mridulm commented on a change in pull request #33078: URL: https://github.com/apache/spark/pull/33078#discussion_r670907624
########## File path: common/network-shuffle/src/main/java/org/apache/spark/network/shuffle/RemoteBlockPushResolver.java ########## @@ -778,11 +773,6 @@ public void onComplete(String streamId) throws IOException { // IOException to the client. This may increase the chunk size however the increase is // still limited because of the limit on the number of IOExceptions for a // particular shuffle partition. - } catch (NullPointerException e) { - throw new RuntimeException( - String.format("The merged shuffle partition info for appId %s shuffleId %s " - + "reduceId %s has been cleaned up", partitionInfo.appId, - partitionInfo.shuffleId, partitionInfo.reduceId)); Review comment: As discussed offline, let us not do this - this is inherently buggy approach. Let us do the alternative discussed - a) Remove use of direct field reference, and rely on accessor methods. b) In the getter, do the relevant checks to ensure non-null values (and throw exception as relevant). c) Use `AtomicReference` for the field related fields in partition info - given they are getting mutated async. d) Ensure close/cleanup relies on atomic getAndSet to ensure no MT-safety issues : note, we need to do this only in `AppShufflePartitionInfo`. e) We can also make `channel` and `dos` `final` in `MergeShuffleFile` - since `AppShufflePartitionInfo` will atomically handle state transitions. (e) is something we had not discussed .. thoughts @zhouyejoe, @otterc ? +CC @Ngone51 -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org --------------------------------------------------------------------- To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org