Hey David,
Thanks for the feedback.
> For streaming, this is probably something we could address by
book-keeping jobs submitted by the jar and canceling them on exception.
I considered two options. 1/ cancel on error as you proposed. This has the
downside that it could start processing data temp
Hi Danny,
> My current proposal is that the REST API should not leave the Flink
cluster
in an inconsistent state.
Regarding consistency, Flink only cares about individual jobs, but I can
see your point.
For streaming, this is probably something we could address by book-keeping
jobs submitted by
Hey all,
We run Flink clusters in session mode; we upload the user jar and then
invoke "/jars/:jarid/run" [1] REST API endpoint. We have noticed a
discrepancy in the run endpoint and were hoping to get some feedback from
the community before proposing a FLIP or Jira to fix it.
Some problem contex
