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46210035c5
## Problem halfvec data type was introduced in pgvector 0.7.0 and is popular because it allows smaller vectors, smaller indexes and potentially better performance. So far we have not tested halfvec in our periodic performance tests. This PR adds halfvec indexing and halfvec queries to the test.
287 lines
19 KiB
Python
287 lines
19 KiB
Python
import os
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from dataclasses import dataclass
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from typing import Dict, List, Tuple
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import pytest
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from _pytest.mark import ParameterSet
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from fixtures.compare_fixtures import RemoteCompare
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from fixtures.log_helper import log
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from fixtures.utils import get_self_dir
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@dataclass
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class LabelledQuery:
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"""An SQL query with a label for the test report."""
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label: str
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query: str
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# This must run before all tests in this module
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# create extension pg_stat_statements if it does not exist
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# and TEST_OLAP_COLLECT_PG_STAT_STATEMENTS is set to true (default false)
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# Theoretically this could be in a module or session scope fixture,
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# however the code depends on other fixtures that have function scope
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@pytest.mark.skipif(
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os.getenv("TEST_OLAP_COLLECT_PG_STAT_STATEMENTS", "false").lower() == "false",
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reason="Skipping - Creating extension pg_stat_statements",
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)
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@pytest.mark.remote_cluster
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def test_clickbench_create_pg_stat_statements(remote_compare: RemoteCompare):
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log.info("Creating extension pg_stat_statements")
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query = LabelledQuery(
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"Q_CREATE_EXTENSION", r"CREATE EXTENSION IF NOT EXISTS pg_stat_statements;"
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)
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run_psql(remote_compare, query, times=1, explain=False)
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log.info("Reset pg_stat_statements")
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query = LabelledQuery("Q_RESET", r"SELECT pg_stat_statements_reset();")
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run_psql(remote_compare, query, times=1, explain=False)
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# A list of queries to run.
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# Please do not alter the label for the query, as it is used to identify it.
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# Labels for ClickBench queries match the labels in ClickBench reports
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# on https://benchmark.clickhouse.com/ (the DB size may differ).
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#
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# Disable auto formatting for the list of queries so that it's easier to read
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# fmt: off
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QUERIES: Tuple[LabelledQuery, ...] = (
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### ClickBench queries:
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LabelledQuery("Q0", r"SELECT COUNT(*) FROM hits;"),
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LabelledQuery("Q1", r"SELECT COUNT(*) FROM hits WHERE AdvEngineID <> 0;"),
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LabelledQuery("Q2", r"SELECT SUM(AdvEngineID), COUNT(*), AVG(ResolutionWidth) FROM hits;"),
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LabelledQuery("Q3", r"SELECT AVG(UserID) FROM hits;"),
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LabelledQuery("Q4", r"SELECT COUNT(DISTINCT UserID) FROM hits;"),
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LabelledQuery("Q5", r"SELECT COUNT(DISTINCT SearchPhrase) FROM hits;"),
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LabelledQuery("Q6", r"SELECT MIN(EventDate), MAX(EventDate) FROM hits;"),
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LabelledQuery("Q7", r"SELECT AdvEngineID, COUNT(*) FROM hits WHERE AdvEngineID <> 0 GROUP BY AdvEngineID ORDER BY COUNT(*) DESC;"),
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LabelledQuery("Q8", r"SELECT RegionID, COUNT(DISTINCT UserID) AS u FROM hits GROUP BY RegionID ORDER BY u DESC LIMIT 10;"),
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LabelledQuery("Q9", r"SELECT RegionID, SUM(AdvEngineID), COUNT(*) AS c, AVG(ResolutionWidth), COUNT(DISTINCT UserID) FROM hits GROUP BY RegionID ORDER BY c DESC LIMIT 10;"),
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LabelledQuery("Q10", r"SELECT MobilePhoneModel, COUNT(DISTINCT UserID) AS u FROM hits WHERE MobilePhoneModel <> '' GROUP BY MobilePhoneModel ORDER BY u DESC LIMIT 10;"),
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LabelledQuery("Q11", r"SELECT MobilePhone, MobilePhoneModel, COUNT(DISTINCT UserID) AS u FROM hits WHERE MobilePhoneModel <> '' GROUP BY MobilePhone, MobilePhoneModel ORDER BY u DESC LIMIT 10;"),
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LabelledQuery("Q12", r"SELECT SearchPhrase, COUNT(*) AS c FROM hits WHERE SearchPhrase <> '' GROUP BY SearchPhrase ORDER BY c DESC LIMIT 10;"),
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LabelledQuery("Q13", r"SELECT SearchPhrase, COUNT(DISTINCT UserID) AS u FROM hits WHERE SearchPhrase <> '' GROUP BY SearchPhrase ORDER BY u DESC LIMIT 10;"),
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LabelledQuery("Q14", r"SELECT SearchEngineID, SearchPhrase, COUNT(*) AS c FROM hits WHERE SearchPhrase <> '' GROUP BY SearchEngineID, SearchPhrase ORDER BY c DESC LIMIT 10;"),
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LabelledQuery("Q15", r"SELECT UserID, COUNT(*) FROM hits GROUP BY UserID ORDER BY COUNT(*) DESC LIMIT 10;"),
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LabelledQuery("Q16", r"SELECT UserID, SearchPhrase, COUNT(*) FROM hits GROUP BY UserID, SearchPhrase ORDER BY COUNT(*) DESC LIMIT 10;"),
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LabelledQuery("Q17", r"SELECT UserID, SearchPhrase, COUNT(*) FROM hits GROUP BY UserID, SearchPhrase LIMIT 10;"),
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LabelledQuery("Q18", r"SELECT UserID, extract(minute FROM EventTime) AS m, SearchPhrase, COUNT(*) FROM hits GROUP BY UserID, m, SearchPhrase ORDER BY COUNT(*) DESC LIMIT 10;"),
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LabelledQuery("Q19", r"SELECT UserID FROM hits WHERE UserID = 435090932899640449;"),
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LabelledQuery("Q20", r"SELECT COUNT(*) FROM hits WHERE URL LIKE '%google%';"),
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LabelledQuery("Q21", r"SELECT SearchPhrase, MIN(URL), COUNT(*) AS c FROM hits WHERE URL LIKE '%google%' AND SearchPhrase <> '' GROUP BY SearchPhrase ORDER BY c DESC LIMIT 10;"),
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LabelledQuery("Q22", r"SELECT SearchPhrase, MIN(URL), MIN(Title), COUNT(*) AS c, COUNT(DISTINCT UserID) FROM hits WHERE Title LIKE '%Google%' AND URL NOT LIKE '%.google.%' AND SearchPhrase <> '' GROUP BY SearchPhrase ORDER BY c DESC LIMIT 10;"),
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LabelledQuery("Q23", r"SELECT * FROM hits WHERE URL LIKE '%google%' ORDER BY EventTime LIMIT 10;"),
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LabelledQuery("Q24", r"SELECT SearchPhrase FROM hits WHERE SearchPhrase <> '' ORDER BY EventTime LIMIT 10;"),
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LabelledQuery("Q25", r"SELECT SearchPhrase FROM hits WHERE SearchPhrase <> '' ORDER BY SearchPhrase LIMIT 10;"),
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LabelledQuery("Q26", r"SELECT SearchPhrase FROM hits WHERE SearchPhrase <> '' ORDER BY EventTime, SearchPhrase LIMIT 10;"),
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LabelledQuery("Q27", r"SELECT CounterID, AVG(length(URL)) AS l, COUNT(*) AS c FROM hits WHERE URL <> '' GROUP BY CounterID HAVING COUNT(*) > 100000 ORDER BY l DESC LIMIT 25;"),
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LabelledQuery("Q28", r"SELECT REGEXP_REPLACE(Referer, '^https?://(?:www\.)?([^/]+)/.*$', '\1') AS k, AVG(length(Referer)) AS l, COUNT(*) AS c, MIN(Referer) FROM hits WHERE Referer <> '' GROUP BY k HAVING COUNT(*) > 100000 ORDER BY l DESC LIMIT 25;"),
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LabelledQuery("Q29", r"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;"),
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LabelledQuery("Q30", r"SELECT SearchEngineID, ClientIP, COUNT(*) AS c, SUM(IsRefresh), AVG(ResolutionWidth) FROM hits WHERE SearchPhrase <> '' GROUP BY SearchEngineID, ClientIP ORDER BY c DESC LIMIT 10;"),
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LabelledQuery("Q31", r"SELECT WatchID, ClientIP, COUNT(*) AS c, SUM(IsRefresh), AVG(ResolutionWidth) FROM hits WHERE SearchPhrase <> '' GROUP BY WatchID, ClientIP ORDER BY c DESC LIMIT 10;"),
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LabelledQuery("Q32", r"SELECT WatchID, ClientIP, COUNT(*) AS c, SUM(IsRefresh), AVG(ResolutionWidth) FROM hits GROUP BY WatchID, ClientIP ORDER BY c DESC LIMIT 10;"),
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LabelledQuery("Q33", r"SELECT URL, COUNT(*) AS c FROM hits GROUP BY URL ORDER BY c DESC LIMIT 10;"),
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LabelledQuery("Q34", r"SELECT 1, URL, COUNT(*) AS c FROM hits GROUP BY 1, URL ORDER BY c DESC LIMIT 10;"),
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LabelledQuery("Q35", r"SELECT ClientIP, ClientIP - 1, ClientIP - 2, ClientIP - 3, COUNT(*) AS c FROM hits GROUP BY ClientIP, ClientIP - 1, ClientIP - 2, ClientIP - 3 ORDER BY c DESC LIMIT 10;"),
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LabelledQuery("Q36", r"SELECT URL, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= '2013-07-01' AND EventDate <= '2013-07-31' AND DontCountHits = 0 AND IsRefresh = 0 AND URL <> '' GROUP BY URL ORDER BY PageViews DESC LIMIT 10;"),
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LabelledQuery("Q37", r"SELECT Title, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= '2013-07-01' AND EventDate <= '2013-07-31' AND DontCountHits = 0 AND IsRefresh = 0 AND Title <> '' GROUP BY Title ORDER BY PageViews DESC LIMIT 10;"),
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LabelledQuery("Q38", r"SELECT URL, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= '2013-07-01' AND EventDate <= '2013-07-31' AND IsRefresh = 0 AND IsLink <> 0 AND IsDownload = 0 GROUP BY URL ORDER BY PageViews DESC LIMIT 10 OFFSET 1000;"),
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LabelledQuery("Q39", r"SELECT TraficSourceID, SearchEngineID, AdvEngineID, CASE WHEN (SearchEngineID = 0 AND AdvEngineID = 0) THEN Referer ELSE '' END AS Src, URL AS Dst, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= '2013-07-01' AND EventDate <= '2013-07-31' AND IsRefresh = 0 GROUP BY TraficSourceID, SearchEngineID, AdvEngineID, Src, Dst ORDER BY PageViews DESC LIMIT 10 OFFSET 1000;"),
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LabelledQuery("Q40", r"SELECT URLHash, EventDate, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= '2013-07-01' AND EventDate <= '2013-07-31' AND IsRefresh = 0 AND TraficSourceID IN (-1, 6) AND RefererHash = 3594120000172545465 GROUP BY URLHash, EventDate ORDER BY PageViews DESC LIMIT 10 OFFSET 100;"),
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LabelledQuery("Q41", r"SELECT WindowClientWidth, WindowClientHeight, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= '2013-07-01' AND EventDate <= '2013-07-31' AND IsRefresh = 0 AND DontCountHits = 0 AND URLHash = 2868770270353813622 GROUP BY WindowClientWidth, WindowClientHeight ORDER BY PageViews DESC LIMIT 10 OFFSET 10000;"),
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LabelledQuery("Q42", r"SELECT DATE_TRUNC('minute', EventTime) AS M, COUNT(*) AS PageViews FROM hits WHERE CounterID = 62 AND EventDate >= '2013-07-14' AND EventDate <= '2013-07-15' AND IsRefresh = 0 AND DontCountHits = 0 GROUP BY DATE_TRUNC('minute', EventTime) ORDER BY DATE_TRUNC('minute', EventTime) LIMIT 10 OFFSET 1000;"),
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### Custom Neon queries:
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# I suggest using the NQ prefix (which stands for Neon Query) instead of Q
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# to not intersect with the original ClickBench queries if their list is extended.
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#
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# LabelledQuery("NQ0", r"..."),
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# LabelledQuery("NQ1", r"..."),
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# ...
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)
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# fmt: on
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# A list of pgvector HNSW index builds to run.
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# Please do not alter the label for the query, as it is used to identify it.
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#
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# Disable auto formatting for the list of queries so that it's easier to read
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# fmt: off
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PGVECTOR_QUERIES: Tuple[LabelledQuery, ...] = (
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LabelledQuery("PGVPREP", r"ALTER EXTENSION VECTOR UPDATE;"),
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LabelledQuery("PGV0", r"DROP TABLE IF EXISTS hnsw_test_table;"),
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LabelledQuery("PGV1", r"CREATE TABLE hnsw_test_table AS TABLE documents WITH NO DATA;"),
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LabelledQuery("PGV2", r"INSERT INTO hnsw_test_table SELECT * FROM documents;"),
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LabelledQuery("PGV3", r"CREATE INDEX ON hnsw_test_table (_id);"),
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LabelledQuery("PGV4", r"CREATE INDEX ON hnsw_test_table USING hnsw (embeddings vector_cosine_ops);"),
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LabelledQuery("PGV5", r"CREATE INDEX ON hnsw_test_table USING hnsw (embeddings vector_ip_ops);"),
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LabelledQuery("PGV6", r"CREATE INDEX ON hnsw_test_table USING hnsw (embeddings vector_l1_ops);"),
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LabelledQuery("PGV7", r"CREATE INDEX ON hnsw_test_table USING hnsw ((binary_quantize(embeddings)::bit(1536)) bit_hamming_ops);"),
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LabelledQuery("PGV8", r"CREATE INDEX ON hnsw_test_table USING hnsw ((binary_quantize(embeddings)::bit(1536)) bit_jaccard_ops);"),
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LabelledQuery("PGV9", r"DROP TABLE IF EXISTS halfvec_test_table;"),
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LabelledQuery("PGV10", r"CREATE TABLE halfvec_test_table (_id text NOT NULL, title text, text text, embeddings halfvec(1536), PRIMARY KEY (_id));"),
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LabelledQuery("PGV11", r"INSERT INTO halfvec_test_table (_id, title, text, embeddings) SELECT _id, title, text, embeddings::halfvec FROM documents;"),
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LabelledQuery("PGV12", r"CREATE INDEX documents_half_precision_hnsw_idx ON halfvec_test_table USING hnsw (embeddings halfvec_cosine_ops) WITH (m = 64, ef_construction = 128);"),
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)
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# fmt: on
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EXPLAIN_STRING: str = "EXPLAIN (ANALYZE, VERBOSE, BUFFERS, COSTS, SETTINGS, FORMAT JSON)"
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def get_scale() -> List[str]:
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# We parametrize each tpc-h and clickbench test with scale
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# to distinguish them from each other, but don't really use it inside.
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# Databases are pre-created and passed through BENCHMARK_CONNSTR env variable.
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scale = os.getenv("TEST_OLAP_SCALE", "noscale")
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return [scale]
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# run the query times times plus once with EXPLAIN VERBOSE if explain is requestd
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def run_psql(
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env: RemoteCompare, labelled_query: LabelledQuery, times: int, explain: bool = False
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) -> None:
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# prepare connstr:
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# - cut out password from connstr to pass it via env
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# - add options to connstr
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password = env.pg.default_options.get("password", None)
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options = f"-cstatement_timeout=0 {env.pg.default_options.get('options', '')}"
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connstr = env.pg.connstr(password=None, options=options)
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environ: Dict[str, str] = {}
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if password is not None:
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environ["PGPASSWORD"] = password
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label, query = labelled_query.label, labelled_query.query
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log.info(f"Running query {label} {times} times")
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for i in range(times):
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run = i + 1
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log.info(f"Run {run}/{times}")
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with env.zenbenchmark.record_duration(f"{label}/{run}"):
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env.pg_bin.run_capture(["psql", connstr, "-c", query], env=environ)
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if explain:
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log.info(f"Explaining query {label}")
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run += 1
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with env.zenbenchmark.record_duration(f"{label}/EXPLAIN"):
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env.pg_bin.run_capture(
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["psql", connstr, "-c", f"{EXPLAIN_STRING} {query}"], env=environ
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)
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@pytest.mark.parametrize("scale", get_scale())
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@pytest.mark.parametrize("query", QUERIES)
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@pytest.mark.remote_cluster
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def test_clickbench(query: LabelledQuery, remote_compare: RemoteCompare, scale: str):
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"""
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An OLAP-style ClickHouse benchmark
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Based on https://github.com/ClickHouse/ClickBench/tree/c00135ca5b6a0d86fedcdbf998fdaa8ed85c1c3b/aurora-postgresql
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The DB prepared manually in advance.
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Important: after intial data load, run `VACUUM (DISABLE_PAGE_SKIPPING, FREEZE, ANALYZE) hits;`
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to ensure that Postgres optimizer chooses the same plans as RDS and Aurora.
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"""
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explain: bool = os.getenv("TEST_OLAP_COLLECT_EXPLAIN", "false").lower() == "true"
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run_psql(remote_compare, query, times=3, explain=explain)
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def tpch_queuies() -> Tuple[ParameterSet, ...]:
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"""
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A list of queries to run for the TPC-H benchmark.
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- querues in returning tuple are ordered by the query number
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- pytest parameters id is adjusted to match the query id (the numbering starts from 1)
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"""
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queries_dir = get_self_dir().parent / "performance" / "tpc-h" / "queries"
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assert queries_dir.exists(), f"TPC-H queries dir not found: {queries_dir}"
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return tuple(
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pytest.param(LabelledQuery(f"Q{f.stem}", f.read_text()), id=f"query{f.stem}")
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for f in sorted(queries_dir.glob("*.sql"), key=lambda f: int(f.stem))
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)
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@pytest.mark.parametrize("scale", get_scale())
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@pytest.mark.parametrize("query", tpch_queuies())
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@pytest.mark.remote_cluster
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def test_tpch(query: LabelledQuery, remote_compare: RemoteCompare, scale: str):
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"""
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TCP-H Benchmark
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The DB prepared manually in advance:
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- schema: test_runner/performance/tpc-h/create-schema.sql
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- indexes: test_runner/performance/tpc-h/create-indexes.sql
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- data generated by `dbgen` program of the official TPC-H benchmark
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- `VACUUM (FREEZE, PARALLEL 0);`
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For query generation `1669822882` is used as a seed to the RNG
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"""
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run_psql(remote_compare, query, times=1)
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@pytest.mark.remote_cluster
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def test_user_examples(remote_compare: RemoteCompare):
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query = LabelledQuery(
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"Q1",
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r"""
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SELECT
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v20.c2263 AS v1,
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v19.c2484 AS v2,
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DATE_TRUNC('month', v18.c37)::DATE AS v3,
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(ARRAY_AGG(c1840 order by v18.c37))[1] AS v4,
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(ARRAY_AGG(c1841 order by v18.c37 DESC))[1] AS v5,
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SUM(v17.c1843) AS v6,
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SUM(v17.c1844) AS v7,
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SUM(v17.c1848) AS v8,
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SUM(v17.c1845) AS v9,
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SUM(v17.c1846) AS v10,
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SUM(v17.c1861) AS v11,
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SUM(v17.c1860) AS v12,
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SUM(v17.c1869) AS v13,
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SUM(v17.c1856) AS v14,
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SUM(v17.c1855) AS v15,
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SUM(v17.c1854) AS v16
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FROM
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s3.t266 v17
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INNER JOIN s1.t41 v18 ON v18.c34 = v17.c1836
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INNER JOIN s3.t571 v19 ON v19.c2482 = v17.c1834
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INNER JOIN s3.t331 v20 ON v20.c2261 = v17.c1835
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WHERE
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(v17.c1835 = 4) AND
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(v18.c37 >= '2019-03-01') AND
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(v17.c1833 = 2)
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GROUP BY v1, v2, v3
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ORDER BY v1, v2, v3
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LIMIT 199;
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""",
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)
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run_psql(remote_compare, query, times=3)
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# This must run after all tests in this module
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# Collect pg_stat_statements after running the tests if TEST_OLAP_COLLECT_PG_STAT_STATEMENTS is set to true (default false)
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@pytest.mark.skipif(
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os.getenv("TEST_OLAP_COLLECT_PG_STAT_STATEMENTS", "false").lower() == "false",
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reason="Skipping - Collecting pg_stat_statements",
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)
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@pytest.mark.remote_cluster
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def test_clickbench_collect_pg_stat_statements(remote_compare: RemoteCompare):
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log.info("Collecting pg_stat_statements")
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query = LabelledQuery("Q_COLLECT_PG_STAT_STATEMENTS", r"SELECT * from pg_stat_statements;")
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run_psql(remote_compare, query, times=1, explain=False)
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@pytest.mark.parametrize("query", PGVECTOR_QUERIES)
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@pytest.mark.remote_cluster
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def test_pgvector_indexing(query: LabelledQuery, remote_compare: RemoteCompare):
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"""
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An pgvector test that tests HNSW index build performance and parallelism.
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The DB prepared manually in advance.
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See
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- test_runner/performance/pgvector/README.md
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- test_runner/performance/pgvector/loaddata.py
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- test_runner/performance/pgvector/HNSW_build.sql
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"""
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run_psql(remote_compare, query, times=1, explain=False)
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