An exception makes different phenomnon

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An exception makes different phenomnon

big data
Hi all,

we have two environments for spark streaming job, which consumes Kafka
topic to do calculation.

Now in one environment, spark streaming job consume an non-standard data
from kafka and throw an excepiton(not catch it in code), then the
sreaming job is down.

But in another environment, spark streaming job also throw an exception(
same exception message in log file), but the streaming job is still
running and consume other data continuously.

Is there some parameters or configuration for this problem? Why one job
is down and another job is still running.



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An exception makes different phenomnon

big data

> Hi all,
>
> we have two environments for spark streaming job, which consumes Kafka
> topic to do calculation.
>
> Now in one environment, spark streaming job consume an non-standard
> data from kafka and throw an excepiton(not catch it in code), then the
> sreaming job is down.
>
> But in another environment, spark streaming job also throw an
> exception( same exception message in log file), but the streaming job
> is still running and consume other data continuously.
>
> Is there some parameters or configuration for this problem? Why one
> job is down and another job is still running.
>
>


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