Github user andrewor14 commented on a diff in the pull request:
https://github.com/apache/spark/pull/4002#discussion_r22815109
--- 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)
--- End diff --
this need not be specific to `Int.MaxValue` and `Int.MinValue`. We can just
do a special case for inclusive range in general and I think the code will be
significantly more straightforward to read. I'll explain below.
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