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https://issues.apache.org/jira/browse/FLINK-2976?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14991570#comment-14991570
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Gyula Fora commented on FLINK-2976:
-----------------------------------

Thanks Ufuk!

This is a critical feature for almost all production streaming job that keep 
around state. In the applications we are experimenting with at King we would 
use this feature extensively to bugfix running streaming jobs that keep a large 
amount of state around. It's not feasible to restart the job from the beginning 
and re-create the whole state.

This is necessary for any production deployment.

> 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
>            Reporter: Ufuk Celebi
>             Fix For: 1.0
>
>
> 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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