We are building a wrapper that makes it possible to use reactive streams
(i.e. Observable, see reactivex.io) as input to Spark Streaming. We
therefore tried to create a custom receiver for Spark. However, the
Observable lives at the driver program and is generally not serializable.

Is it possible to create a receiver that runs next to the driver program
and therefore does not need to be serialized?

---

We tried the following, which gives a `NotSerializableException`:



object Main {
  def main(args: Array[String]): Unit = {
    val conf = new SparkConf().setMaster("local[2]").setAppName("Clock")
    val ssc = new StreamingContext(conf, Seconds(1))

    val data = // A non-serializable stream of data
    val stream = RxcreateStream(ssc, data)

        // Mapping, filtering, etc

        ssc.start()
        ssc.awaitTermination()
      }
    }

with the createStream method something like the following:

    object RxUtils {
      def createStream[T: ClassTag](scc_ : StreamingContext, observable:
Observable[T]): ReceiverInputDStream[T] = {
        new RxInputDStream[T](scc_, observable,
StorageLevel.MEMORY_AND_DISK_SER_2)
      }
    }

    class RxInputDStream[T: ClassTag](ssc_ : StreamingContext, observable:
Observable[T], storageLevel: StorageLevel) extends
ReceiverInputDStream[T](ssc_)  {
      override def getReceiver(): Receiver[T] = {
        new RxReceiver(observable, storageLevel)
      }
    }

    class RxReceiver[T](observable: Observable[T], storageLevel:
StorageLevel) extends Receiver[T](storageLevel) with Logging {
      var subscription: Option[Subscription] = None

      override def onStart(): Unit = {
        // NOTE: 'observable' is a reference to a variable in the driver
program
        subscription = Some(
          observable
            .asInstanceOf[Observable[T]]
            .subscribe(x => store(x))
        )
      }
    }

the comment indicates what causes the `NotSerializableException`.




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