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https://issues.apache.org/jira/browse/FLINK-4271?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15397229#comment-15397229
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ASF GitHub Bot commented on FLINK-4271:
---------------------------------------
GitHub user wuchong opened a pull request:
https://github.com/apache/flink/pull/2305
[FLINK-4271] [DataStreamAPI] Enable CoGroupedStreams and JoinedStreams to
set parallellism
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The CoGroupStream will construct the following graph.
```
source -> MAP ---
|-> WindowOp -> Sink
source -> MAP ---
```
By now , the MAP and WindowOp can not set parallelism. We can keep the MAP
has same parallelism as previous operator (chaining). And we can change
{{CoGroupedStreams.apply}} to return a {{SingleOutputStreamOperator}} instead
of {{DataStream}}, so that we can set WindowOp's parallelism. The same thing
has be done to {{JoinedStream}}.
So that we can do the following things:
```
DataStream<T> result = one.coGroup(two)
.where(new MyFirstKeySelector())
.equalTo(new MyFirstKeySelector())
.window(TumblingEventTimeWindows.of(Time.of(5, TimeUnit.SECONDS)))
.apply(new MyCoGroupFunction());
.setParallelism(10)
.name("MyCoGroupWindow")
```
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/wuchong/flink CoGroupStreams
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/flink/pull/2305.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #2305
----
commit 7b9594a175f33e62826a0cb51380f33dec5857b6
Author: Jark Wu <wuchong...@alibaba-inc.com>
Date: 2016-07-28T06:32:13Z
[FLINK-4271] [DataStreamAPI] Enable CoGroupedStreams and JoinedStreams to
set 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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