Celery does not release memory

Question

It looks like celery does not release memory after task finished. Every time a task finishes, there would be 5m-10m memory leak. So with thousands of tasks, soon it will use up all memory.

BROKER_URL = 'amqp://user@localhost:5672/vhost'
# CELERY_RESULT_BACKEND = 'amqp://user@localhost:5672/vhost'

CELERY_IMPORTS = (
    'tasks.tasks',
)

CELERY_IGNORE_RESULT = True
CELERY_DISABLE_RATE_LIMITS = True
# CELERY_ACKS_LATE = True
CELERY_TASK_RESULT_EXPIRES = 3600
# maximum time for a task to execute
CELERYD_TASK_TIME_LIMIT = 600
CELERY_DEFAULT_ROUTING_KEY = "default"
CELERY_DEFAULT_QUEUE = 'default'
CELERY_DEFAULT_EXCHANGE = "default"
CELERY_DEFAULT_EXCHANGE_TYPE = "direct"
# CELERYD_MAX_TASKS_PER_CHILD = 50
CELERY_DISABLE_RATE_LIMITS = True
CELERYD_CONCURRENCY = 2

Might be same with issue, but it does not has an answer: RabbitMQ/Celery/Django Memory Leak?

I am not using django, and my packages are:

Chameleon==2.11
Fabric==1.6.0
Mako==0.8.0
MarkupSafe==0.15
MySQL-python==1.2.4
Paste==1.7.5.1
PasteDeploy==1.5.0
SQLAlchemy==0.8.1
WebOb==1.2.3
altgraph==0.10.2
amqp==1.0.11
anyjson==0.3.3
argparse==1.2.1
billiard==2.7.3.28
biplist==0.5
celery==3.0.19
chaussette==0.9
distribute==0.6.34
flower==0.5.1
gevent==0.13.8
greenlet==0.4.1
kombu==2.5.10
macholib==1.5.1
objgraph==1.7.2
paramiko==1.10.1
pycrypto==2.6
pyes==0.20.0
pyramid==1.4.1
python-dateutil==2.1
redis==2.7.6
repoze.lru==0.6
requests==1.2.3
six==1.3.0
tornado==3.1
translationstring==1.1
urllib3==1.6
venusian==1.0a8
wsgiref==0.1.2
zope.deprecation==4.0.2
zope.interface==4.0.5

I just added a test task like, test_string is a big string, and it still has memory leak:

@celery.task(ignore_result=True)
def process_crash_xml(test_string, client_ip, request_timestamp):
    logger.info("%s %s" % (client_ip, request_timestamp))
    test = [test_string] * 5

Answer 1

It was this config option that made my worker does not release memory.

CELERYD_TASK_TIME_LIMIT = 600

refer to: https://github.com/celery/celery/issues/1427

Answer 2

There are two settings which can help you mitigate growing memory consumption of celery workers:

• Max tasks per child setting (v2.0+):

  With this option you can configure the maximum number of tasks a worker can execute before it’s replaced by a new process. This is useful if you have memory leaks you have no control over for example from closed source C extensions.

• Max memory per child setting (v4.0+):

  With this option you can configure the maximum amount of resident memory a worker can execute before it’s replaced by a new process. This is useful if you have memory leaks you have no control over for example from closed source C extensions.