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* Add yapf run to CircleCI * Pin yapf version * Enable `SPLIT_ALL_TOP_LEVEL_COMMA_SEPARATED_VALUES` setting * Reformat all existing code with slight manual adjustments * test_runner/README: note that yapf is forced
63 lines
2.2 KiB
Python
63 lines
2.2 KiB
Python
import os
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from contextlib import closing
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from fixtures.zenith_fixtures import PostgresFactory, ZenithPageserver
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from fixtures.log_helper import log
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pytest_plugins = ("fixtures.zenith_fixtures", "fixtures.benchmark_fixture")
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#
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# Run a very short pgbench test.
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#
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# Collects three metrics:
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#
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# 1. Time to initialize the pgbench database (pgbench -s5 -i)
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# 2. Time to run 5000 pgbench transactions
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# 3. Disk space used
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#
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def test_pgbench(postgres: PostgresFactory,
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pageserver: ZenithPageserver,
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pg_bin,
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zenith_cli,
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zenbenchmark,
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repo_dir: str):
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# Create a branch for us
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zenith_cli.run(["branch", "test_pgbench_perf", "empty"])
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pg = postgres.create_start('test_pgbench_perf')
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log.info("postgres is running on 'test_pgbench_perf' branch")
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# Open a connection directly to the page server that we'll use to force
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# flushing the layers to disk
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psconn = pageserver.connect()
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pscur = psconn.cursor()
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# Get the timeline ID of our branch. We need it for the 'do_gc' command
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with closing(pg.connect()) as conn:
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with conn.cursor() as cur:
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cur.execute("SHOW zenith.zenith_timeline")
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timeline = cur.fetchone()[0]
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connstr = pg.connstr()
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# Initialize pgbench database, recording the time and I/O it takes
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with zenbenchmark.record_pageserver_writes(pageserver, 'pageserver_writes'):
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with zenbenchmark.record_duration('init'):
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pg_bin.run_capture(['pgbench', '-s5', '-i', connstr])
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# Flush the layers from memory to disk. This is included in the reported
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# time and I/O
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pscur.execute(f"do_gc {pageserver.initial_tenant} {timeline} 0")
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# Run pgbench for 5000 transactions
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with zenbenchmark.record_duration('5000_xacts'):
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pg_bin.run_capture(['pgbench', '-c1', '-t5000', connstr])
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# Flush the layers to disk again. This is *not' included in the reported time,
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# though.
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pscur.execute(f"do_gc {pageserver.initial_tenant} {timeline} 0")
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# Report disk space used by the repository
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timeline_size = zenbenchmark.get_timeline_size(repo_dir, pageserver.initial_tenant, timeline)
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zenbenchmark.record('size', timeline_size / (1024 * 1024), 'MB')
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