Spark Streaming自定义Receivers

自定义一个Receiver

 class SocketTextStreamReceiver(host: String, port: Int(
         extends NetworkReceiver[String]
       {
         protected lazy val blocksGenerator: BlockGenerator =
           new BlockGenerator(StorageLevel.MEMORY_ONLY_SER_2)

         protected def onStart() = {
           blocksGenerator.start()
           val socket = new Socket(host, port)
           val dataInputStream = new BufferedReader(new InputStreamReader(socket.getInputStream(), "UTF-8"))
           var data: String = dataInputStream.readLine()
           while (data != null) {
             blocksGenerator += data
             data = dataInputStream.readLine()
           }
         }

         protected def onStop() {
           blocksGenerator.stop()
         }
       }

An Actor as Receiver

 class SocketTextStreamReceiver (host:String,
         port:Int,
         bytesToString: ByteString => String) extends Actor with Receiver {

          override def preStart = IOManager(context.system).connect(host, port)

          def receive = {
           case IO.Read(socket, bytes) => pushBlock(bytesToString(bytes))
         }

       }

A Sample Spark Application

  val ssc = new StreamingContext(master, "WordCountCustomStreamSource",
      Seconds(batchDuration))
  //使用自定义的receiver
  val lines = ssc.networkStream[String](new SocketTextStreamReceiver(
      "localhost", 8445))

  //或者使用这个自定义的actor Receiver
  val lines2 = ssc.actorStream[String](Props(new SocketTextStreamReceiver(
      "localhost",8445, z => z.utf8String)),"SocketReceiver") */

提交成功之后，启动Netcat测试一下

$ nc -l localhost 8445 hello world hello hello

下面是合并多个输入流的方法：

  val lines = ssc.actorStream[String](Props(new SocketTextStreamReceiver(
      "localhost",8445, z => z.utf8String)),"SocketReceiver")

  // Another socket stream receiver
  val lines2 = ssc.actorStream[String](Props(new SocketTextStreamReceiver(
      "localhost",8446, z => z.utf8String)),"SocketReceiver")

  val union = lines.union(lines2)