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Posted to commits@spark.apache.org by rx...@apache.org on 2016/08/26 04:08:45 UTC
spark git commit: [SPARK-17242][DOCUMENT] Update links of external
dstream projects
Repository: spark
Updated Branches:
refs/heads/master b964a172a -> 341e0e778
[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 <sh...@databricks.com>
Closes #14814 from zsxwing/dstream-link.
Project: http://git-wip-us.apache.org/repos/asf/spark/repo
Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/341e0e77
Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/341e0e77
Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/341e0e77
Branch: refs/heads/master
Commit: 341e0e778dff8c404b47d34ee7661b658bb91880
Parents: b964a17
Author: Shixiong Zhu <sh...@databricks.com>
Authored: Thu Aug 25 21:08:42 2016 -0700
Committer: Reynold Xin <rx...@databricks.com>
Committed: Thu Aug 25 21:08:42 2016 -0700
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docs/streaming-programming-guide.md | 8 ++------
1 file changed, 2 insertions(+), 6 deletions(-)
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http://git-wip-us.apache.org/repos/asf/spark/blob/341e0e77/docs/streaming-programming-guide.md
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diff --git a/docs/streaming-programming-guide.md b/docs/streaming-programming-guide.md
index df94e95..82d3647 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
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