第102讲： 动手实战Spark Streaming自定义Receiver并进行调试和测试

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1：SparkStreaming虽然说已经支持了很多不同类型的数据来源。但是有时候可能我们的一些数据来源非常特殊 ，不是它天然默认支持的，这时候就要自定义Receiver。而自定义Receiver，一般都是基于网络的方式。因为你传数据的话，一般是从另外一个网络端口传过来，至于传的协议是另外一码事。

2：从本质上来说，SparkStreaming中的所有Receiver，都是自定义的Receiver。所以你要想自定义一个Receiver，最最简单的方式，你就是看下已有的Receiver怎么去实现。

具体步骤：http://spark.apache.org/docs/latest/streaming-custom-receivers.html

class CustomReceiver(host: String, port: Int)  extends Receiver[String](StorageLevel.MEMORY_AND_DISK_2) with Logging {  def onStart() {    // Start the thread that receives data over a connection    new Thread("Socket Receiver") {      override def run() { receive() }//开启线程调receiver()方法    }.start()  }  def onStop() {   // There is nothing much to do as the thread calling receive()   // is designed to stop by itself if isStopped() returns false  }  /** Create a socket connection and receive data until receiver is stopped */  private def receive() {    var socket: Socket = null    var userInput: String = null    try {     // Connect to host:port，Receiver的时候就连上Socket     socket = new Socket(host, port)     // Until stopped or connection broken continue reading     val reader = new BufferedReader(new InputStreamReader(socket.getInputStream(), "UTF-8"))     userInput = reader.readLine()     while(!isStopped && userInput != null) {       store(userInput)       userInput = reader.readLine()//每读一行，存一次，一直循环     }     reader.close()     socket.close()     // Restart in an attempt to connect again when server is active again     restart("Trying to connect again")//先stop，然后再start()    } catch {     case e: java.net.ConnectException =>       // restart if could not connect to server       restart("Error connecting to " + host + ":" + port, e)     case t: Throwable =>       // restart if there is any other error       restart("Error receiving data", t)    }  }}

上面就已经自定义完了一个Receiver，下面就new出它的对象，传进去。因为返回的是Dstream，以前对Dstream怎么操作，继续怎么操作，这里先从flatMap开始。

// Assuming ssc is the StreamingContextval customReceiverStream = ssc.receiverStream(new CustomReceiver(host, port))val words = lines.flatMap(_.split(" "))...