Hi, have you tried letting your source also implement the StoppableFunction interface as suggested by the SourceFunction javadoc?
If a source is stopped, e.g. after identifying some special signal from the outside, it will continue processing all remaining events and the Flink program will shut down gracefully. Is that what you intend to do? Nico On Monday, 14 August 2017 11:15:22 CEST Zor X.L. wrote: > Bump... > > 在 2017/8/11 9:36, Zor X.L. 写道: > > Hi, > > > > What we want to do is cancelling the Flink job after all upstream data > > were processed. > > We use Kafka as our input and output, and use the SQL capability of > > Table API by the way. > > > > A possible solution is: > > * > > > > embed a stop message at the tail of upstream > > > > * > > > > do what should be done in the Flink Job > > > > * > > > > propagate this stop message to downstream untouched after all data > > are processed > > > > * > > > > a downstream monitoring program can thus know if all subtasks are > > finished processing all upstream data > > > > * > > > > then cancel the job > > > > *What we want to do is canelling the job safely without utilizing this > > kind of stop message.* > > > > *But I find this is hard or inefficient to implement in Flink… is it > > possible?* > > > > P.S. If not utilizing Flink, a possible solution is: > > * > > > > the upstream program write a stop signal some where after all data > > were written to Kafka. > > > > o > > > > the data has a unique index for exactly once semantics > > > > o > > > > the signal should include the last data’s index of all partition > > > > * > > > > when the job receive the upstream stop signal > > > > o > > > > if the last data of a partition is processed, then this > > partition is finished. > > > > o > > > > If all partition is finished, the job can be cancelled > > > >
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