Hi! Flink 1.3.2 does not yet exist. Do you mean 1.3.1 or latest master?
Can you tell us whether this occurs only in 1.3.x and worked well in 1.2.x? If you just keep the job running without savepoint/restore, you do not get into backpressure situations? Thanks, Stephan On Fri, Jul 14, 2017 at 1:15 AM, Kien Truong <duckientru...@gmail.com> wrote: > Hi Fabian, > This happens to me even when the restore is immediate, so there's not much > data in Kafka to catch up (5 minutes max) > > Regards > Kien > On Jul 13, 2017, at 23:40, Fabian Hueske <fhue...@gmail.com> wrote: >> >> I would guess that this is quite usual because the job has to "catch-up" >> work. >> For example, if you took a save point two days ago and restore the job >> today, the input data of the last two days has been written to Kafka >> (assuming Kafka as source) and needs to be processed. >> The job will now read as fast as possible from Kafka to catch-up to the >> presence. This means the data is much fast ingested (as fast as Kafka can >> read and ship it) than during regular processing (as fast as your sources >> produce). >> The processing speed is bound by your Flink job which means there will be >> backpressure. >> >> Once the job caught-up, the backpressure should disappear. >> >> Best, Fabian >> >> 2017-07-13 15:48 GMT+02:00 Kien Truong <duckientru...@gmail.com>: >> >>> Hi all, >>> >>> I have one job where back-pressure is significantly higher after >>> resuming from a save point. >>> >>> Because that job makes heavy use of stateful functions with >>> RocksDBStateBackend , >>> >>> I'm suspecting that this is the cause of performance degradation. >>> >>> Does anyone encounter simillar issues or have any tips for debugging ? >>> >>> >>> I'm using Flink 1.3.2 with YARN in detached mode. >>> >>> >>> Regards, >>> >>> Kien >>> >>> >>
