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From srowen <>
Subject [GitHub] spark pull request: [SPARK-14475] Propagate user-defined context f...
Date Fri, 08 Apr 2016 19:35:51 GMT
Github user srowen commented on a diff in the pull request:
    --- Diff: core/src/main/scala/org/apache/spark/scheduler/ShuffleMapTask.scala ---
    @@ -42,20 +43,22 @@ import org.apache.spark.shuffle.ShuffleWriter
      * @param _initialAccums initial set of accumulators to be used in this task for tracking
      *                       internal metrics. Other accumulators will be registered later
      *                       they are deserialized on the executors.
    + * @param localProperties copy of thread-local properties set by the user on the driver
     private[spark] class ShuffleMapTask(
         stageId: Int,
         stageAttemptId: Int,
         taskBinary: Broadcast[Array[Byte]],
         partition: Partition,
         @transient private var locs: Seq[TaskLocation],
    -    _initialAccums: Seq[Accumulator[_]])
    -  extends Task[MapStatus](stageId, stageAttemptId, partition.index, _initialAccums)
    +    _initialAccums: Seq[Accumulator[_]],
    +    localProperties: Properties)
    +  extends Task[MapStatus](stageId, stageAttemptId, partition.index, _initialAccums, localProperties)
       with Logging {
       /** A constructor used only in test suites. This does not require passing in an RDD.
       def this(partitionId: Int) {
    -    this(0, 0, null, new Partition { override def index: Int = 0 }, null, null)
    +    this(0, 0, null, new Partition { override def index: Int = 0 }, null, null, new Properties)
    --- End diff --
    Fair enough, I suppose allocating the empty map/properties object isn't that expensive.

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