rreddy-22 commented on code in PR #15717: URL: https://github.com/apache/kafka/pull/15717#discussion_r1571348485
########## jmh-benchmarks/src/main/java/org/apache/kafka/jmh/assignor/ClientSideAssignorBenchmark.java: ########## @@ -0,0 +1,262 @@ +/* + * 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.assignor; + +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({"100", "500", "1000", "5000", "10000"}) + private int memberCount; + + @Param({"5", "10", "50"}) + private int partitionsToMemberRatio; + + @Param({"10", "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 NUMBER_OF_RACKS = 3; + + private ConsumerPartitionAssignor assignor; + + private Cluster metadata; + + private final List<String> allTopicNames = new ArrayList<>(topicCount); + + @Setup(Level.Trial) + public void setup() { + // Ensure there are enough racks and brokers for the replication factor. + if (NUMBER_OF_RACKS < 2) { + throw new IllegalArgumentException("Number of broker racks must be at least equal to 2."); + } + + populateTopicMetadata(); + + addMemberSubscriptions(); + + assignor = assignorType.assignor(); + + if (simulateRebalanceTrigger) simulateRebalance(); + } + + private void populateTopicMetadata() { + List<PartitionInfo> partitions = new ArrayList<>(); + int partitionsPerTopicCount = (memberCount * partitionsToMemberRatio) / topicCount; + + // Create nodes (brokers), one for each rack. + List<Node> nodes = new ArrayList<>(NUMBER_OF_RACKS); + for (int i = 0; i < NUMBER_OF_RACKS; i++) { + nodes.add(new Node(i, "", i, "rack" + i)); + } + + for (int i = 0; i < topicCount; i++) { + String topicName = "topic" + i; + allTopicNames.add(topicName); + partitions.addAll(partitionInfos(topicName, partitionsPerTopicCount, nodes)); + } + + metadata = new Cluster("test-cluster", nodes, partitions, Collections.emptySet(), Collections.emptySet()); + } + + private void addMemberSubscriptions() { + subscriptions.clear(); Review Comment: No it is reset, I must've left it from something I wrote previously -- This is an automated message from the Apache Git Service. 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