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https://issues.apache.org/jira/browse/SPARK-24434?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16599092#comment-16599092
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Erik Erlandson commented on SPARK-24434:
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There are a few related, but separate, issues here.
I agree that it is most efficient, and considerate, to respect issue
assignments and coordinate our distributed development around absences, etc.
To the best of my knowledge, the work Stavros did on 24434 was not made visible
as a public WIP apache/spark branch. Making dev visible this way is one
important way to minimize coordination problems.
Although this confusion is awkward, nothing in regard to 24434 has violated
FOSS principles, or Spark governance. Onur's PR has been developed and reviewed
on a public apache/spark branch. This Jira was filed, and has hosted discussion
from all stakeholders.
The Kubernetes Big Data SIG is a separate community that overlaps with the
Spark community. Our meetings are open to the public, and we publish recordings
and meeting minutes. Although we discuss topics related to Spark on Kubernetes,
we do not make Spark development decisions in that community. All of the work
that members of the K8s Big Data SIG have contributed to Spark respects Apache
governance and has been done using established Spark processes: SPIP,
discussion on dev, Jira, and the PR workflow.
> Support user-specified driver and executor pod templates
> --------------------------------------------------------
>
> Key: SPARK-24434
> URL: https://issues.apache.org/jira/browse/SPARK-24434
> Project: Spark
> Issue Type: New Feature
> Components: Kubernetes
> Affects Versions: 2.4.0
> Reporter: Yinan Li
> Priority: Major
>
> With more requests for customizing the driver and executor pods coming, the
> current approach of adding new Spark configuration options has some serious
> drawbacks: 1) it means more Kubernetes specific configuration options to
> maintain, and 2) it widens the gap between the declarative model used by
> Kubernetes and the configuration model used by Spark. We should start
> designing a solution that allows users to specify pod templates as central
> places for all customization needs for the driver and executor pods.
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