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From dbtsai <...@git.apache.org>
Subject [GitHub] spark pull request: SPARK-9926: Parallelize partition logic in Uni...
Date Mon, 21 Mar 2016 20:31:07 GMT
Github user dbtsai commented on a diff in the pull request:

    https://github.com/apache/spark/pull/11242#discussion_r56891305
  
    --- Diff: core/src/main/scala/org/apache/spark/rdd/UnionRDD.scala ---
    @@ -62,7 +64,23 @@ class UnionRDD[T: ClassTag](
         var rdds: Seq[RDD[T]])
       extends RDD[T](sc, Nil) {  // Nil since we implement getDependencies
     
    +  // Evaluate partitions in parallel. Partitions of each rdd will be cached by the `partitions`
    +  // val in `RDD`.
    +  private[spark] lazy val parallelPartitionEval: Boolean = {
    --- End diff --
    
    Then I think have `spark.rdd.enableParallelListing` default to `true`, and use the default
thread pool is a good idea. This requires the manual tuning compared with  `spark.rdd.parallelListingThreshold`,
and it's flexible enough to disable it. My 0.02 cents. Thanks.


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