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Diffstat (limited to 'docs')
| -rw-r--r-- | docs/streaming-programming-guide.md | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/docs/streaming-programming-guide.md b/docs/streaming-programming-guide.md index 5c21e912ea..738309c668 100644 --- a/docs/streaming-programming-guide.md +++ b/docs/streaming-programming-guide.md @@ -494,7 +494,7 @@ methods for creating DStreams from files and Akka actors as input sources. For simple text files, there is an easier method `streamingContext.textFileStream(dataDirectory)`. And file streams do not require running a receiver, hence does not require allocating cores. -- **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 Guide](#implementing-and-using-a-custom-actor-based-receiver) for more details. +- **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 Guide](streaming-custom-receivers.html#implementing-and-using-a-custom-actor-based-receiver) for more details. - **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. |