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https://issues.apache.org/jira/browse/FLINK-2976?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15091640#comment-15091640
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ASF GitHub Bot commented on FLINK-2976:
---------------------------------------

Github user uce commented on the pull request:

    https://github.com/apache/flink/pull/1434#issuecomment-170477891
  
    Thanks Gyula! I will rebase and merge this if there are no objections.



> Save and load checkpoints manually
> ----------------------------------
>
>                 Key: FLINK-2976
>                 URL: https://issues.apache.org/jira/browse/FLINK-2976
>             Project: Flink
>          Issue Type: Improvement
>          Components: Distributed Runtime
>    Affects Versions: 0.10.0
>            Reporter: Ufuk Celebi
>            Assignee: Ufuk Celebi
>             Fix For: 1.0.0
>
>
> Currently, all checkpointed state is bound to a job. After the job finishes 
> all state is lost. In case of an HA cluster, jobs can live longer than the 
> cluster, but they still suffer from the same issue when they finish.
> Multiple users have requested the feature to manually save a checkpoint in 
> order to resume from it at a later point. This is especially important for 
> production environments. As an example, consider upgrading your existing 
> production Flink program. Currently, you loose all the state of your program. 
> With the proposed mechanism, it will be possible to save a checkpoint, stop 
> and update your program, and then continue your program with the  checkpoint.
> The required operations can be simple:
> saveCheckpoint(JobID) => checkpointID: long
> loadCheckpoint(JobID, long) => void
> For the initial version, I would apply the following restriction:
> - The topology needs to stay the same (JobGraph parallelism, etc.)
> A user can configure this behaviour via the environment like the 
> checkpointing interval. Furthermore, the user can trigger the save operation 
> via the command line at arbitrary times and load a checkpoint when submitting 
> a job, e.g.
> bin/flink checkpoint <JobID> => checkpointID: long 
> and
> bin/flink run --loadCheckpoint JobID [latest saved checkpoint]
> bin/flink run --loadCheckpoint (JobID,long) [specific saved checkpoint]
> As far as I can tell, the required mechanisms are similar to the ones 
> implemented for JobManager high availability. We need to make sure to persist 
> the CompletedCheckpoint instances as a pointer to the checkpoint state and to 
> *not* remove saved checkpoint state.
> On the client side, we need to give the job and its vertices the same IDs to 
> allow mapping the checkpoint state.



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