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https://issues.apache.org/jira/browse/FLINK-31623?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Fan Hong updated FLINK-31623:
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Summary: Fix non-uniform sampling to uniform sampling on
DataStreamUtils#sample (was: Improvements on DataStreamUtils#sample)
> Fix non-uniform sampling to uniform sampling on DataStreamUtils#sample
> ----------------------------------------------------------------------
>
> Key: FLINK-31623
> URL: https://issues.apache.org/jira/browse/FLINK-31623
> Project: Flink
> Issue Type: Bug
> Components: Library / Machine Learning
> Reporter: Fan Hong
> Priority: Major
>
> Current implementation employs two-level sampling method, which could
> encounter two issues:
> #
> One subtask has a memory footprint twice as large as the other subtasks,
> which could cause unexpected OOM in some situations.
>
> # When data instances are imbalanced distributed among partitions
> (subtasks), the probabilities of instances to be sampled are different in
> different partitions (subtasks).
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