Mirror of Apache Kafka
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# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from ducktape.mark import parametrize
from ducktape.tests.test import Test
from kafkatest.services.kafka import KafkaService
from kafkatest.services.performance import ProducerPerformanceService, ConsumerPerformanceService, EndToEndLatencyService
from kafkatest.services.performance import latency, compute_aggregate_throughput
from kafkatest.services.zookeeper import ZookeeperService
from kafkatest.version import TRUNK, LATEST_0_8_2, LATEST_0_9, KafkaVersion
class PerformanceServiceTest(Test):
def __init__(self, test_context):
super(PerformanceServiceTest, self).__init__(test_context)
self.record_size = 100
self.num_records = 10000
self.topic = "topic"
self.zk = ZookeeperService(test_context, 1)
def setUp(self):
self.zk.start()
# We are keeping 0.8.2 here so that we don't inadvertently break support for it. Since this is just a sanity check,
# the overhead should be manageable.
@parametrize(version=str(LATEST_0_8_2), new_consumer=False)
@parametrize(version=str(LATEST_0_9), new_consumer=False)
@parametrize(version=str(LATEST_0_9))
@parametrize(version=str(TRUNK), new_consumer=False)
@parametrize(version=str(TRUNK))
def test_version(self, version=str(LATEST_0_9), new_consumer=True):
"""
Sanity check out producer performance service - verify that we can run the service with a small
number of messages. The actual stats here are pretty meaningless since the number of messages is quite small.
"""
version = KafkaVersion(version)
self.kafka = KafkaService(
self.test_context, 1,
self.zk, topics={self.topic: {'partitions': 1, 'replication-factor': 1}}, version=version)
self.kafka.start()
# check basic run of producer performance
self.producer_perf = ProducerPerformanceService(
self.test_context, 1, self.kafka, topic=self.topic,
num_records=self.num_records, record_size=self.record_size,
throughput=1000000000, # Set impossibly for no throttling for equivalent behavior between 0.8.X and 0.9.X
version=version,
settings={
'acks': 1,
'batch.size': 8*1024,
'buffer.memory': 64*1024*1024})
self.producer_perf.run()
producer_perf_data = compute_aggregate_throughput(self.producer_perf)
# check basic run of end to end latency
self.end_to_end = EndToEndLatencyService(
self.test_context, 1, self.kafka,
topic=self.topic, num_records=self.num_records, version=version)
self.end_to_end.run()
end_to_end_data = latency(self.end_to_end.results[0]['latency_50th_ms'], self.end_to_end.results[0]['latency_99th_ms'], self.end_to_end.results[0]['latency_999th_ms'])
# check basic run of consumer performance service
self.consumer_perf = ConsumerPerformanceService(
self.test_context, 1, self.kafka, new_consumer=new_consumer,
topic=self.topic, version=version, messages=self.num_records)
self.consumer_perf.group = "test-consumer-group"
self.consumer_perf.run()
consumer_perf_data = compute_aggregate_throughput(self.consumer_perf)
return {
"producer_performance": producer_perf_data,
"end_to_end_latency": end_to_end_data,
"consumer_performance": consumer_perf_data
}