gaborgsomogyi commented on a change in pull request #23716: [SPARK-26734]
[STREAMING] Fix StackOverflowError with large block queue
URL: https://github.com/apache/spark/pull/23716#discussion_r253011009
##########
File path:
streaming/src/main/scala/org/apache/spark/streaming/scheduler/ReceivedBlockTracker.scala
##########
@@ -112,7 +112,7 @@ private[streaming] class ReceivedBlockTracker(
def allocateBlocksToBatch(batchTime: Time): Unit = synchronized {
if (lastAllocatedBatchTime == null || batchTime > lastAllocatedBatchTime) {
val streamIdToBlocks = streamIds.map { streamId =>
- (streamId, getReceivedBlockQueue(streamId).clone())
+ (streamId, getReceivedBlockQueue(streamId).clone().dequeueAll(x =>
true))
Review comment:
That's not a scala but java limitation. Serialization is vulnerable to stack
overflow for certain kind of structures; for example, a long linked list with
no special writeObject() methods will be serialized by recursively writing each
link. If you've got a 100k links, you're going to try to use 100k stack frames,
and quite likely fail with a StackOverflowError. The main thing here is to use
something which is not linked.
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
[email protected]
With regards,
Apache Git Services
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
