Opened 5 years ago
Closed 5 years ago
#31419 closed Bug (invalid)
Django Postgres memory leak
Reported by: | Francesco Meli | Owned by: | nobody |
---|---|---|---|
Component: | Database layer (models, ORM) | Version: | 3.0 |
Severity: | Normal | Keywords: | postgresl memory-leak |
Cc: | Triage Stage: | Unreviewed | |
Has patch: | no | Needs documentation: | no |
Needs tests: | no | Patch needs improvement: | no |
Easy pickings: | no | UI/UX: | no |
Description
Note: I also wrote the detailed issue here: https://stackoverflow.com/questions/60972577/django-postgres-memory-leak
I have a custom Django (v 2.0.0) command to start background job executers in a multi-threaded fashion which seems to give me memory leak issues.
The command can be started like so:
./manage.py start_job_executer --thread=1
Each thread has a while True loop that picks up jobs from a PostgreSQL table.
In order to pick up the job and change the status atomically I used transactions:
# atomic transaction to temporary lock the db access and to # get the most recent job from db with column status = pending with transaction.atomic(): job = Job.objects.select_for_update() \ .filter(status=Job.STATUS['pending']) \ .order_by('created_at').first() if job: job.status = Job.STATUS['executing'] job.save()
Il looks like the allocated memory by this Django custom command keeps growing.
Using tracemalloc I tried to find what is causing the memory leak by creating a background thread that checks the memory allocation:
def check_memory(self): while True: s1 = tracemalloc.take_snapshot() sleep(10) s2 = tracemalloc.take_snapshot() for alog in s2.compare_to(s1, 'lineno')[:10]: log.info(alog)
Finding out the following log:
01.04.20 13:50:06 operations.py:222: size=23.7 KiB (+23.7 KiB), count=66 (+66), average=367 B 01.04.20 13:50:36 operations.py:222: size=127 KiB (+43.7 KiB), count=353 (+122), average=367 B 01.04.20 13:51:04 operations.py:222: size=251 KiB (+66.7 KiB), count=699 (+186), average=367 B 01.04.20 13:51:31 operations.py:222: size=379 KiB (+68.9 KiB), count=1056 (+192), average=367 B 01.04.20 13:51:57 operations.py:222: size=495 KiB (+60.3 KiB), count=1380 (+168), average=367 B
Looks like /usr/local/lib/python3.5/dist-packages/django/db/backends/postgresql/operations.py:222 does not release memory
The leakage is slow for 1 thread but if I use 8 threads the memory leak is worse:
01.04.20 13:07:51 operations.py:222: size=68.3 KiB (+68.3 KiB), count=191 (+191), average=366 B 01.04.20 13:08:56 operations.py:222: size=770 KiB (+140 KiB), count=2151 (+390), average=367 B 01.04.20 13:10:07 operations.py:222: size=1476 KiB (+138 KiB), count=4122 (+386), average=367 B 01.04.20 13:36:22 operations.py:222: size=17.3 MiB (+138 KiB), count=49506 (+385), average=367 B 01.04.20 13:48:16 operations.py:222: size=24.5 MiB (+136 KiB), count=69993 (+379), average=367 B
This is the code at line 222 in /usr/local/lib/python3.5/dist-packages/django/db/backends/postgresql/operations.py:222:
def last_executed_query(self, cursor, sql, params): # http://initd.org/psycopg/docs/cursor.html#cursor.query # The query attribute is a Psycopg extension to the DB API 2.0. if cursor.query is not None: return cursor.query.decode() # this is line 222! return None
I have no clue how to attack this problem. Any ideas at all?
Thanks in advance
UPDATE
I was using Django 2.0 and I thought to update to Django 3.0.5 (latest stable release), but unfortunately the problem is still there.
Below the new logs:
01.04.20 20:15:06 operations.py:235: size=977 KiB (+53.9 KiB), count=2750 (+152), average=364 B 01.04.20 20:15:28 operations.py:235: size=1070 KiB (+50.1 KiB), count=3012 (+141), average=364 B 01.04.20 20:15:53 operations.py:235: size=1156 KiB (+43.7 KiB), count=3255 (+123), average=364 B 01.04.20 20:16:19 operations.py:235: size=1245 KiB (+44.7 KiB), count=3507 (+126), average=364 B 01.04.20 20:20:23 operations.py:235: size=2154 KiB (+44.3 KiB), count=6065 (+125), average=364 B
Django keeps a reference to all executed queries in a ring buffer when
settings.DEBUG = True
From
DEBUG
documentationPlease reopen if you can reproduce without
settings.DEBUG
and please avoid using this bug tracker as a second tier support channel.