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From Aljoscha Krettek <aljos...@apache.org>
Subject Re: Error handling
Date Sat, 14 Nov 2015 21:00:02 GMT
Hi Nick,
these are some interesting Ideas. I have been thinking about this, maybe we can add a special
output stream (for example Kafka, but can be generic) that would get errors/exceptions that
where throws during processing. The actual processing would not stop and the messages in this
special stream would contain some information about the current state of processing, the input
element(s) and the machine/VM where computation is happening.

In cascading you get the erroneous tuples at the end. This is not possible in streaming, therefore
the more stream-y approach/solution.

What do you think about that?

> On 11 Nov 2015, at 21:49, Nick Dimiduk <ndimiduk@gmail.com> wrote:
> Heya,
> I don't see a section in the online manual dedicated to this topic, so I want to raise
the question here: How should errors be handled? Specifically I'm thinking about streaming
jobs, which are expected to "never go down". For example, errors can be raised at the point
where objects are serialized to/from sources/sinks, and UDFs. Cascading provides failure traps
[0] where erroneous tuples are saved off for post-processing. Is there any such functionality
in Flink?
> I started down the road of implementing a Maybe/Optional type, a POJO Generic triple
of <IN, OUT, Throwable> for capturing errors at each stage of a pipeline. However, Java
type erasure means even though it compiles, the job is rejected at submission time.
> How are other people handling errors in their stream processing?
> Thanks,
> Nick
> [0]: http://docs.cascading.org/cascading/1.2/userguide/html/ch06s03.html

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