【kafka源码】TopicCommand之alter源码解析(分区扩容)

脚本参数

sh bin/kafka-topic -help 查看更具体参数

下面只是列出了跟 --alter 相关的参数

Alert Topic脚本

分区扩容

zk方式(不推荐)

bin/kafka-topics.sh --zookeeper localhost:2181 --alter --topic topic1 --partitions 2
1

kafka版本 >= 2.2 支持下面方式（推荐）
单个Topic扩容

bin/kafka-topics.sh --bootstrap-server broker_host:port --alter --topic test_create_topic1 --partitions 4

批量扩容 (将所有正则表达式匹配到的Topic分区扩容到4个)

sh bin/kafka-topics.sh --topic ".*?" --bootstrap-server 172.23.248.85:9092 --alter --partitions 4

".*?" 正则表达式的意思是匹配所有; 您可按需匹配

PS: 当某个Topic的分区少于指定的分区数时候,他会抛出异常;但是不会影响其他Topic正常进行;

---

相关可选参数

PS: 虽然这里配置的是全部的分区副本分配配置,但是真正生效的是新增的分区;
比如: 以前3分区1副本是这样的

源码解析

如果觉得源码解析过程比较枯燥乏味,可以直接如果 源码总结及其后面部分

因为在 【kafka源码】TopicCommand之创建Topic源码解析 里面分析的比较详细; 故本文就着重点分析了;

1. TopicCommand.alterTopic

    override def alterTopic(opts: TopicCommandOptions): Unit = {
      val topic = new CommandTopicPartition(opts)
      val topics = getTopics(opts.topic, opts.excludeInternalTopics)
      //校验Topic是否存在
      ensureTopicExists(topics, opts.topic)
      //获取一下该topic的一些基本信息
      val topicsInfo = adminClient.describeTopics(topics.asJavaCollection).values()
      adminClient.createPartitions(topics.map {topicName =>
        //判断是否有参数 replica-assignment  指定分区分配方式
        if (topic.hasReplicaAssignment) {
          val startPartitionId = topicsInfo.get(topicName).get().partitions().size()
          val newAssignment = {
            val replicaMap = topic.replicaAssignment.get.drop(startPartitionId)
            new util.ArrayList(replicaMap.map(p => p._2.asJava).asJavaCollection).asInstanceOf[util.List[util.List[Integer]]]
          }
          topicName -> NewPartitions.increaseTo(topic.partitions.get, newAssignment)
        } else {
          
          topicName -> NewPartitions.increaseTo(topic.partitions.get)
        }}.toMap.asJava).all().get()
    }
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1. 校验Topic是否存在
2. 如果设置了--replica-assignment 参数, 则会算出新增的分区数的分配; 这个并不会修改原本已经分配好的分区结构.从源码就可以看出来,假如我之前的分配方式是3,3,3(3分区一个副本都在BrokerId-3上)现在我传入的参数是: 3,3,3,3(多出来一个分区),这个时候会把原有的给截取掉;只传入3，(表示在Broker3新增一个分区)
3. 如果没有传入参数--replica-assignment，则后面会用默认分配策略分配

客户端发起请求createPartitions

KafkaAdminClient.createPartitions 省略部分代码

    @Override
    public CreatePartitionsResult createPartitions(Map<String, NewPartitions> newPartitions,
                                                   final CreatePartitionsOptions options) {
        final Map<String, KafkaFutureImpl<Void>> futures = new HashMap<>(newPartitions.size());
        for (String topic : newPartitions.keySet()) {
            futures.put(topic, new KafkaFutureImpl<>());
        }
   runnable.call(new Call("createPartitions", calcDeadlineMs(now, options.timeoutMs()),
                new ControllerNodeProvider()) {
                //省略部分代码
                            @Override
            void handleFailure(Throwable throwable) {
                completeAllExceptionally(futures.values(), throwable);
            }
        }, now);
        return new CreatePartitionsResult(new HashMap<>(futures));
    }
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1. 从源码中可以看到向ControllerNodeProvider 发起来createPartitions请求

2. Controller角色的服务端接受createPartitions请求处理逻辑

KafkaApis.handleCreatePartitionsRequest

def handleCreatePartitionsRequest(request: RequestChannel.Request): Unit = {
    val createPartitionsRequest = request.body[CreatePartitionsRequest]

    //部分代码省略..

     //如果当前不是Controller角色直接抛出异常
    if (!controller.isActive) {
      val result = createPartitionsRequest.data.topics.asScala.map { topic =>
        (topic.name, new ApiError(Errors.NOT_CONTROLLER, null))
      }.toMap
      sendResponseCallback(result)
    } else {
      // Special handling to add duplicate topics to the response
      val topics = createPartitionsRequest.data.topics.asScala
      val dupes = topics.groupBy(_.name)
        .filter { _._2.size > 1 }
        .keySet
      val notDuped = topics.filterNot(topic => dupes.contains(topic.name))
      val authorizedTopics = filterAuthorized(request, ALTER, TOPIC, notDuped.map(_.name))
      val (authorized, unauthorized) = notDuped.partition { topic => authorizedTopics.contains(topic.name) }

      val (queuedForDeletion, valid) = authorized.partition { topic =>
        controller.topicDeletionManager.isTopicQueuedUpForDeletion(topic.name)
      }

      val errors = dupes.map(_ -> new ApiError(Errors.INVALID_REQUEST, "Duplicate topic in request.")) ++
        unauthorized.map(_.name -> new ApiError(Errors.TOPIC_AUTHORIZATION_FAILED, "The topic authorization is failed.")) ++
        queuedForDeletion.map(_.name -> new ApiError(Errors.INVALID_TOPIC_EXCEPTION, "The topic is queued for deletion."))

      adminManager.createPartitions(createPartitionsRequest.data.timeoutMs,
        valid,
        createPartitionsRequest.data.validateOnly,
        request.context.listenerName, result => sendResponseCallback(result ++ errors))
    }
  }

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1. 检验自身是不是Controller角色,不是的话就抛出异常终止流程
2. 鉴权
3. 调用 adminManager.createPartitions
   3.1 从zk中获取/brokers/ids/Brokers列表的元信息的
   3.2 从zk获取/brokers/topics/{topicName}已经存在的副本分配方式,并判断是否有正在进行副本重分配的进程在执行,如果有的话就抛出异常结束流程
   3.3 如果从zk获取/brokers/topics/{topicName}数据不存在则抛出异常 The topic '$topic' does not exist
   3.4 检查修改的分区数是否比原来的分区数大，如果比原来还小或者等于原来分区数则抛出异常结束流程
   3.5 如果传入的参数--replica-assignment 中有不存在的BrokerId;则抛出异常Unknown broker(s) in replica assignment结束流程
   3.5 如果传入的--partitions数量 与--replica-assignment中新增的部分数量不匹配则抛出异常Increasing the number of partitions by... 结束流程
   3.6 调用 adminZkClient.addPartitions

adminZkClient.addPartitions 添加分区

1. 校验--partitions数量是否比存在的分区数大,否则异常The number of partitions for a topic can only be increased
2. 如果传入了--replica-assignment ,则对副本进行一些简单的校验
3. 调用AdminUtils.assignReplicasToBrokers分配副本 ; 这个我们在【kafka源码】TopicCommand之创建Topic源码解析 也分析过; 具体请看【kafka源码】创建Topic的时候是如何分区和副本的分配规则; 当然这里由于我们是新增的分区,只会将新增的分区进行分配计算
4. 得到分配规则只后,调用adminZkClient.writeTopicPartitionAssignment 写入

adminZkClient.writeTopicPartitionAssignment将分区信息写入zk中

我们在 【kafka源码】TopicCommand之创建Topic源码解析的时候也分析过这段代码,但是那个时候调用的是zkClient.createTopicAssignment 创建接口
这里我们是调用 zkClient.setTopicAssignment 写入接口, 写入当然会覆盖掉原有的信息,所以写入的时候会把原来分区信息获取到,重新写入;

1. 获取Topic原有分区副本分配信息
2. 将原有的和现在要添加的组装成一个数据对象写入到zk节点/brokers/topics/{topicName}中

3. Controller监控节点/brokers/topics/{topicName} ,真正在Broker上将分区写入磁盘

监听到节点信息变更之后调用下面的接口;
KafkaController.processPartitionModifications

private def processPartitionModifications(topic: String): Unit = {
    def restorePartitionReplicaAssignment(
      topic: String,
      newPartitionReplicaAssignment: Map[TopicPartition, ReplicaAssignment]
    ): Unit = {
      info("Restoring the partition replica assignment for topic %s".format(topic))

      val existingPartitions = zkClient.getChildren(TopicPartitionsZNode.path(topic))
      val existingPartitionReplicaAssignment = newPartitionReplicaAssignment
        .filter(p => existingPartitions.contains(p._1.partition.toString))
        .map { case (tp, _) =>
          tp -> controllerContext.partitionFullReplicaAssignment(tp)
      }.toMap

      zkClient.setTopicAssignment(topic,
        existingPartitionReplicaAssignment,
        controllerContext.epochZkVersion)
    }

    if (!isActive) return
    val partitionReplicaAssignment = zkClient.getFullReplicaAssignmentForTopics(immutable.Set(topic))
    val partitionsToBeAdded = partitionReplicaAssignment.filter { case (topicPartition, _) =>
      controllerContext.partitionReplicaAssignment(topicPartition).isEmpty
    }

    if (topicDeletionManager.isTopicQueuedUpForDeletion(topic)) {
      if (partitionsToBeAdded.nonEmpty) {
        warn("Skipping adding partitions %s for topic %s since it is currently being deleted"
          .format(partitionsToBeAdded.map(_._1.partition).mkString(","), topic))

        restorePartitionReplicaAssignment(topic, partitionReplicaAssignment)
      } else {
        // This can happen if existing partition replica assignment are restored to prevent increasing partition count during topic deletion
        info("Ignoring partition change during topic deletion as no new partitions are added")
      }
    } else if (partitionsToBeAdded.nonEmpty) {
      info(s"New partitions to be added $partitionsToBeAdded")
      partitionsToBeAdded.foreach { case (topicPartition, assignedReplicas) =>
        controllerContext.updatePartitionFullReplicaAssignment(topicPartition, assignedReplicas)
      }
      onNewPartitionCreation(partitionsToBeAdded.keySet)
    }
  }

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1. 判断是否Controller,不是则直接结束流程
2. 获取/brokers/topics/{topicName} 节点信息, 然后再对比一下当前该节点的分区分配信息; 看看有没有是新增的分区; 如果是新增的分区这个时候是还没有/brokers/topics/{topicName}/partitions/{分区号}/state ;
3. 如果当前的TOPIC正在被删除中,那么就没有必要执行扩分区了
4. 将新增加的分区信息加载到内存中
5. 调用接口KafkaController.onNewPartitionCreation

KafkaController.onNewPartitionCreation 新增分区

从这里开始 , 后面的流程就跟创建Topic的对应流程一样了;

该接口主要是针对新增分区和副本的一些状态流转过程; 在【kafka源码】TopicCommand之创建Topic源码解析 也同样分析过

  /**
   * This callback is invoked by the topic change callback with the list of failed brokers as input.
   * It does the following -
   * 1. Move the newly created partitions to the NewPartition state
   * 2. Move the newly created partitions from NewPartition->OnlinePartition state
   */
  private def onNewPartitionCreation(newPartitions: Set[TopicPartition]): Unit = {
    info(s"New partition creation callback for ${newPartitions.mkString(",")}")
    partitionStateMachine.handleStateChanges(newPartitions.toSeq, NewPartition)
    replicaStateMachine.handleStateChanges(controllerContext.replicasForPartition(newPartitions).toSeq, NewReplica)
    partitionStateMachine.handleStateChanges(
      newPartitions.toSeq,
      OnlinePartition,
      Some(OfflinePartitionLeaderElectionStrategy(false))
    )
    replicaStateMachine.handleStateChanges(controllerContext.replicasForPartition(newPartitions).toSeq, OnlineReplica)
  }
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1. 将待创建的分区状态流转为NewPartition;
   
2. 将待创建的副本 状态流转为NewReplica;
   
3. 将分区状态从刚刚的NewPartition流转为OnlinePartition
   0. 获取leaderIsrAndControllerEpochs; Leader为副本的第一个;
   1. 向zk中写入/brokers/topics/{topicName}/partitions/ 持久节点; 无数据
   2. 向zk中写入/brokers/topics/{topicName}/partitions/{分区号} 持久节点; 无数据
   3. 向zk中写入/brokers/topics/{topicName}/partitions/{分区号}/state 持久节点; 数据为leaderIsrAndControllerEpoch
   4. 向副本所属Broker发送leaderAndIsrRequest请求
   5. 向所有Broker发送UPDATE_METADATA 请求
4. 将副本状态从刚刚的NewReplica流转为OnlineReplica ,更新下内存

关于分区状态机和副本状态机详情请看【kafka源码】Controller中的状态机

4. Broker收到LeaderAndIsrRequest 创建本地Log

上面步骤中有说到向副本所属Broker发送leaderAndIsrRequest请求,那么这里做了什么呢
其实主要做的是 创建本地Log

代码太多,这里我们直接定位到只跟创建Topic相关的关键代码来分析
KafkaApis.handleLeaderAndIsrRequest->replicaManager.becomeLeaderOrFollower->ReplicaManager.makeLeaders...LogManager.getOrCreateLog

  /**
   * 如果日志已经存在，只返回现有日志的副本否则如果 isNew=true 或者如果没有离线日志目录，则为给定的主题和给定的分区创建日志 否则抛出 KafkaStorageException
   */
  def getOrCreateLog(topicPartition: TopicPartition, config: LogConfig, isNew: Boolean = false, isFuture: Boolean = false): Log = {
    logCreationOrDeletionLock synchronized {
      getLog(topicPartition, isFuture).getOrElse {
        // create the log if it has not already been created in another thread
        if (!isNew && offlineLogDirs.nonEmpty)
          throw new KafkaStorageException(s"Can not create log for $topicPartition because log directories ${offlineLogDirs.mkString(",")} are offline")

        val logDirs: List[File] = {
          val preferredLogDir = preferredLogDirs.get(topicPartition)

          if (isFuture) {
            if (preferredLogDir == null)
              throw new IllegalStateException(s"Can not create the future log for $topicPartition without having a preferred log directory")
            else if (getLog(topicPartition).get.dir.getParent == preferredLogDir)
              throw new IllegalStateException(s"Can not create the future log for $topicPartition in the current log directory of this partition")
          }

          if (preferredLogDir != null)
            List(new File(preferredLogDir))
          else
            nextLogDirs()
        }

        val logDirName = {
          if (isFuture)
            Log.logFutureDirName(topicPartition)
          else
            Log.logDirName(topicPartition)
        }

        val logDir = logDirs
          .toStream // to prevent actually mapping the whole list, lazy map
          .map(createLogDirectory(_, logDirName))
          .find(_.isSuccess)
          .getOrElse(Failure(new KafkaStorageException("No log directories available. Tried " + logDirs.map(_.getAbsolutePath).mkString(", "))))
          .get // If Failure, will throw

        val log = Log(
          dir = logDir,
          config = config,
          logStartOffset = 0L,
          recoveryPoint = 0L,
          maxProducerIdExpirationMs = maxPidExpirationMs,
          producerIdExpirationCheckIntervalMs = LogManager.ProducerIdExpirationCheckIntervalMs,
          scheduler = scheduler,
          time = time,
          brokerTopicStats = brokerTopicStats,
          logDirFailureChannel = logDirFailureChannel)

        if (isFuture)
          futureLogs.put(topicPartition, log)
        else
          currentLogs.put(topicPartition, log)

        info(s"Created log for partition $topicPartition in $logDir with properties " + s"{${config.originals.asScala.mkString(", ")}}.")
        // Remove the preferred log dir since it has already been satisfied
        preferredLogDirs.remove(topicPartition)

        log
      }
    }
  }
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1. 如果日志已经存在，只返回现有日志的副本否则如果 isNew=true 或者如果没有离线日志目录，则为给定的主题和给定的分区创建日志 否则抛出 KafkaStorageException

详细请看 【kafka源码】LeaderAndIsrRequest请求

源码总结

看图说话

Q&A

如果自定义的分配Broker不存在会怎么样

会抛出异常Unknown broker(s) in replica assignment, 因为在执行的时候会去zk获取当前的在线Broker列表，然后判断是否在线;

如果设置的分区数不等于 --replica-assignment中新增的数目会怎么样

会抛出异常Increasing the number of partitions by..结束流程

如果写入/brokers/topics/{topicName}之后 Controller监听到请求正好挂掉怎么办

Controller挂掉会发生重新选举,选举成功之后, 检查到/brokers/topics/{topicName}之后发现没有生成对应的分区,会自动执行接下来的流程;

如果我手动在zk中写入节点/brokers/topics/{topicName}/partitions/{分区号}/state 会怎么样

Controller并没有监听这个节点,所以不会有变化; 但是当Controller发生重新选举的时候,
被删除的节点会被重新添加回来;
但是写入的节点 就不会被删除了;写入的节点信息会被保存在Controller内存中;
同样这会影响到分区扩容

---

例子🌰：
当前分区3个,副本一个,手贱在zk上添加了一个节点如下图:

这个时候我想扩展一个分区; 然后执行了脚本, 虽然/brokers/topics/test_create_topic3节点数据变; 但是Broker真正在LeaderAndIsrRequest请求里面没有执行创建本地Log文件; 这是因为源码读取到zk下面partitions的节点数量和新增之后的节点数量没有变更,那么它就认为本次请求没有变更就不会执行创建本地Log文件了;
如果判断有变更,还是会去创建的;
手贱zk写入N个partition节点 + 扩充N个分区 = Log文件不会被创建
手贱zk写入N个partition节点 + 扩充>N个分区 = 正常扩容

如果直接修改节点/brokers/topics/{topicName}中的配置会怎么样

如果该节点信息是{"version":2,"partitions":{"2":[1],"1":[1],"0":[1]},"adding_replicas":{},"removing_replicas":{}} 看数据,说明3个分区1个副本都在Broker-1上;
我在zk上修改成{"version":2,"partitions":{"2":[2],"1":[1],"0":[0]},"adding_replicas":{},"removing_replicas":{}}
想将分区分配到 Broker-0，Broker-1，Broker-2上
TODO。。。

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Tips:如果关于本篇文章你有疑问,可以在评论区留下,我会在Q&A部分进行解答

PS: 文章阅读的源码版本是kafka-2.5