rreddy-22 commented on code in PR #15717: URL: https://github.com/apache/kafka/pull/15717#discussion_r1576507146
########## jmh-benchmarks/src/main/java/org/apache/kafka/jmh/assignor/ServerSideAssignorBenchmark.java: ########## @@ -0,0 +1,281 @@ +/* + * 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.common.Uuid; +import org.apache.kafka.coordinator.group.assignor.AssignmentMemberSpec; +import org.apache.kafka.coordinator.group.assignor.AssignmentSpec; +import org.apache.kafka.coordinator.group.assignor.GroupAssignment; +import org.apache.kafka.coordinator.group.assignor.MemberAssignment; +import org.apache.kafka.coordinator.group.assignor.PartitionAssignor; +import org.apache.kafka.coordinator.group.assignor.RangeAssignor; +import org.apache.kafka.coordinator.group.assignor.SubscribedTopicDescriber; +import org.apache.kafka.coordinator.group.assignor.UniformAssignor; +import org.apache.kafka.coordinator.group.consumer.SubscribedTopicMetadata; +import org.apache.kafka.coordinator.group.consumer.TopicMetadata; +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.Collection; +import java.util.Collections; +import java.util.HashMap; +import java.util.HashSet; +import java.util.List; +import java.util.Map; +import java.util.Optional; +import java.util.Set; +import java.util.concurrent.TimeUnit; + +@State(Scope.Benchmark) +@Fork(value = 1) +@Warmup(iterations = 5) +@Measurement(iterations = 5) +@BenchmarkMode(Mode.AverageTime) +@OutputTimeUnit(TimeUnit.MILLISECONDS) +public class ServerSideAssignorBenchmark { + + public enum AssignorType { + RANGE(new RangeAssignor()), + UNIFORM(new UniformAssignor()); + + private final PartitionAssignor assignor; + + AssignorType(PartitionAssignor assignor) { + this.assignor = assignor; + } + + public PartitionAssignor 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 + } + + /** + * The assignment type is decided based on whether all the members are assigned partitions + * for the first time (full), or incrementally when a rebalance is triggered. + */ + public enum AssignmentType { + FULL, INCREMENTAL + } + + @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", "UNIFORM"}) + private AssignorType assignorType; + + @Param({"FULL", "INCREMENTAL"}) + private AssignmentType assignmentType; + + private PartitionAssignor partitionAssignor; + + private static final int NUMBER_OF_RACKS = 3; + + private static final int MAX_BUCKET_COUNT = 5; + + private AssignmentSpec assignmentSpec; + + private SubscribedTopicDescriber subscribedTopicDescriber; + + private final List<Uuid> allTopicIds = new ArrayList<>(topicCount); + + @Setup(Level.Trial) + public void setup() { + Map<Uuid, TopicMetadata> topicMetadata = createTopicMetadata(); + subscribedTopicDescriber = new SubscribedTopicMetadata(topicMetadata); + + createAssignmentSpec(); + + partitionAssignor = assignorType.assignor(); + + if (assignmentType == AssignmentType.INCREMENTAL) { + simulateIncrementalRebalance(); + } + } + + private Map<Uuid, TopicMetadata> createTopicMetadata() { + Map<Uuid, TopicMetadata> topicMetadata = new HashMap<>(); + int partitionsPerTopicCount = (memberCount * partitionsToMemberRatio) / topicCount; + + Map<Integer, Set<String>> partitionRacks = isRackAware ? + mkMapOfPartitionRacks(partitionsPerTopicCount) : + Collections.emptyMap(); + + for (int i = 0; i < topicCount; i++) { + Uuid topicUuid = Uuid.randomUuid(); + String topicName = "topic" + i; + allTopicIds.add(topicUuid); + topicMetadata.put(topicUuid, new TopicMetadata( + topicUuid, + topicName, + partitionsPerTopicCount, + partitionRacks + )); + } + + return topicMetadata; + } + + private void createAssignmentSpec() { + Map<String, AssignmentMemberSpec> members = new HashMap<>(); + + // In the rebalance case, we will add the last member as a trigger. + // This is done to keep the total members count consistent with the input. + int numberOfMembers = assignmentType.equals(AssignmentType.INCREMENTAL) ? memberCount - 1 : memberCount; + + if (subscriptionModel.equals(SubscriptionModel.HOMOGENEOUS)) { + for (int i = 0; i < numberOfMembers; i++) { + addMemberSpec(members, i, new HashSet<>(allTopicIds)); + } + } else { + // Adjust bucket count based on member count when member count < max bucket count. + int bucketCount = Math.min(MAX_BUCKET_COUNT, numberOfMembers); + + // Check minimum topics requirement + if (topicCount < bucketCount) { + throw new IllegalArgumentException("At least " + bucketCount + " topics are recommended for effective bucketing."); + } + + int bucketSizeTopics = (int) Math.ceil((double) topicCount / bucketCount); + int bucketSizeMembers = (int) Math.ceil((double) numberOfMembers / bucketCount); + + // Define buckets for each member and assign topics from the same bucket + for (int bucket = 0; bucket < bucketCount; bucket++) { + int memberStartIndex = bucket * bucketSizeMembers; + int memberEndIndex = Math.min((bucket + 1) * bucketSizeMembers, numberOfMembers); + + int topicStartIndex = bucket * bucketSizeTopics; + int topicEndIndex = Math.min((bucket + 1) * bucketSizeTopics, topicCount); + + Set<Uuid> bucketTopics = new HashSet<>(allTopicIds.subList(topicStartIndex, topicEndIndex)); + + // Assign topics to each member in the current bucket + for (int i = memberStartIndex; i < memberEndIndex; i++) { + addMemberSpec(members, i, new HashSet<>(bucketTopics)); + } + } + } + + this.assignmentSpec = new AssignmentSpec(members); + } + + private Optional<String> rackId(int memberIndex) { + return isRackAware ? Optional.of("rack" + memberIndex % NUMBER_OF_RACKS) : Optional.empty(); + } + + private void addMemberSpec( + Map<String, AssignmentMemberSpec> members, + int memberIndex, + Set<Uuid> subscribedTopicIds + ) { + String memberId = "member" + memberIndex; + Optional<String> rackId = rackId(memberIndex); + + members.put(memberId, new AssignmentMemberSpec( + Optional.empty(), + rackId, + subscribedTopicIds, + Collections.emptyMap() + )); + } + + private static Map<Integer, Set<String>> mkMapOfPartitionRacks(int numPartitions) { + Map<Integer, Set<String>> partitionRacks = new HashMap<>(numPartitions); + for (int i = 0; i < numPartitions; i++) { + partitionRacks.put(i, new HashSet<>(Arrays.asList( + "rack" + i % NUMBER_OF_RACKS, + "rack" + (i + 1) % NUMBER_OF_RACKS, + "rack" + (i + 2) % NUMBER_OF_RACKS + ))); + } + return partitionRacks; + } + + private void simulateIncrementalRebalance() { + GroupAssignment initialAssignment = partitionAssignor.assign(assignmentSpec, subscribedTopicDescriber); + Map<String, MemberAssignment> members = initialAssignment.members(); + + Map<String, AssignmentMemberSpec> updatedMembers = new HashMap<>(); + members.forEach((memberId, memberAssignment) -> { + AssignmentMemberSpec memberSpec = assignmentSpec.members().get(memberId); + updatedMembers.put(memberId, new AssignmentMemberSpec( + memberSpec.instanceId(), + memberSpec.rackId(), + memberSpec.subscribedTopicIds(), + memberAssignment.targetPartitions() + )); + }); + + Collection<Uuid> subscribedTopicIdsForNewMember; + if (subscriptionModel == SubscriptionModel.HETEROGENEOUS) { + subscribedTopicIdsForNewMember = updatedMembers.values().iterator().next().subscribedTopicIds(); Review Comment: I made the buckets based on the number of members = memberCount-1 for the first assignment, so I figured we could add a member and assign it any member's subscription list. -- This is an automated message from the Apache Git Service. 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