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 >
