Github user andrewor14 commented on a diff in the pull request:
https://github.com/apache/spark/pull/50#discussion_r10238815
--- Diff: core/src/main/scala/org/apache/spark/CacheManager.scala ---
@@ -71,10 +71,21 @@ private[spark] class CacheManager(blockManager:
BlockManager) extends Logging {
val computedValues = rdd.computeOrReadCheckpoint(split, context)
// Persist the result, so long as the task is not running locally
if (context.runningLocally) { return computedValues }
- val elements = new ArrayBuffer[Any]
- elements ++= computedValues
- blockManager.put(key, elements, storageLevel, tellMaster = true)
- elements.iterator.asInstanceOf[Iterator[T]]
+ if (storageLevel.useDisk && !storageLevel.useMemory) {
+ blockManager.put(key, computedValues, storageLevel, tellMaster
= true)
+ return blockManager.get(key) match {
+ case Some(values) =>
+ return new InterruptibleIterator(context,
values.asInstanceOf[Iterator[T]])
+ case None =>
+ logInfo("Failure to store %s".format(key))
+ return null
+ }
+ } else {
+ val elements = new ArrayBuffer[Any]
+ elements ++= computedValues
+ blockManager.put(key, elements, storageLevel, tellMaster =
true)
+ return elements.iterator.asInstanceOf[Iterator[T]]
+ }
--- End diff --
Is there any reason why we still want to keep around the legacy case? It
seems that the IteratorValues and ArrayBufferValues are handled in very similar
ways downstream (e.g. in BlockManager.doPut, and memoryStore.putValues), and it
would be nice if we could somehow merge these two code paths into a simpler one.
The other thing is that computeValues in L71 is already an iterator anyway,
so we can just feed this directly into BlockManager. The existing way of making
it an ArrayBuffer arbitrarily and back into an Iterator seems a little
unnecessary.
(That said, there might be a performance reason that I haven't thought of.)
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