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pythoncelerycelery-task

Celery Generating group tasks from chain task


I am trying to chain following tasks with celery(v4.0),

task = group([tasks1.s(), task2.s()) | generate_job_requests.s() | execute_job.map() | aggregate_result.s()
result = task.get()

Above part is working fine upto generate_job_requests as chord. But problem starts with execute_job where it gets list of jobs from generate_job_requests, for which I need to create parallel tasks and later on aggregate result of all jobs.

I am trying to validate whether such kind of taskgraph is possible with celery ? Is there any possible alternate workflow to solve problem with such dependency ? Anything I am missing in documentation.


Solution

  • I used map like functionality with intermediate task creator which acts like chord,

    @shared_task(ignore_result=False)
    def dmap(it, callback, end_task):
        callback = subtask(callback)
        grp = group(callback.clone([arg, ]) for arg in it)
        c = (grp | end_task)
        return c()
    

    So task flow was reduced as this,

    task = (group([tasks1.s(), task2.s()) | generate_job_requests.s() | dmap.s(
            execute_job.s(), aggregate_result.s())).apply_async()
    

    For getting ultimate output of task, I did few tweaks,

    # As we get dmap task id here
    dmap_task = celery_app.AsyncResult(task.id)
    dmap_result = dmap_task.get()
    # Get actual aggregate_result task id
    aggr_res_task_id = dmap_result[0][0]
    result = celery_app.AsyncResult(aggr_res_task_id)
    # Here we receive actual output of overall task
    result.get()
    

    I referred answer