Github user andrewor14 commented on a diff in the pull request:
https://github.com/apache/spark/pull/4002#discussion_r22880771
--- Diff:
core/src/main/scala/org/apache/spark/rdd/ParallelCollectionRDD.scala ---
@@ -127,18 +127,15 @@ private object ParallelCollectionRDD {
})
}
seq match {
- case r: Range.Inclusive => {
- val sign = if (r.step < 0) {
- -1
- } else {
- 1
- }
- slice(new Range(
- r.start, r.end + sign, r.step).asInstanceOf[Seq[T]], numSlices)
- }
case r: Range => {
- positions(r.length, numSlices).map({
- case (start, end) =>
+ // 1 to Int.MaxValue and (-2 to Int.MinValue by -1) can trigger
exclusive range int overflow
+ val needsInclusiveRange = r.isInclusive && (r.end == Int.MaxValue
|| r.end == Int.MinValue)
+ positions(r.length, numSlices).zipWithIndex.map({
+ // we need an inclusive range to avoid int overflow and setting
the last range to be
+ // inclusive is suffice
+ case ((start, end), index) if needsInclusiveRange && index ==
numSlices - 1 =>
+ new Range.Inclusive(r.start + start * r.step, r.end, r.step)
+ case ((start, end), _) =>
new Range(r.start + start * r.step, r.start + end * r.step,
r.step)
--- End diff --
I think as long as we don't change the behavior it's preferrable to rewrite
it in a readable manner. Here it's pretty clear to me that if the range is
inclusive we should include the last element in the last slice, regardless of
whether the range ends in a special value like `Int.MaxValue`.
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