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Posted to issues@flink.apache.org by "Robert Metzger (Jira)" <ji...@apache.org> on 2021/01/29 12:54:00 UTC
[jira] [Closed] (FLINK-21099) Introduce JobType to distinguish
between batch and streaming jobs
[ https://issues.apache.org/jira/browse/FLINK-21099?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Robert Metzger closed FLINK-21099.
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Resolution: Fixed
Resolved on master: https://github.com/apache/flink/commit/95f8b61b60d57e2ddb7d4f43fa7e96cb95348d75
> Introduce JobType to distinguish between batch and streaming jobs
> -----------------------------------------------------------------
>
> Key: FLINK-21099
> URL: https://issues.apache.org/jira/browse/FLINK-21099
> Project: Flink
> Issue Type: Sub-task
> Components: Runtime / Coordination
> Affects Versions: 1.13.0
> Reporter: Till Rohrmann
> Assignee: Robert Metzger
> Priority: Major
> Labels: pull-request-available
> Fix For: 1.13.0
>
>
> In order to distinguish between batch and streaming jobs we propose to introduce an enum {{JobType}} which is set in the {{JobGraph}} when creating it. Using the {{JobType}} it will be possible to decide which scheduler to use depending on the nature of the job.
> For batch jobs (from the DataSet API), setting this field is trivial (in the JobGraphGenerator).
> For streaming jobs the situation is more complicated, since FLIP-134 introduced support for bounded (batch) jobs in the DataStream API. For the DataStream API, we rely on the result of StreamGraphGenerator#shouldExecuteInBatchMode, which checks if the DataStream program has unbounded sources.
> Lastly, the Blink Table API / SQL Planner also generates StreamGraph instances, which contain batch jobs. We are tagging the StreamGraph as a batch job in the ExecutorUtils.setBatchProperties() method.
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