What we want to do is cancelling the Flink job after all upstream data
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
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
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.
the data has a unique index for exactly once semantics
the signal should include the last data’s index of all partition
when the job receive the upstream stop signal
if the last data of a partition is processed, then this
partition is finished.
If all partition is finished, the job can be cancelled