mirror of https://github.com/apache/kafka.git
99 lines
4.9 KiB
Python
99 lines
4.9 KiB
Python
# Licensed to the Apache Software Foundation (ASF) under one or more
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# contributor license agreements. See the NOTICE file distributed with
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# this work for additional information regarding copyright ownership.
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# The ASF licenses this file to You under the Apache License, Version 2.0
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# (the "License"); you may not use this file except in compliance with
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# the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from ducktape.utils.util import wait_until
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from ducktape.mark import matrix, parametrize
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from ducktape.mark.resource import cluster
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from ducktape.tests.test import Test
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from kafkatest.services.kafka import KafkaService, quorum
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from kafkatest.services.performance import ProducerPerformanceService, ConsumerPerformanceService, EndToEndLatencyService, ShareConsumerPerformanceService
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from kafkatest.services.performance import latency, compute_aggregate_throughput
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from kafkatest.version import DEV_BRANCH, LATEST_2_1, V_4_1_0, KafkaVersion
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class PerformanceServiceTest(Test):
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def __init__(self, test_context):
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super(PerformanceServiceTest, self).__init__(test_context)
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self.record_size = 100
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self.num_records = 10000
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self.topic = "topic"
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@cluster(num_nodes=6)
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@matrix(version=[str(LATEST_2_1)], metadata_quorum=quorum.all_kraft)
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@matrix(version=[str(DEV_BRANCH)], metadata_quorum=quorum.all_kraft, use_share_groups=[True])
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def test_version(self, version=str(LATEST_2_1), metadata_quorum=quorum.zk, use_share_groups=False):
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"""
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Sanity check out producer performance service - verify that we can run the service with a small
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number of messages. The actual stats here are pretty meaningless since the number of messages is quite small.
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"""
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version = KafkaVersion(version)
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self.kafka = KafkaService(
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self.test_context, 1,
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None, topics={self.topic: {'partitions': 1, 'replication-factor': 1}}, version=DEV_BRANCH)
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self.kafka.start()
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# check basic run of producer performance
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self.producer_perf = ProducerPerformanceService(
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self.test_context, 1, self.kafka, topic=self.topic,
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num_records=self.num_records, record_size=self.record_size,
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throughput=1000000000, # Set impossibly for no throttling for equivalent behavior between 0.8.X and 0.9.X
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version=version,
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settings={
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'acks': 1,
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'batch.size': 8*1024,
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'buffer.memory': 64*1024*1024})
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self.producer_perf.run()
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producer_perf_data = compute_aggregate_throughput(self.producer_perf)
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assert producer_perf_data['records_per_sec'] > 0
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# check basic run of end to end latency
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self.end_to_end = EndToEndLatencyService(
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self.test_context, 1, self.kafka,
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topic=self.topic, num_records=self.num_records, version=version)
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self.end_to_end.run()
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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'])
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# check basic run of consumer performance service
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self.consumer_perf = ConsumerPerformanceService(
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self.test_context, 1, self.kafka,
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topic=self.topic, version=version, messages=self.num_records)
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self.consumer_perf.group = "test-consumer-group"
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self.consumer_perf.run()
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consumer_perf_data = compute_aggregate_throughput(self.consumer_perf)
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assert consumer_perf_data['records_per_sec'] > 0
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results = {
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"producer_performance": producer_perf_data,
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"end_to_end_latency": end_to_end_data,
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"consumer_performance": consumer_perf_data,
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}
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if version >= V_4_1_0:
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# check basic run of share consumer performance service
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self.share_consumer_perf = ShareConsumerPerformanceService(
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self.test_context, 1, self.kafka,
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topic=self.topic, version=version, messages=self.num_records)
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share_group = "test-share-consumer-group"
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self.share_consumer_perf.group = share_group
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wait_until(lambda: self.kafka.set_share_group_offset_reset_strategy(group=share_group, strategy="earliest"),
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timeout_sec=20, backoff_sec=2, err_msg="share.auto.offset.reset not set to earliest")
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self.share_consumer_perf.run()
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share_consumer_perf_data = compute_aggregate_throughput(self.share_consumer_perf)
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assert share_consumer_perf_data['records_per_sec'] > 0
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results["share_consumer_performance"] = share_consumer_perf_data
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return results
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