Bounded Streaming Applications
Apache Flink® takes a unified approach to batch and streaming data processing. The core building block is “continuous processing of unbounded data streams”: if you can do that, you can also do offline processing of bounded data sets (batch processing use cases), because these are just streams that happen to end at some point.
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Ververica Platform understands this relationship and supports running bounded streaming applications either as finite DataStream applications or through Flink’s DataSet and Table API’s. When a batch job finishes successfully, the Deployment will change to state “FINISHED”. You can see the full job lifecycle on the Jobs page.
If you want to re-run a batch job that has already run and FINISHED, you have to manually cancel the Deployment before running again.
Apache Flink® 1.12 introduced a BATCH execution mode for the DataStream API. The Ververica Platform supports this mode on a best-effort basis.