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 >>> >>
