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https://issues.apache.org/jira/browse/FLINK-10298?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16624217#comment-16624217
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JIN SUN commented on FLINK-10298:
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Hi Tison,
Thanks for point this. Yes, i know there is a DataConsumptionException, and we
can refer DataComsumptionException as PartitionDataMissingError,
DataComsumptionException is one of the issue we need to handle. This JIRA is
target for a framework to improve failover, especially in Batch job scenario.
Jin
> Batch Job Failover Strategy
> ---------------------------
>
> Key: FLINK-10298
> URL: https://issues.apache.org/jira/browse/FLINK-10298
> Project: Flink
> Issue Type: Sub-task
> Components: JobManager
> Reporter: JIN SUN
> Assignee: JIN SUN
> Priority: Major
>
> The new failover strategy needs to consider handling failures according to
> different failure types. It orchestrates all the logics we mentioned in this
> [document|https://docs.google.com/document/d/1FdZdcA63tPUEewcCimTFy9Iz2jlVlMRANZkO4RngIuk/edit],
> we can put the logic in onTaskFailure method of the FailoverStrategy
> interface, with the logic inline:
> {code:java}
> public void onTaskFailure(Execution taskExecution, Throwable cause) {
> //1. Get the throwable type
> //2. If the type is NonrecoverableType fail the job
> //3. If the type is PatritionDataMissingError, do revocation
> //4. If the type is EnvironmentError, do check blacklist
> //5. Other failure types are recoverable, but we need to remember the
> count of the failure,
> //6. if it exceeds the threshold, fail the job
> }{code}
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