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From mateiz <...@git.apache.org>
Subject [GitHub] spark pull request: fix #SPARK-1149 Bad partitioners can cause Spa...
Date Sun, 02 Mar 2014 23:09:09 GMT
Github user mateiz commented on a diff in the pull request:

    https://github.com/apache/spark/pull/44#discussion_r10198205
  
    --- Diff: core/src/main/scala/org/apache/spark/SparkContext.scala ---
    @@ -950,6 +952,8 @@ class SparkContext(
           resultHandler: (Int, U) => Unit,
           resultFunc: => R): SimpleFutureAction[R] =
       {
    +    val rddPartitions = rdd.partitions.map(_.index)
    +    require(partitions.forall(rddPartitions.contains(_)), "partition index out of range")
    --- End diff --
    
    This check as written is going to have quadratic complexity. If you have 100 partitions
for example, you're going to create a list of length 100 at the top and then check for all
100 partitions whether they're in that list, getting 10,000 operations. Can't you just check
that all the indices in partitions are between 0 and rdd.partitions.size? I don't think RDDs
can have non-contiguous partition numbers, though there might have been some stuff in the
past with partition pruning that I may be misremembering.


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