aboutsummaryrefslogtreecommitdiff
path: root/docs/streaming-programming-guide.md
diff options
context:
space:
mode:
authorShixiong Zhu <shixiong@databricks.com>2016-08-25 21:08:42 -0700
committerReynold Xin <rxin@databricks.com>2016-08-25 21:08:42 -0700
commit341e0e778dff8c404b47d34ee7661b658bb91880 (patch)
treeb5c796effe9dc99f20d9ee0970e532fb3431b172 /docs/streaming-programming-guide.md
parentb964a172a8c075486189cc9be09a51b8446f0da4 (diff)
downloadspark-341e0e778dff8c404b47d34ee7661b658bb91880.tar.gz
spark-341e0e778dff8c404b47d34ee7661b658bb91880.tar.bz2
spark-341e0e778dff8c404b47d34ee7661b658bb91880.zip
[SPARK-17242][DOCUMENT] Update links of external dstream projects
## What changes were proposed in this pull request? Updated links of external dstream projects. ## How was this patch tested? Just document changes. Author: Shixiong Zhu <shixiong@databricks.com> Closes #14814 from zsxwing/dstream-link.
Diffstat (limited to 'docs/streaming-programming-guide.md')
-rw-r--r--docs/streaming-programming-guide.md8
1 files changed, 2 insertions, 6 deletions
diff --git a/docs/streaming-programming-guide.md b/docs/streaming-programming-guide.md
index df94e9533e..82d36474ff 100644
--- a/docs/streaming-programming-guide.md
+++ b/docs/streaming-programming-guide.md
@@ -656,7 +656,7 @@ methods for creating DStreams from files 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 Receivers:** DStreams can be created with data streams received through custom receivers. See the [Custom Receiver
- Guide](streaming-custom-receivers.html) and [DStream Akka](https://github.com/spark-packages/dstream-akka) for more details.
+ Guide](streaming-custom-receivers.html) 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.
@@ -2383,11 +2383,7 @@ additional effort may be necessary to achieve exactly-once semantics. There are
- [Kafka Integration Guide](streaming-kafka-integration.html)
- [Kinesis Integration Guide](streaming-kinesis-integration.html)
- [Custom Receiver Guide](streaming-custom-receivers.html)
-* External DStream data sources:
- - [DStream MQTT](https://github.com/spark-packages/dstream-mqtt)
- - [DStream Twitter](https://github.com/spark-packages/dstream-twitter)
- - [DStream Akka](https://github.com/spark-packages/dstream-akka)
- - [DStream ZeroMQ](https://github.com/spark-packages/dstream-zeromq)
+* Third-party DStream data sources can be found in [Spark Packages](https://spark-packages.org/)
* API documentation
- Scala docs
* [StreamingContext](api/scala/index.html#org.apache.spark.streaming.StreamingContext) and