Github user mateiz commented on a diff in the pull request:
https://github.com/apache/spark/pull/776#discussion_r13195998
--- Diff:
core/src/main/scala/org/apache/spark/rdd/ParallelCollectionRDD.scala ---
@@ -128,18 +137,17 @@ private object ParallelCollectionRDD {
r.start, r.end + sign, r.step).asInstanceOf[Seq[T]], numSlices)
}
case r: Range => {
- (0 until numSlices).map(i => {
- val start = ((i * r.length.toLong) / numSlices).toInt
- val end = (((i + 1) * r.length.toLong) / numSlices).toInt
- new Range(r.start + start * r.step, r.start + end * r.step,
r.step)
+ positions(r.length, numSlices).map({
+ case (start, end) =>
+ new Range(r.start + start * r.step, r.start + end * r.step,
r.step)
}).asInstanceOf[Seq[Seq[T]]]
}
case nr: NumericRange[_] => {
// For ranges of Long, Double, BigInteger, etc
val slices = new ArrayBuffer[Seq[T]](numSlices)
- val sliceSize = (nr.size + numSlices - 1) / numSlices // Round up
to catch everything
var r = nr
- for (i <- 0 until numSlices) {
+ for ((start, end) <- positions(nr.length, numSlices)) {
+ val sliceSize = end - start
slices += r.take(sliceSize).asInstanceOf[Seq[T]]
--- End diff --
Alright, maybe we should wait for Scala then. By the way, for your original
use case, was the range you wanted always (0 to numElements)? If so you can
also try RDD.zipWithIndex.
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