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https://issues.apache.org/jira/browse/FLINK-6309?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Flink Jira Bot updated FLINK-6309:
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Labels: auto-deprioritized-major auto-deprioritized-minor auto-unassigned
(was: auto-deprioritized-major auto-unassigned stale-minor)
Priority: Not a Priority (was: Minor)
This issue was labeled "stale-minor" 7 days ago and has not received any
updates so it is being deprioritized. If this ticket is actually Minor, please
raise the priority and ask a committer to assign you the issue or revive the
public discussion.
> Memory consumer weights should be calculated in job vertex level
> ----------------------------------------------------------------
>
> Key: FLINK-6309
> URL: https://issues.apache.org/jira/browse/FLINK-6309
> Project: Flink
> Issue Type: Improvement
> Components: API / DataSet
> Reporter: Kurt Young
> Priority: Not a Priority
> Labels: auto-deprioritized-major, auto-deprioritized-minor,
> auto-unassigned
>
> Currently, in {{PlanFinalizer}}, we travel all the job vertices to calculate
> the consumer weights of the memory and then assign the weights for each job
> vertex. In the case of a large job graph, e.g. with multiple joins, group
> reduces, the value of consumer weights will be very high and the available
> memory for each job vertex will be very low.
> I think it makes more sense to calculate the consumer weights of the memory
> at the job vertex level (after chaining), in order to maximize the usage
> ratio of the memory.
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