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Instead of having a lot of separate fixtures for setting up the page server, the compute nodes, the safekeepers etc., have one big ZenithEnv object that encapsulates the whole environment. Every test either uses a shared "zenith_simple_env" fixture, which contains the default setup of a pageserver with no authentication, and no safekeepers. Tests that want to use safekeepers or authentication set up a custom test-specific ZenithEnv fixture. Gathering information about the whole environment into one object makes some things simpler. For example, when a new compute node is created, you no longer need to pass the 'wal_acceptors' connection string as argument to the 'postgres.create_start' function. The 'create_start' function fetches that information directly from the ZenithEnv object.
59 lines
2.1 KiB
Python
59 lines
2.1 KiB
Python
import os
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from contextlib import closing
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from fixtures.zenith_fixtures import ZenithEnv
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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(zenith_simple_env: ZenithEnv, pg_bin, zenbenchmark):
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env = zenith_simple_env
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# Create a branch for us
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env.zenith_cli(["branch", "test_pgbench_perf", "empty"])
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pg = env.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 = env.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(env.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 {env.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 {env.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(env.repo_dir, env.initial_tenant, timeline)
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zenbenchmark.record('size', timeline_size / (1024 * 1024), 'MB')
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