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https://issues.apache.org/jira/browse/FLINK-2976?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15046702#comment-15046702
]
ASF GitHub Bot commented on FLINK-2976:
---------------------------------------
Github user tillrohrmann commented on a diff in the pull request:
https://github.com/apache/flink/pull/1434#discussion_r46936527
--- Diff:
flink-runtime/src/main/scala/org/apache/flink/runtime/jobmanager/JobManager.scala
---
@@ -495,6 +513,76 @@ class JobManager(
case checkpointMessage : AbstractCheckpointMessage =>
handleCheckpointMessage(checkpointMessage)
+ case TriggerSavepoint(jobId) =>
+ currentJobs.get(jobId) match {
+ case Some((graph, _)) =>
+ val savepointCoordinator = graph.getSavepointCoordinator()
+
+ if (savepointCoordinator != null) {
+ // Immutable copy for the future
+ val senderRef = sender()
+
+ future {
+ try {
+ // Do this async, because checkpoint coordinator
operations can
+ // contain blocking calls to the state backend or
ZooKeeper.
+ val savepointFuture =
savepointCoordinator.triggerSavepoint(
+ System.currentTimeMillis())
+
+ savepointFuture.onComplete {
+ // Success, respond with the savepoint path
+ case scala.util.Success(savepointPath) =>
+ senderRef ! TriggerSavepointSuccess(jobId,
savepointPath)
+
+ // Failure, respond with the cause
+ case scala.util.Failure(t) =>
+ senderRef ! TriggerSavepointFailure(jobId,
+ new Exception("Failed to complete savepoint", t))
+ }(context.dispatcher)
+ }
+ catch {
+ case e: Exception =>
+ senderRef ! TriggerSavepointFailure(jobId, new Exception(
+ "Failed to trigger savepoint", e))
+ }
+ }(context.dispatcher)
+ }
+ else {
+ sender() ! TriggerSavepointFailure(jobId, new
IllegalStateException(
+ "Checkpointing disabled. You can enable it via the execution
environment of " +
--- End diff --
This is also breaking the argument list.
> 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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