def __init__(self, test_context):
super(StreamsOptimizedTest, self).__init__(test_context)
self.topics = {
self.input_topic: {
'partitions': 6
},
self.aggregation_topic: {
'partitions': 6
},
self.reduce_topic: {
'partitions': 6
},
self.join_topic: {
'partitions': 6
}
}
self.zookeeper = ZookeeperService(self.test_context, num_nodes=1)
self.kafka = KafkaService(self.test_context,
num_nodes=3,
zk=self.zookeeper,
topics=self.topics)
self.producer = VerifiableProducer(self.test_context,
1,
self.kafka,
self.input_topic,
throughput=1000,
acks=1)
def test_produce_consume(self, broker_version):
print("running producer_consumer_compat with broker_version = %s" %
broker_version)
self.kafka.set_version(KafkaVersion(broker_version))
self.kafka.security_protocol = "PLAINTEXT"
self.kafka.interbroker_security_protocol = self.kafka.security_protocol
self.producer = VerifiableProducer(
self.test_context,
self.num_producers,
self.kafka,
self.topic,
throughput=self.producer_throughput,
message_validator=is_int_with_prefix)
self.consumer = ConsoleConsumer(self.test_context,
self.num_consumers,
self.kafka,
self.topic,
consumer_timeout_ms=60000,
message_validator=is_int_with_prefix)
self.kafka.start()
self.run_produce_consume_validate(lambda: wait_until(
lambda: self.producer.each_produced_at_least(
self.messages_per_producer) == True,
timeout_sec=120,
backoff_sec=1,
err_msg=
"Producer did not produce all messages in reasonable amount of time"
))
def produce_and_consume(self, producer_version, consumer_version, group):
self.producer = VerifiableProducer(
self.test_context,
self.num_producers,
self.kafka,
self.topic,
throughput=self.producer_throughput,
message_validator=is_int,
version=KafkaVersion(producer_version))
self.consumer = ConsoleConsumer(self.test_context,
self.num_consumers,
self.kafka,
self.topic,
consumer_timeout_ms=30000,
message_validator=is_int,
version=KafkaVersion(consumer_version))
self.consumer.group_id = group
self.run_produce_consume_validate(lambda: wait_until(
lambda: self.producer.each_produced_at_least(
self.messages_per_producer) == True,
timeout_sec=120,
backoff_sec=1,
err_msg=
"Producer did not produce all messages in reasonable amount of time"
))
def test_reassign_partitions(self, bounce_brokers, security_protocol):
"""Reassign partitions tests.
Setup: 1 zk, 3 kafka nodes, 1 topic with partitions=3, replication-factor=3, and min.insync.replicas=2
- Produce messages in the background
- Consume messages in the background
- Reassign partitions
- If bounce_brokers is True, also bounce a few brokers while partition re-assignment is in progress
- When done reassigning partitions and bouncing brokers, stop producing, and finish consuming
- Validate that every acked message was consumed
"""
self.kafka.security_protocol = security_protocol
self.kafka.interbroker_security_protocol = security_protocol
new_consumer = False if self.kafka.security_protocol == "PLAINTEXT" else True
self.producer = VerifiableProducer(self.test_context,
self.num_producers,
self.kafka,
self.topic,
throughput=self.producer_throughput)
self.consumer = ConsoleConsumer(self.test_context,
self.num_consumers,
self.kafka,
self.topic,
new_consumer=new_consumer,
consumer_timeout_ms=60000,
message_validator=is_int)
self.kafka.start()
self.run_produce_consume_validate(
core_test_action=lambda: self.reassign_partitions(bounce_brokers))
def test_consumer_back_compatibility(self):
"""Run the scala 0.8.X consumer against an 0.9.X cluster.
Expect 0.8.X scala consumer to fail with buffer underflow. This error is the same as when an 0.9.X producer
is run against an 0.8.X broker: the broker responds to a V1 fetch request with a V0 fetch response; the
client then tries to parse this V0 fetch response as a V1 fetch response, resulting in a BufferUnderflowException
"""
num_messages = 10
self.producer = VerifiableProducer(
self.test_context, self.num_producers, self.kafka, self.topic, max_messages=num_messages,
throughput=self.producer_throughput, version=LATEST_0_8_2)
self.consumer = ConsoleConsumer(
self.test_context, self.num_consumers, self.kafka, self.topic, group_id="consumer-09X",
consumer_timeout_ms=10000, message_validator=is_int, version=TRUNK)
self.old_consumer = ConsoleConsumer(
self.test_context, self.num_consumers, self.kafka, self.topic, group_id="consumer-08X",
consumer_timeout_ms=10000, message_validator=is_int, version=LATEST_0_8_2)
self.producer.run()
self.consumer.run()
self.old_consumer.run()
consumed = len(self.consumer.messages_consumed[1])
old_consumed = len(self.old_consumer.messages_consumed[1])
assert old_consumed == num_messages, "Expected 0.8.X scala consumer to consume %d, but only got %d" % (num_messages, old_consumed)
assert consumed == 0, "Expected 0.9.X scala consumer to fail to consume any messages, but got %d" % consumed
self.logger.info("Grepping consumer log for expected error type")
node = self.consumer.nodes[0]
node.account.ssh("egrep -m 1 %s %s" % ("\"java\.nio\.BufferUnderflowException\"", self.consumer.LOG_FILE), allow_fail=False)
def test_replication_with_broker_failure(self, failure_mode, security_protocol, broker_type,
client_sasl_mechanism="GSSAPI", interbroker_sasl_mechanism="GSSAPI",
compression_type=None, enable_idempotence=False):
"""Replication tests.
These tests verify that replication provides simple durability guarantees by checking that data acked by
brokers is still available for consumption in the face of various failure scenarios.
Setup: 1 zk, 3 kafka nodes, 1 topic with partitions=3, replication-factor=3, and min.insync.replicas=2
- Produce messages in the background
- Consume messages in the background
- Drive broker failures (shutdown, or bounce repeatedly with kill -15 or kill -9)
- When done driving failures, stop producing, and finish consuming
- Validate that every acked message was consumed
"""
self.kafka.security_protocol = security_protocol
self.kafka.interbroker_security_protocol = security_protocol
self.kafka.client_sasl_mechanism = client_sasl_mechanism
self.kafka.interbroker_sasl_mechanism = interbroker_sasl_mechanism
new_consumer = False if self.kafka.security_protocol == "PLAINTEXT" else True
self.enable_idempotence = enable_idempotence
compression_types = None if not compression_type else [compression_type] * self.num_producers
self.producer = VerifiableProducer(self.test_context, self.num_producers, self.kafka, self.topic,
throughput=self.producer_throughput, compression_types=compression_types,
enable_idempotence=enable_idempotence)
self.consumer = ConsoleConsumer(self.test_context, self.num_consumers, self.kafka, self.topic, new_consumer=new_consumer, consumer_timeout_ms=60000, message_validator=is_int)
self.kafka.start()
self.run_produce_consume_validate(core_test_action=lambda: failures[failure_mode](self, broker_type))
def get_producer(self, num_messages):
return VerifiableProducer(self.test_context,
1,
self.kafka,
self.inputTopic,
max_messages=num_messages,
acks=1)
def start_producer(self):
# This will produce to kafka cluster
self.producer = VerifiableProducer(self.test_context, num_nodes=1, kafka=self.kafka, topic=TOPIC, throughput=1000, max_messages=MAX_MESSAGES)
self.producer.start()
current_acked = self.producer.num_acked
wait_until(lambda: self.producer.num_acked >= current_acked + MAX_MESSAGES, timeout_sec=10,
err_msg="Timeout awaiting messages to be produced and acked")
def test_producer_back_compatibility(self):
"""Run 0.9.X java producer against 0.8.X brokers.
This test documents the fact that java producer v0.9.0.0 and later won't run against 0.8.X brokers
the broker responds to a V1 produce request with a V0 fetch response; the client then tries to parse this V0
produce response as a V1 produce response, resulting in a BufferUnderflowException
"""
self.producer = VerifiableProducer(self.test_context,
self.num_producers,
self.kafka,
self.topic,
max_messages=100,
throughput=self.producer_throughput,
version=TRUNK)
node = self.producer.nodes[0]
try:
self.producer.start()
self.producer.wait()
raise Exception(
"0.9.X java producer should not run successfully against 0.8.X broker"
)
except:
# Expected
pass
finally:
self.producer.kill_node(node, clean_shutdown=False)
self.logger.info("Grepping producer log for expected error type")
node.account.ssh("egrep -m 1 %s %s" % (
"\"org\.apache\.kafka\.common\.protocol\.types\.SchemaException.*throttle_time_ms.*: java\.nio\.BufferUnderflowException\"",
self.producer.LOG_FILE),
allow_fail=False)
def start_producer(self, max_messages, acks, timeout):
# This will produce to kafka cluster
current_acked = 0
self.producer = VerifiableProducer(self.test_context, num_nodes=1, kafka=self.kafka, topic=TOPIC, throughput=1000, acks=acks, max_messages=max_messages)
self.producer.start()
wait_until(lambda: acks == 0 or self.producer.num_acked >= current_acked + max_messages, timeout_sec=timeout,
err_msg="Timeout awaiting messages to be produced and acked")
def create_producer(self, num_nodes=1, throughput=1000, **kwargs):
self.producer = VerifiableProducer(self.test_context,
num_nodes=num_nodes,
kafka=self.kafka,
topic=self.topic,
throughput=throughput,
**kwargs)
def setup_producer(self, topic, max_messages=-1):
return VerifiableProducer(self.test_context,
self.num_producers,
self.kafka,
topic,
max_messages=max_messages,
throughput=500)
def test_reassign_partitions(self, bounce_brokers,
reassign_from_offset_zero):
"""Reassign partitions tests.
Setup: 1 zk, 4 kafka nodes, 1 topic with partitions=20, replication-factor=3,
and min.insync.replicas=3
- Produce messages in the background
- Consume messages in the background
- Reassign partitions
- If bounce_brokers is True, also bounce a few brokers while partition re-assignment is in progress
- When done reassigning partitions and bouncing brokers, stop producing, and finish consuming
- Validate that every acked message was consumed
"""
self.kafka.start()
if not reassign_from_offset_zero:
self.move_start_offset()
self.producer = VerifiableProducer(self.test_context,
self.num_producers,
self.kafka,
self.topic,
throughput=self.producer_throughput,
enable_idempotence=True)
self.consumer = ConsoleConsumer(self.test_context,
self.num_consumers,
self.kafka,
self.topic,
consumer_timeout_ms=60000,
message_validator=is_int)
self.enable_idempotence = True
self.run_produce_consume_validate(
core_test_action=lambda: self.reassign_partitions(bounce_brokers))
def move_start_offset(self):
"""We move the start offset of the topic by writing really old messages
and waiting for them to be cleaned up.
"""
producer = VerifiableProducer(self.test_context,
1,
self.kafka,
self.topic,
throughput=-1,
enable_idempotence=True,
create_time=1000)
producer.start()
wait_until(lambda: producer.num_acked > 0,
timeout_sec=30,
err_msg="Failed to get an acknowledgement for %ds" % 30)
# Wait 8 seconds to let the topic be seeded with messages that will
# be deleted. The 8 seconds is important, since we should get 2 deleted
# segments in this period based on the configured log roll time and the
# retention check interval.
time.sleep(8)
producer.stop()
self.logger.info("Seeded topic with %d messages which will be deleted" %\
producer.num_acked)
# Since the configured check interval is 5 seconds, we wait another
# 6 seconds to ensure that at least one more cleaning so that the last
# segment is deleted. An altenate to using timeouts is to poll each
# partition until the log start offset matches the end offset. The
# latter is more robust.
time.sleep(6)
def test_replication_with_broker_failure(self, failure_mode,
security_protocol):
"""Replication tests.
These tests verify that replication provides simple durability guarantees by checking that data acked by
brokers is still available for consumption in the face of various failure scenarios.
Setup: 1 zk, 3 kafka nodes, 1 topic with partitions=3, replication-factor=3, and min.insync.replicas=2
- Produce messages in the background
- Consume messages in the background
- Drive broker failures (shutdown, or bounce repeatedly with kill -15 or kill -9)
- When done driving failures, stop producing, and finish consuming
- Validate that every acked message was consumed
"""
self.kafka.security_protocol = 'PLAINTEXT'
self.kafka.interbroker_security_protocol = security_protocol
self.producer = VerifiableProducer(self.test_context,
self.num_producers,
self.kafka,
self.topic,
throughput=self.producer_throughput)
self.consumer = ConsoleConsumer(self.test_context,
self.num_consumers,
self.kafka,
self.topic,
consumer_timeout_ms=60000,
message_validator=is_int)
self.kafka.start()
self.run_produce_consume_validate(
core_test_action=lambda: failures[failure_mode](self))
def test_compatibility(self, producer_version, consumer_version, compression_types, new_consumer=True, timestamp_type=None):
self.kafka = KafkaService(self.test_context, num_nodes=3, zk=self.zk, version=DEV_BRANCH, topics={self.topic: {
"partitions": 3,
"replication-factor": 3,
'configs': {"min.insync.replicas": 2}}})
for node in self.kafka.nodes:
if timestamp_type is not None:
node.config[config_property.MESSAGE_TIMESTAMP_TYPE] = timestamp_type
self.kafka.start()
self.producer = VerifiableProducer(self.test_context, self.num_producers, self.kafka,
self.topic, throughput=self.producer_throughput,
message_validator=is_int,
compression_types=compression_types,
version=KafkaVersion(producer_version))
self.consumer = ConsoleConsumer(self.test_context, self.num_consumers, self.kafka,
self.topic, consumer_timeout_ms=30000, new_consumer=new_consumer,
message_validator=is_int, version=KafkaVersion(consumer_version))
self.run_produce_consume_validate(lambda: wait_until(
lambda: self.producer.each_produced_at_least(self.messages_per_producer) == True,
timeout_sec=120, backoff_sec=1,
err_msg="Producer did not produce all messages in reasonable amount of time"))
def run_with_failure(self, failure):
"""This is the top-level test template.
The steps are:
Produce messages in the background while driving some failure condition
When done driving failures, immediately stop producing
Consume all messages
Validate that messages acked by brokers were consumed
Note that consuming is a bit tricky, at least with console consumer. The goal is to consume all messages
(foreach partition) in the topic. In this case, waiting for the last message may cause the consumer to stop
too soon since console consumer is consuming multiple partitions from a single thread and therefore we lose
ordering guarantees.
Waiting on a count of consumed messages can be unreliable: if we stop consuming when num_consumed == num_acked,
we might exit early if some messages are duplicated (though not an issue here since producer retries==0)
Therefore rely here on the consumer.timeout.ms setting which times out on the interval between successively
consumed messages. Since we run the producer to completion before running the consumer, this is a reliable
indicator that nothing is left to consume.
"""
self.producer = VerifiableProducer(self.test_context,
self.num_producers,
self.kafka,
self.topic,
throughput=self.producer_throughput)
self.consumer = ConsoleConsumer(self.test_context,
self.num_consumers,
self.kafka,
self.topic,
consumer_timeout_ms=3000)
# Produce in a background thread while driving broker failures
self.producer.start()
if not wait_until(lambda: self.producer.num_acked > 5, timeout_sec=5):
raise RuntimeError(
"Producer failed to start in a reasonable amount of time.")
failure()
self.producer.stop()
self.acked = self.producer.acked
self.not_acked = self.producer.not_acked
self.logger.info("num not acked: %d" % self.producer.num_not_acked)
self.logger.info("num acked: %d" % self.producer.num_acked)
# Consume all messages
self.consumer.start()
self.consumer.wait()
self.consumed = self.consumer.messages_consumed[1]
self.logger.info("num consumed: %d" % len(self.consumed))
# Check produced vs consumed
success, msg = self.validate()
if not success:
self.mark_for_collect(self.producer)
assert success, msg
def create_producer(self):
# This will produce to source kafka cluster
self.producer = VerifiableProducer(self.test_context,
num_nodes=1,
kafka=self.kafka,
topic=self.topic,
max_messages=self.num_messages,
throughput=self.num_messages // 10)
def get_producer(self, topic, num_messages, repeating_keys=None):
return VerifiableProducer(self.test_context,
1,
self.kafka,
topic,
max_messages=num_messages,
acks=1,
repeating_keys=repeating_keys)
def setup_producer(self, topic, max_messages=-1):
return VerifiableProducer(
self.test_context,
self.num_producers,
self.kafka,
topic,
max_messages=max_messages,
throughput=500,
request_timeout_sec=self.PRODUCER_REQUEST_TIMEOUT_SEC,
log_level="DEBUG")
def create_producer_and_consumer(self):
self.producer = VerifiableProducer(
self.test_context, self.num_producers, self.kafka, self.topic,
throughput=self.producer_throughput)
self.consumer = ConsoleConsumer(
self.test_context, self.num_consumers, self.kafka, self.topic,
consumer_timeout_ms=60000, message_validator=is_int, new_consumer=True)
self.consumer.group_id = "group"
def __init__(self, test_context):
super(DelegationTokenTest, self).__init__(test_context)
self.test_context = test_context
self.topic = "topic"
self.zk = ZookeeperService(test_context, num_nodes=1)
self.kafka = KafkaService(
self.test_context,
num_nodes=1,
zk=self.zk,
zk_chroot="/kafka",
topics={self.topic: {
"partitions": 1,
"replication-factor": 1
}},
server_prop_overides=[[
config_property.DELEGATION_TOKEN_MAX_LIFETIME_MS, "604800000"
], [config_property.DELEGATION_TOKEN_EXPIRY_TIME_MS, "86400000"
], [config_property.DELEGATION_TOKEN_SECRET_KEY, "test12345"],
[
config_property.SASL_ENABLED_MECHANISMS,
"GSSAPI,SCRAM-SHA-256"
]])
self.jaas_deleg_conf_path = "/tmp/jaas_deleg.conf"
self.jaas_deleg_conf = ""
self.client_properties_content = """
security.protocol=SASL_PLAINTEXT
sasl.mechanism=SCRAM-SHA-256
sasl.kerberos.service.name=kafka
client.id=console-consumer
"""
self.client_kafka_opts = ' -Djava.security.auth.login.config=' + self.jaas_deleg_conf_path
self.producer = VerifiableProducer(
self.test_context,
num_nodes=1,
kafka=self.kafka,
topic=self.topic,
max_messages=1,
throughput=1,
kafka_opts_override=self.client_kafka_opts,
client_prop_file_override=self.client_properties_content)
self.consumer = ConsoleConsumer(
self.test_context,
num_nodes=1,
kafka=self.kafka,
topic=self.topic,
kafka_opts_override=self.client_kafka_opts,
client_prop_file_override=self.client_properties_content)
self.kafka.security_protocol = 'SASL_PLAINTEXT'
self.kafka.client_sasl_mechanism = 'GSSAPI,SCRAM-SHA-256'
self.kafka.interbroker_sasl_mechanism = 'GSSAPI'
def test_upgrade(self, from_kafka_version, to_message_format_version, compression_types,
new_consumer=True, security_protocol="PLAINTEXT"):
"""Test upgrade of Kafka broker cluster from 0.8.2, 0.9.0 or 0.10.0 to the current version
from_kafka_version is a Kafka version to upgrade from: either 0.8.2.X, 0.9.0.x or 0.10.0.x
If to_message_format_version is None, it means that we will upgrade to default (latest)
message format version. It is possible to upgrade to 0.10 brokers but still use message
format version 0.9
- Start 3 node broker cluster on version 'from_kafka_version'
- Start producer and consumer in the background
- Perform two-phase rolling upgrade
- First phase: upgrade brokers to 0.10 with inter.broker.protocol.version set to
from_kafka_version and log.message.format.version set to from_kafka_version
- Second phase: remove inter.broker.protocol.version config with rolling bounce; if
to_message_format_version is set to 0.9, set log.message.format.version to
to_message_format_version, otherwise remove log.message.format.version config
- Finally, validate that every message acked by the producer was consumed by the consumer
"""
self.kafka = KafkaService(self.test_context, num_nodes=3, zk=self.zk,
version=KafkaVersion(from_kafka_version),
topics={self.topic: {"partitions": 3, "replication-factor": 3,
'configs': {"min.insync.replicas": 2}}})
self.kafka.security_protocol = security_protocol
self.kafka.interbroker_security_protocol = security_protocol
self.kafka.start()
self.producer = VerifiableProducer(self.test_context, self.num_producers, self.kafka,
self.topic, throughput=self.producer_throughput,
message_validator=is_int,
compression_types=compression_types,
version=KafkaVersion(from_kafka_version))
assert self.zk.query("/cluster/id") is None
# TODO - reduce the timeout
self.consumer = ConsoleConsumer(self.test_context, self.num_consumers, self.kafka,
self.topic, consumer_timeout_ms=30000, new_consumer=new_consumer,
message_validator=is_int, version=KafkaVersion(from_kafka_version))
self.run_produce_consume_validate(core_test_action=lambda: self.perform_upgrade(from_kafka_version,
to_message_format_version))
cluster_id_json = self.zk.query("/cluster/id")
assert cluster_id_json is not None
try:
cluster_id = json.loads(cluster_id_json)
except :
self.logger.debug("Data in /cluster/id znode could not be parsed. Data = %s" % cluster_id_json)
self.logger.debug("Cluster id [%s]", cluster_id)
assert len(cluster_id["id"]) == 22
def __init__(self, test_context):
super(TestVerifiableProducer, self).__init__(test_context)
self.topic = "topic"
self.zk = ZookeeperService(test_context, num_nodes=1) if quorum.for_test(test_context) == quorum.zk else None
self.kafka = KafkaService(test_context, num_nodes=1, zk=self.zk,
topics={self.topic: {"partitions": 1, "replication-factor": 1}})
self.num_messages = 1000
# This will produce to source kafka cluster
self.producer = VerifiableProducer(test_context, num_nodes=1, kafka=self.kafka, topic=self.topic,
max_messages=self.num_messages, throughput=self.num_messages // 10)
def get_producer(self,
topic,
num_messages,
throughput=1000,
repeating_keys=None):
return VerifiableProducer(self.test_context,
1,
self.kafka,
topic,
max_messages=num_messages,
acks=-1,
throughput=throughput,
repeating_keys=repeating_keys,
retries=10)
def seed_messages(self, topic, num_seed_messages):
seed_timeout_sec = 10000
seed_producer = VerifiableProducer(context=self.test_context,
num_nodes=1,
kafka=self.kafka,
topic=topic,
message_validator=is_int,
max_messages=num_seed_messages,
enable_idempotence=True)
seed_producer.start()
wait_until(lambda: seed_producer.num_acked >= num_seed_messages,
timeout_sec=seed_timeout_sec,
err_msg="Producer failed to produce messages %d in %ds." %\
(self.num_seed_messages, seed_timeout_sec))
return seed_producer.acked
def __init__(self, test_context):
super(StreamsStaticMembershipTest, self).__init__(test_context)
self.topics = {
self.input_topic: {'partitions': 18},
}
self.zookeeper = ZookeeperService(self.test_context, num_nodes=1)
self.kafka = KafkaService(self.test_context, num_nodes=3,
zk=self.zookeeper, topics=self.topics)
self.producer = VerifiableProducer(self.test_context,
1,
self.kafka,
self.input_topic,
throughput=1000,
acks=1)
def __init__(self, test_context):
super(TestMirrorMakerService, self).__init__(test_context)
self.topic = "topic"
self.source_zk = ZookeeperService(test_context, num_nodes=1)
self.target_zk = ZookeeperService(test_context, num_nodes=1)
self.source_kafka = KafkaService(
test_context,
num_nodes=1,
zk=self.source_zk,
topics={self.topic: {
"partitions": 1,
"replication-factor": 1
}})
self.target_kafka = KafkaService(
test_context,
num_nodes=1,
zk=self.target_zk,
topics={self.topic: {
"partitions": 1,
"replication-factor": 1
}})
self.num_messages = 1000
# This will produce to source kafka cluster
self.producer = VerifiableProducer(test_context,
num_nodes=1,
kafka=self.source_kafka,
topic=self.topic,
max_messages=self.num_messages,
throughput=1000)
# Use a regex whitelist to check that the start command is well-formed in this case
self.mirror_maker = MirrorMaker(test_context,
num_nodes=1,
source=self.source_kafka,
target=self.target_kafka,
whitelist=".*",
consumer_timeout_ms=2000)
# This will consume from target kafka cluster
self.consumer = ConsoleConsumer(test_context,
num_nodes=1,
kafka=self.target_kafka,
topic=self.topic,
consumer_timeout_ms=1000)
def __init__(self, test_context):
super(StreamsCooperativeRebalanceUpgradeTest, self).__init__(test_context)
self.topics = {
self.source_topic: {'partitions': 9},
self.sink_topic: {'partitions': 9}
}
self.zookeeper = ZookeeperService(self.test_context, num_nodes=1)
self.kafka = KafkaService(self.test_context, num_nodes=3,
zk=self.zookeeper, topics=self.topics)
self.producer = VerifiableProducer(self.test_context,
1,
self.kafka,
self.source_topic,
throughput=1000,
acks=1)
def test_throttled_reassignment(self, bounce_brokers):
security_protocol = 'PLAINTEXT'
self.kafka.security_protocol = security_protocol
self.kafka.interbroker_security_protocol = security_protocol
producer_id = 'bulk_producer'
bulk_producer = ProducerPerformanceService(
context=self.test_context,
num_nodes=1,
kafka=self.kafka,
topic=self.topic,
num_records=self.num_records,
record_size=self.record_size,
throughput=-1,
client_id=producer_id)
self.producer = VerifiableProducer(context=self.test_context,
num_nodes=1,
kafka=self.kafka,
topic=self.topic,
message_validator=is_int,
throughput=self.producer_throughput)
self.consumer = ConsoleConsumer(self.test_context,
self.num_consumers,
self.kafka,
self.topic,
consumer_timeout_ms=60000,
message_validator=is_int,
from_beginning=False,
wait_until_partitions_assigned=True)
self.kafka.start()
bulk_producer.run()
self.run_produce_consume_validate(
core_test_action=lambda: self.reassign_partitions(
bounce_brokers, self.throttle))
self.logger.debug(
"Bulk producer outgoing-byte-rates: %s",
(metric.value
for k, metrics in bulk_producer.metrics(group='producer-metrics',
name='outgoing-byte-rate',
client_id=producer_id)
for metric in metrics))
