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I have a setup where I'm using Celery as the task queue with Amazon SQS FIFO. My goal is to ensure sequential processing of tasks within the same message group ID, while allowing tasks with different message group IDs to be processed in parallel. However, despite following the recommended configurations and understanding the behavior of SQS message groups, I'm experiencing parallel processing of tasks within the same message group by multiple Celery worker processes. How can I ensure that tasks with the same message group ID are processed sequentially by a single worker process, while maintaining parallel processing for tasks with different message group IDs?

Some extra details (for reference) : For celery I haven't used --concurrency setting, so it is by default spawning 4 pool processes (no. of cores). I am passing message group id using following syntax :

    message_properties = {
        "MessageGroupId": f"{supplier_id}"
    }
    celery_task.s(
        param1, **message_properties
    ).apply_async(**message_properties)

and I have made sure the queue is fifo and it ends with .fifo . additional settings - { 'polling_interval': 60, 'wait_time_seconds': 10, 'visibility_timeout': 600 }

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I tried to play around with the settings but nothing seems to work. Even with the same group ids the task are still being processed in parallel by spawned processes of celery worker.

Manish Patel
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1 Answers1

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I am not sure exactly but you can try this celery configuration prefetch_multiplier=1 Check this documentation

The prefetch limit is a limit for the number of tasks (messages) a worker can reserve for itself.

And you can also set the concurrency=1

With these both setting each worker will process one request at a time per Group ID hence we could achieve the sequential message processing.

Madiha Khalid
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  • yes but it take a hit on performance. By using amazon sqs fifo , I wanted to run the other tasks parallely but only the tasks within the same message group to be executed sequentially which is not happening. Setting concurrency to 1 may work as workaround but I don't see it as a solution. – Manish Patel Jul 12 '23 at 06:46