Github user mateiz commented on a diff in the pull request:
https://github.com/apache/spark/pull/156#discussion_r11266448
--- Diff: core/src/main/scala/org/apache/spark/rdd/RDD.scala ---
@@ -664,6 +664,24 @@ abstract class RDD[T: ClassTag](
}
/**
+ * Return a Stream that contains all of the elements in this RDD.
+ *
+ * In case of iterating it consumes memory as the biggest partition in
cluster.
+ */
+ def toLocallyIterable: Stream[T] = {
+ def collectPartition(p: Int): Array[T] = {
+ sc.runJob(this, (iter: Iterator[T]) => iter.toArray, Seq(p),
allowLocal = false).head
+ }
+ var buffer = Stream.empty[T]
+ for (p <- 0 until this.partitions.length) {
+ buffer = buffer append {
+ collectPartition(p).toStream
--- End diff --
Actually it would probably be cleaner to write this code like this:
```
(0 until partitions.length).iterator.flatMap(i => collectPartition(i))
```
Since we're not returning a Stream anymore, but rather an iterator. You
could also just make `collectPartition` take a Partition object and then do
`partitions.iterator.flatMap(...)`.
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