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https://issues.apache.org/jira/browse/SPARK-24122?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16491338#comment-16491338
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Yinan Li commented on SPARK-24122:
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The operator does cover automatic restart of an application with a configurable
restart policy. For batch ETL jobs, this is probably sufficient for common
needs to restart jobs on failures. For streaming jobs, checkpointing is needed.
https://issues.apache.org/jira/browse/SPARK-23980 is also relevant.
> Allow automatic driver restarts on K8s
> --------------------------------------
>
> Key: SPARK-24122
> URL: https://issues.apache.org/jira/browse/SPARK-24122
> Project: Spark
> Issue Type: Improvement
> Components: Kubernetes
> Affects Versions: 2.3.0
> Reporter: Oz Ben-Ami
> Priority: Minor
>
> [~foxish]
> Right now SparkSubmit creates the driver as a bare pod, rather than a managed
> controller like a Deployment or a StatefulSet. This means there is no way to
> guarantee automatic restarts, eg in case a node has an issue. Note Pod
> RestartPolicy does not apply if a node fails. A StatefulSet would allow us to
> guarantee that, and keep the ability for executors to find the driver using
> DNS.
> This is particularly helpful for long-running streaming workloads, where we
> currently use {{yarn.resourcemanager.am.max-attempts}} with YARN. I can
> confirm that Spark Streaming and Structured Streaming applications can be
> made to recover from such a restart, with the help of checkpointing. The
> executors will have to be started again by the driver, but this should not be
> a problem.
> For batch processing, we could alternatively use Kubernetes {{Job}} objects,
> which restart pods on failure but not success. For example, note the
> semantics provided by the {{kubectl run}}
> [command|https://kubernetes.io/docs/reference/generated/kubectl/kubectl-commands#run]
> * {{--restart=Never}}: bare Pod
> * {{--restart=Always}}: Deployment
> * {{--restart=OnFailure}}: Job
> https://github.com/apache-spark-on-k8s/spark/issues/288
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