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From "ASF GitHub Bot (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (FLINK-9289) Parallelism of generated operators should have max parallism of input
Date Wed, 15 Aug 2018 10:58:00 GMT

    [ https://issues.apache.org/jira/browse/FLINK-9289?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16580923#comment-16580923
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ASF GitHub Bot commented on FLINK-9289:
---------------------------------------

xccui commented on issue #6003: [FLINK-9289][Dataset] Parallelism of generated operators should
have max parallelism of input
URL: https://github.com/apache/flink/pull/6003#issuecomment-413163702
 
 
   Hi @fhueske. I just added some tests for the union operator. 
   
   Thanks, Xingcan

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> Parallelism of generated operators should have max parallism of input
> ---------------------------------------------------------------------
>
>                 Key: FLINK-9289
>                 URL: https://issues.apache.org/jira/browse/FLINK-9289
>             Project: Flink
>          Issue Type: Bug
>          Components: DataSet API
>    Affects Versions: 1.5.0, 1.4.2, 1.6.0
>            Reporter: Fabian Hueske
>            Assignee: Xingcan Cui
>            Priority: Major
>              Labels: pull-request-available
>
> The DataSet API aims to chain generated operators such as key extraction mappers to their
predecessor. This is done by assigning the same parallelism as the input operator.
> If a generated operator has more than two inputs, the operator cannot be chained anymore
and the operator is generated with default parallelism. This can lead to a {code}NoResourceAvailableException:
Not enough free slots available to run the job.{code} as reported by a user on the mailing
list: https://lists.apache.org/thread.html/60a8bffcce54717b6273bf3de0f43f1940fbb711590f4b90cd666c9a@%3Cuser.flink.apache.org%3E
> I suggest to set the parallelism of a generated operator to the max parallelism of all
of its inputs to fix this problem.
> Until the problem is fixed, a workaround is to set the default parallelism at the {{ExecutionEnvironment}}:
> {code}
> ExecutionEnvironment env = ...
> env.setParallelism(2);
> {code}



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