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Add more variants of the sequential scan performance tests.
More rows, and test with serial and parallel plans. But fewer iterations, so that the tests run in < 1 minutes, and we don't need to mark them as "slow".
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@@ -1,8 +1,5 @@
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# Test sequential scan speed
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#
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# The test table is large enough (3-4 MB) that it doesn't fit in the compute node
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# cache, so the seqscans go to the page server. But small enough that it fits
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# into memory in the page server.
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from contextlib import closing
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from dataclasses import dataclass
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from fixtures.zenith_fixtures import ZenithEnv
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@@ -12,11 +9,18 @@ from fixtures.compare_fixtures import PgCompare
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import pytest
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@pytest.mark.parametrize('rows', [
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pytest.param(100000),
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pytest.param(1000000, marks=pytest.mark.slow),
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])
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def test_small_seqscans(zenith_with_baseline: PgCompare, rows: int):
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@pytest.mark.parametrize(
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'rows,iters,workers',
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[
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# The test table is large enough (3-4 MB) that it doesn't fit in the compute node
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# cache, so the seqscans go to the page server. But small enough that it fits
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# into memory in the page server.
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pytest.param(100000, 100, 0),
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# Also test with a larger table, with and without parallelism
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pytest.param(10000000, 1, 0),
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pytest.param(10000000, 1, 4)
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])
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def test_seqscans(zenith_with_baseline: PgCompare, rows: int, iters: int, workers: int):
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env = zenith_with_baseline
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with closing(env.pg.connect()) as conn:
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@@ -36,6 +40,8 @@ def test_small_seqscans(zenith_with_baseline: PgCompare, rows: int):
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assert int(shared_buffers) < int(table_size)
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env.zenbenchmark.record("table_size", table_size, 'bytes', MetricReport.TEST_PARAM)
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cur.execute(f"set max_parallel_workers_per_gather = {workers}")
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with env.record_duration('run'):
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for i in range(1000):
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for i in range(iters):
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cur.execute('select count(*) from t;')
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