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https://issues.apache.org/jira/browse/SPARK-3714?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Sean Owen updated SPARK-3714:
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Component/s: Deploy
> Spark workflow scheduler
> ------------------------
>
> Key: SPARK-3714
> URL: https://issues.apache.org/jira/browse/SPARK-3714
> Project: Spark
> Issue Type: New Feature
> Components: Deploy, Scheduler
> Reporter: Egor Pakhomov
> Priority: Minor
>
> [Design doc |
> https://docs.google.com/document/d/1q2Q8Ux-6uAkH7wtLJpc3jz-GfrDEjlbWlXtf20hvguk/edit?usp=sharing]
> Spark stack currently hard to use in the production processes due to the lack
> of next features:
> * Scheduling spark jobs
> * Retrying failed spark job in big pipeline
> * Share context among jobs in pipeline
> * Queue jobs
> Typical usecase for such platform would be - wait for new data, process new
> data, learn ML models on new data, compare model with previous one, in case
> of success - rewrite model in HDFS directory for current production model
> with new one.
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