[SPARK-13888][DOC] Remove Akka Receiver doc and refer to the DStream Akka project

## What changes were proposed in this pull request?

I have copied the docs of Streaming Akka to https://github.com/spark-packages/dstream-akka/blob/master/README.md

So we can remove them from Spark now.

## How was this patch tested?

Only document changes.

(If this patch involves UI changes, please attach a screenshot; otherwise, remove this)

Author: Shixiong Zhu <shixiong@databricks.com>

Closes #11711 from zsxwing/remove-akka-doc.

1 files changed, 0 insertions, 61 deletions

diff --git a/docs/streaming-custom-receivers.md b/docs/streaming-custom-receivers.md
index 732c83dc84..a4e17fd24e 100644
--- a/docs/streaming-custom-receivers.md
+++ b/docs/streaming-custom-receivers.md
@@ -256,64 +256,3 @@ The following table summarizes the characteristics of both types of receivers
   <td></td>
 </tr>
 </table>
-
-## Implementing and Using a Custom Actor-based Receiver
-
-Custom [Akka Actors](http://doc.akka.io/docs/akka/2.3.11/scala/actors.html) can also be used to
-receive data. Here are the instructions.
-
-1. **Linking:** You need to add the following dependency to your SBT or Maven project (see [Linking section](streaming-programming-guide.html#linking) in the main programming guide for further information).
-
-		groupId = org.apache.spark
-		artifactId = spark-streaming-akka_{{site.SCALA_BINARY_VERSION}}
-		version = {{site.SPARK_VERSION_SHORT}}
-
-2. **Programming:**
-
-	<div class="codetabs">
-	<div data-lang="scala"  markdown="1" >
-
-	You need to extend [`ActorReceiver`](api/scala/index.html#org.apache.spark.streaming.akka.ActorReceiver)
-	so as to store received data into Spark using `store(...)` methods. The supervisor strategy of
-	this actor can be configured to handle failures, etc.
-
-		class CustomActor extends ActorReceiver {
-		  def receive = {
-		    case data: String => store(data)
-		  }
-		}
-
-		// A new input stream can be created with this custom actor as
-		val ssc: StreamingContext = ...
-		val lines = AkkaUtils.createStream[String](ssc, Props[CustomActor](), "CustomReceiver")
-
-	See [ActorWordCount.scala](https://github.com/apache/spark/blob/master/examples/src/main/scala/org/apache/spark/examples/streaming/ActorWordCount.scala) for an end-to-end example.
-	</div>
-	<div data-lang="java" markdown="1">
-
-	You need to extend [`JavaActorReceiver`](api/scala/index.html#org.apache.spark.streaming.akka.JavaActorReceiver)
-	so as to store received data into Spark using `store(...)` methods. The supervisor strategy of
-	this actor can be configured to handle failures, etc.
-
-		class CustomActor extends JavaActorReceiver {
-		  @Override
-		  public void onReceive(Object msg) throws Exception {
-		    store((String) msg);
-		  }
-		}
-
-		// A new input stream can be created with this custom actor as
-		JavaStreamingContext jssc = ...;
-		JavaDStream<String> lines = AkkaUtils.<String>createStream(jssc, Props.create(CustomActor.class), "CustomReceiver");
-
-	See [JavaActorWordCount.scala](https://github.com/apache/spark/blob/master/examples/src/main/scala/org/apache/spark/examples/streaming/JavaActorWordCount.scala) for an end-to-end example.
-	</div>
-	</div>
-
-3. **Deploying:** As with any Spark applications, `spark-submit` is used to launch your application.
-You need to package `spark-streaming-akka_{{site.SCALA_BINARY_VERSION}}` and its dependencies into
-the application JAR. Make sure `spark-core_{{site.SCALA_BINARY_VERSION}}` and `spark-streaming_{{site.SCALA_BINARY_VERSION}}`
-are marked as `provided` dependencies as those are already present in a Spark installation. Then
-use `spark-submit` to launch your application (see [Deploying section](streaming-programming-guide.html#deploying-applications) in the main programming guide).
-
-<span class="badge" style="background-color: grey">Python API</span> Since actors are available only in the Java and Scala libraries, AkkaUtils is not available in the Python API.