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https://github.com/neondatabase/neon.git
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30a7dd630c
## Problem `TYPE_CHECKING` is used inconsistently across Python tests. ## Summary of changes - Update `ruff`: 0.7.0 -> 0.11.2 - Enable TC (flake8-type-checking): https://docs.astral.sh/ruff/rules/#flake8-type-checking-tc - (auto)fix all new issues
120 lines
4.8 KiB
Python
120 lines
4.8 KiB
Python
from __future__ import annotations
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import time
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from pathlib import Path
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from typing import TYPE_CHECKING
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import pytest
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from fixtures.log_helper import log
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from fixtures.utils import USE_LFC, query_scalar
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if TYPE_CHECKING:
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from fixtures.neon_fixtures import NeonEnv
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@pytest.mark.skipif(not USE_LFC, reason="LFC is disabled, skipping")
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def test_lfc_working_set_approximation(neon_simple_env: NeonEnv):
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env = neon_simple_env
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cache_dir = Path(env.repo_dir) / "file_cache"
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cache_dir.mkdir(exist_ok=True)
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log.info("Creating endpoint with 1MB shared_buffers and 64 MB LFC")
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endpoint = env.endpoints.create_start(
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"main",
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config_lines=["neon.max_file_cache_size='128MB'", "neon.file_cache_size_limit='64MB'"],
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)
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cur = endpoint.connect().cursor()
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cur.execute("create extension neon")
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log.info(f"preparing some data in {endpoint.connstr()}")
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ddl = """
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CREATE TABLE pgbench_accounts (
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aid bigint NOT NULL,
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bid integer,
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abalance integer,
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filler character(84),
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-- more web-app like columns
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text_column_plain TEXT DEFAULT repeat('NeonIsCool', 5),
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jsonb_column_extended JSONB DEFAULT ('{ "tell everyone": [' || repeat('{"Neon": "IsCool"},',9) || ' {"Neon": "IsCool"}]}')::jsonb
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)
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WITH (fillfactor='100');
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"""
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cur.execute(ddl)
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# prepare index access below
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cur.execute(
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"ALTER TABLE ONLY pgbench_accounts ADD CONSTRAINT pgbench_accounts_pkey PRIMARY KEY (aid)"
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)
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cur.execute(
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"insert into pgbench_accounts(aid,bid,abalance,filler) select aid, (aid - 1) / 100000 + 1, 0, '' from generate_series(1, 100000) as aid;"
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)
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# ensure correct query plans and stats
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cur.execute("vacuum ANALYZE pgbench_accounts")
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# determine table size - working set should approximate table size after sequential scan
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pages = query_scalar(cur, "SELECT relpages FROM pg_class WHERE relname = 'pgbench_accounts'")
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log.info(f"pgbench_accounts has {pages} pages, resetting working set to zero")
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cur.execute("select approximate_working_set_size(true)")
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cur.execute(
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'SELECT count(*) FROM pgbench_accounts WHERE abalance > 0 or jsonb_column_extended @> \'{"tell everyone": [{"Neon": "IsCool"}]}\'::jsonb'
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)
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# verify working set size after sequential scan matches table size and reset working set for next test
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blocks = query_scalar(cur, "select approximate_working_set_size(true)")
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log.info(f"working set size after sequential scan on pgbench_accounts {blocks}")
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assert pages * 0.8 < blocks < pages * 1.2
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# run a few point queries with index lookup
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cur.execute("SELECT abalance FROM pgbench_accounts WHERE aid = 4242")
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cur.execute("SELECT abalance FROM pgbench_accounts WHERE aid = 54242")
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cur.execute("SELECT abalance FROM pgbench_accounts WHERE aid = 104242")
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cur.execute("SELECT abalance FROM pgbench_accounts WHERE aid = 204242")
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# verify working set size after some index access of a few select pages only
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blocks = query_scalar(cur, "select approximate_working_set_size(true)")
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log.info(f"working set size after some index access of a few select pages only {blocks}")
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assert blocks < 12
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@pytest.mark.skipif(not USE_LFC, reason="LFC is disabled, skipping")
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def test_sliding_working_set_approximation(neon_simple_env: NeonEnv):
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env = neon_simple_env
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endpoint = env.endpoints.create_start(
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branch_name="main",
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config_lines=[
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"autovacuum = off",
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"shared_buffers=1MB",
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"neon.max_file_cache_size=256MB",
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"neon.file_cache_size_limit=245MB",
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],
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)
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conn = endpoint.connect()
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cur = conn.cursor()
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cur.execute("create extension neon")
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cur.execute(
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"create table t(pk integer primary key, count integer default 0, payload text default repeat('?', 128))"
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)
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cur.execute("insert into t (pk) values (generate_series(1,1000000))")
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time.sleep(2)
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before_10k = time.monotonic()
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cur.execute("select sum(count) from t where pk between 10000 and 20000")
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time.sleep(2)
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before_1k = time.monotonic()
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cur.execute("select sum(count) from t where pk between 1000 and 2000")
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after = time.monotonic()
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cur.execute(f"select approximate_working_set_size_seconds({int(after - before_1k + 1)})")
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estimation_1k = cur.fetchall()[0][0]
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log.info(f"Working set size for selecting 1k records {estimation_1k}")
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cur.execute(f"select approximate_working_set_size_seconds({int(after - before_10k + 1)})")
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estimation_10k = cur.fetchall()[0][0]
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log.info(f"Working set size for selecting 10k records {estimation_10k}")
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cur.execute("select pg_table_size('t')")
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size = cur.fetchall()[0][0] // 8192
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log.info(f"Table size {size} blocks")
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assert estimation_1k >= 20 and estimation_1k <= 40
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assert estimation_10k >= 200 and estimation_10k <= 440
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