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Shammon commented on FLINK-25055: --------------------------------- [~trohrmann] Thank you for your rely. Yes, your understanding is quite correct, this mechanism helps to optimize the interaction between tasks. And thank you for suggestions, I agree with you that it's necessary and important to delete the specified callback in case of timeout or task deployment failure. I want to add this mechanism in flink when job's tasks are deployed in a same pipelined region, and users can use it in their clusters with a specify config. Could you assign this issue to me? Thanks > Support listen and notify mechanism for PartitionRequest > -------------------------------------------------------- > > Key: FLINK-25055 > URL: https://issues.apache.org/jira/browse/FLINK-25055 > Project: Flink > Issue Type: Improvement > Components: Runtime / Network > Affects Versions: 1.14.0, 1.12.5, 1.13.3 > Reporter: Shammon > Priority: Major > > We submit batch jobs to flink session cluster with eager scheduler for olap. > JM deploys subtasks to TaskManager independently, and the downstream subtasks > may start before the upstream ones are ready. The downstream subtask sends > PartitionRequest to upstream ones, and may receive PartitionNotFoundException > from them. Then it will retry to send PartitionRequest after a few ms until > timeout. > The current approach raises two problems. First, there will be too many retry > PartitionRequest messages. Each downstream subtask will send PartitionRequest > to all its upstream subtasks and the total number of messages will be O(N*N), > where N is the parallelism of subtasks. Secondly, the interval between > polling retries will increase the delay for upstream and downstream tasks to > confirm PartitionRequest. > We want to support listen and notify mechanism for PartitionRequest when the > job needs no failover. Upstream TaskManager will add the PartitionRequest to > a listen list with a timeout checker, and notify the request when the task > register its partition in the TaskManager. > [~nkubicek] I noticed that your scenario of using flink is similar to ours. > What do you think? And hope to hear from you [~trohrmann] THX -- This message was sent by Atlassian Jira (v8.20.1#820001)