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110 lines
3.1 KiB
Python
110 lines
3.1 KiB
Python
import threading
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import timeit
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from threading import BoundedSemaphore
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import pytest
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from fixtures.benchmark_fixture import MetricReport
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from fixtures.compare_fixtures import NeonCompare
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from fixtures.neon_fixtures import NeonEnvBuilder
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# Run bulk tenant creation test.
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#
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# Collects metrics:
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#
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# 1. Time to create {1,10,50} tenants
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# 2. Average creation time per tenant
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@pytest.mark.parametrize("tenants_count", [1, 5, 10])
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def test_bulk_tenant_create(
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neon_env_builder: NeonEnvBuilder,
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tenants_count: int,
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zenbenchmark,
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):
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neon_env_builder.num_safekeepers = 3
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env = neon_env_builder.init_start()
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time_slices = []
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for i in range(tenants_count):
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start = timeit.default_timer()
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tenant, _ = env.neon_cli.create_tenant()
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env.neon_cli.create_timeline(
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f"test_bulk_tenant_create_{tenants_count}_{i}", tenant_id=tenant
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)
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# FIXME: We used to start new safekeepers here. Did that make sense? Should we do it now?
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# if use_safekeepers == 'with_sa':
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# wa_factory.start_n_new(3)
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endpoint_tenant = env.endpoints.create_start(
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f"test_bulk_tenant_create_{tenants_count}_{i}", tenant_id=tenant
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)
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end = timeit.default_timer()
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time_slices.append(end - start)
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endpoint_tenant.stop()
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zenbenchmark.record(
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"tenant_creation_time",
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sum(time_slices) / len(time_slices),
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"s",
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report=MetricReport.LOWER_IS_BETTER,
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)
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@pytest.mark.parametrize("tenants_count", [50])
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def test_parallel_tenant_create(
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neon_compare: NeonCompare,
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tenants_count: int,
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):
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"""Create lots of tenants in parallel
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One important thing that this measures is the amount of prometheus
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metrics per tenant. The pageserver exposes a lot of metrics for
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each timeline, and this test gives some visibility to how much
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exactly. (We've had to raise the prometheus scraper's limit on
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the max metrics size several times, because we expose so many.)
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"""
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env = neon_compare.env
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zenbenchmark = neon_compare.zenbenchmark
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max_concurrent = 5
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pool_sema = BoundedSemaphore(value=max_concurrent)
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def worker(i: int):
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with pool_sema:
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tenant, timeline_id = env.neon_cli.create_tenant()
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endpoint_tenant = env.endpoints.create_start("main", tenant_id=tenant)
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with endpoint_tenant.cursor() as cur:
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cur.execute("select count(*) from pg_class")
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endpoint_tenant.stop()
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threads = [threading.Thread(target=worker, args=(i,)) for i in range(tenants_count)]
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start = timeit.default_timer()
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for thread in threads:
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thread.start()
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for thread in threads:
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thread.join()
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end = timeit.default_timer()
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zenbenchmark.record(
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"tenant_creation_time",
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end - start,
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"s",
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report=MetricReport.LOWER_IS_BETTER,
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)
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metrics = env.pageserver.http_client().get_metrics_str()
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zenbenchmark.record(
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"prometheus_metrics_size",
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len(metrics) / tenants_count,
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"bytes",
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report=MetricReport.LOWER_IS_BETTER,
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)
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