Add performance test for bulk INSERT

test_runner/performance/test_bulk_insert.py

@@ -0,0 +1,60 @@
+import os
+from contextlib import closing
+from fixtures.zenith_fixtures import PostgresFactory, ZenithPageserver
+
+pytest_plugins = ("fixtures.zenith_fixtures", "fixtures.benchmark_fixture")
+
+def get_timeline_size(repo_dir: str, tenantid: str, timelineid: str):
+    path = "{}/tenants/{}/timelines/{}".format(repo_dir, tenantid, timelineid)
+
+    totalbytes = 0
+    for root, dirs, files in os.walk(path):
+        for name in files:
+            totalbytes += os.path.getsize(os.path.join(root, name))
+
+        if 'wal' in dirs:
+            dirs.remove('wal')  # don't visit 'wal' subdirectory
+
+    return totalbytes
+
+#
+# Run bulk INSERT test.
+#
+# Collects metrics:
+#
+# 1. Time to INSERT 5 million rows
+# 2. Disk writes
+# 3. Disk space used
+#
+def test_bulk_insert(postgres: PostgresFactory, pageserver: ZenithPageserver, pg_bin, zenith_cli, zenbenchmark, repo_dir: str):
+    # Create a branch for us
+    zenith_cli.run(["branch", "test_bulk_insert", "empty"])
+
+    pg = postgres.create_start('test_bulk_insert')
+    print("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 = 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 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(pageserver, 'pageserver_writes'):
+                with zenbenchmark.record_duration('insert'):
+                    cur.execute("insert into huge values (generate_series(1, 5000000), 0);")
+
+                    # Flush the layers from memory to disk. This is included in the reported
+                    # time and I/O
+                    pscur.execute(f"do_gc {pageserver.initial_tenant} {timeline} 0")
+
+            # Report disk space used by the repository
+            timeline_size = get_timeline_size(repo_dir, pageserver.initial_tenant, timeline)
+            zenbenchmark.record('size', timeline_size / (1024*1024), 'MB')