Add vanilla pg baseline tests (#1275)

This commit is contained in:
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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@@ -2,8 +2,13 @@ from contextlib import closing
from fixtures.zenith_fixtures import ZenithEnv
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",
)
#
@@ -16,47 +21,19 @@ pytest_plugins = ("fixtures.zenith_fixtures", "fixtures.benchmark_fixture")
# 3. Disk space used
# 4. Peak memory usage
#
def test_bulk_insert(zenith_simple_env: ZenithEnv, zenbenchmark: ZenithBenchmarker):
env = zenith_simple_env
# Create a branch for us
env.zenith_cli(["branch", "test_bulk_insert", "empty"])
pg = env.postgres.create_start('test_bulk_insert')
log.info("postgres is running on 'test_bulk_insert' 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()
def test_bulk_insert(zenith_with_baseline: PgCompare):
env = zenith_with_baseline
# Get the timeline ID of our branch. We need it for the 'do_gc' command
with closing(pg.connect()) as conn:
with closing(env.pg.connect()) as conn:
with conn.cursor() as cur:
cur.execute("SHOW zenith.zenith_timeline")
timeline = cur.fetchone()[0]
cur.execute("create table huge (i int, j int);")
# Run INSERT, recording the time and I/O it takes
with zenbenchmark.record_pageserver_writes(env.pageserver, 'pageserver_writes'):
with zenbenchmark.record_duration('insert'):
with env.record_pageserver_writes('pageserver_writes'):
with env.record_duration('insert'):
cur.execute("insert into huge values (generate_series(1, 5000000), 0);")
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()

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@@ -2,10 +2,15 @@ from contextlib import closing
from fixtures.zenith_fixtures import ZenithEnv
from fixtures.log_helper import log
from fixtures.benchmark_fixture import MetricReport, ZenithBenchmarker
from fixtures.compare_fixtures import PgCompare, VanillaCompare, ZenithCompare
from io import BufferedReader, RawIOBase
from itertools import repeat
pytest_plugins = ("fixtures.zenith_fixtures", "fixtures.benchmark_fixture")
pytest_plugins = (
"fixtures.zenith_fixtures",
"fixtures.benchmark_fixture",
"fixtures.compare_fixtures",
)
class CopyTestData(RawIOBase):
@@ -42,77 +47,41 @@ def copy_test_data(rows: int):
#
# COPY performance tests.
#
def test_copy(zenith_simple_env: ZenithEnv, zenbenchmark: ZenithBenchmarker):
env = zenith_simple_env
# Create a branch for us
env.zenith_cli(["branch", "test_copy", "empty"])
pg = env.postgres.create_start('test_copy')
log.info("postgres is running on 'test_copy' 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()
def test_copy(zenith_with_baseline: PgCompare):
env = zenith_with_baseline
# Get the timeline ID of our branch. We need it for the pageserver 'checkpoint' command
with closing(pg.connect()) as conn:
with closing(env.pg.connect()) as conn:
with conn.cursor() as cur:
cur.execute("SHOW zenith.zenith_timeline")
timeline = cur.fetchone()[0]
cur.execute("create table copytest (i int, t text);")
# Load data with COPY, recording the time and I/O it takes.
#
# Since there's no data in the table previously, this extends it.
with zenbenchmark.record_pageserver_writes(env.pageserver,
'copy_extend_pageserver_writes'):
with zenbenchmark.record_duration('copy_extend'):
with env.record_pageserver_writes('copy_extend_pageserver_writes'):
with env.record_duration('copy_extend'):
cur.copy_from(copy_test_data(1000000), 'copytest')
# Flush the layers from memory to disk. This is included in the reported
# time and I/O
pscur.execute(f"checkpoint {env.initial_tenant} {timeline}")
env.flush()
# Delete most rows, and VACUUM to make the space available for reuse.
with zenbenchmark.record_pageserver_writes(env.pageserver, 'delete_pageserver_writes'):
with zenbenchmark.record_duration('delete'):
with env.record_pageserver_writes('delete_pageserver_writes'):
with env.record_duration('delete'):
cur.execute("delete from copytest where i % 100 <> 0;")
# Flush the layers from memory to disk. This is included in the reported
# time and I/O
pscur.execute(f"checkpoint {env.initial_tenant} {timeline}")
env.flush()
with zenbenchmark.record_pageserver_writes(env.pageserver, 'vacuum_pageserver_writes'):
with zenbenchmark.record_duration('vacuum'):
with env.record_pageserver_writes('vacuum_pageserver_writes'):
with env.record_duration('vacuum'):
cur.execute("vacuum copytest")
# Flush the layers from memory to disk. This is included in the reported
# time and I/O
pscur.execute(f"checkpoint {env.initial_tenant} {timeline}")
env.flush()
# Load data into the table again. This time, this will use the space free'd
# by the VACUUM.
#
# This will also clear all the VM bits.
with zenbenchmark.record_pageserver_writes(env.pageserver,
'copy_reuse_pageserver_writes'):
with zenbenchmark.record_duration('copy_reuse'):
with env.record_pageserver_writes('copy_reuse_pageserver_writes'):
with env.record_duration('copy_reuse'):
cur.copy_from(copy_test_data(1000000), 'copytest')
env.flush()
# Flush the layers from memory to disk. This is included in the reported
# time and I/O
pscur.execute(f"checkpoint {env.initial_tenant} {timeline}")
# 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()

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@@ -2,9 +2,14 @@ import os
from contextlib import closing
from fixtures.benchmark_fixture import MetricReport
from fixtures.zenith_fixtures import ZenithEnv
from fixtures.compare_fixtures import PgCompare, VanillaCompare, ZenithCompare
from fixtures.log_helper import log
pytest_plugins = ("fixtures.zenith_fixtures", "fixtures.benchmark_fixture")
pytest_plugins = (
"fixtures.zenith_fixtures",
"fixtures.benchmark_fixture",
"fixtures.compare_fixtures",
)
#
@@ -12,24 +17,11 @@ pytest_plugins = ("fixtures.zenith_fixtures", "fixtures.benchmark_fixture")
# As of this writing, we're duplicate those giant WAL records for each page,
# which makes the delta layer about 32x larger than it needs to be.
#
def test_gist_buffering_build(zenith_simple_env: ZenithEnv, zenbenchmark):
env = zenith_simple_env
# Create a branch for us
env.zenith_cli(["branch", "test_gist_buffering_build", "empty"])
def test_gist_buffering_build(zenith_with_baseline: PgCompare):
env = zenith_with_baseline
pg = env.postgres.create_start('test_gist_buffering_build')
log.info("postgres is running on 'test_gist_buffering_build' 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
with closing(pg.connect()) as conn:
with closing(env.pg.connect()) as conn:
with conn.cursor() as cur:
cur.execute("SHOW zenith.zenith_timeline")
timeline = cur.fetchone()[0]
# Create test table.
cur.execute("create table gist_point_tbl(id int4, p point)")
@@ -38,27 +30,12 @@ def test_gist_buffering_build(zenith_simple_env: ZenithEnv, zenbenchmark):
)
# Build the index.
with zenbenchmark.record_pageserver_writes(env.pageserver, 'pageserver_writes'):
with zenbenchmark.record_duration('build'):
with env.record_pageserver_writes('pageserver_writes'):
with env.record_duration('build'):
cur.execute(
"create index gist_pointidx2 on gist_point_tbl using gist(p) with (buffering = on)"
)
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} 1000000")
# 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()

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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()

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@@ -1,18 +1,15 @@
from contextlib import closing
from fixtures.zenith_fixtures import PgBin, VanillaPostgres, ZenithEnv
from fixtures.compare_fixtures import PgCompare, VanillaCompare, ZenithCompare
from fixtures.benchmark_fixture import MetricReport, ZenithBenchmarker
from fixtures.log_helper import log
pytest_plugins = ("fixtures.zenith_fixtures", "fixtures.benchmark_fixture")
def pgbench_init(pg_bin: PgBin, connstr: str):
pg_bin.run_capture(['pgbench', '-s5', '-i', connstr])
def pgbench_run_5000_transactions(pg_bin: PgBin, connstr: str):
pg_bin.run_capture(['pgbench', '-c1', '-t5000', connstr])
pytest_plugins = (
"fixtures.zenith_fixtures",
"fixtures.benchmark_fixture",
"fixtures.compare_fixtures",
)
#
@@ -24,82 +21,16 @@ def pgbench_run_5000_transactions(pg_bin: PgBin, connstr: str):
# 2. Time to run 5000 pgbench transactions
# 3. Disk space used
#
def test_pgbench(zenith_simple_env: ZenithEnv, pg_bin: PgBin, zenbenchmark: ZenithBenchmarker):
env = zenith_simple_env
# Create a branch for us
env.zenith_cli(["branch", "test_pgbench_perf", "empty"])
def test_pgbench(zenith_with_baseline: PgCompare):
env = zenith_with_baseline
pg = env.postgres.create_start('test_pgbench_perf')
log.info("postgres is running on 'test_pgbench_perf' branch")
with env.record_pageserver_writes('pageserver_writes'):
with env.record_duration('init'):
env.pg_bin.run_capture(['pgbench', '-s5', '-i', env.pg.connstr()])
env.flush()
# 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()
with env.record_duration('5000_xacts'):
env.pg_bin.run_capture(['pgbench', '-c1', '-t5000', env.pg.connstr()])
env.flush()
# 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(env.pageserver, 'pageserver_writes'):
with zenbenchmark.record_duration('init'):
pgbench_init(pg_bin, connstr)
# 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")
# Run pgbench for 5000 transactions
with zenbenchmark.record_duration('5000_xacts'):
pgbench_run_5000_transactions(pg_bin, connstr)
# Flush the layers to disk again. This is *not' included in the reported time,
# though.
pscur.execute(f"do_gc {env.initial_tenant} {timeline} 0")
# 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)
def test_pgbench_baseline(vanilla_pg: VanillaPostgres, zenbenchmark: ZenithBenchmarker):
vanilla_pg.configure(['shared_buffers=1MB'])
vanilla_pg.start()
pg_bin = vanilla_pg.pg_bin
connstr = vanilla_pg.connstr()
conn = vanilla_pg.connect()
cur = conn.cursor()
with zenbenchmark.record_duration('init'):
pgbench_init(pg_bin, connstr)
# This is roughly equivalent to flushing the layers from memory to disk with Zenith.
cur.execute(f"checkpoint")
# Run pgbench for 5000 transactions
with zenbenchmark.record_duration('5000_xacts'):
pgbench_run_5000_transactions(pg_bin, connstr)
# This is roughly equivalent to flush the layers from memory to disk with Zenith.
cur.execute(f"checkpoint")
# Report disk space used by the repository
data_size = vanilla_pg.get_subdir_size('base')
zenbenchmark.record('data_size',
data_size / (1024 * 1024),
'MB',
report=MetricReport.LOWER_IS_BETTER)
wal_size = vanilla_pg.get_subdir_size('pg_wal')
zenbenchmark.record('wal_size',
wal_size / (1024 * 1024),
'MB',
report=MetricReport.LOWER_IS_BETTER)
env.report_size()

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@@ -7,24 +7,19 @@ from contextlib import closing
from fixtures.zenith_fixtures import ZenithEnv
from fixtures.log_helper import log
from fixtures.benchmark_fixture import MetricReport, ZenithBenchmarker
from fixtures.compare_fixtures import PgCompare
pytest_plugins = ("fixtures.zenith_fixtures", "fixtures.benchmark_fixture")
pytest_plugins = (
"fixtures.zenith_fixtures",
"fixtures.benchmark_fixture",
"fixtures.compare_fixtures",
)
def test_small_seqscans(zenith_simple_env: ZenithEnv, zenbenchmark: ZenithBenchmarker):
env = zenith_simple_env
# Create a branch for us
env.zenith_cli(["branch", "test_small_seqscans", "empty"])
def test_small_seqscans(zenith_with_baseline: PgCompare):
env = zenith_with_baseline
pg = env.postgres.create_start('test_small_seqscans')
log.info("postgres is running on 'test_small_seqscans' 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()
with closing(pg.connect()) as conn:
with closing(env.pg.connect()) as conn:
with conn.cursor() as cur:
cur.execute('create table t (i integer);')
cur.execute('insert into t values (generate_series(1,100000));')
@@ -38,6 +33,6 @@ def test_small_seqscans(zenith_simple_env: ZenithEnv, zenbenchmark: ZenithBenchm
log.info(f"shared_buffers is {row[0]}, table size {row[1]}")
assert int(row[0]) < int(row[1])
with zenbenchmark.record_duration('run'):
with env.record_duration('run'):
for i in range(1000):
cur.execute('select count(*) from t;')

View File

@@ -14,32 +14,23 @@ import os
from contextlib import closing
from fixtures.benchmark_fixture import MetricReport
from fixtures.zenith_fixtures import ZenithEnv
from fixtures.compare_fixtures import PgCompare, VanillaCompare, ZenithCompare
from fixtures.log_helper import log
pytest_plugins = ("fixtures.zenith_fixtures", "fixtures.benchmark_fixture")
pytest_plugins = (
"fixtures.zenith_fixtures",
"fixtures.benchmark_fixture",
"fixtures.compare_fixtures",
)
def test_write_amplification(zenith_simple_env: ZenithEnv, zenbenchmark):
env = zenith_simple_env
# Create a branch for us
env.zenith_cli(["branch", "test_write_amplification", "empty"])
def test_write_amplification(zenith_with_baseline: PgCompare):
env = zenith_with_baseline
pg = env.postgres.create_start('test_write_amplification')
log.info("postgres is running on 'test_write_amplification' 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()
with closing(pg.connect()) as conn:
with closing(env.pg.connect()) as conn:
with conn.cursor() as cur:
# Get the timeline ID of our branch. We need it for the 'do_gc' command
cur.execute("SHOW zenith.zenith_timeline")
timeline = cur.fetchone()[0]
with zenbenchmark.record_pageserver_writes(env.pageserver, 'pageserver_writes'):
with zenbenchmark.record_duration('run'):
with env.record_pageserver_writes('pageserver_writes'):
with env.record_duration('run'):
# NOTE: Because each iteration updates every table already created,
# the runtime and write amplification is O(n^2), where n is the
@@ -71,13 +62,6 @@ def test_write_amplification(zenith_simple_env: ZenithEnv, zenbenchmark):
# slower, adding some delays in this loop. But forcing
# the checkpointing and GC makes the test go faster,
# with the same total I/O effect.
pscur.execute(f"do_gc {env.initial_tenant} {timeline} 0")
env.flush()
# 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_size()