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https://issues.apache.org/jira/browse/FLINK-14362?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Gary Yao closed FLINK-14362.
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    Resolution: Fixed

master: f87bc82a8c6f1c1778497fa73bfee11fbf3c750f

> Change DefaultSchedulingResultPartition to return correct partition state
> -------------------------------------------------------------------------
>
>                 Key: FLINK-14362
>                 URL: https://issues.apache.org/jira/browse/FLINK-14362
>             Project: Flink
>          Issue Type: Sub-task
>          Components: Runtime / Coordination
>    Affects Versions: 1.10.0
>            Reporter: Zhu Zhu
>            Assignee: Zhu Zhu
>            Priority: Major
>              Labels: pull-request-available
>             Fix For: 1.10.0
>
>          Time Spent: 20m
>  Remaining Estimate: 0h
>
> Currently {{DefaultSchedulingResultPartition#getState()}} returns the state 
> of partitions based on the partition producer's state. The state is used to 
> make scheduling decision.
> However, it does not correctly reflect the true state of a partition.
> For example, when producer task turns to RUNNING but has not produced any 
> data yet, it's consumers should not be scheduled to reduce unnecessary 
> resource cost in lazy scheduling mode. However, the partition state will be 
> RUNNING in {{DefaultSchedulingResultPartition}} and will trigger the 
> scheduling of its consumers. This may lead to some vertices scheduled earlier 
> than expected with no data to consume, which means a waste of resources.
> I'd propose to change the enums in {{ResultPartitionState}} to be:
> * CREATED // partition is just created or is just reset
> * CONSUMABLE // pipelined partition has data produced or blocking partition's 
> parent result finishes. Corresponds to 
> IntermediateResultPartition#isConsumable.
> The CONSUMABLE state is what the scheduler really cares to make scheduling 
> decisions.
> The DefaultResultPartition should be fixed to return {{ResultPartitionState}} 
> based the true partition state, rather than the vertex state.



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