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Diffstat (limited to 'docs/streaming-programming-guide.md')
| -rw-r--r-- | docs/streaming-programming-guide.md | 4 |
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. |