Hi,

I'm quite new to the world of stream and batch processing. I've been
reading about pipelined regions in Flink and am quite confused by what it
means. My specific problem involves a streaming job that looks like the
following:

1. There is a Kafka source that takes in an input data that sets off a
series of operations
2. As part of the first operation, I have an operator that produces
multiple values, each of which has to be fed into several different
operators in parallel
3. The operators each produce a result which I keyBy and merge together
using the union operator
4. The merged result is then written to a Kafka sink

The problem is that when one of the parallel operators throws an exception,
all the tasks in the entire pipeline gets restarted including the source
which then replays the input data and the process starts off once again. My
question is if it's possible to make the tasks of only the branch that
failed restart rather than the whole job. I do realize that it is possible
to split up the job such that the first operator produces its output to a
sink and having that as the source to the subsequent operations can
mitigate the problem. I was just wondering if it's possible in the scenario
that I have described above. In general, how can I "create" a pipelined
region?


Thanks,
Sunny

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