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| -rw-r--r-- | docs/streaming-programming-guide.md | 8 |
1 files changed, 4 insertions, 4 deletions
diff --git a/docs/streaming-programming-guide.md b/docs/streaming-programming-guide.md index bd863d48d5..42b3394787 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"> |