Github user andrewor14 commented on a diff in the pull request:
https://github.com/apache/spark/pull/1165#discussion_r15092309
--- Diff: core/src/main/scala/org/apache/spark/CacheManager.scala ---
@@ -140,14 +144,39 @@ private[spark] class CacheManager(blockManager:
BlockManager) extends Logging {
throw new BlockException(key, s"Block manager failed to return
cached value for $key!")
}
} else {
- /* This RDD is to be cached in memory. In this case we cannot pass
the computed values
+ /*
+ * This RDD is to be cached in memory. In this case we cannot pass
the computed values
* to the BlockManager as an iterator and expect to read it back
later. This is because
* we may end up dropping a partition from memory store before
getting it back, e.g.
- * when the entirety of the RDD does not fit in memory. */
- val elements = new ArrayBuffer[Any]
- elements ++= values
- updatedBlocks ++= blockManager.put(key, elements, storageLevel,
tellMaster = true)
- elements.iterator.asInstanceOf[Iterator[T]]
+ * when the entirety of the RDD does not fit in memory.
+ *
+ * In addition, we must be careful to not unfold the entire
partition in memory at once.
+ * Otherwise, we may cause an OOM exception if the JVM does not have
enough space for this
+ * single partition. Instead, we unfold the values cautiously,
potentially aborting and
+ * dropping the partition to disk if applicable.
+ */
+ blockManager.memoryStore.unfoldSafely(key, values, updatedBlocks)
match {
+ case Left(arrayValues) =>
+ // We have successfully unfolded the entire partition, so cache
it in memory
+ updatedBlocks ++= blockManager.put(key, arrayValues,
storageLevel, tellMaster = true)
+ arrayValues.iterator.asInstanceOf[Iterator[T]]
--- End diff --
We actually can't make `unrollSafely` more specific because arrays are not
covariant. See my comment elsewhere.
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