The only known workaround is to provide your own source(function) that doesn't finish until all of the source subtasks finish and a final checkpoint is completed. However, coordinating the sources with the old SourceFunction interface requires some external tool.
FLIP-147 is targeted for 1.14 in August. On Sat, Jul 10, 2021 at 7:46 PM Rakshit Ramesh < rakshit.ram...@datakaveri.org> wrote: > Hi Arvid, > Since I'm trying to save checkpoints for a bounded process > the checkpoint isn't being written on time since the job finishes before > that can happen. > > Looks like one major feature that would be required for this to work is > discussed in FLIP-147 > > https://cwiki.apache.org/confluence/display/FLINK/FLIP-147%3A+Support+Checkpoints+After+Tasks+Finished > > Is there any userland workaround for this? > > Thanks! > > On Thu, 8 Jul 2021 at 11:52, Rakshit Ramesh <rakshit.ram...@datakaveri.org> > wrote: > >> Yes! I was only worried about the jobid changing and the checkpoint being >> un-referenceable. >> But since I can pass a path to the checkpoint that will not be an issue. >> >> >> Thanks a lot for your suggestions! >> >> On Thu, 8 Jul 2021 at 11:26, Arvid Heise <ar...@apache.org> wrote: >> >>> Hi Rakshit, >>> >>> It sounds to me as if you don't need the Savepoint API at all. You can >>> (re)start all applications with the previous state (be it retained >>> checkpoint or savepoint). You just need to provide the path to that in your >>> application invocation [1] (every entry point has such a parameter, you >>> might need to check the respective documentation if you are not using CLI). >>> Note that although it only says savepoint, starting from a checkpoint is >>> fine as well (just not recommended in the beginning). >>> >>> [1] >>> https://ci.apache.org/projects/flink/flink-docs-master/docs/deployment/cli/#starting-a-job-from-a-savepoint >>> >>> On Thu, Jul 8, 2021 at 6:31 AM Rakshit Ramesh < >>> rakshit.ram...@datakaveri.org> wrote: >>> >>>> Sorry for being a little vague there. >>>> I want to create a Savepoint from a DataStream right before the job is >>>> finished or cancelled. >>>> What you have shown in the IT case is how a datastream can be >>>> bootstrapped with state that is >>>> formed formed by means of DataSet. >>>> My jobs are triggered by a scheduler periodically (every day) using the >>>> api and I would like >>>> to bootstrap each day's job with the state of the previous day. >>>> >>>> But thanks for the input on the Checkpoint behaviour wrt a FINISHED >>>> state, >>>> I think that will work for me. >>>> >>>> Thanks! >>>> >>>> On Thu, 8 Jul 2021 at 02:03, Arvid Heise <ar...@apache.org> wrote: >>>> >>>>> I don't quite understand your question. You use Savepoint API to >>>>> create a savepoint with a batch job (that's why it's DataSet Transform >>>>> currently). That savepoint can only be restored through a datastream >>>>> application. Dataset applications cannot start from a savepoint. >>>>> >>>>> So I don't understand why you see a difference between "restoring a >>>>> savepoint to a datastream" and "create a NewSavepoint for a datastream". >>>>> It's ultimately the same thing for me. Just to be very clear: the main >>>>> purpose of Savepoint API is to create the initial state of a datastream >>>>> application. >>>>> >>>>> For your second question, yes retained checkpoints outlive the job in >>>>> all regards. It's the users responsibility to eventually clean that up. >>>>> >>>>> >>>>> >>>>> On Wed, Jul 7, 2021 at 6:56 PM Rakshit Ramesh < >>>>> rakshit.ram...@datakaveri.org> wrote: >>>>> >>>>>> Yes I could understand restoring a savepoint to a datastream. >>>>>> What I couldn't figure out is to create a NewSavepoint for a >>>>>> datastream. >>>>>> What I understand is that NewSavepoints only take in Bootstrap >>>>>> transformation for Dataset Transform functions. >>>>>> >>>>>> >>>>>> About the checkpoints, does >>>>>> CheckpointConfig.ExternalizedCheckpointCleanup = >>>>>> RETAIN_ON_CANCELLATION >>>>>> offer the same behaviour when the job is "FINISHED" and not >>>>>> "CANCELLED" ? >>>>>> >>>>>> What I'm looking for is a way to retain the state for a bounded job >>>>>> so that the state is reloaded on the next job run (through api). >>>>>> >>>>>> On Wed, 7 Jul 2021 at 14:18, Arvid Heise <ar...@apache.org> wrote: >>>>>> >>>>>>> Hi Rakshit, >>>>>>> >>>>>>> The example is valid. The state processor API is kinda working like >>>>>>> a DataSet application but the state is meant to be read in DataStream. >>>>>>> Please check out the SavepointWriterITCase [1] for a full example. >>>>>>> There is >>>>>>> no checkpoint/savepoint in DataSet applications. >>>>>>> >>>>>>> Checkpoints can be stored on different checkpoint storages, such as >>>>>>> S3 or HDFS. If you use RocksDB state backend, Flink pretty much just >>>>>>> copy >>>>>>> the SST files of RocksDB to S3. Checkpoints are usually bound to the >>>>>>> life >>>>>>> of an application. So they are created by the application and deleted on >>>>>>> termination. >>>>>>> However, you can resume an application both from savepoint and >>>>>>> checkpoints. Checkpoints can be retained [2] to avoid them being >>>>>>> deleted by >>>>>>> the application during termination. But that's considered an advanced >>>>>>> feature and you should first try it with savepoints. >>>>>>> >>>>>>> [1] >>>>>>> https://github.com/apache/flink/blob/release-1.13.0/flink-libraries/flink-state-processing-api/src/test/java/org/apache/flink/state/api/SavepointWriterITCase.java#L141-L141 >>>>>>> [2] >>>>>>> https://ci.apache.org/projects/flink/flink-docs-release-1.13/docs/ops/state/checkpoints/#retained-checkpoints >>>>>>> >>>>>>> On Mon, Jul 5, 2021 at 5:56 PM Rakshit Ramesh < >>>>>>> rakshit.ram...@datakaveri.org> wrote: >>>>>>> >>>>>>>> I'm trying to bootstrap state into a KeyedProcessFunction >>>>>>>> equivalent that takes in >>>>>>>> a DataStream but I'm unable to find a reference for the same. >>>>>>>> I found this gist >>>>>>>> https://gist.github.com/alpinegizmo/ff3d2e748287853c88f21259830b29cf >>>>>>>> But it seems to only apply for DataSet. >>>>>>>> My usecase is to manually trigger a Savepoint into s3 for later >>>>>>>> reuse. >>>>>>>> I'm also guessing that checkpoints can't be stored in rocksdb or s3 >>>>>>>> for later reuse. >>>>>>>> >>>>>>>
