Github user pwendell commented on a diff in the pull request:
https://github.com/apache/spark/pull/1165#discussion_r15214812
--- Diff: core/src/main/scala/org/apache/spark/CacheManager.scala ---
@@ -124,15 +124,20 @@ private[spark] class CacheManager(blockManager:
BlockManager) extends Logging {
private def putInBlockManager[T](
key: BlockId,
values: Iterator[T],
- storageLevel: StorageLevel,
- updatedBlocks: ArrayBuffer[(BlockId, BlockStatus)]): Iterator[T] = {
-
- if (!storageLevel.useMemory) {
- /* This RDD is not to be cached in memory, so we can just pass the
computed values
+ level: StorageLevel,
+ updatedBlocks: ArrayBuffer[(BlockId, BlockStatus)],
+ effectiveStorageLevel: Option[StorageLevel] = None): Iterator[T] = {
+
+ val putLevel = effectiveStorageLevel.getOrElse(level)
+ if (!putLevel.useMemory) {
+ /*
+ * This RDD is not to be cached in memory, so we can just pass the
computed values
* as an iterator directly to the BlockManager, rather than first
fully unrolling
* it in memory. The latter option potentially uses much more memory
and risks OOM
--- End diff --
This doc is a bit outdated now (we no longer risk OOM ideally). I think
it's a bit overly complicated anyways. I'd just make it something like:
```
// This RDD is not being cached in memory, so pass an iterator directly to
the block manager.
```
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