content: /*
   * 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.api.assignor.GroupAssignment;
  import org.apache.kafka.coordinator.group.api.assignor.GroupSpec;
  import org.apache.kafka.coordinator.group.api.assignor.MemberAssignment;
  import org.apache.kafka.coordinator.group.api.assignor.PartitionAssignor;
  import org.apache.kafka.coordinator.group.api.assignor.SubscribedTopicDescriber;
  import org.apache.kafka.coordinator.group.api.assignor.SubscriptionType;
  import org.apache.kafka.coordinator.group.assignor.RangeAssignor;
  import org.apache.kafka.coordinator.group.assignor.UniformAssignor;
  import org.apache.kafka.coordinator.group.modern.Assignment;
  import org.apache.kafka.coordinator.group.modern.GroupSpecImpl;
  import org.apache.kafka.coordinator.group.modern.MemberAssignmentImpl;
  import org.apache.kafka.coordinator.group.modern.MemberSubscriptionAndAssignmentImpl;
  import org.apache.kafka.coordinator.group.modern.SubscribedTopicDescriberImpl;
  import org.apache.kafka.coordinator.group.modern.TopicIds;
  import org.apache.kafka.coordinator.group.modern.consumer.ConsumerGroupMember;
  import org.apache.kafka.image.MetadataImage;
  
  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.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;
  
  import static org.apache.kafka.coordinator.group.api.assignor.SubscriptionType.HETEROGENEOUS;
  import static org.apache.kafka.coordinator.group.api.assignor.SubscriptionType.HOMOGENEOUS;
  
  @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 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 SubscriptionType subscriptionType;
  
      @Param({"RANGE", "UNIFORM"})
      private AssignorType assignorType;
  
      @Param({"FULL", "INCREMENTAL"})
      private AssignmentType assignmentType;
  
      private PartitionAssignor partitionAssignor;
  
      private static final int NUMBER_OF_RACKS = 3;
  
      /** The number of homogeneous subgroups to create for the heterogeneous subscription case. */
      private static final int MAX_BUCKET_COUNT = 5;
  
      private GroupSpec groupSpec;
  
      private List<String> allTopicNames = Collections.emptyList();
  
      private MetadataImage metadataImage = MetadataImage.EMPTY;
  
      private TopicIds.TopicResolver topicResolver;
  
      private SubscribedTopicDescriber subscribedTopicDescriber;
  
      @Setup(Level.Trial)
      public void setup() {
          partitionAssignor = assignorType.assignor();
  
          setupTopics();
  
          Map<String, ConsumerGroupMember> members = createMembers();
          this.groupSpec = AssignorBenchmarkUtils.createGroupSpec(members, subscriptionType, topicResolver);
  
          if (assignmentType == AssignmentType.INCREMENTAL) {
              simulateIncrementalRebalance();
          }
      }
  
      private void setupTopics() {
          allTopicNames = AssignorBenchmarkUtils.createTopicNames(topicCount);
  
          int partitionsPerTopic = (memberCount * partitionsToMemberRatio) / topicCount;
  
          metadataImage = AssignorBenchmarkUtils.createMetadataImage(allTopicNames, partitionsPerTopic);
          topicResolver = new TopicIds.CachedTopicResolver(metadataImage.topics());
  
          subscribedTopicDescriber = new SubscribedTopicDescriberImpl(metadataImage);
      }
  
      private Map<String, ConsumerGroupMember> createMembers() {
          // 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 (subscriptionType == HOMOGENEOUS) {
              return AssignorBenchmarkUtils.createHomogeneousMembers(
                  numberOfMembers,
                  this::memberId,
                  this::rackId,
                  allTopicNames
              );
          } else {
              return AssignorBenchmarkUtils.createHeterogeneousBucketedMembers(
                  numberOfMembers,
                  MAX_BUCKET_COUNT,
                  this::memberId,
                  this::rackId,
                  allTopicNames
              );
          }
      }
  
      private String memberId(int memberIndex) {
          return "member" + memberIndex;
      }
  
      private Optional<String> rackId(int memberIndex) {
          return isRackAware ? Optional.of("rack" + memberIndex % NUMBER_OF_RACKS) : Optional.empty();
      }
  
      private void simulateIncrementalRebalance() {
          GroupAssignment initialAssignment = partitionAssignor.assign(groupSpec, subscribedTopicDescriber);
          Map<String, MemberAssignment> members = initialAssignment.members();
  
          Map<Uuid, Map<Integer, String>> invertedTargetAssignment = AssignorBenchmarkUtils.computeInvertedTargetAssignment(initialAssignment);
  
          Map<String, MemberSubscriptionAndAssignmentImpl> updatedMemberSpec = new HashMap<>();
  
          for (String memberId : groupSpec.memberIds()) {
              MemberAssignment memberAssignment = members.getOrDefault(
                  memberId,
                  new MemberAssignmentImpl(Collections.emptyMap())
              );
  
              updatedMemberSpec.put(memberId, new MemberSubscriptionAndAssignmentImpl(
                  groupSpec.memberSubscription(memberId).rackId(),
                  Optional.empty(),
                  groupSpec.memberSubscription(memberId).subscribedTopicIds(),
                  new Assignment(Collections.unmodifiableMap(memberAssignment.partitions()))
              ));
          }
  
          Set<Uuid> subscribedTopicIdsForNewMember;
          if (subscriptionType == HETEROGENEOUS) {
              subscribedTopicIdsForNewMember = updatedMemberSpec.get(memberId(memberCount - 2)).subscribedTopicIds();
          } else {
              subscribedTopicIdsForNewMember = new TopicIds(new HashSet<>(allTopicNames), topicResolver);
          }
  
          Optional<String> rackId = rackId(memberCount - 1);
          updatedMemberSpec.put("newMember", new MemberSubscriptionAndAssignmentImpl(
              rackId,
              Optional.empty(),
              subscribedTopicIdsForNewMember,
              Assignment.EMPTY
          ));
  
          groupSpec = new GroupSpecImpl(
              updatedMemberSpec,
              subscriptionType,
              invertedTargetAssignment
          );
      }
  
      @Benchmark
      @Threads(1)
      @OutputTimeUnit(TimeUnit.MILLISECONDS)
      public void doAssignment() {
          topicResolver.clear();
          partitionAssignor.assign(groupSpec, subscribedTopicDescriber);
      }
  }
  