Spark Streaming Custom Receivers

Spark Streaming can receive streaming data from any arbitrary data source beyond the one’s for which it has in-built support (that is, beyond Flume, Kafka, Kinesis, files, sockets, etc.). This requires the developer to implement a receiver that is customized for receiving data from the concerned data source. This guide walks through the process of implementing a custom receiver and using it in a Spark Streaming application.

Implementing a Custom Receiver

This starts with implementing a Receiver. A custom receiver must extend this abstract class by implementing two methods - onStart(): Things to do to start receiving data. - onStop(): Things to do to stop receiving data.

Note that onStart() and onStop() must not block indefinitely. Typically, onStart() would start the threads that responsible for receiving the data and onStop() would ensure that the receiving by those threads are stopped. The receiving threads can also use isStopped(), a Receiver method, to check whether they should stop receiving data.

Once the data is received, that data can be stored inside Spark by calling store(data), which is a method provided by the Receiver class. There are number of flavours of store() which allow you store the received data record-at-a-time or as whole collection of objects / serialized bytes.

Any exception in the receiving threads should be caught and handled properly to avoid silent failures of the receiver. restart(<exception>) will restart the receiver by asynchronously calling onStop() and then calling onStart() after a delay. stop(<exception>) will call onStop() and terminate the receiver. Also, reportError(<error>) reports a error message to the driver (visible in the logs and UI) without stopping / restarting the receiver.

The following is a custom receiver that receives a stream of text over a socket. It treats ‘\n’ delimited lines in the text stream as records and stores them with Spark. If the receiving thread has any error connecting or receiving, the receiver is restarted to make another attempt to connect.

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() }
    }.start()
  }

  def onStop() {
   // There is nothing much to do as the thread calling receive()
   // is designed to stop by itself 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
     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()
     }
     reader.close()
     socket.close()

     // Restart in an attempt to connect again when server is active again
     restart("Trying to connect again")
    } 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)
    }
  }
}

public class JavaCustomReceiver extends Receiver<String> {

  String host = null;
  int port = -1;

  public JavaCustomReceiver(String host_ , int port_) {
    super(StorageLevel.MEMORY_AND_DISK_2());
    host = host_;
    port = port_;
  }

  public void onStart() {
    // Start the thread that receives data over a connection
    new Thread()  {
      @Override public void run() {
        receive();
      }
    }.start();
  }

  public void onStop() {
    // There is nothing much to do as the thread calling receive()
    // is designed to stop by itself isStopped() returns false
  }

  /** Create a socket connection and receive data until receiver is stopped */
  private void receive() {
    Socket socket = null;
    String userInput = null;

    try {
      // connect to the server
      socket = new Socket(host, port);

      BufferedReader reader = new BufferedReader(new InputStreamReader(socket.getInputStream()));

      // Until stopped or connection broken continue reading
      while (!isStopped() && (userInput = reader.readLine()) != null) {
        System.out.println("Received data '" + userInput + "'");
        store(userInput);
      }
      reader.close();
      socket.close();

      // Restart in an attempt to connect again when server is active again
      restart("Trying to connect again");
    } catch(ConnectException ce) {
      // restart if could not connect to server
      restart("Could not connect", ce);
    } catch(Throwable t) {
      // restart if there is any other error
      restart("Error receiving data", t);
    }
  }
}

Using the custom receiver in a Spark Streaming application

The custom receiver can be used in a Spark Streaming application by using streamingContext.receiverStream(<instance of custom receiver>). This will create input DStream using data received by the instance of custom receiver, as shown below

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

The full source code is in the example CustomReceiver.scala.

// Assuming ssc is the JavaStreamingContext
JavaDStream<String> customReceiverStream = ssc.receiverStream(new JavaCustomReceiver(host, port));
JavaDStream<String> words = lines.flatMap(new FlatMapFunction<String, String>() { ... });
...

The full source code is in the example JavaCustomReceiver.java.

Implementing and Using a Custom Actor-based Receiver

Custom Akka Actors can also be used to receive data. The ActorHelper trait can be applied on any Akka actor, which allows received data to be stored in Spark using store(...) methods. The supervisor strategy of this actor can be configured to handle failures, etc.

class CustomActor extends Actor with ActorHelper {
  def receive = {
   case data: String => store(data)
  }
}

And a new input stream can be created with this custom actor as

// Assuming ssc is the StreamingContext
val lines = ssc.actorStream[String](Props(new CustomActor()), "CustomReceiver")

See ActorWordCount.scala for an end-to-end example.