[ https://issues.apache.org/jira/browse/FLINK-19011?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17181898#comment-17181898 ]
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. -- This message was sent by Atlassian Jira (v8.3.4#803005)