Hi Georg, I'm not aware of those examples being available publicly.
Best regards, Martijn On Mon, 9 May 2022 at 23:04, Georg Heiler <georg.kf.hei...@gmail.com> wrote: > Hi Martijn, > > many thanks for this clarification. Do you know of any example somewhere > which would showcase such an approach? > > Best, > Georg > > Am Mo., 9. Mai 2022 um 14:45 Uhr schrieb Martijn Visser < > martijnvis...@apache.org>: > >> Hi Georg, >> >> No they wouldn't. There is no capability out of the box that lets you >> start Flink in streaming mode, run everything that's available at that >> moment and then stops when there's no data anymore. You would need to >> trigger the stop yourself. >> >> Best regards, >> >> Martijn >> >> On Fri, 6 May 2022 at 13:37, Georg Heiler <georg.kf.hei...@gmail.com> >> wrote: >> >>> Hi, >>> >>> I would disagree: >>> In the case of spark, it is a streaming application that is offering >>> full streaming semantics (but with less cost and bigger latency) as it >>> triggers less often. In particular, windowing and stateful semantics as >>> well as late-arriving data are handled automatically using the regular >>> streaming features. >>> >>> Would these features be available in a Flink Batch job as well? >>> >>> Best, >>> Georg >>> >>> Am Fr., 6. Mai 2022 um 13:26 Uhr schrieb Martijn Visser < >>> martijnvis...@apache.org>: >>> >>>> Hi Georg, >>>> >>>> Flink batch applications run until all their input is processed. When >>>> that's the case, the application finishes. You can read more about this in >>>> the documentation for DataStream [1] or Table API [2]. I think this matches >>>> the same as Spark is explaining in the documentation. >>>> >>>> Best regards, >>>> >>>> Martijn >>>> >>>> [1] >>>> https://nightlies.apache.org/flink/flink-docs-master/docs/dev/datastream/execution_mode/ >>>> [2] >>>> https://nightlies.apache.org/flink/flink-docs-master/docs/dev/table/common/ >>>> >>>> On Mon, 2 May 2022 at 16:46, Georg Heiler <georg.kf.hei...@gmail.com> >>>> wrote: >>>> >>>>> Hi, >>>>> >>>>> spark >>>>> https://spark.apache.org/docs/latest/structured-streaming-programming-guide.html#triggers >>>>> offers a variety of triggers. >>>>> >>>>> In particular, it also has the "once" mode: >>>>> >>>>> *One-time micro-batch* The query will execute *only one* micro-batch >>>>> to process all the available data and then stop on its own. This is useful >>>>> in scenarios you want to periodically spin up a cluster, process >>>>> everything >>>>> that is available since the last period, and then shutdown the cluster. In >>>>> some case, this may lead to significant cost savings. >>>>> >>>>> Does flink have a similar possibility? >>>>> >>>>> Best, >>>>> Georg >>>>> >>>>
