2 files changed, 41 insertions, 12 deletions
diff --git a/docs/streaming-custom-receivers.md b/docs/streaming-custom-receivers.md
index 97db865daa..95b99862ec 100644
--- a/docs/streaming-custom-receivers.md
+++ b/docs/streaming-custom-receivers.md
@@ -257,25 +257,54 @@ The following table summarizes the characteristics of both types of receivers
 
 ## Implementing and Using a Custom Actor-based Receiver
 
+<div class="codetabs">
+<div data-lang="scala"  markdown="1" >
+
 Custom [Akka Actors](http://doc.akka.io/docs/akka/2.3.11/scala/actors.html) can also be used to
-receive data. The [`ActorHelper`](api/scala/index.html#org.apache.spark.streaming.receiver.ActorHelper)
-trait can be mixed in to 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.
+receive data. Extending [`ActorReceiver`](api/scala/index.html#org.apache.spark.streaming.akka.ActorReceiver)
+allows received data to be stored in Spark using `store(...)` methods. The supervisor strategy of
+this actor can be configured to handle failures, etc.
 
 {% highlight scala %}
-class CustomActor extends Actor with ActorHelper {
+
+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")
+
 {% endhighlight %}
 
-And a new input stream can be created with this custom actor as
+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">
+
+Custom [Akka UntypedActors](http://doc.akka.io/docs/akka/2.3.11/java/untyped-actors.html) can also be used to
+receive data. Extending [`JavaActorReceiver`](api/scala/index.html#org.apache.spark.streaming.akka.JavaActorReceiver)
+allows received data to be stored in Spark using `store(...)` methods. The supervisor strategy of
+this actor can be configured to handle failures, etc.
+
+{% highlight java %}
+
+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");
 
-{% highlight scala %}
-val ssc: StreamingContext = ...
-val lines = ssc.actorStream[String](Props[CustomActor], "CustomReceiver")
 {% endhighlight %}
 
-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.
+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>
+
+<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.
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.