Files
neon/test_runner/performance/test_storage_controller_scale.py
2024-03-28 17:57:11 +00:00

110 lines
3.9 KiB
Python

import concurrent.futures
import random
import time
from fixtures.neon_fixtures import (
NeonEnvBuilder,
)
from fixtures.pageserver.http import PageserverHttpClient
from fixtures.pg_version import PgVersion
from fixtures.types import TenantId, TenantShardId, TimelineId
def test_sharding_service_many_tenants(
neon_env_builder: NeonEnvBuilder,
):
"""
Check that we cope well with a not-totally-trivial number of tenants.
This is checking for:
- Obvious concurrency bugs from issuing many tenant creations/modifications
concurrently.
- Obvious scaling bugs like O(N^2) scaling that would be so slow that even
a basic test starts failing from slowness.
This is _not_ a comprehensive scale test: just a basic sanity check that
we don't fall over for a thousand shards.
"""
neon_env_builder.num_pageservers = 5
env = neon_env_builder.init_start()
# Total tenants
tenant_count = 2000
# Shards per tenant
shard_count = 2
stripe_size = 1024
tenants = set(TenantId.generate() for _i in range(0, tenant_count))
virtual_ps_http = PageserverHttpClient(env.storage_controller_port, lambda: True)
# We use a fixed seed to make the test reproducible: we want a randomly
# chosen order, but not to change the order every time we run the test.
rng = random.Random(1234)
# We will create tenants directly via API, not via neon_local, to avoid any false
# serialization of operations in neon_local (it e.g. loads/saves a config file on each call)
with concurrent.futures.ThreadPoolExecutor() as executor:
futs = []
for tenant_id in tenants:
f = executor.submit(
env.storage_controller.tenant_create, tenant_id, shard_count, stripe_size
)
futs.append(f)
# Wait for creations to finish
for f in futs:
f.result()
# Generate a mixture of operations and dispatch them all concurrently
futs = []
for tenant_id in tenants:
op = rng.choice([0, 1, 2])
if op == 0:
# A fan-out write operation to all shards in a tenant (timeline creation)
f = executor.submit(
virtual_ps_http.timeline_create,
PgVersion.NOT_SET,
tenant_id,
TimelineId.generate(),
)
elif op == 1:
# A reconciler operation: migrate a shard.
shard_number = rng.randint(0, shard_count - 1)
tenant_shard_id = TenantShardId(tenant_id, shard_number, shard_count)
dest_ps_id = rng.choice([ps.id for ps in env.pageservers])
f = executor.submit(
env.storage_controller.tenant_shard_migrate, tenant_shard_id, dest_ps_id
)
elif op == 2:
# A passthrough read to shard zero
f = executor.submit(virtual_ps_http.tenant_status, tenant_id)
futs.append(f)
# Wait for mixed ops to finish
for f in futs:
f.result()
# Rolling node failures: this is a small number of requests, but results in a large
# number of scheduler calls and reconcile tasks.
for pageserver in env.pageservers:
env.storage_controller.node_configure(pageserver.id, {"availability": "Offline"})
# The sleeps are just to make sure we aren't optimizing-away any re-scheduling operations
# from a brief flap in node state.
time.sleep(1)
env.storage_controller.node_configure(pageserver.id, {"availability": "Active"})
time.sleep(1)
# Restart the storage controller
env.storage_controller.stop()
env.storage_controller.start()
# Restart pageservers: this exercises the /re-attach API
for pageserver in env.pageservers:
pageserver.stop()
pageserver.start()