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https://issues.apache.org/jira/browse/FLINK-4271?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15432906#comment-15432906
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ASF GitHub Bot commented on FLINK-4271:
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Github user StephanEwen commented on the issue:
https://github.com/apache/flink/pull/2305
It seems we are go for the `with(...)` approach.
Pending decision is whether we want `with` to be the long-run solution, or
stay with `apply`.
The reason why `DataStream` has `apply()` and `DataSet` has `with()` is
that different people wrote the API functions and everyone has their favorite
name and style that they stick to ;-)
I agree that consistency should be key in the future. The `DataStream` API
has more traction right now, and should long-term subsume the DataSet API, so I
have a slight bias to keep the DataStream style for now (many people will not
even use the `with(...)` variant because they don't set individual parallelism).
> There is no way to set parallelism of operators produced by CoGroupedStreams
> ----------------------------------------------------------------------------
>
> Key: FLINK-4271
> URL: https://issues.apache.org/jira/browse/FLINK-4271
> Project: Flink
> Issue Type: Bug
> Components: DataStream API
> Reporter: Wenlong Lyu
> Assignee: Jark Wu
>
> Currently, CoGroupStreams package the map/keyBy/window operators with a human
> friendly interface, like:
> dataStreamA.cogroup(streamB).where(...).equalsTo().window().apply(), both the
> intermediate operators and final window operators can not be accessed by
> users, and we cannot set attributes of the operators, which make co-group
> hard to use in production environment.
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