понедельник, 29 марта 2021 г. в 19:37:03 UTC+3, Dieter Maurer: > Alexey wrote at 2021-3-29 06:26 -0700: > >понедельник, 29 марта 2021 г. в 15:57:43 UTC+3, Julio Oña: > >> It looks like the problem is on celery. > >> The mentioned issue is still open, so not sure if it was corrected. > >> > >> https://manhtai.github.io/posts/memory-leak-in-celery/ > > > >As I mentioned in my first message, I tried to run > >this task(class) via Flask API calls, without Celery. > >And results are the same. Flask worker receives the API call and > >executes MyClass().run() inside of view. After a few calls > >worker size increases to 1Gb of RAM. In production I have 8 workers, > > so in idle they will hold 8Gb. > Depending on your system (this works for `glibc` systems), > you can instruct the memory management via the envvar > `MALLOC_ARENA_MAX` to use a common memory pool (called "arena") > for all threads. > It is known that this can drastically reduce memory consumption > in multi thread systems.
Tried with this variable. No luck. Thanks anyway. -- https://mail.python.org/mailman/listinfo/python-list
