def test_run_pgsql(self, transactions, pod_name):
"""
Test pgsql workload
"""
# Create pgbench benchmark
log.info("Create resource file for pgbench workload")
pg_trans = transactions
timeout = pg_trans * 3
pg_data = templating.load_yaml(constants.PGSQL_BENCHMARK_YAML)
pg_data['spec']['workload']['args']['transactions'] = pg_trans
pg_obj = OCS(**pg_data)
pg_obj.create()
# Wait for pgbench pod to be created
for pgbench_pod in TimeoutSampler(pg_trans, 3, get_pod_name_by_pattern,
'pgbench', 'my-ripsaw'):
try:
if pgbench_pod[0] is not None:
pgbench_client_pod = pgbench_pod[0]
break
except IndexError:
log.info("Bench pod not ready yet")
# Respin Ceph pod
resource_osd = [f'{pod_name}']
log.info(f"Respin Ceph pod {pod_name}")
disruption = disruption_helpers.Disruptions()
for resource in resource_osd:
disruption.set_resource(resource=resource)
disruption.delete_resource()
# Wait for pg_bench pod to initialized and complete
log.info("Waiting for pgbench_client to complete")
pod_obj = OCP(kind='pod')
pod_obj.wait_for_resource(
condition='Completed',
resource_name=pgbench_client_pod,
timeout=timeout,
sleep=10,
)
# Running pgbench and parsing logs
output = run_cmd(f'oc logs {pgbench_client_pod}')
pg_output = utils.parse_pgsql_logs(output)
log.info("*******PGBench output log*********\n" f"{pg_output}")
for data in pg_output:
latency_avg = data['latency_avg']
if not latency_avg:
raise UnexpectedBehaviour(
"PGBench failed to run, no data found on latency_avg")
log.info("PGBench has completed successfully")
# Collect data and export to Google doc spreadsheet
g_sheet = GoogleSpreadSheetAPI(sheet_name="OCS PGSQL", sheet_index=2)
for lat in pg_output:
lat_avg = lat['latency_avg']
lat_stddev = lat['lat_stddev']
tps_incl = lat['tps_incl']
tps_excl = lat['tps_excl']
g_sheet.insert_row(
[int(lat_avg),
int(lat_stddev),
int(tps_incl),
int(tps_excl)], 2)
# Clean up pgbench benchmark
log.info("Deleting PG bench benchmark")
pg_obj.delete()
def test_run_pgsql_node_drain(self, transactions=900, node_type='master'):
"""
Test pgsql workload
"""
# Create pgbench benchmark
log.info("Create resource file for pgbench workload")
pg_trans = transactions
timeout = pg_trans * 3
pg_data = templating.load_yaml(constants.PGSQL_BENCHMARK_YAML)
pg_data['spec']['workload']['args']['transactions'] = pg_trans
pg_obj = OCS(**pg_data)
pg_obj.create()
# Getting pgbench podname
for pgbench_pod in TimeoutSampler(
pg_trans, 3, get_pod_name_by_pattern,
'pgbench', 'my-ripsaw'
):
try:
if pgbench_pod[0] is not None:
pgbench_client_pod = pgbench_pod[0]
break
except IndexError:
log.info("Bench pod is not found")
# Wait for pg_bench pod to be in running state
log.info("Waiting for pgbench_pod to be in running state")
pod_obj = OCP(kind='pod')
pod_obj.wait_for_resource(
condition='Running',
resource_name=pgbench_client_pod,
timeout=timeout,
sleep=5,
)
# Node drain with specific node type
typed_nodes = node.get_typed_nodes(node_type=node_type, num_of_nodes=1)
typed_node_name = typed_nodes[0].name
# Node maintenance - to gracefully terminate all pods on the node
node.drain_nodes([typed_node_name])
# Make the node schedulable again
node.schedule_nodes([typed_node_name])
# Perform cluster and Ceph health checks
self.sanity_helpers.health_check()
# Wait for pg_bench pod to complete workload
log.info("Waiting for pgbench_client to complete")
pod_obj.wait_for_resource(
condition='Completed',
resource_name=pgbench_client_pod,
timeout=timeout,
sleep=10,
)
# Parsing the results
output = run_cmd(f'oc logs {pgbench_client_pod}')
pg_output = utils.parse_pgsql_logs(output)
log.info(
"*******PGBench output log*********\n"
f"{pg_output}"
)
for data in pg_output:
latency_avg = data['latency_avg']
if not latency_avg:
raise UnexpectedBehaviour(
"PGBench failed to run, no data found on latency_avg"
)
log.info("PGBench has completed successfully")
# Collect data and export to Google doc spreadsheet
g_sheet = GoogleSpreadSheetAPI(sheet_name="OCS PGSQL", sheet_index=3)
for lat in pg_output:
lat_avg = lat['latency_avg']
lat_stddev = lat['lat_stddev']
tps_incl = lat['tps_incl']
tps_excl = lat['tps_excl']
g_sheet.insert_row(
[int(lat_avg),
int(lat_stddev),
int(tps_incl),
int(tps_excl)], 2
)
# Clean up pgbench benchmark
log.info("Deleting PG bench benchmark")
pg_obj.delete()
