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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-unassigned stale-minor (was:
auto-deprioritized-major auto-unassigned)
I am the [Flink Jira Bot|https://github.com/apache/flink-jira-bot/] and I help
the community manage its development. I see this issues has been marked as
Minor but is unassigned and neither itself nor its Sub-Tasks have been updated
for 180 days. I have gone ahead and marked it "stale-minor". If this ticket is
still Minor, please either assign yourself or give an update. Afterwards,
please remove the label or in 7 days the issue will be deprioritized.
> 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: Minor
> Labels: auto-deprioritized-major, auto-unassigned, stale-minor
>
> 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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