bench: run branch_creation_many at 500, seeded (#6959)

We have a benchmark for creating a lot of branches, but it does random
things, and the branch count is not what we is the largest maximum we
aim to support. If this PR would stabilize the benchmark total duration
it means that there are some structures which are very much slower than
others. Then we should add a seed-outputting variant to help find and
reproduce such cases.

Additionally, record for the benchmark:
- shutdown duration
- startup metrics once done (on restart)
- duration of first compaction completion via debug logging
This commit is contained in:
Joonas Koivunen
2024-03-07 16:23:42 +02:00
committed by GitHub
parent d3c583efbe
commit 602a4da9a5
2 changed files with 109 additions and 8 deletions

View File

@@ -101,6 +101,7 @@ pub fn start_background_loops(
_ = completion::Barrier::maybe_wait(background_jobs_can_start) => {}
};
compaction_loop(tenant, cancel)
// If you rename this span, change the RUST_LOG env variable in test_runner/performance/test_branch_creation.py
.instrument(info_span!("compaction_loop", tenant_id = %tenant_shard_id.tenant_id, shard_id = %tenant_shard_id.shard_slug()))
.await;
Ok(())
@@ -198,7 +199,11 @@ async fn compaction_loop(tenant: Arc<Tenant>, cancel: CancellationToken) {
}
};
warn_when_period_overrun(started_at.elapsed(), period, BackgroundLoopKind::Compaction);
let elapsed = started_at.elapsed();
warn_when_period_overrun(elapsed, period, BackgroundLoopKind::Compaction);
// the duration is recorded by performance tests by enabling debug in this function
tracing::debug!(elapsed_ms=elapsed.as_millis(), "compaction iteration complete");
// Perhaps we did no work and the walredo process has been idle for some time:
// give it a chance to shut down to avoid leaving walredo process running indefinitely.

View File

@@ -1,4 +1,5 @@
import random
import re
import statistics
import threading
import time
@@ -7,11 +8,14 @@ from contextlib import closing
from typing import List
import pytest
from fixtures.benchmark_fixture import MetricReport
from fixtures.benchmark_fixture import MetricReport, NeonBenchmarker
from fixtures.compare_fixtures import NeonCompare
from fixtures.log_helper import log
from fixtures.neon_fixtures import NeonPageserver
from fixtures.pageserver.utils import wait_for_last_record_lsn
from fixtures.types import Lsn
from fixtures.utils import wait_until
from prometheus_client.samples import Sample
def _record_branch_creation_durations(neon_compare: NeonCompare, durs: List[float]):
@@ -89,11 +93,17 @@ def test_branch_creation_heavy_write(neon_compare: NeonCompare, n_branches: int)
_record_branch_creation_durations(neon_compare, branch_creation_durations)
@pytest.mark.parametrize("n_branches", [1024])
# Test measures the latency of branch creation when creating a lot of branches.
def test_branch_creation_many(neon_compare: NeonCompare, n_branches: int):
@pytest.mark.parametrize("n_branches", [500, 1024])
@pytest.mark.parametrize("shape", ["one_ancestor", "random"])
def test_branch_creation_many(neon_compare: NeonCompare, n_branches: int, shape: str):
"""
Test measures the latency of branch creation when creating a lot of branches.
"""
env = neon_compare.env
# seed the prng so we will measure the same structure every time
rng = random.Random("2024-02-29")
env.neon_cli.create_branch("b0")
endpoint = env.endpoints.create_start("b0")
@@ -102,15 +112,101 @@ def test_branch_creation_many(neon_compare: NeonCompare, n_branches: int):
branch_creation_durations = []
for i in range(n_branches):
# random a source branch
p = random.randint(0, i)
if shape == "random":
parent = f"b{rng.randint(0, i)}"
elif shape == "one_ancestor":
parent = "b0"
else:
raise RuntimeError(f"unimplemented shape: {shape}")
timer = timeit.default_timer()
env.neon_cli.create_branch("b{}".format(i + 1), "b{}".format(p))
# each of these uploads to remote storage before completion
env.neon_cli.create_branch(f"b{i + 1}", parent)
dur = timeit.default_timer() - timer
branch_creation_durations.append(dur)
_record_branch_creation_durations(neon_compare, branch_creation_durations)
endpoint.stop_and_destroy()
with neon_compare.record_duration("shutdown"):
# this sleeps 100ms between polls
env.pageserver.stop()
startup_line = "INFO version: git(-env)?:"
# find the first line of the log file so we can find the next start later
_, first_start = wait_until(5, 1, lambda: env.pageserver.assert_log_contains(startup_line))
# start without gc so we can time compaction with less noise; use shorter
# period for compaction so it starts earlier
env.pageserver.start(
overrides=(
"--pageserver-config-override=tenant_config={ compaction_period = '3s', gc_period = '0s' }",
),
# this does print more than we want, but the number should be comparable between runs
extra_env_vars={
"RUST_LOG": f"[compaction_loop{{tenant_id={env.initial_tenant}}}]=debug,info"
},
)
_, second_start = wait_until(
5, 1, lambda: env.pageserver.assert_log_contains(startup_line, first_start)
)
env.pageserver.quiesce_tenants()
wait_and_record_startup_metrics(env.pageserver, neon_compare.zenbenchmark, "restart_after")
# wait for compaction to complete, which most likely has already done so multiple times
msg, _ = wait_until(
30,
1,
lambda: env.pageserver.assert_log_contains(
f".*tenant_id={env.initial_tenant}.*: compaction iteration complete.*", second_start
),
)
needle = re.search(" elapsed_ms=([0-9]+)", msg)
assert needle is not None, "failed to find the elapsed time"
duration = int(needle.group(1)) / 1000.0
neon_compare.zenbenchmark.record("compaction", duration, "s", MetricReport.LOWER_IS_BETTER)
def wait_and_record_startup_metrics(
pageserver: NeonPageserver, target: NeonBenchmarker, prefix: str
):
"""
Waits until all startup metrics have non-zero values on the pageserver, then records them on the target
"""
client = pageserver.http_client()
expected_labels = set(
[
"background_jobs_can_start",
"complete",
"initial",
"initial_tenant_load",
"initial_tenant_load_remote",
]
)
def metrics_are_filled() -> List[Sample]:
m = client.get_metrics()
samples = m.query_all("pageserver_startup_duration_seconds")
# we should not have duplicate labels
matching = [
x for x in samples if x.labels.get("phase") in expected_labels and x.value > 0.0
]
assert len(matching) == len(expected_labels)
return matching
samples = wait_until(10, 1, metrics_are_filled)
for sample in samples:
phase = sample.labels["phase"]
name = f"{prefix}.{phase}"
target.record(name, sample.value, "s", MetricReport.LOWER_IS_BETTER)
# Test measures the branch creation time when branching from a timeline with a lot of relations.
#