Kafka-服务端-网络层-源码流程

整体架构如下所示：

responseQueue不在RequestChannel中，在Processor中，每个Processor内部有一个responseQueue

客户端发送的请求被Acceptor转发给Processor处理
处理器将请求放到RequestChannel的requestQueue中
KafkaRequestHandler取出requestQueue中的请求
调用KafkaApis进行业务逻辑处理
KafkaApis将响应结果放到对应的Processor的responseQueue中
processor从responseQueue中取出响应结果
processor将响应结果返回给客户端

KafkaServer是Kafka服务端的主类，KafkaServer中和网络成相关的服务组件包括SocketServer、KafkaApis和KafkaRequestHandlerPool。SocketServer主要关注网络层的通信协议，具体的业务处理逻辑则交给KafkaRequestHandler和KafkaApis来完成。

scala 复制代码

class KafkaServer(val config: KafkaConfig) {
       def startup() {
       	socketServer = new SocketServer(config, metrics, time, credentialProvider)
        socketServer.startup(startupProcessors = false)
                /* start processing requests */
        apis = new KafkaApis(socketServer.requestChannel, ...)
        requestHandlerPool = new KafkaRequestHandlerPool(config.brokerId, ...)
          }
     }

SocketServer

scala 复制代码

  def startup(startupProcessors: Boolean = true) {
    this.synchronized {
      ...
      createAcceptorAndProcessors(config.numNetworkThreads, config.listeners)
      if (startupProcessors) {
        startProcessors()
      }
    }
      
  private def createAcceptorAndProcessors(processorsPerListener: Int,
                                          endpoints: Seq[EndPoint]): Unit = synchronized {
	...
    endpoints.foreach { endpoint =>
	  ...
      val acceptor = new Acceptor(endpoint, ...)
      addProcessors(acceptor, endpoint, processorsPerListener)
      KafkaThread.nonDaemon(s"kafka-socket-acceptor-$listenerName-$securityProtocol-${endpoint.port}", acceptor).start()
      acceptor.awaitStartup()
      acceptors.put(endpoint, acceptor)
    }
  }

可以看出SocketServer.startup()中会根据listener的个数创建相同个数的acceptor，每个acceptor关联数个processor。这是一种典型的Reactor模式，acceptor负责与客户端建立连接，并将连接分发给processor，processor负责所分连接后续的所有读写交互。

Acceptor

scala 复制代码

  def run() {
    serverChannel.register(nioSelector, SelectionKey.OP_ACCEPT)
    startupComplete()
    try {
      var currentProcessor = 0
      while (isRunning) {
        try {
          val ready = nioSelector.select(500)
          if (ready > 0) {
            val keys = nioSelector.selectedKeys()
            val iter = keys.iterator()
            while (iter.hasNext && isRunning) {
              try {
                val key = iter.next
                iter.remove()
                if (key.isAcceptable) {
                  val processor = synchronized {
                    currentProcessor = currentProcessor % processors.size
                    processors(currentProcessor)
                  }
                  accept(key, processor)
                } else
                  throw new IllegalStateException("Unrecognized key state for acceptor thread.")

                // round robin to the next processor thread, mod(numProcessors) will be done later
                currentProcessor = currentProcessor + 1
              } catch {
                case e: Throwable => error("Error while accepting connection", e)
              }
            }
          }
        }
        catch {
          // We catch all the throwables to prevent the acceptor thread from exiting on exceptions due
          // to a select operation on a specific channel or a bad request. We don't want
          // the broker to stop responding to requests from other clients in these scenarios.
          case e: ControlThrowable => throw e
          case e: Throwable => error("Error occurred", e)
        }
      }
    } finally {
      debug("Closing server socket and selector.")
      CoreUtils.swallow(serverChannel.close(), this, Level.ERROR)
      CoreUtils.swallow(nioSelector.close(), this, Level.ERROR)
      shutdownComplete()
    }
  }

上面是Acceptor的run()方法，可以看出，Acceptor在通道上注册了SelectionKey.OP_ACCEPT事件（OP_READ、OP_WRITE、OP_CONNECT、OP_ACCEPT，客户端监听OP_CONNECT事件，负责发起连接，服务端监听OP_CONNECT事件，负责建立连接），负责与客户端建立连接。并将建立的连接通过轮询的方式指派给processor。

Processor

每个Processor都会分到数个与客户端的连接。Processor的处理逻辑如下所示：

scala 复制代码

  override def run() {
    startupComplete()
    try {
      while (isRunning) {
        try {
          // 在新分到的客户端连接上注册OP_READ事件
          configureNewConnections()
          // 从responseQueue中取响应，赋值给KafkaChannel的send，等待poll时发送
          processNewResponses()
          // selector轮询各种事件，读取请求或者发送响应
          poll()
          // 封装selector.completedReceives中的请求，放入requestQueue
          processCompletedReceives()
          // 处理selector.completedSends响应（移除inflightResponses中的记录；执行响应的回调函数）
          processCompletedSends()
          processDisconnected()
        } catch {
          ...
        }
      }
    } finally {
      ...
    }
  }

Processor线程的名字中有kafka-network字样，可以通过jstack -l pid | grep kafka-network进行筛选。

KafkaRequestHandlerPool

KafkaServer会创建请求处理线程池（KafkaRequestHandlerPool），在请求处理线程池中会创建并启动多个请求处理线程（KafkaRequestHandler）。KafkaRequestHandler会获取RequestChannel.requestQueue中的请求进行处理，在内部实际处理会交给KafkaApis完成。

scala 复制代码

class KafkaRequestHandlerPool(val brokerId: Int, ...) {
  ...
  for (i <- 0 until numThreads) {
    createHandler(i)
  }

  def createHandler(id: Int): Unit = synchronized {
    runnables += new KafkaRequestHandler(..., requestChannel, apis, time)
    KafkaThread.daemon("kafka-request-handler-" + id, runnables(id)).start()
  }
}

KafkaRequestHandler的run()方法如下：

scala 复制代码

class KafkaRequestHandler(id: Int,...) extends Runnable with Logging {
  ...
  def run() {
    while (!stopped) {

      val req = requestChannel.receiveRequest(300)

      req match {
        case RequestChannel.ShutdownRequest =>
          shutdownComplete.countDown()
          return

        case request: RequestChannel.Request =>
          try {
            request.requestDequeueTimeNanos = endTime
            apis.handle(request)
          } catch {
            case e: FatalExitError =>
              shutdownComplete.countDown()
              Exit.exit(e.statusCode)
            case e: Throwable => error("Exception when handling request", e)
          } finally {
            request.releaseBuffer()
          }

        case null => // continue
      }
    }
    shutdownComplete.countDown()
  }

}