Currently, Flink does not cache anything across runs, except JAR files on
the workers.

The reason the first run is slower may be:
 - Because in the first run, code is distributed in the cluster. In
subsequent runs, the JAR files need not be redistributed.
 - Because the JIT takes a bit to kick in and compile code in the first
run. In subsequent runs, the code is already JIT-ted.


The system should not freeze after 100 runs. Can you tell us a bit more of
what you see? Can you identify which process hangs and send us a
stack-trace of that one? Then we could look into this...



On Tue, Jun 23, 2015 at 10:56 AM, Pa Rö <paul.roewer1...@googlemail.com>
wrote:

> hi flink community,
>
> to time i test my flink app with a benchmark on an hadoop cluster (flink
> on yarn).
> my results show me that flink need for the first round more time as all
> other rounds. maybe flink cache something in memory? and if i run the
> benchmark 100 rounds my system freeze, i think the memory is full. give it
> a way to flush the memory after the execution?
>
> best regards,
> paul
>

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