apache kafka源码分析-Producer分析-载

DefaultEventHandler类中初始化实例化BrokerPartitionInfo类，然后定期brokerPartitionInfo.updateInfo方法，DefaultEventHandler部分代码如下：
  def handle(events: Seq[KeyedMessage[K,V]]) {
    ......
    while (remainingRetries > 0 && outstandingProduceRequests.size > 0) {
      topicMetadataToRefresh ++= outstandingProduceRequests.map(_.topic)
      if (topicMetadataRefreshInterval >= 0 &&
          SystemTime.milliseconds - lastTopicMetadataRefreshTime > topicMetadataRefreshInterval) {
        Utils.swallowError(brokerPartitionInfo.updateInfo(topicMetadataToRefresh.toSet, correlationId.getAndIncrement))
        sendPartitionPerTopicCache.clear()
        topicMetadataToRefresh.clear
        lastTopicMetadataRefreshTime = SystemTime.milliseconds
      }
      outstandingProduceRequests = dispatchSerializedData(outstandingProduceRequests)
      if (outstandingProduceRequests.size > 0) {
        info("Back off for %d ms before retrying send. Remaining retries = %d".format(config.retryBackoffMs, remainingRetries-1))
        //休眠时间，多长时间刷新一次
        Thread.sleep(config.retryBackoffMs)
        // 生产者定期请求刷新最新topics的broker元数据信息
        Utils.swallowError(brokerPartitionInfo.updateInfo(outstandingProduceRequests.map(_.topic).toSet, correlationId.getAndIncrement))
        .....
      }
    }
  }

 def updateInfo(topics: Set[String], correlationId: Int) {
    var topicsMetadata: Seq[TopicMetadata] = Nil
    //根据topics列表,meta.broker.list,其他配置参数,correlationId表示请求次数，一个计数器参数而已
    //创建一个topicMetadataRequest，并随机的选取传入的broker信息中任何一个去取metadata，直到取到为止
    val topicMetadataResponse = ClientUtils.fetchTopicMetadata(topics, brokers, producerConfig, correlationId)
    topicsMetadata = topicMetadataResponse.topicsMetadata
    // throw partition specific exception
    topicsMetadata.foreach(tmd =>{
      trace("Metadata for topic %s is %s".format(tmd.topic, tmd))
      if(tmd.errorCode == ErrorMapping.NoError) {
        topicPartitionInfo.put(tmd.topic, tmd)
      } else
        warn("Error while fetching metadata [%s] for topic [%s]: %s ".format(tmd, tmd.topic, ErrorMapping.exceptionFor(tmd.errorCode).getClass))
      tmd.partitionsMetadata.foreach(pmd =>{
        if (pmd.errorCode != ErrorMapping.NoError && pmd.errorCode == ErrorMapping.LeaderNotAvailableCode) {
          warn("Error while fetching metadata %s for topic partition [%s,%d]: [%s]".format(pmd, tmd.topic, pmd.partitionId,
            ErrorMapping.exceptionFor(pmd.errorCode).getClass))
        } // any other error code (e.g. ReplicaNotAvailable) can be ignored since the producer does not need to access the replica and isr metadata
      })
    })
    producerPool.updateProducer(topicsMetadata)
  }

def fetchTopicMetadata(topics: Set[String], brokers: Seq[Broker], producerConfig: ProducerConfig, correlationId: Int): TopicMetadataResponse = {
    var fetchMetaDataSucceeded: Boolean = false
    var i: Int = 0
    val topicMetadataRequest = new TopicMetadataRequest(TopicMetadataRequest.CurrentVersion, correlationId, producerConfig.clientId, topics.toSeq)
    var topicMetadataResponse: TopicMetadataResponse = null
    var t: Throwable = null
    val shuffledBrokers = Random.shuffle(brokers) //生成随机数
    while(i 
ProducerPool的updateProducer
def updateProducer(topicMetadata: Seq[TopicMetadata]) {
    val newBrokers = new collection.mutable.HashSet[Broker]
    topicMetadata.foreach(tmd => {
      tmd.partitionsMetadata.foreach(pmd => {
        if(pmd.leader.isDefined)
          newBrokers+=(pmd.leader.get)
      })
    })
    lock synchronized {
      newBrokers.foreach(b => {
        if(syncProducers.contains(b.id)){
          syncProducers(b.id).close()
          syncProducers.put(b.id, ProducerPool.createSyncProducer(config, b))
        } else
          syncProducers.put(b.id, ProducerPool.createSyncProducer(config, b))
      })
    }
  }