', 'death', 'female-nudity') AND mi.info = 'Horror' AND n.gender = 'm' AND t.production_year > 2010 AND t.title LIKE 'Vampire%' AND t.id = mi.movie_id AND t.id = mi_idx.movie_id AND t.id = ci.movie_id AND t.id = mk.movie_id AND ci.movie_id = mi.movie_id AND ci.movie_id = mi_idx.movie_id AND ci.movie_id = mk.movie_id AND mi.movie_id = mi_idx.movie_id AND mi.movie_id = mk.movie_id AND mi_idx.movie_id = mk.movie_id AND n.id = ci.person_id AND it1.id = mi.info_type_id AND it2.id = mi_idx.info_type_id AND k.id = mk.keyword_id", + "SELECT MIN(mi.info) AS movie_budget, MIN(mi_idx.info) AS movie_votes, MIN(n.name) AS male_writer, MIN(t.title) AS violent_movie_title FROM cast_info AS ci, info_type AS it1, info_type AS it2, keyword AS k, movie_info AS mi, movie_info_idx AS mi_idx, movie_keyword AS mk, name AS n, title AS t WHERE ci.note IN ('(writer)', '(head writer)', '(written by)', '(story)', '(story editor)') AND it1.info = 'genres' AND it2.info = 'votes' AND k.keyword IN ('murder', 'violence', 'blood', 'gore', 'death', 'female-nudity', 'hospital') AND mi.info IN ('Horror', 'Action', 'Sci-Fi', 'Thriller', 'Crime', 'War') AND n.gender = 'm' AND t.id = mi.movie_id AND t.id = mi_idx.movie_id AND t.id = ci.movie_id AND t.id = mk.movie_id AND ci.movie_id = mi.movie_id AND ci.movie_id = mi_idx.movie_id AND ci.movie_id = mk.movie_id AND mi.movie_id = mi_idx.movie_id AND mi.movie_id = mk.movie_id AND mi_idx.movie_id = mk.movie_id AND n.id = ci.person_id AND it1.id = mi.info_type_id AND it2.id = mi_idx.info_type_id AND k.id = mk.keyword_id", + "SELECT MIN(chn.name) AS character_name, MIN(mi_idx.info) AS rating, MIN(n.name) AS playing_actor, MIN(t.title) AS complete_hero_movie FROM complete_cast AS cc, comp_cast_type AS cct1, comp_cast_type AS cct2, char_name AS chn, cast_info AS ci, info_type AS it2, keyword AS k, kind_type AS kt, movie_info_idx AS mi_idx, movie_keyword AS mk, name AS n, title AS t WHERE cct1.kind = 'cast' AND cct2.kind LIKE '%complete%' AND chn.name IS NOT NULL AND (chn.name LIKE '%man%' OR chn.name LIKE '%Man%') AND it2.info = 'rating' AND k.keyword IN ('superhero', 'marvel-comics', 'based-on-comic', 'tv-special', 'fight', 'violence', 'magnet', 'web', 'claw', 'laser') AND kt.kind = 'movie' AND mi_idx.info > '7.0' AND t.production_year > 2000 AND kt.id = t.kind_id AND t.id = mk.movie_id AND t.id = ci.movie_id AND t.id = cc.movie_id AND t.id = mi_idx.movie_id AND mk.movie_id = ci.movie_id AND mk.movie_id = cc.movie_id AND mk.movie_id = mi_idx.movie_id AND ci.movie_id = cc.movie_id AND ci.movie_id = mi_idx.movie_id AND cc.movie_id = mi_idx.movie_id AND chn.id = ci.person_role_id AND n.id = ci.person_id AND k.id = mk.keyword_id AND cct1.id = cc.subject_id AND cct2.id = cc.status_id AND it2.id = mi_idx.info_type_id", + "SELECT MIN(chn.name) AS character_name, MIN(mi_idx.info) AS rating, MIN(t.title) AS complete_hero_movie FROM complete_cast AS cc, comp_cast_type AS cct1, comp_cast_type AS cct2, char_name AS chn, cast_info AS ci, info_type AS it2, keyword AS k, kind_type AS kt, movie_info_idx AS mi_idx, movie_keyword AS mk, name AS n, title AS t WHERE cct1.kind = 'cast' AND cct2.kind LIKE '%complete%' AND chn.name IS NOT NULL AND (chn.name LIKE '%man%' OR chn.name LIKE '%Man%') AND it2.info = 'rating' AND k.keyword IN ('superhero', 'marvel-comics', 'based-on-comic', 'fight') AND kt.kind = 'movie' AND mi_idx.info > '8.0' AND t.production_year > 2005 AND kt.id = t.kind_id AND t.id = mk.movie_id AND t.id = ci.movie_id AND t.id = cc.movie_id AND t.id = mi_idx.movie_id AND mk.movie_id = ci.movie_id AND mk.movie_id = cc.movie_id AND mk.movie_id = mi_idx.movie_id AND ci.movie_id = cc.movie_id AND ci.movie_id = mi_idx.movie_id AND cc.movie_id = mi_idx.movie_id AND chn.id = ci.person_role_id AND n.id = ci.person_id AND k.id = mk.keyword_id AND cct1.id = cc.subject_id AND cct2.id = cc.status_id AND it2.id = mi_idx.info_type_id", + "SELECT MIN(chn.name) AS character_name, MIN(mi_idx.info) AS rating, MIN(t.title) AS complete_hero_movie FROM complete_cast AS cc, comp_cast_type AS cct1, comp_cast_type AS cct2, char_name AS chn, cast_info AS ci, info_type AS it2, keyword AS k, kind_type AS kt, movie_info_idx AS mi_idx, movie_keyword AS mk, name AS n, title AS t WHERE cct1.kind = 'cast' AND cct2.kind LIKE '%complete%' AND chn.name IS NOT NULL AND (chn.name LIKE '%man%' OR chn.name LIKE '%Man%') AND it2.info = 'rating' AND k.keyword IN ('superhero', 'marvel-comics', 'based-on-comic', 'tv-special', 'fight', 'violence', 'magnet', 'web', 'claw', 'laser') AND kt.kind = 'movie' AND t.production_year > 2000 AND kt.id = t.kind_id AND t.id = mk.movie_id AND t.id = ci.movie_id AND t.id = cc.movie_id AND t.id = mi_idx.movie_id AND mk.movie_id = ci.movie_id AND mk.movie_id = cc.movie_id AND mk.movie_id = mi_idx.movie_id AND ci.movie_id = cc.movie_id AND ci.movie_id = mi_idx.movie_id AND cc.movie_id = mi_idx.movie_id AND chn.id = ci.person_role_id AND n.id = ci.person_id AND k.id = mk.keyword_id AND cct1.id = cc.subject_id AND cct2.id = cc.status_id AND it2.id = mi_idx.info_type_id", + "SELECT MIN(cn.name) AS producing_company, MIN(lt.link) AS link_type, MIN(t.title) AS complete_western_sequel FROM complete_cast AS cc, comp_cast_type AS cct1, comp_cast_type AS cct2, company_name AS cn, company_type AS ct, keyword AS k, link_type AS lt, movie_companies AS mc, movie_info AS mi, movie_keyword AS mk, movie_link AS ml, title AS t WHERE cct1.kind IN ('cast', 'crew') AND cct2.kind = 'complete' AND cn.country_code !='[pl]' AND (cn.name LIKE '%Film%' OR cn.name LIKE '%Warner%') AND ct.kind ='production companies' AND k.keyword ='sequel' AND lt.link LIKE '%follow%' AND mc.note IS NULL AND mi.info IN ('Sweden', 'Germany', 'Swedish', 'German') AND t.production_year BETWEEN 1950 AND 2000 AND lt.id = ml.link_type_id AND ml.movie_id = t.id AND t.id = mk.movie_id AND mk.keyword_id = k.id AND t.id = mc.movie_id AND mc.company_type_id = ct.id AND mc.company_id = cn.id AND mi.movie_id = t.id AND t.id = cc.movie_id AND cct1.id = cc.subject_id AND cct2.id = cc.status_id AND ml.movie_id = mk.movie_id AND ml.movie_id = mc.movie_id AND mk.movie_id = mc.movie_id AND ml.movie_id = mi.movie_id AND mk.movie_id = mi.movie_id AND mc.movie_id = mi.movie_id AND ml.movie_id = cc.movie_id AND mk.movie_id = cc.movie_id AND mc.movie_id = cc.movie_id AND mi.movie_id = cc.movie_id", + "SELECT MIN(cn.name) AS producing_company, MIN(lt.link) AS link_type, MIN(t.title) AS complete_western_sequel FROM complete_cast AS cc, comp_cast_type AS cct1, comp_cast_type AS cct2, company_name AS cn, company_type AS ct, keyword AS k, link_type AS lt, movie_companies AS mc, movie_info AS mi, movie_keyword AS mk, movie_link AS ml, title AS t WHERE cct1.kind IN ('cast', 'crew') AND cct2.kind = 'complete' AND cn.country_code !='[pl]' AND (cn.name LIKE '%Film%' OR cn.name LIKE '%Warner%') AND ct.kind ='production companies' AND k.keyword ='sequel' AND lt.link LIKE '%follow%' AND mc.note IS NULL AND mi.info IN ('Sweden', 'Germany', 'Swedish', 'German') AND t.production_year = 1998 AND lt.id = ml.link_type_id AND ml.movie_id = t.id AND t.id = mk.movie_id AND mk.keyword_id = k.id AND t.id = mc.movie_id AND mc.company_type_id = ct.id AND mc.company_id = cn.id AND mi.movie_id = t.id AND t.id = cc.movie_id AND cct1.id = cc.subject_id AND cct2.id = cc.status_id AND ml.movie_id = mk.movie_id AND ml.movie_id = mc.movie_id AND mk.movie_id = mc.movie_id AND ml.movie_id = mi.movie_id AND mk.movie_id = mi.movie_id AND mc.movie_id = mi.movie_id AND ml.movie_id = cc.movie_id AND mk.movie_id = cc.movie_id AND mc.movie_id = cc.movie_id AND mi.movie_id = cc.movie_id", + "SELECT MIN(cn.name) AS producing_company, MIN(lt.link) AS link_type, MIN(t.title) AS complete_western_sequel FROM complete_cast AS cc, comp_cast_type AS cct1, comp_cast_type AS cct2, company_name AS cn, company_type AS ct, keyword AS k, link_type AS lt, movie_companies AS mc, movie_info AS mi, movie_keyword AS mk, movie_link AS ml, title AS t WHERE cct1.kind = 'cast' AND cct2.kind LIKE 'complete%' AND cn.country_code !='[pl]' AND (cn.name LIKE '%Film%' OR cn.name LIKE '%Warner%') AND ct.kind ='production companies' AND k.keyword ='sequel' AND lt.link LIKE '%follow%' AND mc.note IS NULL AND mi.info IN ('Sweden', 'Norway', 'Germany', 'Denmark', 'Swedish', 'Denish', 'Norwegian', 'German', 'English') AND t.production_year BETWEEN 1950 AND 2010 AND lt.id = ml.link_type_id AND ml.movie_id = t.id AND t.id = mk.movie_id AND mk.keyword_id = k.id AND t.id = mc.movie_id AND mc.company_type_id = ct.id AND mc.company_id = cn.id AND mi.movie_id = t.id AND t.id = cc.movie_id AND cct1.id = cc.subject_id AND cct2.id = cc.status_id AND ml.movie_id = mk.movie_id AND ml.movie_id = mc.movie_id AND mk.movie_id = mc.movie_id AND ml.movie_id = mi.movie_id AND mk.movie_id = mi.movie_id AND mc.movie_id = mi.movie_id AND ml.movie_id = cc.movie_id AND mk.movie_id = cc.movie_id AND mc.movie_id = cc.movie_id AND mi.movie_id = cc.movie_id", + "SELECT MIN(cn.name) AS movie_company, MIN(mi_idx.info) AS rating, MIN(t.title) AS complete_euro_dark_movie FROM complete_cast AS cc, comp_cast_type AS cct1, comp_cast_type AS cct2, company_name AS cn, company_type AS ct, info_type AS it1, info_type AS it2, keyword AS k, kind_type AS kt, movie_companies AS mc, movie_info AS mi, movie_info_idx AS mi_idx, movie_keyword AS mk, title AS t WHERE cct1.kind = 'crew' AND cct2.kind != 'complete+verified' AND cn.country_code != '[us]' AND it1.info = 'countries' AND it2.info = 'rating' AND k.keyword IN ('murder', 'murder-in-title', 'blood', 'violence') AND kt.kind IN ('movie', 'episode') AND mc.note NOT LIKE '%(USA)%' AND mc.note LIKE '%(200%)%' AND mi.info IN ('Sweden', 'Norway', 'Germany', 'Denmark', 'Swedish', 'Danish', 'Norwegian', 'German', 'USA', 'American') AND mi_idx.info < '8.5' AND t.production_year > 2000 AND kt.id = t.kind_id AND t.id = mi.movie_id AND t.id = mk.movie_id AND t.id = mi_idx.movie_id AND t.id = mc.movie_id AND t.id = cc.movie_id AND mk.movie_id = mi.movie_id AND mk.movie_id = mi_idx.movie_id AND mk.movie_id = mc.movie_id AND mk.movie_id = cc.movie_id AND mi.movie_id = mi_idx.movie_id AND mi.movie_id = mc.movie_id AND mi.movie_id = cc.movie_id AND mc.movie_id = mi_idx.movie_id AND mc.movie_id = cc.movie_id AND mi_idx.movie_id = cc.movie_id AND k.id = mk.keyword_id AND it1.id = mi.info_type_id AND it2.id = mi_idx.info_type_id AND ct.id = mc.company_type_id AND cn.id = mc.company_id AND cct1.id = cc.subject_id AND cct2.id = cc.status_id", + "SELECT MIN(cn.name) AS movie_company, MIN(mi_idx.info) AS rating, MIN(t.title) AS complete_euro_dark_movie FROM complete_cast AS cc, comp_cast_type AS cct1, comp_cast_type AS cct2, company_name AS cn, company_type AS ct, info_type AS it1, info_type AS it2, keyword AS k, kind_type AS kt, movie_companies AS mc, movie_info AS mi, movie_info_idx AS mi_idx, movie_keyword AS mk, title AS t WHERE cct1.kind = 'crew' AND cct2.kind != 'complete+verified' AND cn.country_code != '[us]' AND it1.info = 'countries' AND it2.info = 'rating' AND k.keyword IN ('murder', 'murder-in-title', 'blood', 'violence') AND kt.kind IN ('movie', 'episode') AND mc.note NOT LIKE '%(USA)%' AND mc.note LIKE '%(200%)%' AND mi.info IN ('Sweden', 'Germany', 'Swedish', 'German') AND mi_idx.info > '6.5' AND t.production_year > 2005 AND kt.id = t.kind_id AND t.id = mi.movie_id AND t.id = mk.movie_id AND t.id = mi_idx.movie_id AND t.id = mc.movie_id AND t.id = cc.movie_id AND mk.movie_id = mi.movie_id AND mk.movie_id = mi_idx.movie_id AND mk.movie_id = mc.movie_id AND mk.movie_id = cc.movie_id AND mi.movie_id = mi_idx.movie_id AND mi.movie_id = mc.movie_id AND mi.movie_id = cc.movie_id AND mc.movie_id = mi_idx.movie_id AND mc.movie_id = cc.movie_id AND mi_idx.movie_id = cc.movie_id AND k.id = mk.keyword_id AND it1.id = mi.info_type_id AND it2.id = mi_idx.info_type_id AND ct.id = mc.company_type_id AND cn.id = mc.company_id AND cct1.id = cc.subject_id AND cct2.id = cc.status_id", + "SELECT MIN(cn.name) AS movie_company, MIN(mi_idx.info) AS rating, MIN(t.title) AS complete_euro_dark_movie FROM complete_cast AS cc, comp_cast_type AS cct1, comp_cast_type AS cct2, company_name AS cn, company_type AS ct, info_type AS it1, info_type AS it2, keyword AS k, kind_type AS kt, movie_companies AS mc, movie_info AS mi, movie_info_idx AS mi_idx, movie_keyword AS mk, title AS t WHERE cct1.kind = 'cast' AND cct2.kind = 'complete' AND cn.country_code != '[us]' AND it1.info = 'countries' AND it2.info = 'rating' AND k.keyword IN ('murder', 'murder-in-title', 'blood', 'violence') AND kt.kind IN ('movie', 'episode') AND mc.note NOT LIKE '%(USA)%' AND mc.note LIKE '%(200%)%' AND mi.info IN ('Sweden', 'Norway', 'Germany', 'Denmark', 'Swedish', 'Danish', 'Norwegian', 'German', 'USA', 'American') AND mi_idx.info < '8.5' AND t.production_year > 2005 AND kt.id = t.kind_id AND t.id = mi.movie_id AND t.id = mk.movie_id AND t.id = mi_idx.movie_id AND t.id = mc.movie_id AND t.id = cc.movie_id AND mk.movie_id = mi.movie_id AND mk.movie_id = mi_idx.movie_id AND mk.movie_id = mc.movie_id AND mk.movie_id = cc.movie_id AND mi.movie_id = mi_idx.movie_id AND mi.movie_id = mc.movie_id AND mi.movie_id = cc.movie_id AND mc.movie_id = mi_idx.movie_id AND mc.movie_id = cc.movie_id AND mi_idx.movie_id = cc.movie_id AND k.id = mk.keyword_id AND it1.id = mi.info_type_id AND it2.id = mi_idx.info_type_id AND ct.id = mc.company_type_id AND cn.id = mc.company_id AND cct1.id = cc.subject_id AND cct2.id = cc.status_id", + "SELECT MIN(chn.name) AS voiced_char, MIN(n.name) AS voicing_actress, MIN(t.title) AS voiced_animation FROM aka_name AS an, complete_cast AS cc, comp_cast_type AS cct1, comp_cast_type AS cct2, char_name AS chn, cast_info AS ci, company_name AS cn, info_type AS it, info_type AS it3, keyword AS k, movie_companies AS mc, movie_info AS mi, movie_keyword AS mk, name AS n, person_info AS pi, role_type AS rt, title AS t WHERE cct1.kind ='cast' AND cct2.kind ='complete+verified' AND chn.name = 'Queen' AND ci.note IN ('(voice)', '(voice) (uncredited)', '(voice: English version)') AND cn.country_code ='[us]' AND it.info = 'release dates' AND it3.info = 'trivia' AND k.keyword = 'computer-animation' AND mi.info IS NOT NULL AND (mi.info LIKE 'Japan:%200%' OR mi.info LIKE 'USA:%200%') AND n.gender ='f' AND n.name LIKE '%An%' AND rt.role ='actress' AND t.title = 'Shrek 2' AND t.production_year BETWEEN 2000 AND 2010 AND t.id = mi.movie_id AND t.id = mc.movie_id AND t.id = ci.movie_id AND t.id = mk.movie_id AND t.id = cc.movie_id AND mc.movie_id = ci.movie_id AND mc.movie_id = mi.movie_id AND mc.movie_id = mk.movie_id AND mc.movie_id = cc.movie_id AND mi.movie_id = ci.movie_id AND mi.movie_id = mk.movie_id AND mi.movie_id = cc.movie_id AND ci.movie_id = mk.movie_id AND ci.movie_id = cc.movie_id AND mk.movie_id = cc.movie_id AND cn.id = mc.company_id AND it.id = mi.info_type_id AND n.id = ci.person_id AND rt.id = ci.role_id AND n.id = an.person_id AND ci.person_id = an.person_id AND chn.id = ci.person_role_id AND n.id = pi.person_id AND ci.person_id = pi.person_id AND it3.id = pi.info_type_id AND k.id = mk.keyword_id AND cct1.id = cc.subject_id AND cct2.id = cc.status_id", + "SELECT MIN(chn.name) AS voiced_char, MIN(n.name) AS voicing_actress, MIN(t.title) AS voiced_animation FROM aka_name AS an, complete_cast AS cc, comp_cast_type AS cct1, comp_cast_type AS cct2, char_name AS chn, cast_info AS ci, company_name AS cn, info_type AS it, info_type AS it3, keyword AS k, movie_companies AS mc, movie_info AS mi, movie_keyword AS mk, name AS n, person_info AS pi, role_type AS rt, title AS t WHERE cct1.kind ='cast' AND cct2.kind ='complete+verified' AND chn.name = 'Queen' AND ci.note IN ('(voice)', '(voice) (uncredited)', '(voice: English version)') AND cn.country_code ='[us]' AND it.info = 'release dates' AND it3.info = 'height' AND k.keyword = 'computer-animation' AND mi.info LIKE 'USA:%200%' AND n.gender ='f' AND n.name LIKE '%An%' AND rt.role ='actress' AND t.title = 'Shrek 2' AND t.production_year BETWEEN 2000 AND 2005 AND t.id = mi.movie_id AND t.id = mc.movie_id AND t.id = ci.movie_id AND t.id = mk.movie_id AND t.id = cc.movie_id AND mc.movie_id = ci.movie_id AND mc.movie_id = mi.movie_id AND mc.movie_id = mk.movie_id AND mc.movie_id = cc.movie_id AND mi.movie_id = ci.movie_id AND mi.movie_id = mk.movie_id AND mi.movie_id = cc.movie_id AND ci.movie_id = mk.movie_id AND ci.movie_id = cc.movie_id AND mk.movie_id = cc.movie_id AND cn.id = mc.company_id AND it.id = mi.info_type_id AND n.id = ci.person_id AND rt.id = ci.role_id AND n.id = an.person_id AND ci.person_id = an.person_id AND chn.id = ci.person_role_id AND n.id = pi.person_id AND ci.person_id = pi.person_id AND it3.id = pi.info_type_id AND k.id = mk.keyword_id AND cct1.id = cc.subject_id AND cct2.id = cc.status_id", + "SELECT MIN(chn.name) AS voiced_char, MIN(n.name) AS voicing_actress, MIN(t.title) AS voiced_animation FROM aka_name AS an, complete_cast AS cc, comp_cast_type AS cct1, comp_cast_type AS cct2, char_name AS chn, cast_info AS ci, company_name AS cn, info_type AS it, info_type AS it3, keyword AS k, movie_companies AS mc, movie_info AS mi, movie_keyword AS mk, name AS n, person_info AS pi, role_type AS rt, title AS t WHERE cct1.kind ='cast' AND cct2.kind ='complete+verified' AND ci.note IN ('(voice)', '(voice: Japanese version)', '(voice) (uncredited)', '(voice: English version)') AND cn.country_code ='[us]' AND it.info = 'release dates' AND it3.info = 'trivia' AND k.keyword = 'computer-animation' AND mi.info IS NOT NULL AND (mi.info LIKE 'Japan:%200%' OR mi.info LIKE 'USA:%200%') AND n.gender ='f' AND n.name LIKE '%An%' AND rt.role ='actress' AND t.production_year BETWEEN 2000 AND 2010 AND t.id = mi.movie_id AND t.id = mc.movie_id AND t.id = ci.movie_id AND t.id = mk.movie_id AND t.id = cc.movie_id AND mc.movie_id = ci.movie_id AND mc.movie_id = mi.movie_id AND mc.movie_id = mk.movie_id AND mc.movie_id = cc.movie_id AND mi.movie_id = ci.movie_id AND mi.movie_id = mk.movie_id AND mi.movie_id = cc.movie_id AND ci.movie_id = mk.movie_id AND ci.movie_id = cc.movie_id AND mk.movie_id = cc.movie_id AND cn.id = mc.company_id AND it.id = mi.info_type_id AND n.id = ci.person_id AND rt.id = ci.role_id AND n.id = an.person_id AND ci.person_id = an.person_id AND chn.id = ci.person_role_id AND n.id = pi.person_id AND ci.person_id = pi.person_id AND it3.id = pi.info_type_id AND k.id = mk.keyword_id AND cct1.id = cc.subject_id AND cct2.id = cc.status_id", + "SELECT MIN(mi.info) AS movie_budget, MIN(mi_idx.info) AS movie_votes, MIN(n.name) AS writer, MIN(t.title) AS complete_violent_movie FROM complete_cast AS cc, comp_cast_type AS cct1, comp_cast_type AS cct2, cast_info AS ci, info_type AS it1, info_type AS it2, keyword AS k, movie_info AS mi, movie_info_idx AS mi_idx, movie_keyword AS mk, name AS n, title AS t WHERE cct1.kind IN ('cast', 'crew') AND cct2.kind ='complete+verified' AND ci.note IN ('(writer)', '(head writer)', '(written by)', '(story)', '(story editor)') AND it1.info = 'genres' AND it2.info = 'votes' AND k.keyword IN ('murder', 'violence', 'blood', 'gore', 'death', 'female-nudity', 'hospital') AND mi.info IN ('Horror', 'Thriller') AND n.gender = 'm' AND t.production_year > 2000 AND t.id = mi.movie_id AND t.id = mi_idx.movie_id AND t.id = ci.movie_id AND t.id = mk.movie_id AND t.id = cc.movie_id AND ci.movie_id = mi.movie_id AND ci.movie_id = mi_idx.movie_id AND ci.movie_id = mk.movie_id AND ci.movie_id = cc.movie_id AND mi.movie_id = mi_idx.movie_id AND mi.movie_id = mk.movie_id AND mi.movie_id = cc.movie_id AND mi_idx.movie_id = mk.movie_id AND mi_idx.movie_id = cc.movie_id AND mk.movie_id = cc.movie_id AND n.id = ci.person_id AND it1.id = mi.info_type_id AND it2.id = mi_idx.info_type_id AND k.id = mk.keyword_id AND cct1.id = cc.subject_id AND cct2.id = cc.status_id", + "SELECT MIN(mi.info) AS movie_budget, MIN(mi_idx.info) AS movie_votes, MIN(n.name) AS writer, MIN(t.title) AS complete_gore_movie FROM complete_cast AS cc, comp_cast_type AS cct1, comp_cast_type AS cct2, cast_info AS ci, info_type AS it1, info_type AS it2, keyword AS k, movie_info AS mi, movie_info_idx AS mi_idx, movie_keyword AS mk, name AS n, title AS t WHERE cct1.kind IN ('cast', 'crew') AND cct2.kind ='complete+verified' AND ci.note IN ('(writer)', '(head writer)', '(written by)', '(story)', '(story editor)') AND it1.info = 'genres' AND it2.info = 'votes' AND k.keyword IN ('murder', 'violence', 'blood', 'gore', 'death', 'female-nudity', 'hospital') AND mi.info IN ('Horror', 'Thriller') AND n.gender = 'm' AND t.production_year > 2000 AND (t.title LIKE '%Freddy%' OR t.title LIKE '%Jason%' OR t.title LIKE 'Saw%') AND t.id = mi.movie_id AND t.id = mi_idx.movie_id AND t.id = ci.movie_id AND t.id = mk.movie_id AND t.id = cc.movie_id AND ci.movie_id = mi.movie_id AND ci.movie_id = mi_idx.movie_id AND ci.movie_id = mk.movie_id AND ci.movie_id = cc.movie_id AND mi.movie_id = mi_idx.movie_id AND mi.movie_id = mk.movie_id AND mi.movie_id = cc.movie_id AND mi_idx.movie_id = mk.movie_id AND mi_idx.movie_id = cc.movie_id AND mk.movie_id = cc.movie_id AND n.id = ci.person_id AND it1.id = mi.info_type_id AND it2.id = mi_idx.info_type_id AND k.id = mk.keyword_id AND cct1.id = cc.subject_id AND cct2.id = cc.status_id", + "SELECT MIN(mi.info) AS movie_budget, MIN(mi_idx.info) AS movie_votes, MIN(n.name) AS writer, MIN(t.title) AS complete_violent_movie FROM complete_cast AS cc, comp_cast_type AS cct1, comp_cast_type AS cct2, cast_info AS ci, info_type AS it1, info_type AS it2, keyword AS k, movie_info AS mi, movie_info_idx AS mi_idx, movie_keyword AS mk, name AS n, title AS t WHERE cct1.kind = 'cast' AND cct2.kind ='complete+verified' AND ci.note IN ('(writer)', '(head writer)', '(written by)', '(story)', '(story editor)') AND it1.info = 'genres' AND it2.info = 'votes' AND k.keyword IN ('murder', 'violence', 'blood', 'gore', 'death', 'female-nudity', 'hospital') AND mi.info IN ('Horror', 'Action', 'Sci-Fi', 'Thriller', 'Crime', 'War') AND n.gender = 'm' AND t.id = mi.movie_id AND t.id = mi_idx.movie_id AND t.id = ci.movie_id AND t.id = mk.movie_id AND t.id = cc.movie_id AND ci.movie_id = mi.movie_id AND ci.movie_id = mi_idx.movie_id AND ci.movie_id = mk.movie_id AND ci.movie_id = cc.movie_id AND mi.movie_id = mi_idx.movie_id AND mi.movie_id = mk.movie_id AND mi.movie_id = cc.movie_id AND mi_idx.movie_id = mk.movie_id AND mi_idx.movie_id = cc.movie_id AND mk.movie_id = cc.movie_id AND n.id = ci.person_id AND it1.id = mi.info_type_id AND it2.id = mi_idx.info_type_id AND k.id = mk.keyword_id AND cct1.id = cc.subject_id AND cct2.id = cc.status_id", + "SELECT MIN(mi.info) AS movie_budget, MIN(mi_idx.info) AS movie_votes, MIN(n.name) AS writer, MIN(t.title) AS violent_liongate_movie FROM cast_info AS ci, company_name AS cn, info_type AS it1, info_type AS it2, keyword AS k, movie_companies AS mc, movie_info AS mi, movie_info_idx AS mi_idx, movie_keyword AS mk, name AS n, title AS t WHERE ci.note IN ('(writer)', '(head writer)', '(written by)', '(story)', '(story editor)') AND cn.name LIKE 'Lionsgate%' AND it1.info = 'genres' AND it2.info = 'votes' AND k.keyword IN ('murder', 'violence', 'blood', 'gore', 'death', 'female-nudity', 'hospital') AND mi.info IN ('Horror', 'Thriller') AND n.gender = 'm' AND t.id = mi.movie_id AND t.id = mi_idx.movie_id AND t.id = ci.movie_id AND t.id = mk.movie_id AND t.id = mc.movie_id AND ci.movie_id = mi.movie_id AND ci.movie_id = mi_idx.movie_id AND ci.movie_id = mk.movie_id AND ci.movie_id = mc.movie_id AND mi.movie_id = mi_idx.movie_id AND mi.movie_id = mk.movie_id AND mi.movie_id = mc.movie_id AND mi_idx.movie_id = mk.movie_id AND mi_idx.movie_id = mc.movie_id AND mk.movie_id = mc.movie_id AND n.id = ci.person_id AND it1.id = mi.info_type_id AND it2.id = mi_idx.info_type_id AND k.id = mk.keyword_id AND cn.id = mc.company_id", + "SELECT MIN(mi.info) AS movie_budget, MIN(mi_idx.info) AS movie_votes, MIN(n.name) AS writer, MIN(t.title) AS violent_liongate_movie FROM cast_info AS ci, company_name AS cn, info_type AS it1, info_type AS it2, keyword AS k, movie_companies AS mc, movie_info AS mi, movie_info_idx AS mi_idx, movie_keyword AS mk, name AS n, title AS t WHERE ci.note IN ('(writer)', '(head writer)', '(written by)', '(story)', '(story editor)') AND cn.name LIKE 'Lionsgate%' AND it1.info = 'genres' AND it2.info = 'votes' AND k.keyword IN ('murder', 'violence', 'blood', 'gore', 'death', 'female-nudity', 'hospital') AND mc.note LIKE '%(Blu-ray)%' AND mi.info IN ('Horror', 'Thriller') AND n.gender = 'm' AND t.production_year > 2000 AND (t.title LIKE '%Freddy%' OR t.title LIKE '%Jason%' OR t.title LIKE 'Saw%') AND t.id = mi.movie_id AND t.id = mi_idx.movie_id AND t.id = ci.movie_id AND t.id = mk.movie_id AND t.id = mc.movie_id AND ci.movie_id = mi.movie_id AND ci.movie_id = mi_idx.movie_id AND ci.movie_id = mk.movie_id AND ci.movie_id = mc.movie_id AND mi.movie_id = mi_idx.movie_id AND mi.movie_id = mk.movie_id AND mi.movie_id = mc.movie_id AND mi_idx.movie_id = mk.movie_id AND mi_idx.movie_id = mc.movie_id AND mk.movie_id = mc.movie_id AND n.id = ci.person_id AND it1.id = mi.info_type_id AND it2.id = mi_idx.info_type_id AND k.id = mk.keyword_id AND cn.id = mc.company_id", + "SELECT MIN(mi.info) AS movie_budget, MIN(mi_idx.info) AS movie_votes, MIN(n.name) AS writer, MIN(t.title) AS violent_liongate_movie FROM cast_info AS ci, company_name AS cn, info_type AS it1, info_type AS it2, keyword AS k, movie_companies AS mc, movie_info AS mi, movie_info_idx AS mi_idx, movie_keyword AS mk, name AS n, title AS t WHERE ci.note IN ('(writer)', '(head writer)', '(written by)', '(story)', '(story editor)') AND cn.name LIKE 'Lionsgate%' AND it1.info = 'genres' AND it2.info = 'votes' AND k.keyword IN ('murder', 'violence', 'blood', 'gore', 'death', 'female-nudity', 'hospital') AND mi.info IN ('Horror', 'Action', 'Sci-Fi', 'Thriller', 'Crime', 'War') AND t.id = mi.movie_id AND t.id = mi_idx.movie_id AND t.id = ci.movie_id AND t.id = mk.movie_id AND t.id = mc.movie_id AND ci.movie_id = mi.movie_id AND ci.movie_id = mi_idx.movie_id AND ci.movie_id = mk.movie_id AND ci.movie_id = mc.movie_id AND mi.movie_id = mi_idx.movie_id AND mi.movie_id = mk.movie_id AND mi.movie_id = mc.movie_id AND mi_idx.movie_id = mk.movie_id AND mi_idx.movie_id = mc.movie_id AND mk.movie_id = mc.movie_id AND n.id = ci.person_id AND it1.id = mi.info_type_id AND it2.id = mi_idx.info_type_id AND k.id = mk.keyword_id AND cn.id = mc.company_id", + "SELECT MIN(lt.link) AS link_type, MIN(t1.title) AS first_movie, MIN(t2.title) AS second_movie FROM keyword AS k, link_type AS lt, movie_keyword AS mk, movie_link AS ml, title AS t1, title AS t2 WHERE k.keyword ='10,000-mile-club' AND mk.keyword_id = k.id AND t1.id = mk.movie_id AND ml.movie_id = t1.id AND ml.linked_movie_id = t2.id AND lt.id = ml.link_type_id AND mk.movie_id = t1.id", + "SELECT MIN(lt.link) AS link_type, MIN(t1.title) AS first_movie, MIN(t2.title) AS second_movie FROM keyword AS k, link_type AS lt, movie_keyword AS mk, movie_link AS ml, title AS t1, title AS t2 WHERE k.keyword ='character-name-in-title' AND mk.keyword_id = k.id AND t1.id = mk.movie_id AND ml.movie_id = t1.id AND ml.linked_movie_id = t2.id AND lt.id = ml.link_type_id AND mk.movie_id = t1.id", + "SELECT MIN(cn1.name) AS first_company, MIN(cn2.name) AS second_company, MIN(mi_idx1.info) AS first_rating, MIN(mi_idx2.info) AS second_rating, MIN(t1.title) AS first_movie, MIN(t2.title) AS second_movie FROM company_name AS cn1, company_name AS cn2, info_type AS it1, info_type AS it2, kind_type AS kt1, kind_type AS kt2, link_type AS lt, movie_companies AS mc1, movie_companies AS mc2, movie_info_idx AS mi_idx1, movie_info_idx AS mi_idx2, movie_link AS ml, title AS t1, title AS t2 WHERE cn1.country_code = '[us]' AND it1.info = 'rating' AND it2.info = 'rating' AND kt1.kind IN ('tv series') AND kt2.kind IN ('tv series') AND lt.link IN ('sequel', 'follows', 'followed by') AND mi_idx2.info < '3.0' AND t2.production_year BETWEEN 2005 AND 2008 AND lt.id = ml.link_type_id AND t1.id = ml.movie_id AND t2.id = ml.linked_movie_id AND it1.id = mi_idx1.info_type_id AND t1.id = mi_idx1.movie_id AND kt1.id = t1.kind_id AND cn1.id = mc1.company_id AND t1.id = mc1.movie_id AND ml.movie_id = mi_idx1.movie_id AND ml.movie_id = mc1.movie_id AND mi_idx1.movie_id = mc1.movie_id AND it2.id = mi_idx2.info_type_id AND t2.id = mi_idx2.movie_id AND kt2.id = t2.kind_id AND cn2.id = mc2.company_id AND t2.id = mc2.movie_id AND ml.linked_movie_id = mi_idx2.movie_id AND ml.linked_movie_id = mc2.movie_id AND mi_idx2.movie_id = mc2.movie_id", + "SELECT MIN(cn1.name) AS first_company, MIN(cn2.name) AS second_company, MIN(mi_idx1.info) AS first_rating, MIN(mi_idx2.info) AS second_rating, MIN(t1.title) AS first_movie, MIN(t2.title) AS second_movie FROM company_name AS cn1, company_name AS cn2, info_type AS it1, info_type AS it2, kind_type AS kt1, kind_type AS kt2, link_type AS lt, movie_companies AS mc1, movie_companies AS mc2, movie_info_idx AS mi_idx1, movie_info_idx AS mi_idx2, movie_link AS ml, title AS t1, title AS t2 WHERE cn1.country_code = '[nl]' AND it1.info = 'rating' AND it2.info = 'rating' AND kt1.kind IN ('tv series') AND kt2.kind IN ('tv series') AND lt.link LIKE '%follow%' AND mi_idx2.info < '3.0' AND t2.production_year = 2007 AND lt.id = ml.link_type_id AND t1.id = ml.movie_id AND t2.id = ml.linked_movie_id AND it1.id = mi_idx1.info_type_id AND t1.id = mi_idx1.movie_id AND kt1.id = t1.kind_id AND cn1.id = mc1.company_id AND t1.id = mc1.movie_id AND ml.movie_id = mi_idx1.movie_id AND ml.movie_id = mc1.movie_id AND mi_idx1.movie_id = mc1.movie_id AND it2.id = mi_idx2.info_type_id AND t2.id = mi_idx2.movie_id AND kt2.id = t2.kind_id AND cn2.id = mc2.company_id AND t2.id = mc2.movie_id AND ml.linked_movie_id = mi_idx2.movie_id AND ml.linked_movie_id = mc2.movie_id AND mi_idx2.movie_id = mc2.movie_id", + "SELECT MIN(cn1.name) AS first_company, MIN(cn2.name) AS second_company, MIN(mi_idx1.info) AS first_rating, MIN(mi_idx2.info) AS second_rating, MIN(t1.title) AS first_movie, MIN(t2.title) AS second_movie FROM company_name AS cn1, company_name AS cn2, info_type AS it1, info_type AS it2, kind_type AS kt1, kind_type AS kt2, link_type AS lt, movie_companies AS mc1, movie_companies AS mc2, movie_info_idx AS mi_idx1, movie_info_idx AS mi_idx2, movie_link AS ml, title AS t1, title AS t2 WHERE cn1.country_code != '[us]' AND it1.info = 'rating' AND it2.info = 'rating' AND kt1.kind IN ('tv series', 'episode') AND kt2.kind IN ('tv series', 'episode') AND lt.link IN ('sequel', 'follows', 'followed by') AND mi_idx2.info < '3.5' AND t2.production_year BETWEEN 2000 AND 2010 AND lt.id = ml.link_type_id AND t1.id = ml.movie_id AND t2.id = ml.linked_movie_id AND it1.id = mi_idx1.info_type_id AND t1.id = mi_idx1.movie_id AND kt1.id = t1.kind_id AND cn1.id = mc1.company_id AND t1.id = mc1.movie_id AND ml.movie_id = mi_idx1.movie_id AND ml.movie_id = mc1.movie_id AND mi_idx1.movie_id = mc1.movie_id AND it2.id = mi_idx2.info_type_id AND t2.id = mi_idx2.movie_id AND kt2.id = t2.kind_id AND cn2.id = mc2.company_id AND t2.id = mc2.movie_id AND ml.linked_movie_id = mi_idx2.movie_id AND ml.linked_movie_id = mc2.movie_id AND mi_idx2.movie_id = mc2.movie_id" +]} +]; + +const data = [{"actual_version":"1.1.53990","data_size":{"default":4096,"hits":4096,"job":4096,"mgbench":4096,"ontime":4096,"ssb":4096,"taxi":4096,"tpcds":4096,"tpch":4096,"uk":4096},"kind":"versions-benchmark","load_time":{},"machine":"c7a.4xlarge","release_date":"2016-07-01","result":[[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,null,null],[null,null,null,null,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,0.453,0.536],[1.509,0.562,0.660,0.579,0.500,0.415],[2.142,1.230,1.162,1.339,1.206,1.224],[0.244,0.114,0.120,0.085,0.097,0.074],[0.198,0.085,0.066,0.067,0.058,0.059],[0.416,0.395,0.364,0.365,0.328,0.353],[0.585,0.197,0.204,0.155,0.182,0.187],[0.381,0.127,0.208,0.098,0.094,0.110],[0.349,0.135,0.123,0.214,0.129,0.114],[0.529,0.147,0.171,0.147,0.232,0.139],[0.459,0.168,0.205,0.236,0.176,0.142],[0.302,0.092,0.081,0.082,0.081,0.086],[0.278,0.080,0.164,0.064,0.076,0.073],[0.470,0.254,0.269,0.240,0.357,0.224],[0.006,0.006,0.006,0.006,0.006,0.006],[0.006,0.006,0.006,0.006,0.006,0.006],[0.344,0.183,0.119,0.139,0.122,0.145],[0.387,0.318,0.316,0.350,0.305,0.316],[0.574,0.163,0.148,0.148,0.155,0.159],[0.144,0.042,0.038,0.037,0.049,0.038],[0.631,0.253,0.229,0.212,0.231,0.204],[0.433,0.222,0.329,0.274,0.156,0.200],[0.298,0.219,0.166,0.186,0.164,0.184],[0.316,0.238,0.207,0.244,0.195,0.198],[0.278,0.315,0.223,0.302,0.271,0.289],[0.562,0.294,0.267,0.281,0.281,0.308],[0.546,0.121,0.117,0.115,0.115,0.118],[0.588,0.329,0.310,0.288,0.274,0.275],[0.377,0.129,0.110,0.100,0.116,0.098],[0.330,0.065,0.063,0.064,0.064,0.063],[0.337,0.238,0.205,0.205,0.231,0.175],[0.298,0.160,0.183,0.180,0.173,0.186],[0.640,0.386,0.359,0.424,0.367,0.403],[0.430,0.254,0.233,0.220,0.217,0.218],[0.764,0.423,0.405,0.389,0.446,0.396],[0.660,0.394,0.414,0.416,0.440,0.398],[0.339,0.134,0.123,0.106,0.127,0.113],[0.262,0.165,0.109,0.121,0.105,0.095],[0.238,1.245,0.698,0.693,0.715,0.685],[0.311,0.119,0.104,0.114,0.102,0.104],[0.563,0.356,0.359,0.313,0.313,0.326],[0.518,0.178,0.150,0.152,0.169,0.159],[0.217,0.154,0.158,0.146,0.138,0.140],[0.007,0.006,0.006,0.007,0.006,0.007],[0.654,0.168,0.168,0.168,0.172,0.150],[0.754,0.311,0.211,0.200,0.211,0.196],[0.766,0.338,0.238,0.195,0.220,0.192],[0.837,0.349,0.225,0.221,0.304,0.262],[0.700,0.385,0.403,0.484,0.423,0.338],[0.271,0.176,0.121,0.111,0.093,0.125],[0.226,0.070,0.061,0.060,0.058,0.063],[0.505,0.138,0.120,0.118,0.216,0.206],[0.007,0.007,0.007,0.007,0.007,0.007],[0.007,0.007,0.007,0.007,0.007,0.007],[0.007,0.007,0.007,0.006,0.007,0.007],[0.678,0.176,0.164,0.176,0.168,0.170],[0.626,0.164,0.164,0.168,0.175,0.173],[0.641,0.177,0.172,0.184,0.170,0.169],[0.638,0.194,0.197,0.181,0.178,0.188],[0.448,0.169,0.153,0.169,0.149,0.151],[0.353,0.239,0.238,0.242,0.229,0.216],[0.508,0.275,0.240,0.262,0.243,0.179],[0.725,0.184,0.181,0.211,0.180,0.176],[0.695,0.184,0.171,0.166,0.178,0.172],[0.727,0.164,0.160,0.163,0.158,0.145],[0.680,0.193,0.178,0.160,0.182,0.175],[0.791,0.220,0.230,0.227,0.235,0.218],[0.465,0.179,0.129,0.130,0.237,0.126],[0.406,0.170,0.131,0.154,0.200,0.233],[0.476,0.186,0.237,0.177,0.129,0.143],[0.007,0.006,0.007,0.006,0.006,0.006],[0.006,0.006,0.006,0.007,0.006,0.006],[0.006,0.006,0.006,0.006,0.006,0.006],[0.722,0.201,0.177,0.174,0.178,0.176],[0.629,0.156,0.155,0.149,0.149,0.147],[0.690,0.199,0.183,0.189,0.195,0.179],[0.781,0.207,0.185,0.198,0.181,0.184],[0.774,0.192,0.172,0.174,0.173,0.170],[0.730,0.188,0.188,0.198,0.186,0.186],[0.745,0.342,0.267,0.305,0.295,0.286],[0.815,0.316,0.308,0.317,0.312,0.290],[0.714,0.210,0.207,0.203,0.202,0.210],[0.849,0.232,0.211,0.206,0.204,0.197],[0.724,0.181,0.168,0.169,0.167,0.173],[0.906,0.251,0.338,0.318,0.311,0.247],[0.620,0.080,0.071,0.079,0.067,0.049],[0.200,0.158,0.060,0.074,0.059,0.064],[0.197,0.233,0.234,0.230,0.228,0.189],[0.260,0.170,0.156,0.166,0.180,0.151],[0.376,0.324,0.260,0.256,0.266,0.266],[1.619,1.303,1.281,1.286,1.310,1.288],[8.457,0.941,0.931,0.954,0.918,0.927],[1.810,0.928,0.932,0.960,0.928,0.931],[12.728,2.226,2.224,2.241,2.221,2.221]],"version":"26.6.1.1193","source":"results/26.6.1.1193.json"} + +]; diff --git a/versions/fetch-results.sh b/versions/fetch-results.sh index 504fc4084f..69b1753027 100755 --- a/versions/fetch-results.sh +++ b/versions/fetch-results.sh @@ -32,6 +32,7 @@ mapfile -t VERSIONS < <(CH --query " SELECT DISTINCT JSONExtractString(content, 'version') AS v FROM sink.data WHERE JSONExtractString(content, 'kind') = 'versions-benchmark' AND v != '' + AND length(JSONExtractArrayRaw(content, 'result')) = 344 ORDER BY v FORMAT TSV") @@ -44,10 +45,12 @@ for v in "${VERSIONS[@]}"; do SELECT argMax(content, time) FROM sink.data WHERE JSONExtractString(content, 'kind') = 'versions-benchmark' AND JSONExtractString(content, 'version') = '${v}' + AND length(JSONExtractArrayRaw(content, 'result')) = 344 FORMAT TSVRaw" > /tmp/vb-content.json rd="$(reldate "${v}")" # Keep the recorded fields; add release_date (preferring one already in the payload). - jq -S --arg rd "${rd}" \ + # Compact one line per file: these are generated artifacts, kept small in git. + jq -cS --arg rd "${rd}" \ '. + {release_date: (.release_date // (if $rd == "" then null else $rd end))}' \ /tmp/vb-content.json > "results/${v}.json" echo " results/${v}.json (released ${rd:-unknown})" >&2 diff --git a/versions/generate-results.sh b/versions/generate-results.sh index a6241c1fb4..0b40e9383d 100755 --- a/versions/generate-results.sh +++ b/versions/generate-results.sh @@ -1,31 +1,58 @@ #!/bin/bash -e -# This script will substitute the benchmark results into the HTML page. -# Note: editing HTML with sed may look strange, but at least we avoid using node.js and npm, and that's good. - -# This is needed on Mac OS. Do `brew install coreutils`. -[ -n "$HOMEBREW_PREFIX" ] && PATH="${HOMEBREW_PREFIX}/opt/coreutils/libexec/gnubin:${PATH}" -if command -v gsed >/dev/null 2>&1 -then - alias sed='gsed' -fi - -( - sed '/^const data = \[$/q' index.html - - FIRST=1 - ls -1 results/*.json | while read file - do - >&2 echo processing ${file} - [ "${FIRST}" = "0" ] && echo -n ',' - jq --compact-output ". += {\"source\": \"${file}\"}" "${file}" - FIRST=0 - done +# Build data.generated.js (loaded by index.html) from the committed per-version result +# files in results/ (produced by fetch-results.sh) and the query sets in queries/. +# +# Output has two consts: +# const datasets = [{name, queries:[...]}, ...] // in the QUERY_ORDER the result +# // arrays are concatenated in +# const data = [{version, actual_version, release_date, machine, +# load_time:{ds:sec}, data_size:{ds:bytes}, result:[[...]], source}] +# +# Keeping data out of index.html (as the main ClickBench page does with +# data.generated.js) keeps the page diffable and lets the data regenerate on its own. + +HERE="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" +cd "${HERE}" + +# The order the runner concatenates per-dataset query results into result[] (see +# QUERY_ORDER in run-version.sh). datasets[].queries line up with result[] by offset. +QUERY_ORDER="mgbench ssb hits uk ontime taxi coffeeshop tpch tpcds job" - echo ']; // end of data' - sed '0,/^\]; \/\/ end of data$/d' index.html +OUT=data.generated.js -) > index.html.new +{ + echo '// Generated by generate-results.sh from results/*.json and queries/*.sql. Do not edit.' + + # datasets: name + its queries (one per non-empty line of queries/.sql). + echo -n 'const datasets = [' + first=1 + for ds in ${QUERY_ORDER}; do + [ "${first}" = 0 ] && echo -n ',' + first=0 + queries_json="$(jq -R -s 'split("\n") | map(select(length > 0))' "queries/${ds}.sql")" + printf '\n{"name":"%s","queries":%s}' "${ds}" "${queries_json}" + done + echo '' + echo '];' + echo '' + + # data: one entry per version, oldest release first (ties broken by version). + echo -n 'const data = [' + first=1 + while IFS=$'\t' read -r _rd file; do + [ -z "${file}" ] && continue + >&2 echo "processing ${file}" + [ "${first}" = 0 ] && echo -n ',' + first=0 + jq --compact-output ". += {\"source\": \"${file}\"}" "${file}" + done < <( + for f in results/*.json; do + printf '%s\t%s\n' "$(jq -r '.release_date // "9999-99-99"' "${f}")" "${f}" + done | sort -t$'\t' -k1,1 -k2,2V + ) + echo '' + echo '];' +} > "${OUT}" -mv index.html index.html.bak -mv index.html.new index.html +>&2 echo "wrote ${OUT} ($(wc -c < "${OUT}") bytes)" diff --git a/versions/index.html b/versions/index.html index d47c505d94..2bdb1285a8 100644 --- a/versions/index.html +++ b/versions/index.html @@ -285,212 +285,29 @@ font-size: 90%; } - + +
🌚🌞

ClickHouse Versions Benchmark

- Source | Report Mistake | Benchmark For Analytical DBMS | Hardware Benchmark + Source | Report Mistake | Benchmark For Analytical DBMS | Hardware Benchmark
@@ -500,6 +317,12 @@

ClickHouse Versions Benchmark

All + + + +
Dataset: + All +
Metric: @@ -540,12 +363,11 @@

Detailed Comparison

-

This includes a combination of three benchmarks: MgBench, Star Schema Benchmark, New York Taxi Rides Benchmark and ClickBench.

-

Hardware used to run tests: x86_64 AWS m5.8xlarge Ubuntu 20.04.

-

In 23.7 sparse columns feature is enabled by default. Tables were populated again to utilize sparse columns.

-

Old versions had no support of these features/syntax: toISOWeek, SUBSTRING, EXTRACT, WITH. Queries were changed. All version runs use same queries.

-

Star Schema Benchmark Patrick O'Neil, Elizabeth (Betty) O'Neil and Xuedong Chen. "The Star Schema Benchmark," Online Publication of Database Generation program., January 2007. http://www.cs.umb.edu/~poneil/StarSchemaB.pdf

-

Summary of the 1.1 Billion Taxi Rides Benchmarks, Mark Litwintschikhttps://tech.marksblogg.com/benchmarks.html

+

The same benchmark run on the same data across the whole history of ClickHouse versions, to show how performance evolved over the years. It combines several datasets and query sets: MgBench, the Star Schema Benchmark, ClickBench (the "hits" web-analytics dataset), the UK property price paid dataset, the airline OnTime dataset, the New York taxi rides benchmark, a coffee-shop sales dataset, TPC-H, TPC-DS, and the Join Order Benchmark (JOB).

+

Every version is packaged as a Docker image and runs the identical set of queries over the identical (Native-format) data. Versions with no published image — down to the earliest 2013–2016 snapshots — are reconstructed and built from source (see build-from-source). Very old versions predate SELECT version() and report their revision as 0.0.<revision>.

+

"Cold Run" is the first run of a query (cold OS/page cache dropped between queries); "Hot Run" is the fastest of the subsequent runs. A query that failed or is unsupported on a version is shown as ☠ and penalised in the relative-time summary. Per-dataset load time (sum of the load of that dataset's tables) and on-disk data size are shown in the dataset header rows.

+

Star Schema Benchmark: Patrick O'Neil, Elizabeth O'Neil and Xuedong Chen, "The Star Schema Benchmark", January 2007. http://www.cs.umb.edu/~poneil/StarSchemaB.pdf

+

1.1 Billion Taxi Rides Benchmarks: Mark Litwintschik. https://tech.marksblogg.com/benchmarks.html

@@ -362,14 +381,6 @@

Detailed Comparison

-
-

The same benchmark run on the same data across the whole history of ClickHouse versions, to show how performance evolved over the years. It combines several datasets and query sets: MgBench, the Star Schema Benchmark, ClickBench (the "hits" web-analytics dataset), the UK property price paid dataset, the airline OnTime dataset, the New York taxi rides benchmark, a coffee-shop sales dataset, TPC-H, TPC-DS, and the Join Order Benchmark (JOB).

-

Every version is packaged as a Docker image and runs the identical set of queries over the identical (Native-format) data. Versions with no published image — down to the earliest 2013–2016 snapshots — are reconstructed and built from source (see build-from-source). Very old versions predate SELECT version() and report their revision as 0.0.<revision>.

-

"Cold Run" is the first run of a query (cold OS/page cache dropped between queries); "Hot Run" is the fastest of the subsequent runs. A query that failed or is unsupported on a version is shown as ☠ and penalised in the relative-time summary. Per-dataset load time (sum of the load of that dataset's tables) and on-disk data size are shown in the dataset header rows.

-

Star Schema Benchmark: Patrick O'Neil, Elizabeth O'Neil and Xuedong Chen, "The Star Schema Benchmark", January 2007. http://www.cs.umb.edu/~poneil/StarSchemaB.pdf

-

1.1 Billion Taxi Rides Benchmarks: Mark Litwintschik. https://tech.marksblogg.com/benchmarks.html

-
-