Merge pull request #701 from ScrapCodes/documentation-suggestions

Documentation suggestions for spark streaming.

docs/streaming-custom-receivers.md

@@ -7,10 +7,45 @@ A "Spark Streaming" receiver can be a simple network stream, streams of messages
 
 This guide shows the programming model and features by walking through a simple sample receiver and corresponding Spark Streaming application.
 
+### Write a simple receiver
 
-## A quick and naive walk-through
+This starts with implementing [NetworkReceiver](#References)
 
-### Write a simple receiver
+Following is a simple socket text-stream receiver.
+
+{% highlight scala %}
+
+       class SocketTextStreamReceiver(host: String,
+                                      port: Int
+                                       ) extends NetworkReceiver[String] {
+
+         protected lazy val blocksGenerator: BlockGenerator =
+           new BlockGenerator(StorageLevel.MEMORY_ONLY_SER_2)
+
+         protected def onStart() = {
+           blocksGenerator.start()
+           val socket = new Socket(host, port)
+           val dataInputStream = new BufferedReader(new InputStreamReader(socket.getInputStream(), "UTF-8"))
+           var data: String = dataInputStream.readLine()
+           while (data != null) {
+             blocksGenerator += data
+             data = dataInputStream.readLine()
+           }
+         }
+
+         protected def onStop() {
+           blocksGenerator.stop()
+         }
+
+       }
+
+{% endhighlight %}
+
+
+All we did here is extended NetworkReceiver and called blockGenerator's API method (i.e. +=) to push our blocks of data. Please refer to scala-docs of NetworkReceiver for more details.
+
+
+### An Actor as Receiver.
 
 This starts with implementing [Actor](#References)
 
@@ -46,7 +81,16 @@ All we did here is mixed in trait Receiver and called pushBlock api method to pu
 
 {% endhighlight %}
 
-* Plug-in the actor configuration into the spark streaming context and create a DStream.
+* Plug-in the custom receiver into the spark streaming context and create a DStream.
+
+{% highlight scala %}
+
+    val lines = ssc.networkStream[String](new SocketTextStreamReceiver(
+      "localhost", 8445))
+
+{% endhighlight %}
+
+* OR Plug-in the actor as receiver into the spark streaming context and create a DStream.
 
 {% highlight scala %}
 
@@ -99,3 +143,4 @@ _A more comprehensive example is provided in the spark streaming examples_
 ## References
 
 1.[Akka Actor documentation](http://doc.akka.io/docs/akka/2.0.5/scala/actors.html)
+2.[NetworkReceiver](http://spark-project.org/docs/latest/api/streaming/index.html#spark.streaming.dstream.NetworkReceiver)

docs/streaming-programming-guide.md

@@ -301,6 +301,9 @@ dstream.checkpoint(checkpointInterval) // checkpointInterval must be a multiple
 For DStreams that must be checkpointed (that is, DStreams created by `updateStateByKey` and `reduceByKeyAndWindow` with inverse function), the checkpoint interval of the DStream is by default set to a multiple of the DStream's sliding interval such that its at least 10 seconds.
 
 
+## Customizing Receiver
+Spark comes with a built in support for most common usage scenarios where input stream source can be either a network socket stream to support for a few message queues. Apart from that it is also possible to supply your own custom receiver via a convenient API. Find more details at [Custom Receiver Guide](streaming-custom-receivers.html)
+
 # Performance Tuning
 Getting the best performance of a Spark Streaming application on a cluster requires a bit of tuning. This section explains a number of the parameters and configurations that can tuned to improve the performance of you application. At a high level, you need to consider two things:
 <ol>

streaming/src/main/scala/spark/streaming/StreamingContext.scala

@@ -183,6 +183,7 @@ class StreamingContext private (
 
   /**
    * Create an input stream with any arbitrary user implemented network receiver.
+   * Find more details at: http://spark-project.org/docs/latest/streaming-custom-receivers.html
    * @param receiver Custom implementation of NetworkReceiver
    */
   def networkStream[T: ClassManifest](
@@ -195,6 +196,7 @@ class StreamingContext private (
 
   /**
    * Create an input stream with any arbitrary user implemented actor receiver.
+   * Find more details at: http://spark-project.org/docs/latest/streaming-custom-receivers.html
    * @param props Props object defining creation of the actor
    * @param name Name of the actor
    * @param storageLevel RDD storage level. Defaults to memory-only.

streaming/src/main/scala/spark/streaming/dstream/NetworkInputDStream.scala

@@ -145,8 +145,8 @@ abstract class NetworkReceiver[T: ClassManifest]() extends Serializable with Log
   }
 
   /**
-   * Stops the receiver and reports to exception to the tracker.
-   * This should be called whenever an exception has happened on any thread
+   * Stops the receiver and reports exception to the tracker.
+   * This should be called whenever an exception is to be handled on any thread
    * of the receiver.
    */
   protected def stopOnError(e: Exception) {
@@ -202,7 +202,7 @@ abstract class NetworkReceiver[T: ClassManifest]() extends Serializable with Log
   }
 
   /**
-   * Batches objects created by a [[spark.streaming.NetworkReceiver]] and puts them into
+   * Batches objects created by a [[spark.streaming.dstream.NetworkReceiver]] and puts them into
    * appropriately named blocks at regular intervals. This class starts two threads,
    * one to periodically start a new batch and prepare the previous batch of as a block,
    * the other to push the blocks into the block manager.

streaming/src/main/scala/spark/streaming/receivers/ActorReceiver.scala

@@ -45,6 +45,8 @@ object ReceiverSupervisorStrategy {
  * A receiver trait to be mixed in with your Actor to gain access to
  * pushBlock API.
  *
+ * Find more details at: http://spark-project.org/docs/latest/streaming-custom-receivers.html
+ * 
  * @example {{{
  * 	class MyActor extends Actor with Receiver{
  * 		def receive {