[jira] [Updated] (FLINK-30198) Support AdaptiveBatchScheduler to set per-task size for reducer task

["Aitozi (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/FLINK-30198?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Aitozi updated FLINK-30198:
---------------------------
    Description: 
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.

  was:
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 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.


> 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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