• 消息从客户端产生后，发送到哪个broker；
• 发送到broker后，broker如何接收，如何存储;

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KafkaApis中响应LeaderAndIsr Request

• 针对topic，KafkaController会进行partition选主，产生最新的isr, replicas, 然后发送到topic的各个replica，详细参考Kafka集群建立过程分析和KafkaController分析5-Partition状态机
• KafkaApis中处理LeaderAndIsr Request并发送LeaderAndIsrResponse；

    val correlationId = request.header.correlationId
    val leaderAndIsrRequest = request.body.asInstanceOf[LeaderAndIsrRequest]

      def onLeadershipChange(updatedLeaders: Iterable[Partition], updatedFollowers: Iterable[Partition]) {
        // for each new leader or follower, call coordinator to handle consumer group migration.
        // this callback is invoked under the replica state change lock to ensure proper order of
        // leadership changes
        updatedLeaders.foreach { partition =>
          if (partition.topic == GroupCoordinator.GroupMetadataTopicName)
            coordinator.handleGroupImmigration(partition.partitionId)
        }
        updatedFollowers.foreach { partition =>
          if (partition.topic == GroupCoordinator.GroupMetadataTopicName)
            coordinator.handleGroupEmigration(partition.partitionId)
        }
      }

      val responseHeader = new ResponseHeader(correlationId)
      val leaderAndIsrResponse=
        if (authorize(request.session, ClusterAction, Resource.ClusterResource)) {
          val result = replicaManager.becomeLeaderOrFollower(correlationId, leaderAndIsrRequest, metadataCache, onLeadershipChange)
          new LeaderAndIsrResponse(result.errorCode, result.responseMap.mapValues(new JShort(_)).asJava)
        } else {
          val result = leaderAndIsrRequest.partitionStates.asScala.keys.map((_, new JShort(Errors.CLUSTER_AUTHORIZATION_FAILED.code))).toMap
          new LeaderAndIsrResponse(Errors.CLUSTER_AUTHORIZATION_FAILED.code, result.asJava)
        }

      requestChannel.sendResponse(new Response(request, new ResponseSend(request.connectionId, responseHeader, leaderAndIsrResponse)))

其中最主要的操作调用ReplicaManager.becomeLeaderOrFollower来初始化Partition

val result = replicaManager.becomeLeaderOrFollower(correlationId, leaderAndIsrRequest, metadataCache, onLeadershipChange)

• ReplicaManager.becomeLeaderOrFollower

1. 判断LeaderAndIsr请求中的controllerEpoch和ReplicaManager保存的controllerEpoch(在处理UpdateMetadata Request时更新, 参见Kafka集群Metadata管理), 如果本地存的controllerEpoch大，则忽略当前的LeaderAndIsr请求, 产生BecomeLeaderOrFollowerResult(responseMap, ErrorMapping.StaleControllerEpochCode)；
2. 处理leaderAndISRRequest.partitionStates中的第个partition state;
   2.1 创建Partition对象，这个我们后面会讲到;

allPartitions.putIfNotExists((topic, partitionId), new Partition(topic, partitionId, time, this))

2.2 如果partitionStateInfo中的leaderEpoch更新，则存储它在val partitionState = new mutable.HashMap[Partition, LeaderAndIsrRequest.PartitionState]()中

if (partitionLeaderEpoch < stateInfo.leaderEpoch) {
          if(stateInfo.replicas.contains(config.brokerId))
                 partitionState.put(partition, stateInfo)
}

2.3 分离出转换成leader和follower的partitions;

 val partitionsTobeLeader = partitionState.filter { case (partition, stateInfo) =>
          stateInfo.leader == config.brokerId
        }
  val partitionsToBeFollower = (partitionState -- partitionsTobeLeader.keys)

2.4 处理转换成leader

makeLeaders(controllerId, controllerEpoch, partitionsTobeLeader, correlationId, responseMap)

实现上干两件事:
停止从leader来同步消息: replicaFetcherManager.removeFetcherForPartitions(partitionState.keySet.map(new TopicAndPartition(_))),参见ReplicaManager源码解析1-消息同步线程管理
调用Partition的makeLeader方法:partition.makeLeader(controllerId, partitionStateInfo, correlationId)来作leader的转换
2.5 处理转换成follower

makeFollowers(controllerId, controllerEpoch, partitionsToBeFollower, leaderAndISRRequest.correlationId, responseMap, metadataCache)

2.6 启动HighWaterMarkCheckPointThread, 具体后面章节会讲到,

if (!hwThreadInitialized) {
          startHighWaterMarksCheckPointThread()
          hwThreadInitialized = true
}

2.7 回调KafkaApis.handleLeaderAndIsrRequest.onLeadershipChange

• 针对makeLeaders和makeFollowers的分析我们等分析完Parition, ReplicaFetcherManager后一并分析.
• LeaderAndIsr 请求响应流程图:

LeaderAndIsr 请求响应.png

Kafka源码分析-汇总