[SPARK-7799][SPARK-12786][STREAMING] Add "streaming-akka" project

Include the following changes:

1. Add "streaming-akka" project and org.apache.spark.streaming.akka.AkkaUtils for creating an actorStream
2. Remove "StreamingContext.actorStream" and "JavaStreamingContext.actorStream"
3. Update the ActorWordCount example and add the JavaActorWordCount example
4. Make "streaming-zeromq" depend on "streaming-akka" and update the codes accordingly

Author: Shixiong Zhu <shixiong@databricks.com>

Closes #10744 from zsxwing/streaming-akka-2.

1 files changed, 2 insertions, 2 deletions

diff --git a/docs/streaming-programming-guide.md b/docs/streaming-programming-guide.md
index 8fd075d02b..93c34efb66 100644
--- a/docs/streaming-programming-guide.md
+++ b/docs/streaming-programming-guide.md
@@ -659,11 +659,11 @@ methods for creating DStreams from files and Akka actors as input sources.
 	<span class="badge" style="background-color: grey">Python API</span> `fileStream` is not available in the Python API, only	`textFileStream` is	available.
 
 - **Streams based on Custom Actors:** DStreams can be created with data streams received through Akka
-  actors by using `streamingContext.actorStream(actorProps, actor-name)`. See the [Custom Receiver
+  actors by using `AkkaUtils.createStream(ssc, actorProps, actor-name)`. See the [Custom Receiver
   Guide](streaming-custom-receivers.html) for more details.
 
   <span class="badge" style="background-color: grey">Python API</span> Since actors are available only in the Java and Scala
-  libraries, `actorStream` is not available in the Python API.
+  libraries, `AkkaUtils.createStream` is not available in the Python API.
 
 - **Queue of RDDs as a Stream:** For testing a Spark Streaming application with test data, one can also create a DStream based on a queue of RDDs, using `streamingContext.queueStream(queueOfRDDs)`. Each RDD pushed into the queue will be treated as a batch of data in the DStream, and processed like a stream.