Hi Julien,
AFAIK, streaming jobs put data objects on heap, so the it depends on the JVM GC to release the memory. Best, Paul Lam > 在 2018年10月12日，14:29，jpreis...@free.fr 写道： > > Hi, > > My use case is : > - I use Flink 1.4.1 in standalone cluster with 5 VM (1 VM = 1 JobManager + 1 > TaskManager) > - I run N jobs per days. N may vary (one day : N=20, another day : N=50, > ...). All jobs are the same. They connect to Kafka topics and have two DB2 > connector. > - Depending on a special event, a job can self-restart via the command : > bin/flink cancel <JobID> > - At the end of the day, I cancel all jobs > - Each VM is configured with 16Gb RAM > - Allocated memory configured for one taskmanager is 10Gb > > After several days, the memory saturates (we exceed 14Gb of used memory). > > I read the following posts but I did not succeed in understanding my problem : > - https://flink.apache.org/news/2015/05/11/Juggling-with-Bits-and-Bytes.html > - http://mail-archives.apache.org/mod_mbox/flink-user/201711.mbox/browser > > I did some tests on a machine (outside the cluster) with the top command and > this is what I concluded (please see attached file - Flink_memory.PNG) : > - When a job is started and running, it consumes memory > - When a job is cancelled, a large part of the memory is still used > - When another job is started and running (after to have cancel the previous > job), even more memory is consumed > - When I restart jobmanager and taskmanager, memory returns to normal > > Why when a job is canceled, the memory is not released? > > I added another attachment that represents the graph of a job - Graph.PNG. > If it can be useful we use MapFunction, FlatMapFunction, FilterFunction, > triggers and windows, ... > > Thanks in advance, > Julien<Flink_memory.xlsx><Graph.PNG><Flink_memory.PNG>
