Github user JoshRosen commented on a diff in the pull request:
https://github.com/apache/spark/pull/10748#discussion_r49678166
--- Diff: core/src/main/scala/org/apache/spark/CacheManager.scala ---
@@ -126,67 +136,4 @@ private[spark] class CacheManager(blockManager:
BlockManager) extends Logging {
}
}
}
-
- /**
- * Cache the values of a partition, keeping track of any updates in the
storage statuses of
- * other blocks along the way.
- *
- * The effective storage level refers to the level that actually
specifies BlockManager put
- * behavior, not the level originally specified by the user. This is
mainly for forcing a
- * MEMORY_AND_DISK partition to disk if there is not enough room to
unroll the partition,
- * while preserving the the original semantics of the RDD as specified
by the application.
- */
- private def putInBlockManager[T](
- key: BlockId,
- values: Iterator[T],
- 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.
- */
- updatedBlocks ++=
- blockManager.putIterator(key, values, level, tellMaster = true,
effectiveStorageLevel)
- blockManager.get(key) match {
- case Some(v) => v.data.asInstanceOf[Iterator[T]]
- case None =>
- logInfo(s"Failure to store $key")
- 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
- * 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.
- *
- * In addition, we must be careful to not unroll 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 unroll the values cautiously,
potentially aborting and
- * dropping the partition to disk if applicable.
- */
- blockManager.memoryStore.unrollSafely(key, values, updatedBlocks)
match {
- case Left(arr) =>
- // We have successfully unrolled the entire partition, so cache
it in memory
- updatedBlocks ++=
- blockManager.putArray(key, arr, level, tellMaster = true,
effectiveStorageLevel)
--- End diff --
The `BlockManager.putArray()` method was only called from here, hence the
cleanup of those methods.
---
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