def test_single_workload(self):
"""This test exercises the auto-scaling logic in the admission controller. It spins up
a base cluster (coordinator, catalog, statestore), runs a workload to initiate a
scaling up event as the queries start queuing, then stops the workload and observes
that the cluster gets shutdown."""
GROUP_SIZE = 2
EXECUTOR_SLOTS = 3
auto_scaler = AutoScaler(executor_slots=EXECUTOR_SLOTS,
group_size=GROUP_SIZE)
workload = None
try:
auto_scaler.start()
sleep(self.INITIAL_STARTUP_TIME_S)
workload = ConcurrentWorkload(self.QUERY, num_streams=5)
LOG.info("Starting workload")
workload.start()
# Wait for workers to spin up
cluster_size = GROUP_SIZE + 1 # +1 to include coordinator.
assert any(self._get_num_backends() >= cluster_size or sleep(1)
for _ in range(self.STATE_CHANGE_TIMEOUT_S)), \
"Number of backends did not increase within %s s" % self.STATE_CHANGE_TIMEOUT_S
assert self.impalad_test_service.get_metric_value(
"cluster-membership.executor-groups.total-healthy") >= 1
# Wait until we admitted at least 10 queries
assert any(self._get_total_admitted_queries() >= 10 or sleep(1)
for _ in range(self.STATE_CHANGE_TIMEOUT_S)), \
"Did not admit enough queries within %s s" % self.STATE_CHANGE_TIMEOUT_S
# Wait for second executor group to start
cluster_size = (2 * GROUP_SIZE) + 1
assert any(self._get_num_backends() >= cluster_size or sleep(1)
for _ in range(self.STATE_CHANGE_TIMEOUT_S)), \
"Number of backends did not reach %s within %s s" % (
cluster_size, self.STATE_CHANGE_TIMEOUT_S)
assert self.impalad_test_service.get_metric_value(
"cluster-membership.executor-groups.total-healthy") >= 2
LOG.info("Stopping workload")
workload.stop()
# Wait for workers to spin down
self.impalad_test_service.wait_for_metric_value(
TOTAL_BACKENDS_METRIC_NAME,
1,
timeout=self.STATE_CHANGE_TIMEOUT_S,
interval=1)
assert self.impalad_test_service.get_metric_value(
"cluster-membership.executor-groups.total") == 0
finally:
if workload:
workload.stop()
LOG.info("Stopping auto scaler")
auto_scaler.stop()
def test_sequential_startup(self):
"""This test starts an executor group sequentially and observes that no queries are
admitted until the group has been fully started."""
# Larger groups size so it takes a while to start up
GROUP_SIZE = 4
EXECUTOR_SLOTS = 3
auto_scaler = AutoScaler(executor_slots=EXECUTOR_SLOTS,
group_size=GROUP_SIZE,
start_batch_size=1,
max_groups=1)
workload = None
try:
auto_scaler.start()
sleep(self.INITIAL_STARTUP_TIME_S)
workload = ConcurrentWorkload(self.QUERY, num_streams=5)
LOG.info("Starting workload")
workload.start()
# Wait for first executor to start up
assert any(self._get_num_executors() >= 1 or sleep(1)
for _ in range(self.STATE_CHANGE_TIMEOUT_S)), \
"Number of backends did not increase within %s s" % self.STATE_CHANGE_TIMEOUT_S
# Wait for remaining executors to start up and make sure that no queries are
# admitted during startup
end_time = time() + self.STATE_CHANGE_TIMEOUT_S
startup_complete = False
while time() < end_time:
num_admitted = self._get_total_admitted_queries()
num_backends = self._get_num_executors()
if num_backends < GROUP_SIZE:
assert num_admitted == 0, "%s/%s backends started but %s queries have " \
"already been admitted." % (num_backends, GROUP_SIZE, num_admitted)
if num_admitted > 0:
assert num_backends == GROUP_SIZE
startup_complete = True
break
sleep(1)
assert startup_complete, "Did not start up in %s s" % self.STATE_CHANGE_TIMEOUT_S
LOG.info("Stopping workload")
workload.stop()
# Wait for workers to spin down
assert any(self._get_num_executors() == 0 or sleep(1)
for _ in range(self.STATE_CHANGE_TIMEOUT_S)), \
"Backends did not shut down within %s s" % self.STATE_CHANGE_TIMEOUT_S
finally:
if workload:
workload.stop()
LOG.info("Stopping auto scaler")
auto_scaler.stop()
def test_single_group_maxed_out(self):
"""This test starts an auto scaler and limits it to a single executor group. It then
makes sure that the query throughput does not exceed the expected limit."""
GROUP_SIZE = 2
EXECUTOR_SLOTS = 3
auto_scaler = AutoScaler(executor_slots=EXECUTOR_SLOTS,
group_size=GROUP_SIZE,
max_groups=1)
workload = None
try:
auto_scaler.start()
sleep(self.INITIAL_STARTUP_TIME_S)
workload = ConcurrentWorkload(self.QUERY, num_streams=5)
LOG.info("Starting workload")
workload.start()
# Wait for workers to spin up
assert any(self._get_num_executors() >= GROUP_SIZE or sleep(1)
for _ in range(self.STATE_CHANGE_TIMEOUT_S)), \
"Number of backends did not increase within %s s" % self.STATE_CHANGE_TIMEOUT_S
# Wait until we admitted at least 10 queries
assert any(self._get_total_admitted_queries() >= 10 or sleep(1)
for _ in range(self.STATE_CHANGE_TIMEOUT_S)), \
"Did not admit enough queries within %s s" % self.STATE_CHANGE_TIMEOUT_S
# Sample the number of running queries for while
SAMPLE_NUM_RUNNING_S = 30
end_time = time() + SAMPLE_NUM_RUNNING_S
num_running = []
while time() < end_time:
num_running.append(self._get_num_running_queries())
sleep(1)
# Must reach EXECUTOR_SLOTS but not exceed it
assert max(num_running) == EXECUTOR_SLOTS, \
"Unexpected number of running queries: %s" % num_running
# Check that only a single group started
assert self._get_num_executors() == GROUP_SIZE
LOG.info("Stopping workload")
workload.stop()
# Wait for workers to spin down
assert any(self._get_num_executors() == 0 or sleep(1)
for _ in range(self.STATE_CHANGE_TIMEOUT_S)), \
"Backends did not shut down within %s s" % self.STATE_CHANGE_TIMEOUT_S
finally:
if workload:
workload.stop()
LOG.info("Stopping auto scaler")
auto_scaler.stop()
def test_executor_concurrency(self):
"""Tests that the command line flag to limit query concurrency on executors works as
expected."""
# Query that runs on every executor
QUERY = "select * from functional_parquet.alltypestiny \
where month < 3 and id + random() < sleep(500);"
self._add_executor_group("group1", 2, max_concurrent_queries=3)
workload = None
try:
workload = ConcurrentWorkload(QUERY, num_streams=5)
LOG.info("Starting workload")
workload.start()
RAMP_UP_TIMEOUT_S = 60
# Wait until we admitted at least 10 queries
assert any(self._get_total_admitted_queries() >= 10 or sleep(1)
for _ in range(RAMP_UP_TIMEOUT_S)), \
"Did not admit enough queries within %s s" % RAMP_UP_TIMEOUT_S
# Sample the number of running queries for while
NUM_RUNNING_SAMPLES = 30
num_running = []
for _ in xrange(NUM_RUNNING_SAMPLES):
num_running.append(self._get_num_running_queries())
sleep(1)
# Must reach 3 but not exceed it
assert max(num_running) == 3, \
"Unexpected number of running queries: %s" % num_running
finally:
LOG.info("Stopping workload")
if workload:
workload.stop()
def test_executor_concurrency(self):
"""Tests that the command line flag to limit query concurrency on executors works as
expected."""
# Query that runs on every executor
QUERY = "select * from functional_parquet.alltypestiny \
where month < 3 and id + random() < sleep(500);"
self._add_executor_group("group1", 2, admission_control_slots=3)
workload = None
try:
workload = ConcurrentWorkload(QUERY, num_streams=5)
LOG.info("Starting workload")
workload.start()
RAMP_UP_TIMEOUT_S = 60
# Wait until we admitted at least 10 queries
assert any(self._get_total_admitted_queries() >= 10 or sleep(1)
for _ in range(RAMP_UP_TIMEOUT_S)), \
"Did not admit enough queries within %s s" % RAMP_UP_TIMEOUT_S
# Sample the number of admitted queries on each backend for while.
# Note that the total number of queries in the cluster can higher
# than 3 because resources may be released on some backends, allowing
# a new query to fit (see IMPALA-9073).
NUM_SAMPLES = 30
executor_slots_in_use = []
for _ in xrange(NUM_SAMPLES):
backends_json = json.loads(
self.impalad_test_service.read_debug_webpage(
'backends?json'))
for backend in backends_json['backends']:
if backend['is_executor']:
executor_slots_in_use.append(
backend['admission_slots_in_use'])
sleep(1)
# Must reach 3 but not exceed it
assert max(executor_slots_in_use) == 3, \
"Unexpected number of slots in use: %s" % executor_slots_in_use
finally:
LOG.info("Stopping workload")
if workload:
workload.stop()
def test_sequential_startup(self):
"""This test starts an executor group sequentially and observes that no queries are
admitted until the group has been fully started."""
# Larger groups size so it takes a while to start up
GROUP_SIZE = 4
EXECUTOR_SLOTS = 3
auto_scaler = AutoScaler(executor_slots=EXECUTOR_SLOTS,
group_size=GROUP_SIZE,
start_batch_size=1,
max_groups=1)
workload = None
try:
auto_scaler.start()
sleep(self.INITIAL_STARTUP_TIME_S)
workload = ConcurrentWorkload(self.QUERY, num_streams=5)
LOG.info("Starting workload")
workload.start()
# Wait for first executor to start up
self.impalad_test_service.wait_for_metric_value(
"cluster-membership.executor-groups.total",
1,
timeout=self.STATE_CHANGE_TIMEOUT_S,
interval=1)
# Wait for remaining executors to start up and make sure that no queries are
# admitted during startup
end_time = time() + self.STATE_CHANGE_TIMEOUT_S
startup_complete = False
cluster_size = GROUP_SIZE + 1 # +1 to include coordinator.
while time() < end_time:
num_admitted = self._get_total_admitted_queries()
num_backends = self._get_num_backends()
if num_backends < cluster_size:
assert num_admitted == 0, "%s/%s backends started but %s queries have " \
"already been admitted." % (num_backends, cluster_size, num_admitted)
if num_admitted > 0:
assert num_backends == cluster_size
startup_complete = True
break
sleep(1)
assert startup_complete, "Did not start up in %s s" % self.STATE_CHANGE_TIMEOUT_S
LOG.info("Stopping workload")
workload.stop()
# Wait for workers to spin down
self.impalad_test_service.wait_for_metric_value(
"cluster-membership.backends.total",
1,
timeout=self.STATE_CHANGE_TIMEOUT_S,
interval=1)
assert self.impalad_test_service.get_metric_value(
"cluster-membership.executor-groups.total") == 0
finally:
if workload:
workload.stop()
LOG.info("Stopping auto scaler")
auto_scaler.stop()
def test_single_group_maxed_out(self):
"""This test starts an auto scaler and limits it to a single executor group. It then
makes sure that the query throughput does not exceed the expected limit."""
GROUP_SIZE = 2
EXECUTOR_SLOTS = 3
auto_scaler = AutoScaler(executor_slots=EXECUTOR_SLOTS,
group_size=GROUP_SIZE,
max_groups=1)
workload = None
try:
auto_scaler.start()
sleep(self.INITIAL_STARTUP_TIME_S)
workload = ConcurrentWorkload(self.QUERY, num_streams=5)
LOG.info("Starting workload")
workload.start()
# Wait for workers to spin up
cluster_size = GROUP_SIZE + 1 # +1 to include coordinator.
self.impalad_test_service.wait_for_metric_value(
"cluster-membership.backends.total",
cluster_size,
timeout=self.STATE_CHANGE_TIMEOUT_S,
interval=1)
# Wait until we admitted at least 10 queries
assert any(self._get_total_admitted_queries() >= 10 or sleep(1)
for _ in range(self.STATE_CHANGE_TIMEOUT_S)), \
"Did not admit enough queries within %s s" % self.STATE_CHANGE_TIMEOUT_S
# Sample the number of running queries for while
SAMPLE_NUM_RUNNING_S = 30
end_time = time() + SAMPLE_NUM_RUNNING_S
num_running = []
while time() < end_time:
num_running.append(self._get_num_running_queries())
sleep(1)
# Must reach EXECUTOR_SLOTS but not exceed it
assert max(num_running) == EXECUTOR_SLOTS, \
"Unexpected number of running queries: %s" % num_running
# Check that only a single group started
assert self.impalad_test_service.get_metric_value(
"cluster-membership.executor-groups.total-healthy") == 1
LOG.info("Stopping workload")
workload.stop()
# Wait for workers to spin down
self.impalad_test_service.wait_for_metric_value(
"cluster-membership.backends.total",
1,
timeout=self.STATE_CHANGE_TIMEOUT_S,
interval=1)
assert self.impalad_test_service.get_metric_value(
"cluster-membership.executor-groups.total") == 0
finally:
if workload:
workload.stop()
LOG.info("Stopping auto scaler")
auto_scaler.stop()
def test_single_workload(self):
"""This test exercises the auto-scaling logic in the admission controller. It spins up
a base cluster (coordinator, catalog, statestore), runs some queries to observe that
new executors are started, then stops the workload and observes that the cluster gets
shutdown."""
GROUP_SIZE = 2
EXECUTOR_SLOTS = 3
auto_scaler = AutoScaler(executor_slots=EXECUTOR_SLOTS,
group_size=GROUP_SIZE)
workload = None
try:
auto_scaler.start()
sleep(self.INITIAL_STARTUP_TIME_S)
workload = ConcurrentWorkload(self.QUERY, num_streams=5)
LOG.info("Starting workload")
workload.start()
# Wait for workers to spin up
cluster_size = GROUP_SIZE + 1 # +1 to include coordinator.
assert any(self._get_num_backends() >= cluster_size or sleep(1)
for _ in range(self.STATE_CHANGE_TIMEOUT_S)), \
"Number of backends did not increase within %s s" % self.STATE_CHANGE_TIMEOUT_S
assert self.impalad_test_service.get_metric_value(
"cluster-membership.executor-groups.total-healthy") >= 1
# Wait until we admitted at least 10 queries
assert any(self._get_total_admitted_queries() >= 10 or sleep(1)
for _ in range(self.STATE_CHANGE_TIMEOUT_S)), \
"Did not admit enough queries within %s s" % self.STATE_CHANGE_TIMEOUT_S
single_group_query_rate = workload.get_query_rate()
# Wait for second executor group to start
cluster_size = (2 * GROUP_SIZE) + 1
assert any(self._get_num_backends() >= cluster_size or sleep(1)
for _ in range(self.STATE_CHANGE_TIMEOUT_S)), \
"Number of backends did not reach %s within %s s" % (
cluster_size, self.STATE_CHANGE_TIMEOUT_S)
assert self.impalad_test_service.get_metric_value(
"cluster-membership.executor-groups.total-healthy") >= 2
# Wait for query rate to exceed the maximum for a single executor group. In the past
# we tried to wait for it to pass a higher threshold but on some platforms we saw
# that it was too flaky.
max_query_rate = 0
# This barrier has been flaky in the past so we wait 2x as long as for the other
# checks.
end = time() + 2 * self.STATE_CHANGE_TIMEOUT_S
while time() < end:
current_rate = workload.get_query_rate()
LOG.info("Current rate: %s" % current_rate)
max_query_rate = max(max_query_rate, current_rate)
if max_query_rate > single_group_query_rate:
break
sleep(1)
assert max_query_rate > single_group_query_rate, "Query rate did not exceed %s " \
"within %s s. Maximum was %s. Cluster size is %s." % (single_group_query_rate,
self.STATE_CHANGE_TIMEOUT_S, max_query_rate, cluster_size)
LOG.info("Stopping workload")
workload.stop()
# Wait for workers to spin down
self.impalad_test_service.wait_for_metric_value(
TOTAL_BACKENDS_METRIC_NAME,
1,
timeout=self.STATE_CHANGE_TIMEOUT_S,
interval=1)
assert self.impalad_test_service.get_metric_value(
"cluster-membership.executor-groups.total") == 0
finally:
if workload:
workload.stop()
LOG.info("Stopping auto scaler")
auto_scaler.stop()
