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https://issues.apache.org/jira/browse/FLINK-4256?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15391849#comment-15391849
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Wenlong Lyu commented on FLINK-4256:
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hi, Stephan, we have implemented similar solution before, but simple back
tracking and forward cannot work well in situation following:
Assuming job graph has A/B/C job vertices, A is connected to C with forward
strategy, and B is connected to C all-to-all strategy, when a task of A failed,
only one C task will be added to restart node set.
I suggesting divide the job graph in maximal connected sub-graphs treating the
job graph as an undirected graph, when a job graph is submitted. Besides, when
the job graph is in large scale because extracting related nodes according to a
given node can be time costly and will be repeatedly used in long running,
using sub-graphs can avoid the problem
> Fine-grained recovery
> ---------------------
>
> Key: FLINK-4256
> URL: https://issues.apache.org/jira/browse/FLINK-4256
> Project: Flink
> Issue Type: Improvement
> Components: JobManager
> Affects Versions: 1.1.0
> Reporter: Stephan Ewen
> Assignee: Stephan Ewen
> Fix For: 1.2.0
>
>
> When a task fails during execution, Flink currently resets the entire
> execution graph and triggers complete re-execution from the last completed
> checkpoint. This is more expensive than just re-executing the failed tasks.
> In many cases, more fine-grained recovery is possible.
> The full description and design is in the corresponding FLIP.
> https://cwiki.apache.org/confluence/display/FLINK/FLIP-1+%3A+Fine+Grained+Recovery+from+Task+Failures
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