Hi Stephan,

Thank you for the clarification.
Yes with RocksDB I don't see Full GC happening, also I am using Flink 1.2.0
version and I have set the statebackend in flink-conf.yaml file to rocksdb,
so by default does this do asynchronous checkpointing or I have to specify
it at the job level  ?

Regards,
Vinay Patil

On Fri, Feb 10, 2017 at 4:16 PM, Stefan Richter [via Apache Flink User
Mailing List archive.] <ml-node+s2336050n11565...@n4.nabble.com> wrote:

> Hi,
>
> FSStateBackend operates completely on-heap and only snapshots for
> checkpoints go against the file system. This is why the backend is
> typically faster for small states, but can become problematic for larger
> states. If your state exceeds a certain size, you should strongly consider
> to use RocksDB as backend. In particular, RocksDB also offers asynchronous
> snapshots which is very valuable to keep stream processing running for
> large state. RocksDB works on native memory/disk, so there is no GC to
> observe. For cases in which your state fits in memory but GC is a problem
> you could try using the G1 garbage collector which offers better
> performance for the FSStateBackend than the default.
>
> Best,
> Stefan
>
>
> Am 10.02.2017 um 11:16 schrieb Vinay Patil <[hidden email]
> <http:///user/SendEmail.jtp?type=node&node=11565&i=0>>:
>
> Hi,
>
> I am doing performance test for my pipeline keeping FSStateBackend, I have
> observed frequent Full GC's after processing 20M records.
>
> When I did memory analysis using MAT, it showed that the many objects
> maintained by Flink state are live.
>
> Flink keeps the state in memory even after checkpointing , when does this
> state gets removed / GC. (I am using window operator in which the DTO comes
> as input)
>
> Also why does Flink keep the state in memory after checkpointing ?
>
> P.S Using RocksDB is not causing Full GC at all.
>
> Regards,
> Vinay Patil
>
>
>
>
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