class TestSnapshots(ProduceConsumeValidateTest):
TOPIC_NAME_PREFIX = "test_topic_"
def __init__(self, test_context):
super(TestSnapshots, self).__init__(test_context=test_context)
self.topics_created = 0
self.topic = "test_topic"
self.partitions = 3
self.replication_factor = 3
self.num_nodes = 3
# Producer and consumer
self.producer_throughput = 1000
self.num_producers = 1
self.num_consumers = 1
security_protocol = 'PLAINTEXT'
# Setup Custom Config to ensure snapshot will be generated deterministically
self.kafka = KafkaService(
self.test_context,
self.num_nodes,
zk=None,
topics={
self.topic: {
"partitions": self.partitions,
"replication-factor": self.replication_factor,
'configs': {
"min.insync.replicas": 2
}
}
},
server_prop_overrides=[
[
config_property.METADATA_LOG_DIR,
KafkaService.METADATA_LOG_DIR
], [config_property.METADATA_LOG_SEGMENT_MS, "10000"],
[config_property.METADATA_LOG_RETENTION_BYTES, "2048"],
[config_property.METADATA_LOG_BYTES_BETWEEN_SNAPSHOTS, "2048"]
])
self.kafka.interbroker_security_protocol = security_protocol
self.kafka.security_protocol = security_protocol
def setUp(self):
# Start the cluster and ensure that a snapshot is generated
self.logger.info(
"Starting the cluster and running until snapshot creation")
assert quorum.for_test(self.test_context) in quorum.all_kraft, \
"Snapshot test should be run Kraft Modes only"
self.kafka.start()
topic_count = 10
self.topics_created += self.create_n_topics(topic_count)
if self.kafka.remote_controller_quorum:
self.controller_nodes = self.kafka.remote_controller_quorum.nodes
else:
self.controller_nodes = self.kafka.nodes[:self.kafka.
num_nodes_controller_role]
# Waiting for snapshot creation and first log segment
# cleanup on all controller nodes
for node in self.controller_nodes:
self.logger.debug("Waiting for snapshot on: %s" %
self.kafka.who_am_i(node))
self.wait_for_log_segment_delete(node)
self.wait_for_snapshot(node)
self.logger.debug("Verified Snapshots exist on controller nodes")
def create_n_topics(self, topic_count):
for i in range(self.topics_created, topic_count):
topic = "%s%d" % (TestSnapshots.TOPIC_NAME_PREFIX, i)
self.logger.debug("Creating topic %s" % topic)
topic_cfg = {
"topic": topic,
"partitions": self.partitions,
"replication-factor": self.replication_factor,
"configs": {
"min.insync.replicas": 2
}
}
self.kafka.create_topic(topic_cfg)
self.logger.debug("Created %d more topics" % topic_count)
return topic_count
def wait_for_log_segment_delete(self, node):
file_path = self.kafka.METADATA_FIRST_LOG
# Wait until the first log segment in metadata log is marked for deletion
wait_until(
lambda: not self.file_exists(node, file_path),
timeout_sec=100,
backoff_sec=1,
err_msg=
"Not able to verify cleanup of log file %s in a reasonable amount of time"
% file_path)
def wait_for_snapshot(self, node):
# Wait for a snapshot file to show up
file_path = self.kafka.METADATA_SNAPSHOT_SEARCH_STR
wait_until(
lambda: self.file_exists(node, file_path),
timeout_sec=100,
backoff_sec=1,
err_msg=
"Not able to verify snapshot existence in a reasonable amount of time"
)
def file_exists(self, node, file_path):
# Check if the first log segment is cleaned up
self.logger.debug("Checking if file %s exists" % file_path)
cmd = "ls %s" % file_path
files = node.account.ssh_output(cmd,
allow_fail=True,
combine_stderr=False)
if len(files) is 0:
self.logger.debug("File %s does not exist" % file_path)
return False
else:
self.logger.debug("File %s was found" % file_path)
return True
def validate_success(self, topic=None):
if topic is None:
# Create a new topic
topic = "%s%d" % (TestSnapshots.TOPIC_NAME_PREFIX,
self.topics_created)
self.topics_created += self.create_n_topics(topic_count=1)
# Produce to the newly created topic to ensure broker has caught up
self.producer = VerifiableProducer(self.test_context,
self.num_producers,
self.kafka,
topic,
throughput=self.producer_throughput,
message_validator=is_int)
self.consumer = ConsoleConsumer(self.test_context,
self.num_consumers,
self.kafka,
topic,
consumer_timeout_ms=30000,
message_validator=is_int)
self.start_producer_and_consumer()
self.stop_producer_and_consumer()
self.validate()
@cluster(num_nodes=9)
@matrix(metadata_quorum=quorum.all_kraft)
def test_broker(self, metadata_quorum=quorum.colocated_kraft):
""" Test the ability of a broker to consume metadata snapshots
and to recover the cluster metadata state using them
The test ensures that that there is atleast one snapshot created on
the controller quorum during the setup phase and that at least the first
log segment in the metadata log has been marked for deletion, thereby ensuring
that any observer of the log needs to always load a snapshot to catch
up to the current metadata state.
Each scenario is a progression over the previous one.
The scenarios build on top of each other by:
* Loading a snapshot
* Loading and snapshot and some delta records
* Loading a snapshot and delta and ensuring that the most recent metadata state
has been caught up.
Even though a subsequent scenario covers the previous one, they are all
left in the test to make debugging a failure of the test easier
e.g. if the first scenario passes and the second fails, it hints towards
a problem with the application of delta records while catching up
"""
# Scenario -- Re-init broker after cleaning up all persistent state
node = random.choice(self.kafka.nodes)
self.logger.debug("Scenario: kill-clean-start on broker node %s",
self.kafka.who_am_i(node))
self.kafka.clean_node(node)
self.kafka.start_node(node)
# Scenario -- Re-init broker after cleaning up all persistent state
# Create some metadata changes for the broker to consume as well.
node = random.choice(self.kafka.nodes)
self.logger.debug(
"Scenario: kill-clean-create_topics-start on broker node %s",
self.kafka.who_am_i(node))
self.kafka.clean_node(node)
# Now modify the cluster to create more metadata changes
self.topics_created += self.create_n_topics(topic_count=10)
self.kafka.start_node(node)
# Scenario -- Re-init broker after cleaning up all persistent state
# And ensure that the broker has replicated the metadata log
node = random.choice(self.kafka.nodes)
self.logger.debug(
"Scenario: kill-clean-start-verify-produce on broker node %s",
self.kafka.who_am_i(node))
self.kafka.clean_node(node)
self.kafka.start_node(node)
# Create a topic where the affected broker must be the leader
broker_topic = "%s%d" % (TestSnapshots.TOPIC_NAME_PREFIX,
self.topics_created)
self.topics_created += 1
self.logger.debug("Creating topic %s" % broker_topic)
topic_cfg = {
"topic": broker_topic,
"replica-assignment": self.kafka.idx(node),
"configs": {
"min.insync.replicas": 1
}
}
self.kafka.create_topic(topic_cfg)
# Produce to the newly created topic and make sure it works.
self.validate_success(broker_topic)
@cluster(num_nodes=9)
@matrix(metadata_quorum=quorum.all_kraft)
def test_controller(self, metadata_quorum=quorum.colocated_kraft):
""" Test the ability of controllers to consume metadata snapshots
and to recover the cluster metadata state using them
The test ensures that that there is atleast one snapshot created on
the controller quorum during the setup phase and that at least the first
log segment in the metadata log has been marked for deletion, thereby ensuring
that any observer of the log needs to always load a snapshot to catch
up to the current metadata state.
Each scenario is a progression over the previous one.
The scenarios build on top of each other by:
* Loading a snapshot
* Loading and snapshot and some delta records
* Loading a snapshot and delta and ensuring that the most recent metadata state
has been caught up.
Even though a subsequent scenario covers the previous one, they are all
left in the test to make debugging a failure of the test easier
e.g. if the first scenario passes and the second fails, it hints towards
a problem with the application of delta records while catching up
"""
# Scenario -- Re-init controllers with a clean kafka dir
self.logger.debug("Scenario: kill-clean-start controller node")
for node in self.controller_nodes:
self.logger.debug("Restarting node: %s",
self.kafka.controller_quorum.who_am_i(node))
self.kafka.controller_quorum.clean_node(node)
self.kafka.controller_quorum.start_node(node)
# Scenario -- Re-init controllers with a clean kafka dir and
# make metadata changes while they are down.
# This will force the entire quorum to load from snapshots
# and verify the quorum's ability to catch up to the latest metadata
self.logger.debug(
"Scenario: kill-clean-create_topics-start on controller node %s")
for node in self.controller_nodes:
self.logger.debug("Restarting node: %s",
self.kafka.controller_quorum.who_am_i(node))
self.kafka.controller_quorum.clean_node(node)
# Now modify the cluster to create more metadata changes
self.topics_created += self.create_n_topics(topic_count=5)
self.kafka.controller_quorum.start_node(node)
# Produce to a newly created topic and make sure it works.
self.validate_success()
class ReplicaScaleTest(Test):
def __init__(self, test_context):
super(ReplicaScaleTest, self).__init__(test_context=test_context)
self.test_context = test_context
self.zk = ZookeeperService(test_context, num_nodes=1)
self.kafka = KafkaService(self.test_context, num_nodes=8, zk=self.zk)
def setUp(self):
self.zk.start()
self.kafka.start()
def teardown(self):
# Need to increase the timeout due to partition count
for node in self.kafka.nodes:
self.kafka.stop_node(node, clean_shutdown=False, timeout_sec=60)
self.kafka.stop()
self.zk.stop()
@cluster(num_nodes=12)
@parametrize(topic_count=500, partition_count=34, replication_factor=3)
def test_produce_consume(self, topic_count, partition_count, replication_factor):
topics_create_start_time = time.time()
for i in range(topic_count):
topic = "replicas_produce_consume_%d" % i
print("Creating topic %s" % topic) # Force some stdout for Jenkins
topic_cfg = {
"topic": topic,
"partitions": partition_count,
"replication-factor": replication_factor,
"configs": {"min.insync.replicas": 2}
}
self.kafka.create_topic(topic_cfg)
topics_create_end_time = time.time()
self.logger.info("Time to create topics: %d" % (topics_create_end_time - topics_create_start_time))
producer_workload_service = ProduceBenchWorkloadService(self.test_context, self.kafka)
consumer_workload_service = ConsumeBenchWorkloadService(self.test_context, self.kafka)
trogdor = TrogdorService(context=self.test_context,
client_services=[self.kafka, producer_workload_service, consumer_workload_service])
trogdor.start()
produce_spec = ProduceBenchWorkloadSpec(0, TaskSpec.MAX_DURATION_MS,
producer_workload_service.producer_node,
producer_workload_service.bootstrap_servers,
target_messages_per_sec=10000,
max_messages=3400000,
producer_conf={},
admin_client_conf={},
common_client_conf={},
inactive_topics={},
active_topics={"replicas_produce_consume_[0-2]": {
"numPartitions": partition_count, "replicationFactor": replication_factor
}})
produce_workload = trogdor.create_task("replicas-produce-workload", produce_spec)
produce_workload.wait_for_done(timeout_sec=600)
self.logger.info("Completed produce bench")
consume_spec = ConsumeBenchWorkloadSpec(0, TaskSpec.MAX_DURATION_MS,
consumer_workload_service.consumer_node,
consumer_workload_service.bootstrap_servers,
target_messages_per_sec=10000,
max_messages=3400000,
consumer_conf={},
admin_client_conf={},
common_client_conf={},
active_topics=["replicas_produce_consume_[0-2]"])
consume_workload = trogdor.create_task("replicas-consume-workload", consume_spec)
consume_workload.wait_for_done(timeout_sec=600)
self.logger.info("Completed consume bench")
trogdor.stop()
@cluster(num_nodes=12)
@parametrize(topic_count=500, partition_count=34, replication_factor=3)
def test_clean_bounce(self, topic_count, partition_count, replication_factor):
topics_create_start_time = time.time()
for i in range(topic_count):
topic = "topic-%04d" % i
print("Creating topic %s" % topic) # Force some stdout for Jenkins
topic_cfg = {
"topic": topic,
"partitions": partition_count,
"replication-factor": replication_factor,
"configs": {"min.insync.replicas": 2}
}
self.kafka.create_topic(topic_cfg)
topics_create_end_time = time.time()
self.logger.info("Time to create topics: %d" % (topics_create_end_time - topics_create_start_time))
restart_times = []
for node in self.kafka.nodes:
broker_bounce_start_time = time.time()
self.kafka.stop_node(node, clean_shutdown=True, timeout_sec=600)
self.kafka.start_node(node, timeout_sec=600)
broker_bounce_end_time = time.time()
restart_times.append(broker_bounce_end_time - broker_bounce_start_time)
self.logger.info("Time to restart %s: %d" % (node.name, broker_bounce_end_time - broker_bounce_start_time))
self.logger.info("Restart times: %s" % restart_times)
delete_start_time = time.time()
for i in range(topic_count):
topic = "topic-%04d" % i
self.logger.info("Deleting topic %s" % topic)
self.kafka.delete_topic(topic)
delete_end_time = time.time()
self.logger.info("Time to delete topics: %d" % (delete_end_time - delete_start_time))
