@Nico & @Piotr Could you please have a look at this? You both recently worked on the network stack and might be most familiar with this.
> On 8. Nov 2017, at 10:25, Flavio Pompermaier <pomperma...@okkam.it> wrote: > > We also have the same problem in production. At the moment the solution is to > restart the entire Flink cluster after every job.. > We've tried to reproduce this problem with a test (see > https://issues.apache.org/jira/browse/FLINK-7845 > <https://issues.apache.org/jira/browse/FLINK-7845>) but we don't know whether > the error produced by the test and the leak are correlated.. > > Best, > Flavio > > On Wed, Nov 8, 2017 at 9:51 AM, ÇETİNKAYA EBRU ÇETİNKAYA EBRU > <b20926...@cs.hacettepe.edu.tr <mailto:b20926...@cs.hacettepe.edu.tr>> wrote: > On 2017-11-07 16:53, Ufuk Celebi wrote: > Do you use any windowing? If yes, could you please share that code? If > there is no stateful operation at all, it's strange where the list > state instances are coming from. > > On Tue, Nov 7, 2017 at 2:35 PM, ebru <b20926...@cs.hacettepe.edu.tr > <mailto:b20926...@cs.hacettepe.edu.tr>> wrote: > Hi Ufuk, > > We don’t explicitly define any state descriptor. We only use map and filters > operator. We thought that gc handle clearing the flink’s internal states. > So how can we manage the memory if it is always increasing? > > - Ebru > > On 7 Nov 2017, at 16:23, Ufuk Celebi <u...@apache.org > <mailto:u...@apache.org>> wrote: > > Hey Ebru, the memory usage might be increasing as long as a job is running. > This is expected (also in the case of multiple running jobs). The > screenshots are not helpful in that regard. :-( > > What kind of stateful operations are you using? Depending on your use case, > you have to manually call `clear()` on the state instance in order to > release the managed state. > > Best, > > Ufuk > > On Tue, Nov 7, 2017 at 12:43 PM, ebru <b20926...@cs.hacettepe.edu.tr > <mailto:b20926...@cs.hacettepe.edu.tr>> wrote: > > > > Begin forwarded message: > > From: ebru <b20926...@cs.hacettepe.edu.tr > <mailto:b20926...@cs.hacettepe.edu.tr>> > Subject: Re: Flink memory leak > Date: 7 November 2017 at 14:09:17 GMT+3 > To: Ufuk Celebi <u...@apache.org <mailto:u...@apache.org>> > > Hi Ufuk, > > There are there snapshots of htop output. > 1. snapshot is initial state. > 2. snapshot is after submitted one job. > 3. Snapshot is the output of the one job with 15000 EPS. And the memory > usage is always increasing over time. > > > > > <1.png><2.png><3.png> > > On 7 Nov 2017, at 13:34, Ufuk Celebi <u...@apache.org > <mailto:u...@apache.org>> wrote: > > Hey Ebru, > > let me pull in Aljoscha (CC'd) who might have an idea what's causing this. > > Since multiple jobs are running, it will be hard to understand to > which job the state descriptors from the heap snapshot belong to. > - Is it possible to isolate the problem and reproduce the behaviour > with only a single job? > > – Ufuk > > > On Tue, Nov 7, 2017 at 10:27 AM, ÇETİNKAYA EBRU ÇETİNKAYA EBRU > <b20926...@cs.hacettepe.edu.tr <mailto:b20926...@cs.hacettepe.edu.tr>> wrote: > > Hi, > > We are using Flink 1.3.1 in production, we have one job manager and 3 task > managers in standalone mode. Recently, we've noticed that we have memory > related problems. We use docker container to serve Flink cluster. We have > 300 slots and 20 jobs are running with parallelism of 10. Also the job > count > may be change over time. Taskmanager memory usage always increases. After > job cancelation this memory usage doesn't decrease. We've tried to > investigate the problem and we've got the task manager jvm heap snapshot. > According to the jam heap analysis, possible memory leak was Flink list > state descriptor. But we are not sure that is the cause of our memory > problem. How can we solve the problem? > > > > We have two types of Flink job. One has no state full operator contains only > maps and filters and the other has time window with count trigger. > * We've analysed the jvm heaps again in different conditions. First we > analysed the snapshot when no flink jobs running on cluster. (image 1) > * Then, we analysed the jvm heap snapshot when the flink job that has no > state full operator is running. And according to the results, leak suspect > was NetworkBufferPool (image 2) > * Last analys, there were both two types of jobs running and leak suspect > was again NetworkBufferPool. (image 3) > In our system jobs are regularly cancelled and resubmitted so we noticed that > when job is submitted some amount of memory allocated and after cancelation > this allocated memory never freed. So over time memory usage is always > increasing and exceeded the limits. > >
