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From mridulm <...@git.apache.org>
Subject [GitHub] spark pull request: fix #SPARK-1149 Bad partitioners can cause Spa...
Date Tue, 04 Mar 2014 04:07:01 GMT
Github user mridulm commented on a diff in the pull request:

    https://github.com/apache/spark/pull/44#discussion_r10242223
  
    --- Diff: core/src/main/scala/org/apache/spark/SparkContext.scala ---
    @@ -847,6 +847,8 @@ class SparkContext(
           partitions: Seq[Int],
           allowLocal: Boolean,
           resultHandler: (Int, U) => Unit) {
    +    val partitionRange = (0 until rdd.partitions.size)
    +    require(partitions.forall(partitionRange.contains(_)), "partition index out of range")
    --- End diff --
    
    Take a look at use of PartitionPruningRDD ..
    On Mar 4, 2014 9:33 AM, "LiGuoqiang" <notifications@github.com> wrote:
    
    > In core/src/main/scala/org/apache/spark/SparkContext.scala:
    >
    > > @@ -847,6 +847,8 @@ class SparkContext(
    > >        partitions: Seq[Int],
    > >        allowLocal: Boolean,
    > >        resultHandler: (Int, U) => Unit) {
    > > +    val partitionRange = (0 until rdd.partitions.size)
    > > +    require(partitions.forall(partitionRange.contains(_)), "partition index
out of range")
    >
    >
    >    1.
    >
    >    Can be changed
    >
    >    require(partitions.toSet.diff(rdd.partitions.map(_.index).toSet).isEmpty, "partition
index out of range")
    >
    >     2.
    >
    >    Custom Partitioner causing a lot of problems
    >
    >    val partitioner = new Partitioner {
    >      override def numPartitions: Int = 2
    >      override def getPartition(key: Any): Int = key.hashCode() % 2
    >     }
    >
    >    val pairs = sc.parallelize(Array((1, 2), (3, 4), (5, 6), (-1, 7)))
    >    val shuffled = pairs.partitionBy(partitioner)
    >    shuffled.count
    >
    >
    > --
    > Reply to this email directly or view it on GitHub<https://github.com/apache/spark/pull/44/files#r10242185>
    > .
    >


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