rreddy-22 commented on code in PR #15717: URL: https://github.com/apache/kafka/pull/15717#discussion_r1568011957
########## jmh-benchmarks/src/main/java/org/apache/kafka/jmh/group_coordinator/ClientSideAssignorBenchmark.java: ########## @@ -0,0 +1,256 @@ +/* + * 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. + */ +package org.apache.kafka.jmh.group_coordinator; + +import org.apache.kafka.clients.consumer.ConsumerPartitionAssignor; +import org.apache.kafka.clients.consumer.CooperativeStickyAssignor; +import org.apache.kafka.clients.consumer.RangeAssignor; +import org.apache.kafka.common.Cluster; +import org.apache.kafka.common.Node; +import org.apache.kafka.common.PartitionInfo; +import org.apache.kafka.common.TopicPartition; +import org.openjdk.jmh.annotations.Benchmark; +import org.openjdk.jmh.annotations.BenchmarkMode; +import org.openjdk.jmh.annotations.Fork; +import org.openjdk.jmh.annotations.Level; +import org.openjdk.jmh.annotations.Measurement; +import org.openjdk.jmh.annotations.Mode; +import org.openjdk.jmh.annotations.OutputTimeUnit; +import org.openjdk.jmh.annotations.Param; +import org.openjdk.jmh.annotations.Scope; +import org.openjdk.jmh.annotations.Setup; +import org.openjdk.jmh.annotations.State; +import org.openjdk.jmh.annotations.Threads; +import org.openjdk.jmh.annotations.Warmup; + +import java.util.ArrayList; +import java.util.Arrays; +import java.util.Collections; +import java.util.HashMap; +import java.util.List; +import java.util.Map; +import java.util.Optional; +import java.util.concurrent.TimeUnit; + +import static java.lang.Integer.max; +import static org.apache.kafka.clients.consumer.internals.AbstractStickyAssignor.DEFAULT_GENERATION; + +@State(Scope.Benchmark) +@Fork(value = 1) +@Warmup(iterations = 5) +@Measurement(iterations = 5) +@BenchmarkMode(Mode.AverageTime) +@OutputTimeUnit(TimeUnit.MILLISECONDS) +public class ClientSideAssignorBenchmark { + + public enum AssignorType { + RANGE(new RangeAssignor()), + COOPERATIVE_STICKY(new CooperativeStickyAssignor()); + + private final ConsumerPartitionAssignor assignor; + + AssignorType(ConsumerPartitionAssignor assignor) { + this.assignor = assignor; + } + + public ConsumerPartitionAssignor assignor() { + return assignor; + } + } + + /** + * The subscription pattern followed by the members of the group. + * + * A subscription model is considered homogenous if all the members of the group + * are subscribed to the same set of topics, it is heterogeneous otherwise. + */ + public enum SubscriptionModel { + HOMOGENEOUS, HETEROGENEOUS + } + + @Param({"1000", "10000"}) + private int memberCount; + + @Param({"10", "50"}) + private int partitionsPerTopicCount; + + @Param({"100", "1000"}) + private int topicCount; + + @Param({"true", "false"}) + private boolean isRackAware; + + @Param({"HOMOGENEOUS", "HETEROGENEOUS"}) + private SubscriptionModel subscriptionModel; + + @Param({"RANGE", "COOPERATIVE_STICKY"}) + private AssignorType assignorType; + + @Param({"true", "false"}) + private boolean simulateRebalanceTrigger; + + private Map<String, ConsumerPartitionAssignor.Subscription> subscriptions = new HashMap<>(); + + private ConsumerPartitionAssignor.GroupSubscription groupSubscription; + + private static final int numberOfRacks = 3; + + private static final int replicationFactor = 2; Review Comment: For the server side tests I always used replication factor as 2, so in order to get the same distribution of racks for consistency I added the replication factor as 2. That being said I think I'll just hardcode the replication factor here as well -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: jira-unsubscr...@kafka.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org
