【Kafka源码】Kafka启动过程

一般来说，我们是通过命令来启动kafka，但是命令的本质还是调用代码中的main方法，所以，我们重点看下启动类Kafka。源码下下来之后，我们也可以通过直接运行Kafka.scala中的main方法（需要指定启动参数，也就是server.properties的位置）来启动Kafka。因为kafka依赖zookeeper，所以我们需要提前启动zookeeper，然后在server.properties中指定zk地址后，启动。

下面我们首先看一下main()方法：

  def main(args: Array[String]): Unit = {
    try {
      val serverProps = getPropsFromArgs(args)
      val kafkaServerStartable = KafkaServerStartable.fromProps(serverProps)

      // attach shutdown handler to catch control-c
      Runtime.getRuntime().addShutdownHook(new Thread() {
        override def run() = {
          kafkaServerStartable.shutdown
        }
      })

      kafkaServerStartable.startup
      kafkaServerStartable.awaitShutdown
    }
    catch {
      case e: Throwable =>
        fatal(e)
        System.exit(1)
    }
    System.exit(0)
  }

我们慢慢来分析下，首先是getPropsFromArgs(args)，这一行很明确，就是从配置文件中读取我们配置的内容，然后赋值给serverProps。第二步，KafkaServerStartable.fromProps(serverProps)，

object KafkaServerStartable {
  def fromProps(serverProps: Properties) = {
    KafkaMetricsReporter.startReporters(new VerifiableProperties(serverProps))
    new KafkaServerStartable(KafkaConfig.fromProps(serverProps))
  }
}

这块主要是启动了一个内部的监控服务（内部状态监控）。

下面是一个在java中常见的钩子函数，在关闭时会启动一些销毁程序，保证程序安全关闭。之后就是我们启动的重头戏了：kafkaServerStartable.startup。跟进去可以很清楚的看到，里面调用的方法是KafkaServer中的startup方法，下面我们重点看下这个方法(比较长)：

def startup() {
    try {
      info("starting")

      if(isShuttingDown.get)
        throw new IllegalStateException("Kafka server is still shutting down, cannot re-start!")

      if(startupComplete.get)
        return

      val canStartup = isStartingUp.compareAndSet(false, true)
      if (canStartup) {
        metrics = new Metrics(metricConfig, reporters, kafkaMetricsTime, true)

        brokerState.newState(Starting)

        /* start scheduler */
        kafkaScheduler.startup()

        /* setup zookeeper */
        zkUtils = initZk()

        /* start log manager */
        logManager = createLogManager(zkUtils.zkClient, brokerState)
        logManager.startup()

        /* generate brokerId */
        config.brokerId =  getBrokerId
        this.logIdent = "[Kafka Server " + config.brokerId + "], "

        socketServer = new SocketServer(config, metrics, kafkaMetricsTime)
        socketServer.startup()

        /* start replica manager */
        replicaManager = new ReplicaManager(config, metrics, time, kafkaMetricsTime, zkUtils, kafkaScheduler, logManager,
          isShuttingDown)
        replicaManager.startup()

        /* start kafka controller */
        kafkaController = new KafkaController(config, zkUtils, brokerState, kafkaMetricsTime, metrics, threadNamePrefix)
        kafkaController.startup()

        /* start group coordinator */
        groupCoordinator = GroupCoordinator(config, zkUtils, replicaManager, kafkaMetricsTime)
        groupCoordinator.startup()

        /* Get the authorizer and initialize it if one is specified.*/
        authorizer = Option(config.authorizerClassName).filter(_.nonEmpty).map { authorizerClassName =>
          val authZ = CoreUtils.createObject[Authorizer](authorizerClassName)
          authZ.configure(config.originals())
          authZ
        }

        /* start processing requests */
        apis = new KafkaApis(socketServer.requestChannel, replicaManager, groupCoordinator,
          kafkaController, zkUtils, config.brokerId, config, metadataCache, metrics, authorizer)
        requestHandlerPool = new KafkaRequestHandlerPool(config.brokerId, socketServer.requestChannel, apis, config.numIoThreads)
        brokerState.newState(RunningAsBroker)

        Mx4jLoader.maybeLoad()

        /* start dynamic config manager */
        dynamicConfigHandlers = Map[String, ConfigHandler](ConfigType.Topic -> new TopicConfigHandler(logManager, config),
                                                           ConfigType.Client -> new ClientIdConfigHandler(apis.quotaManagers))

        // Apply all existing client configs to the ClientIdConfigHandler to bootstrap the overrides
        // TODO: Move this logic to DynamicConfigManager
        AdminUtils.fetchAllEntityConfigs(zkUtils, ConfigType.Client).foreach {
          case (clientId, properties) => dynamicConfigHandlers(ConfigType.Client).processConfigChanges(clientId, properties)
        }

        // Create the config manager. start listening to notifications
        dynamicConfigManager = new DynamicConfigManager(zkUtils, dynamicConfigHandlers)
        dynamicConfigManager.startup()

        /* tell everyone we are alive */
        val listeners = config.advertisedListeners.map {case(protocol, endpoint) =>
          if (endpoint.port == 0)
            (protocol, EndPoint(endpoint.host, socketServer.boundPort(protocol), endpoint.protocolType))
          else
            (protocol, endpoint)
        }
        kafkaHealthcheck = new KafkaHealthcheck(config.brokerId, listeners, zkUtils, config.rack,
          config.interBrokerProtocolVersion)
        kafkaHealthcheck.startup()

        // Now that the broker id is successfully registered via KafkaHealthcheck, checkpoint it
        checkpointBrokerId(config.brokerId)

        /* register broker metrics */
        registerStats()

        shutdownLatch = new CountDownLatch(1)
        startupComplete.set(true)
        isStartingUp.set(false)
        AppInfoParser.registerAppInfo(jmxPrefix, config.brokerId.toString)
        info("started")
      }
    }
    catch {
      case e: Throwable =>
        fatal("Fatal error during KafkaServer startup. Prepare to shutdown", e)
        isStartingUp.set(false)
        shutdown()
        throw e
    }
  }

首先判断是否目前正在关闭中或者已经启动了，这两种情况直接抛出异常。然后是一个CAS的操作isStartingUp，防止线程并发操作启动，判断是否可以启动。如果可以启动，就开始我们的启动过程。

• 构造Metrics类
• 定义broker状态为启动中starting
• 启动定时器kafkaScheduler.startup()
• 构造zkUtils：利用参数中的zk信息，启动一个zk客户端
• 启动文件管理器：读取zk中的配置信息，包含__consumer_offsets和__system.topic__。重点是启动一些定时任务，来删除符合条件的记录(cleanupLogs)，清理脏记录(flushDirtyLogs)，把所有记录写到一个文本文件中，防止在启动时重启所有的记录文件(checkpointRecoveryPointOffsets)。

  /**
   *  Start the background threads to flush logs and do log cleanup
   */
  def startup() {
    /* Schedule the cleanup task to delete old logs */
    if(scheduler != null) {
      info("Starting log cleanup with a period of %d ms.".format(retentionCheckMs))
      scheduler.schedule("kafka-log-retention", 
                         cleanupLogs, 
                         delay = InitialTaskDelayMs, 
                         period = retentionCheckMs, 
                         TimeUnit.MILLISECONDS)
      info("Starting log flusher with a default period of %d ms.".format(flushCheckMs))
      scheduler.schedule("kafka-log-flusher", 
                         flushDirtyLogs, 
                         delay = InitialTaskDelayMs, 
                         period = flushCheckMs, 
                         TimeUnit.MILLISECONDS)
      scheduler.schedule("kafka-recovery-point-checkpoint",
                         checkpointRecoveryPointOffsets,
                         delay = InitialTaskDelayMs,
                         period = flushCheckpointMs,
                         TimeUnit.MILLISECONDS)
    }
    if(cleanerConfig.enableCleaner)
      cleaner.startup()
  }

• 下一步，获取brokerId
• 启动一个NIO socket服务
• 启动复制管理器：启动ISR超时处理线程
• 启动kafka控制器：注册session过期监听器，同时启动控制器leader选举
• 启动协调器
• 权限认证
• 开启线程，开始处理请求
• 开启配置监听，主要是监听zk节点数据变化，然后广播到所有机器
• 开启健康检查：目前只是把broker节点注册到zk上，注册成功就是活的，否则就是dead
• 注册启动数据信息
• 启动成功
• 等待关闭countDownLatch，如果shutdownLatch变为0，则关闭Kafka