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From "ASF GitHub Bot (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (FLINK-2976) Save and load checkpoints manually
Date Tue, 08 Dec 2015 10:45:10 GMT

    [ https://issues.apache.org/jira/browse/FLINK-2976?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15046716#comment-15046716

ASF GitHub Bot commented on FLINK-2976:

Github user tillrohrmann commented on a diff in the pull request:

    --- Diff: flink-runtime/src/main/java/org/apache/flink/runtime/checkpoint/CheckpointCoordinator.java
    @@ -455,32 +490,43 @@ else if (pendingCheckpoints.size() >= maxConcurrentCheckpointAttempts)
     			return false;
    -	public void receiveAcknowledgeMessage(AcknowledgeCheckpoint message) throws Exception
    +	/**
    +	 * Receives an AcknowledgeCheckpoint message and returns whether the
    +	 * message was associated with a pending checkpoint.
    +	 */
    --- End diff --
    JavaDocs not complete

> 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
>             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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