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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