Github user andrewor14 commented on a diff in the pull request:
https://github.com/apache/spark/pull/10170#discussion_r46997970
--- Diff:
core/src/main/scala/org/apache/spark/memory/UnifiedMemoryManager.scala ---
@@ -100,7 +100,7 @@ private[spark] class UnifiedMemoryManager
private[memory] (
case MemoryMode.OFF_HEAP =>
// For now, we only support on-heap caching of data, so we do not
need to interact with
// the storage pool when allocating off-heap memory. This will
change in the future, though.
- super.acquireExecutionMemory(numBytes, taskAttemptId, memoryMode)
+ offHeapExecutionMemoryPool.acquireMemory(numBytes, taskAttemptId)
--- End diff --
+1 to this change. It's much less brittle!
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature is enabled but not working, please
contact infrastructure at [email protected] or file a JIRA ticket
with INFRA.
---
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
