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https://issues.apache.org/jira/browse/FLINK-30198?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17686326#comment-17686326
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Zhu Zhu commented on FLINK-30198:
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Flink scheduler currently is not aware of operators at the moment, i.e. it does
not know whether a job vertex contains Join, Agg. A workaround is to provide
the task name and the plugin strategy can infer the operators through the name.
It's possible that in the future, we will improve the scheduler to be more
aware of operators, to support advanced optimization.
> Support AdaptiveBatchScheduler to set per-task size for reducer task
> ---------------------------------------------------------------------
>
> Key: FLINK-30198
> URL: https://issues.apache.org/jira/browse/FLINK-30198
> Project: Flink
> Issue Type: Improvement
> Components: Runtime / Coordination
> Reporter: Aitozi
> Priority: Major
>
> When we use AdaptiveBatchScheduler in our case, we found that it can work
> well in most case, but there is a limit that, there is only one global
> parameter for per task data size by
> {{jobmanager.adaptive-batch-scheduler.avg-data-volume-per-task}}.
> However, in a map-reduce architecture, the reducer tasks are usually have
> more complex computation logic such as aggregate/sort/join operators. So I
> think it will be nicer if we can set the reducer and mapper task's data size
> per task individually.
> Then, how to distinguish the reducer task?
> IMO, we can let the parallelism decider know whether the vertex have a hash
> edge inputs. If yes, it should be a reducer task.
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