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From "ASF GitHub Bot (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (FLINK-4271) There is no way to set parallelism of operators produced by CoGroupedStreams
Date Tue, 23 Aug 2016 14:33:20 GMT

    [ https://issues.apache.org/jira/browse/FLINK-4271?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15432906#comment-15432906

ASF GitHub Bot commented on FLINK-4271:

Github user StephanEwen commented on the issue:

    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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