Answer: MySQL has default isolation level set to REPEATABLE-READ, if you don’t really need that, set it to READ-COMMITTED. You can do that by adding the following to your my.cnf:
[mysqld]
transaction-isolation = READ-COMMITTED
For more information about InnoDBs transaction model see MySQL - The InnoDB Transaction Model and Locking in the MySQL user manual.
(Thanks to Honza Kral and Anton Tsigularov for this solution)
Answer: amqplib hangs if it isn’t able to authenticate to the AMQP server, so make sure you are able to access the configured vhost using the user and password.
Answer: multiprocessing.Pool requires a working POSIX semaphore implementation which isn’t enabled in FreeBSD by default. You have to enable POSIX semaphores in the kernel and manually recompile multiprocessing.
Answer: See MySQL is throwing deadlock errors, what can I do?. Thanks to howsthedotcom.
Answer: Did you register the task in the applications tasks.py module? (or in some other module Django loads by default, like models.py?). Also there might be syntax errors preventing the tasks module being imported.
You can find out if the celery daemon is able to run the task by executing the task manually:
>>> from myapp.tasks import MyPeriodicTask
>>> MyPeriodicTask.delay()
Watch celery daemons logfile (or output if not running as a daemon), to see if it’s able to find the task, or if some other error is happening.
Answer: See Why won’t my Task run?.
Answer: Use celery.task.discard_all(), like this:
>>> from celery.task import discard_all
>>> discard_all()
1753
The number 1753 is the number of messages deleted.
You can also start celeryd with the --discard argument which will accomplish the same thing.
Answer: Tasks are acknowledged (removed from the queue) as soon as they are actually executed. After the worker has received a task, it will take some time until it is actually executed, especially if there are a lot of tasks already waiting for execution. Messages that are not acknowledged are hold on to by the worker until it closes the connection to the broker (AMQP server). When that connection is closed (e.g because the worker was stopped) the tasks will be re-sent by the broker to the next available worker (or the same worker when it has been restarted), so to properly purge the queue of waiting tasks you have to stop all the workers, and then discard the tasks using discard_all.
Answer: Yes. But this is somewhat experimental for now. It is certainly working ok for me in a test configuration, but it has not been tested in production like RabbitMQ. If you have any problems with using STOMP and celery, please report the bugs to the issue tracker:
http://github.com/ask/celery/issues/
First you have to use the master branch of celery:
$ git clone git://github.com/ask/celery.git
$ cd celery
$ sudo python setup.py install
$ cd ..
Then you need to install the stompbackend branch of carrot:
$ git clone git://github.com/ask/carrot.git
$ cd carrot
$ git checkout stompbackend
$ sudo python setup.py install
$ cd ..
And my fork of python-stomp which adds non-blocking support:
$ hg clone http://bitbucket.org/asksol/python-stomp/
$ cd python-stomp
$ sudo python setup.py install
$ cd ..
In this example we will use a queue called celery which we created in the ActiveMQ web admin interface.
Note: For ActiveMQ the queue name has to have "/queue/" prepended to it. i.e. the queue celery becomes /queue/celery.
Since a STOMP queue is a single named entity and it doesn’t have the routing capabilities of AMQP you need to set both the queue, and exchange settings to your queue name. This is a minor inconvenience since carrot needs to maintain the same interface for both AMQP and STOMP (obviously the one with the most capabilities won).
Use the following specific settings in your settings.py:
# Makes python-stomp the default backend for carrot.
CARROT_BACKEND = "stomp"
# STOMP hostname and port settings.
AMQP_HOST = "localhost"
AMQP_PORT = 61613
# The queue name to use (both queue and exchange must be set to the
# same queue name when using STOMP)
CELERY_AMQP_CONSUMER_QUEUE = "/queue/celery"
CELERY_AMQP_EXCHANGE = "/queue/celery"
Now you can go on reading the tutorial in the README, ignoring any AMQP specific options.
This is a (possible incomplete) list of features not available when using the STOMP backend:
Answer: As of now there is only one use-case that works like this, and that is tasks of type A can be sent to servers x and y, while tasks of type B can be sent to server z. One server can’t handle more than one routing_key, but this is coming in a later release.
Say you have two servers, x, and y that handles regular tasks, and one server z, that only handles feed related tasks, you can use this configuration:
- Servers x and y: settings.py:
AMQP_SERVER = "rabbit" AMQP_PORT = 5678 AMQP_USER = "myapp" AMQP_PASSWORD = "secret" AMQP_VHOST = "myapp" CELERY_AMQP_CONSUMER_QUEUE = "regular_tasks" CELERY_AMQP_EXCHANGE = "tasks" CELERY_AMQP_PUBLISHER_ROUTING_KEY = "task.regular" CELERY_AMQP_CONSUMER_ROUTING_KEY = "task.#" CELERY_AMQP_EXCHANGE_TYPE = "topic"
- Server z: settings.py:
AMQP_SERVER = "rabbit" AMQP_PORT = 5678 AMQP_USER = "myapp" AMQP_PASSWORD = "secret" AMQP_VHOST = "myapp" CELERY_AMQP_EXCHANGE = "tasks" CELERY_AMQP_PUBLISHER_ROUTING_KEY = "task.regular" CELERY_AMQP_EXCHANGE_TYPE = "topic" # This is the settings different for this server: CELERY_AMQP_CONSUMER_QUEUE = "feed_tasks" CELERY_AMQP_CONSUMER_ROUTING_KEY = "feed.#"
Now to make a Task run on the z server you need to set its routing_key attribute so it starts with the words "task.feed.":
from feedaggregator.models import Feed
from celery.task import Task
class FeedImportTask(Task):
routing_key = "feed.importer"
def run(self, feed_url):
# something importing the feed
Feed.objects.import_feed(feed_url)
You can also override this using the routing_key argument to celery.task.apply_async():
>>> from celery.task import apply_async
>>> from myapp.tasks import RefreshFeedTask
>>> apply_async(RefreshFeedTask, args=["http://cnn.com/rss"],
... routing_key="feed.importer")
Answer: Yes.
Celery uses something called loaders to read/setup configuration, import modules that registers tasks and to decide what happens when a task is executed. Currently there are two loaders, the default loader and the Django loader. If you want to use celery without a Django project, you either have to use the default loader, or write a loader of your own.
The rest of this answer describes how to use the default loader.
First of all, installation. You need to get the development version of celery from github:
$ git clone git://github.com/ask/celery.git
$ cd celery
# python setup.py install # as root
While it is possible to use celery from outside of Django, we still need Django itself to run, this is to use the ORM and cache-framework, etc. Duplicating these features would be time consuming and mostly pointless, so we decided that having a dependency on Django itself was a good thing. Install Django using your favorite install tool, easy_install, pip, or whatever:
# easy_install django # as root
You need a configuration file named celeryconfig.py, either in the directory you run celeryd in, or in a Python library path where it is able to find it. The configuration file can contain any of the settings described in celery.conf, and in additional if you’re using the database backend you have to configure the database. Here is an example configuration using the database backend with MySQL:
# Broker configuration
AMQP_SERVER = "localhost"
AMQP_PORT = "5672"
AMQP_VHOST = "celery"
AMQP_USER = "celery"
AMQP_PASSWORD = "celerysecret"
CARROT_BACKEND="amqp"
# Using the database backend.
CELERY_BACKEND = "database"
DATABASE_ENGINE = "mysql" # see Django docs for a description of these.
DATABASE_NAME = "mydb"
DATABASE_HOST = "mydb.example.org"
DATABASE_USER = "myuser"
DATABASE_PASSWORD = "mysecret"
# Number of processes that processes tasks simultaneously.
CELERYD_CONCURRENCY = 8
# Modules to import when celeryd starts.
# This must import every module where you register tasks so celeryd
# is able to find and run them.
CELERY_IMPORTS = ("mytaskmodule1", "mytaskmodule2")
Now with this configuration file in the current directory you have to run celeryinit to create the database tables:
$ celeryinit
Then you should be able to successfully run celeryd:
$ celeryd --loglevel=INFO
and send a task from a python shell (note that it must be able to import celeryconfig.py):
>>> from celery.task.builtins import PingTask
>>> result = PingTask.apply_async()
>>> result.get()
'pong'