I'm looping in Till and Aljoscha who might have some thoughts on this as well.I'm not sure if this behavior is already supported, but think this would be a desirable feature.Hi Flavio,Thanks for bringing up this topic.I think running periodic jobs with state that gets restored and persisted in a savepoint is a very valid use case and would fit the stream is a superset of batch story quite well.Depending on the discussion we should open a JIRA for this feature.Cheers, Fabian2017-10-25 10:31 GMT+02:00 Flavio Pompermaier <[hidden email]>:Hi to all,in my current use case I'd like to improve one step of our batch pipeline.There's one specific job that ingest a tabular dataset (of Rows) and explode it into a set of RDF statements (as Tuples). The objects we output are a containers of those Tuples (grouped by a field).Flink stateful streaming could be a perfect fit here because we incrementally increase the state of those containers but we don't have to spend a lot of time performing some GET operation to an external Key-value store.The big problem here is that the sources are finite and the state of the job gets lost once the job ends, while I was expecting that Flink was snapshotting the state of its operators before exiting.This idea was inspired by https://data-artisans.com/blog/queryable-state-use-case-d , whit the difference that one can resume the state of the stateful application only when required.emo#no-external-store Do you think that it could be possible to support such a use case (that we can summarize as "periodic batch jobs that pick up where they left")?
Best,Flavio
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