Files
neon/test_runner/performance/test_perf_pgbench.py
Heikki Linnakangas c6678c5dea Include # of bytes written in pgbench benchmark result
Now that the page server collects this metric (since commit 212920e47e),
let's include it in the performance test results

The new metric looks like this:

    performance/test_perf_pgbench.py .         [100%]
    --------------- Benchmark results ----------------
    test_pgbench.init: 6.784 s
    test_pgbench.pageserver_writes: 466 MB    <---- THIS IS NEW
    test_pgbench.5000_xacts: 8.196 s
    test_pgbench.size: 163 MB

    =============== 1 passed in 21.00s ===============
2021-09-03 09:00:26 +03:00

69 lines
2.5 KiB
Python

import os
from contextlib import closing
from fixtures.zenith_fixtures import PostgresFactory, ZenithPageserver
pytest_plugins = ("fixtures.zenith_fixtures", "fixtures.benchmark_fixture")
def get_timeline_size(repo_dir: str, tenantid: str, timelineid: str):
path = "{}/tenants/{}/timelines/{}".format(repo_dir, tenantid, timelineid)
totalbytes = 0
for root, dirs, files in os.walk(path):
for name in files:
totalbytes += os.path.getsize(os.path.join(root, name))
if 'wal' in dirs:
dirs.remove('wal') # don't visit 'wal' subdirectory
return totalbytes
#
# Run a very short pgbench test.
#
# Collects three metrics:
#
# 1. Time to initialize the pgbench database (pgbench -s5 -i)
# 2. Time to run 5000 pgbench transactions
# 3. Disk space used
#
def test_pgbench(postgres: PostgresFactory, pageserver: ZenithPageserver, pg_bin, zenith_cli, zenbenchmark, repo_dir: str):
# Create a branch for us
zenith_cli.run(["branch", "test_pgbench_perf", "empty"])
pg = postgres.create_start('test_pgbench_perf')
print("postgres is running on 'test_pgbench_perf' branch")
# Open a connection directly to the page server that we'll use to force
# flushing the layers to disk
psconn = pageserver.connect();
pscur = psconn.cursor()
# Get the timeline ID of our branch. We need it for the 'do_gc' command
with closing(pg.connect()) as conn:
with conn.cursor() as cur:
cur.execute("SHOW zenith.zenith_timeline")
timeline = cur.fetchone()[0]
connstr = pg.connstr()
# Initialize pgbench database, recording the time and I/O it takes
with zenbenchmark.record_pageserver_writes(pageserver, 'pageserver_writes'):
with zenbenchmark.record_duration('init'):
pg_bin.run_capture(['pgbench', '-s5', '-i', connstr])
# Flush the layers from memory to disk. This is included in the reported
# time and I/O
pscur.execute(f"do_gc {pageserver.initial_tenant} {timeline} 0")
# Run pgbench for 5000 transactions
with zenbenchmark.record_duration('5000_xacts'):
pg_bin.run_capture(['pgbench', '-c1', '-t5000', connstr])
# Flush the layers to disk again. This is *not' included in the reported time,
# though.
pscur.execute(f"do_gc {pageserver.initial_tenant} {timeline} 0")
# Report disk space used by the repository
timeline_size = get_timeline_size(repo_dir, pageserver.initial_tenant, timeline)
zenbenchmark.record('size', timeline_size / (1024*1024), 'MB')