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https://issues.apache.org/jira/browse/FLINK-19011?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17181898#comment-17181898
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Stephan Ewen commented on FLINK-19011:
--------------------------------------

Union state has caused us much trouble through the years.
I am leaning towards deprecating and dropping the feature.

  - The new sources should not need it any more, the new sinks neither.
  - The feature is not really scalable, it has an inherent limit, worse than 
broadcast, because it works linearly until a failure and then becomes quadratic 
(like a broadcast). So it is a non-scalability you discover only when it is too 
late.

What do you think?

> Parallelize the restore operation in OperatorStateBackend 
> ----------------------------------------------------------
>
>                 Key: FLINK-19011
>                 URL: https://issues.apache.org/jira/browse/FLINK-19011
>             Project: Flink
>          Issue Type: Improvement
>          Components: Runtime / Checkpointing
>    Affects Versions: 1.11.1
>            Reporter: Jiayi Liao
>            Priority: Major
>
> To restore the states, union state needs to read state handles produced by 
> all operators. And currently during the restore operation, Flink iterates the 
> state handles one by one, which could last tens of minutes if the magnitude 
> of state handles exceeds ten thousand. 
> To accelerate the process, I propose to parallelize the random reads on HDFS 
> and deserialization. We can create a runnable for each state handle and let 
> it return the metadata and deserialized data, which can be aggregated in main 
> thread.



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