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https://issues.apache.org/jira/browse/FLINK-1284?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17329579#comment-17329579
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Flink Jira Bot commented on FLINK-1284:
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This issue is assigned but has not received an update in 7 days so it has been
labeled "stale-assigned". If you are still working on the issue, please give an
update and remove the label. If you are no longer working on the issue, please
unassign so someone else may work on it. In 7 days the issue will be
automatically unassigned.
> Uniform random sampling operator over windows
> ---------------------------------------------
>
> Key: FLINK-1284
> URL: https://issues.apache.org/jira/browse/FLINK-1284
> Project: Flink
> Issue Type: New Feature
> Components: API / DataStream
> Reporter: Paris Carbone
> Assignee: Austin Ouyang
> Priority: Minor
> Labels: stale-assigned, stale-minor
>
> It would be useful for several use cases to have a built-in uniform random
> sampling operator in the streaming API that can operate on windows. This can
> be used for example for online machine learning operations, evaluating
> heuristics or continuous visualisation of representative values.
> The operator could be given a field and a number of random samples needed,
> following a window statement as such:
> mystream.window(..).sample(fieldID,#samples)
> Given that pre-aggregation is enabled, this could perhaps be implemented as a
> binary reduce operator or a combinable groupreduce that pre-aggregates the
> empiricals of that field.
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