org.apache.spark.streaming.receiver

ActorHelper

trait ActorHelper extends Logging

:: DeveloperApi :: A receiver trait to be mixed in with your Actor to gain access to the API for pushing received data into Spark Streaming for being processed.

Find more details at: http://spark.apache.org/docs/latest/streaming-custom-receivers.html

Self Type
ActorHelper with Actor
Annotations
@DeveloperApi()
Example: 

  1. class MyActor extends Actor with ActorHelper{
    def receive {
        case anything: String => store(anything)
    }
}

// Can be used with an actorStream as follows
ssc.actorStream[String](Props(new MyActor),"MyActorReceiver")
Note

Since Actor may exist outside the spark framework, It is thus user's responsibility to ensure the type safety, i.e parametrized type of push block and InputDStream should be same.

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  15. def log: Logger

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  16. def logDebug(msg: ⇒ String, throwable: Throwable): Unit

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  17. def logDebug(msg: ⇒ String): Unit

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  18. def logError(msg: ⇒ String, throwable: Throwable): Unit

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  19. def logError(msg: ⇒ String): Unit

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  20. def logInfo(msg: ⇒ String, throwable: Throwable): Unit

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  21. def logInfo(msg: ⇒ String): Unit

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  22. def logName: String

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  23. def logTrace(msg: ⇒ String, throwable: Throwable): Unit

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  24. def logTrace(msg: ⇒ String): Unit

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  25. def logWarning(msg: ⇒ String, throwable: Throwable): Unit

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  26. def logWarning(msg: ⇒ String): Unit

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  28. final def notify(): Unit

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  29. final def notifyAll(): Unit

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  30. def store[T](item: T): Unit

    Store a single item of received data to Spark's memory.

    Store a single item of received data to Spark's memory. These single items will be aggregated together into data blocks before being pushed into Spark's memory.

  31. def store(bytes: ByteBuffer): Unit

    Store the bytes of received data as a data block into Spark's memory.

    Store the bytes of received data as a data block into Spark's memory. Note that the data in the ByteBuffer must be serialized using the same serializer that Spark is configured to use.

  32. def store[T](iter: Iterator[T]): Unit

    Store an iterator of received data as a data block into Spark's memory.

  33. final def synchronized[T0](arg0: ⇒ T0): T0

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  34. def toString(): String

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  35. final def wait(): Unit

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