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From Yassine MARZOUGUI <y.marzou...@mindlytix.com>
Subject Re: Checkpoints very slow with high backpressure
Date Mon, 24 Apr 2017 07:32:16 GMT
Im sorry guys if you received multiple instances of this mail, I kept
trying to send it yesterday, but looks like the mailing list was stuck and
didn't dispatch it until now. Sorry for the disturb.

On Apr 23, 2017 20:53, "Yassine MARZOUGUI" <y.marzougui@mindlytix.com>
wrote:

> Hi all,
>
> I have a Streaming pipeline as follows:
> 1 - read a folder continuousely from HDFS
> 2 - filter duplicates (using keyby(x->x) and keeping a state per key
> indicating whether its is seen)
> 3 - schedule some future actions on the stream using ProcessFunction and
> processing time timers (elements are kept in a MapState)
> 4- write results back to HDFS using a BucketingSink.
>
> I am using RocksdbStateBackend, and Flink 1.3-SNAPSHOT (Commit: 9fb074c).
>
> Currenlty the source contain just one a file of 1GB, so that's the maximum
> state that the job might hold. I noticed that the backpressure on the
> operators #1 and #2 is High, and the split reader has only read 60 Mb out
> of 1Gb source source file. I suspect this is because the ProcessFunction is
> slow (on purpose). However looks like this affected the checkpoints which
> are failing after the timeout (which is set to 2 hours), see attached
> screenshot.
>
>
> ‚Äč
> In the job manager logs I keep getting warnings :
>
> 2017-04-23 19:32:38,827 WARN  org.apache.flink.runtime.checkpoint.CheckpointCoordinator
    - Received late message for now expired checkpoint attempt 8 from 210769a077c67841d980776d8caece0a
of job 6c7e44d205d738fc8a6cb4da181d2d86.
>
> Is the high backpressure the cause for the checkpoints being too slow? If
> yes Is there a way to disbale the backpressure mechanism since the records
> will be buffered in the rocksdb state after all which is backed by the disk?
>
> Thank you.
>
> Best,
> Yassine
>
>

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