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Add vanilla pg baseline tests (#1275)

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bojanserafimov
2022-02-15 13:44:22 -05:00
committed by GitHub
parent 5563ff123f
commit afb3342e46
8 changed files with 306 additions and 338 deletions
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109
test_runner/performance/test_parallel_copy_to.py
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@@ -1,11 +1,16 @@
from io import BytesIO
import asyncio
import asyncpg
from fixtures.zenith_fixtures import ZenithEnv, Postgres
from fixtures.zenith_fixtures import ZenithEnv, Postgres, PgProtocol
from fixtures.log_helper import log
from fixtures.benchmark_fixture import MetricReport, ZenithBenchmarker
from fixtures.compare_fixtures import PgCompare, VanillaCompare, ZenithCompare
pytest_plugins = ("fixtures.zenith_fixtures", "fixtures.benchmark_fixture")
pytest_plugins = (
"fixtures.zenith_fixtures",
"fixtures.benchmark_fixture",
"fixtures.compare_fixtures",
)
async def repeat_bytes(buf, repetitions: int):
@@ -13,7 +18,7 @@ async def repeat_bytes(buf, repetitions: int):
yield buf
async def copy_test_data_to_table(pg: Postgres, worker_id: int, table_name: str):
async def copy_test_data_to_table(pg: PgProtocol, worker_id: int, table_name: str):
buf = BytesIO()
for i in range(1000):
buf.write(
@@ -26,7 +31,7 @@ async def copy_test_data_to_table(pg: Postgres, worker_id: int, table_name: str)
await pg_conn.copy_to_table(table_name, source=copy_input)
async def parallel_load_different_tables(pg: Postgres, n_parallel: int):
async def parallel_load_different_tables(pg: PgProtocol, n_parallel: int):
workers = []
for worker_id in range(n_parallel):
worker = copy_test_data_to_table(pg, worker_id, f'copytest_{worker_id}')
@@ -37,54 +42,25 @@ async def parallel_load_different_tables(pg: Postgres, n_parallel: int):
# Load 5 different tables in parallel with COPY TO
def test_parallel_copy_different_tables(zenith_simple_env: ZenithEnv,
zenbenchmark: ZenithBenchmarker,
n_parallel=5):
def test_parallel_copy_different_tables(zenith_with_baseline: PgCompare, n_parallel=5):
env = zenith_simple_env
# Create a branch for us
env.zenith_cli(["branch", "test_parallel_copy_different_tables", "empty"])
pg = env.postgres.create_start('test_parallel_copy_different_tables')
log.info("postgres is running on 'test_parallel_copy_different_tables' branch")
# Open a connection directly to the page server that we'll use to force
# flushing the layers to disk
psconn = env.pageserver.connect()
pscur = psconn.cursor()
# Get the timeline ID of our branch. We need it for the 'do_gc' command
conn = pg.connect()
env = zenith_with_baseline
conn = env.pg.connect()
cur = conn.cursor()
cur.execute("SHOW zenith.zenith_timeline")
timeline = cur.fetchone()[0]
for worker_id in range(n_parallel):
cur.execute(f'CREATE TABLE copytest_{worker_id} (i int, t text)')
with zenbenchmark.record_pageserver_writes(env.pageserver, 'pageserver_writes'):
with zenbenchmark.record_duration('load'):
asyncio.run(parallel_load_different_tables(pg, n_parallel))
with env.record_pageserver_writes('pageserver_writes'):
with env.record_duration('load'):
asyncio.run(parallel_load_different_tables(env.pg, n_parallel))
env.flush()
# Flush the layers from memory to disk. This is included in the reported
# time and I/O
pscur.execute(f"do_gc {env.initial_tenant} {timeline} 0")
# Record peak memory usage
zenbenchmark.record("peak_mem",
zenbenchmark.get_peak_mem(env.pageserver) / 1024,
'MB',
report=MetricReport.LOWER_IS_BETTER)
# Report disk space used by the repository
timeline_size = zenbenchmark.get_timeline_size(env.repo_dir, env.initial_tenant, timeline)
zenbenchmark.record('size',
timeline_size / (1024 * 1024),
'MB',
report=MetricReport.LOWER_IS_BETTER)
env.report_peak_memory_use()
env.report_size()
async def parallel_load_same_table(pg: Postgres, n_parallel: int):
async def parallel_load_same_table(pg: PgProtocol, n_parallel: int):
workers = []
for worker_id in range(n_parallel):
worker = copy_test_data_to_table(pg, worker_id, f'copytest')
@@ -95,46 +71,17 @@ async def parallel_load_same_table(pg: Postgres, n_parallel: int):
# Load data into one table with COPY TO from 5 parallel connections
def test_parallel_copy_same_table(zenith_simple_env: ZenithEnv,
zenbenchmark: ZenithBenchmarker,
n_parallel=5):
env = zenith_simple_env
# Create a branch for us
env.zenith_cli(["branch", "test_parallel_copy_same_table", "empty"])
pg = env.postgres.create_start('test_parallel_copy_same_table')
log.info("postgres is running on 'test_parallel_copy_same_table' branch")
# Open a connection directly to the page server that we'll use to force
# flushing the layers to disk
psconn = env.pageserver.connect()
pscur = psconn.cursor()
# Get the timeline ID of our branch. We need it for the 'do_gc' command
conn = pg.connect()
def test_parallel_copy_same_table(zenith_with_baseline: PgCompare, n_parallel=5):
env = zenith_with_baseline
conn = env.pg.connect()
cur = conn.cursor()
cur.execute("SHOW zenith.zenith_timeline")
timeline = cur.fetchone()[0]
cur.execute(f'CREATE TABLE copytest (i int, t text)')
with zenbenchmark.record_pageserver_writes(env.pageserver, 'pageserver_writes'):
with zenbenchmark.record_duration('load'):
asyncio.run(parallel_load_same_table(pg, n_parallel))
with env.record_pageserver_writes('pageserver_writes'):
with env.record_duration('load'):
asyncio.run(parallel_load_same_table(env.pg, n_parallel))
env.flush()
# Flush the layers from memory to disk. This is included in the reported
# time and I/O
pscur.execute(f"do_gc {env.initial_tenant} {timeline} 0")
# Record peak memory usage
zenbenchmark.record("peak_mem",
zenbenchmark.get_peak_mem(env.pageserver) / 1024,
'MB',
report=MetricReport.LOWER_IS_BETTER)
# Report disk space used by the repository
timeline_size = zenbenchmark.get_timeline_size(env.repo_dir, env.initial_tenant, timeline)
zenbenchmark.record('size',
timeline_size / (1024 * 1024),
'MB',
report=MetricReport.LOWER_IS_BETTER)
env.report_peak_memory_use()
env.report_size()