Understanding celery task prefetching Understanding celery task prefetching python python

Understanding celery task prefetching


  1. Prefetching can improve the performance. Workers don't need to wait for the next message from a broker to process. Communicating with a broker once and processing a lot of messages gives a performance gain. Getting a message from a broker (even from a local one) is expensive compared to the local memory access. Workers are also allowed to acknowledge messages in batches

  2. Prefetching set to zero means "no specific limit" rather than unlimited

  3. Setting prefetching to 1 is documented to be equivalent to turning it off, but this may not always be the case (see https://stackoverflow.com/a/33357180/71522)

  4. Prefetching allows to ack messages in batches. CELERY_ACKS_LATE=True prevents acknowledging messages when they reach to a worker


Old question, but still adding my answer in case it helps someone. My understanding from some initial testing was same as that in David Wolever's answer. I just tested this more in celery 3.1.19 and -Ofair does work. Just that it is not meant to disable prefetch at the worker node level. That will continue to happen. Using -Ofair has a different effect which is at the pool worker level. In summary, to disable prefetch completely, do this:

  1. Set CELERYD_PREFETCH_MULTIPLIER = 1
  2. Set CELERY_ACKS_LATE = True at a global level or task level
  3. Use -Ofair while starting the workers
  4. If you set concurrency to 1, then step 3 is not needed. If you want ahigher concurrency, then step 3 is essential to avoid tasks gettingbacked up in a node that could be run long running tasks.

Adding some more details:

I found that the worker node will always prefetch by default. You can only control how many tasks it prefetches by using CELERYD_PREFETCH_MULTIPLIER. If set to 1, it will only prefetch as many tasks as the number of pool workers (concurrency) in the node. So if you had concurrency = n, the max tasks prefetched by the node will be n.

Without the -Ofair option, what happened for me was that if one of the pool worker processes was executing a long running task, the other workers in the node would also stop processing the tasks already prefetched by the node. By using -Ofair, that changed. Even though one of the workers in the node was executing a long running tasks, others would not stop processing and would continue to process the tasks prefetched by the node. So I see two levels of prefetching. One at the worker node level. The other at the individual worker level. Using -Ofair for me seemed to disable it at the worker level.

How is ACKS_LATE related? ACKS_LATE = True means that the task will be acknowledged only when the task succeeds. If not, I suppose it would happen when it is received by a worker. In case of prefetch, the task is first received by the worker (confirmed from logs) but will be executed later. I just realized that prefetched messages show up under "unacknowledged messages" in rabbitmq. So I'm not sure if setting it to True is absolutely needed. We anyway had our tasks set that way (late ack) for other reasons.


Just a warning: as of my testing with the redis broker + Celery 3.1.15, all of the advice I've read pertaining to CELERYD_PREFETCH_MULTIPLIER = 1 disabling prefetching is demonstrably false.

To demonstrate this:

  1. Set CELERYD_PREFETCH_MULTIPLIER = 1
  2. Queue up 5 tasks that will each take a few seconds (ex, time.sleep(5))
  3. Start watching the length of the task queue in Redis: watch redis-cli -c llen default

  4. Start celery worker -c 1

  5. Notice that the queue length in Redis will immediately drop from 5 to 3

CELERYD_PREFETCH_MULTIPLIER = 1 does not prevent prefetching, it simply limits the prefetching to 1 task per queue.

-Ofair, despite what the documentation says, also does not prevent prefetching.

Short of modifying the source code, I haven't found any method for entirely disabling prefetching.