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Posted to reviews@spark.apache.org by CrazyJvm <gi...@git.apache.org> on 2014/05/14 09:47:44 UTC

[GitHub] spark pull request: default task number misleading in several plac...

GitHub user CrazyJvm opened a pull request:

    https://github.com/apache/spark/pull/766

    default task number misleading in several places

      private[streaming] def defaultPartitioner(numPartitions: Int = self.ssc.sc.defaultParallelism){
        new HashPartitioner(numPartitions)
      }
    
    it represents that the default task number in Spark Streaming relies on the variable defaultParallelism in SparkContext, which is decided by the config property spark.default.parallelism
    
    the property "spark.default.parallelism" refers to https://github.com/apache/spark/pull/389

You can merge this pull request into a Git repository by running:

    $ git pull https://github.com/CrazyJvm/spark patch-7

Alternatively you can review and apply these changes as the patch at:

    https://github.com/apache/spark/pull/766.patch

To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:

    This closes #766
    
----
commit cc5b66c1883eca8862b8f37ef50d64cc0408c54c
Author: Chen Chao <cr...@gmail.com>
Date:   2014-05-14T07:45:10Z

    default task number misleading in several places 
    
    <code>
      private[streaming] def defaultPartitioner(numPartitions: Int = self.ssc.sc.defaultParallelism){
        new HashPartitioner(numPartitions)
      }
    </code>
    
    it represents that the default task number in Spark Streaming relies on the variable defaultParallelism in SparkContext, which is decided by the config property spark.default.parallelism
    
    the property "spark.default.parallelism" refers to https://github.com/apache/spark/pull/389

----


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[GitHub] spark pull request: default task number misleading in several plac...

Posted by rxin <gi...@git.apache.org>.

Github user rxin commented on a diff in the pull request:

    https://github.com/apache/spark/pull/766#discussion_r12655504
  
    --- Diff: docs/streaming-programming-guide.md ---
    @@ -956,9 +957,10 @@ before further processing.
     ### Level of Parallelism in Data Processing
     Cluster resources maybe under-utilized if the number of parallel tasks used in any stage of the
     computation is not high enough. For example, for distributed reduce operations like `reduceByKey`
    -and `reduceByKeyAndWindow`, the default number of parallel tasks is 8. You can pass the level of
    -parallelism as an argument (see the
    -[`PairDStreamFunctions`](api/scala/index.html#org.apache.spark.streaming.dstream.PairDStreamFunctions)
    +and `reduceByKeyAndWindow`, the default number of parallel tasks is decided by the [config property]
    +(configuration.html#spark-properties) `spark.default.parallelism`. You can pass the level of
    +parallelism as an argument (see the [`PairDStreamFunctions`]
    --- End diff --
    
    remove the "the" before [`PairDStreamFunctions`]


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