spark git commit: [DOC] Minor modification to Streaming docs with regards to parallel data receiving

[sr...@apache.org]

Repository: spark
Updated Branches:
  refs/heads/master 3c0156899 -> e7c7e51f2


[DOC] Minor modification to Streaming docs with regards to parallel data receiving

pwendell tdas

Author: Nishkam Ravi <nr...@cloudera.com>
Author: nishkamravi2 <ni...@gmail.com>
Author: nravi <nr...@c1704.halxg.cloudera.com>

Closes #6544 from nishkamravi2/master_nravi and squashes the following commits:

46e8c03 [Nishkam Ravi] Slight modification to streaming docs


Project: http://git-wip-us.apache.org/repos/asf/spark/repo
Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/e7c7e51f
Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/e7c7e51f
Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/e7c7e51f

Branch: refs/heads/master
Commit: e7c7e51f2ec158d12a8429f753225c746f92d513
Parents: 3c01568
Author: Nishkam Ravi <nr...@cloudera.com>
Authored: Mon Jun 1 21:34:41 2015 +0100
Committer: Sean Owen <so...@cloudera.com>
Committed: Mon Jun 1 21:36:50 2015 +0100

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 docs/streaming-programming-guide.md | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)
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http://git-wip-us.apache.org/repos/asf/spark/blob/e7c7e51f/docs/streaming-programming-guide.md
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diff --git a/docs/streaming-programming-guide.md b/docs/streaming-programming-guide.md
index bd863d4..42b3394 100644
--- a/docs/streaming-programming-guide.md
+++ b/docs/streaming-programming-guide.md
@@ -1946,10 +1946,10 @@ creates a single receiver (running on a worker machine) that receives a single s
 Receiving multiple data streams can therefore be achieved by creating multiple input DStreams
 and configuring them to receive different partitions of the data stream from the source(s).
 For example, a single Kafka input DStream receiving two topics of data can be split into two
-Kafka input streams, each receiving only one topic. This would run two receivers on two workers,
-thus allowing data to be received in parallel, and increasing overall throughput. These multiple
-DStream can be unioned together to create a single DStream. Then the transformations that was
-being applied on the single input DStream can applied on the unified stream. This is done as follows.
+Kafka input streams, each receiving only one topic. This would run two receivers,
+allowing data to be received in parallel, and increasing overall throughput. These multiple
+DStreams can be unioned together to create a single DStream. Then the transformations that were
+being applied on a single input DStream can be applied on the unified stream. This is done as follows.
 
 <div class="codetabs">
 <div data-lang="scala" markdown="1">


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