test_runner/performance: add sharded ingest benchmark (#9591)

Adds a Python benchmark for sharded ingestion. This ingests 7 GB of WAL
(100M rows) into a Safekeeper and fans out to 10 shards running on 10
different pageservers. The ingest volume and duration is recorded.

Author: erikgrinaker

test_runner/performance/test_sharded_ingest.py

@@ -0,0 +1,71 @@
+from __future__ import annotations
+
+from contextlib import closing
+
+import pytest
+from fixtures.benchmark_fixture import MetricReport, NeonBenchmarker
+from fixtures.common_types import Lsn, TenantShardId
+from fixtures.log_helper import log
+from fixtures.neon_fixtures import (
+    NeonEnvBuilder,
+    tenant_get_shards,
+    wait_for_last_flush_lsn,
+)
+
+
+@pytest.mark.timeout(600)
+@pytest.mark.parametrize("shard_count", [1, 8, 32])
+def test_sharded_ingest(
+    neon_env_builder: NeonEnvBuilder,
+    zenbenchmark: NeonBenchmarker,
+    shard_count: int,
+):
+    """
+    Benchmarks sharded ingestion throughput, by ingesting a large amount of WAL into a Safekeeper
+    and fanning out to a large number of shards on dedicated Pageservers. Comparing the base case
+    (shard_count=1) to the sharded case indicates the overhead of sharding.
+    """
+
+    ROW_COUNT = 100_000_000  # about 7 GB of WAL
+
+    neon_env_builder.num_pageservers = shard_count
+    env = neon_env_builder.init_start()
+
+    # Create a sharded tenant and timeline, and migrate it to the respective pageservers. Ensure
+    # the storage controller doesn't mess with shard placements.
+    #
+    # TODO: there should be a way to disable storage controller background reconciliations.
+    # Currently, disabling reconciliation also disables foreground operations.
+    tenant_id, timeline_id = env.create_tenant(shard_count=shard_count)
+
+    for shard_number in range(0, shard_count):
+        tenant_shard_id = TenantShardId(tenant_id, shard_number, shard_count)
+        pageserver_id = shard_number + 1
+        env.storage_controller.tenant_shard_migrate(tenant_shard_id, pageserver_id)
+
+    shards = tenant_get_shards(env, tenant_id)
+    env.storage_controller.reconcile_until_idle()
+    assert tenant_get_shards(env, tenant_id) == shards, "shards moved"
+
+    # Start the endpoint.
+    endpoint = env.endpoints.create_start("main", tenant_id=tenant_id)
+    start_lsn = Lsn(endpoint.safe_psql("select pg_current_wal_lsn()")[0][0])
+
+    # Ingest data and measure WAL volume and duration.
+    with closing(endpoint.connect()) as conn:
+        with conn.cursor() as cur:
+            log.info("Ingesting data")
+            cur.execute("set statement_timeout = 0")
+            cur.execute("create table huge (i int, j int)")
+
+            with zenbenchmark.record_duration("pageserver_ingest"):
+                with zenbenchmark.record_duration("wal_ingest"):
+                    cur.execute(f"insert into huge values (generate_series(1, {ROW_COUNT}), 0)")
+
+                wait_for_last_flush_lsn(env, endpoint, tenant_id, timeline_id)
+
+    end_lsn = Lsn(endpoint.safe_psql("select pg_current_wal_lsn()")[0][0])
+    wal_written_mb = round((end_lsn - start_lsn) / (1024 * 1024))
+    zenbenchmark.record("wal_written", wal_written_mb, "MB", MetricReport.TEST_PARAM)
+
+    assert tenant_get_shards(env, tenant_id) == shards, "shards moved"