Reputation: 21
I have to schedule some tasks which seem very complex to run in parallel. They do not depend on the result of each other and the function expects 3 arguments.
I already tried using chain, map and starmap methods. With chain I get this error:
[2019-04-23 15:28:00,991: ERROR/PoolWorker-3] Task proj.apps.tasks.generate[112a7426-5ac3-4cd6-8416-5591c3c018a3] raised unexpected: TypeError('get expected at least 1 arguments, got 0',)
Traceback (most recent call last):
File ".../local/lib/python2.7/site-packages/celery/app/trace.py", line 367, in trace_task
R = retval = fun(*args, **kwargs)
File ".../local/lib/python2.7/site-packages/celery/app/trace.py", line 622, in __protected_call__
return self.run(*args, **kwargs)
File ".../tasks.py", line 966, in generate
return res.get()
TypeError: get expected at least 1 arguments, got 0
Using map
I cannot pass all the arguments and with starmap
all the tasks are started simultaneously.
[2019-04-23 15:48:00,991: INFO/MainProcess] Received task: generate[..]
[2019-04-23 15:48:00,991: INFO/MainProcess] Received task: generate[..]
[2019-04-23 15:48:00,991: INFO/MainProcess] Received task: generate[..]
An example of the task:
@shared_task
def generate(field1, field2, field3=None):
if field3 is not None:
return field1 + field2 + field3
return field1 + field2
Code using chain:
res = chain(generate.s(i, 5, j) for i in array1 for j in array2)
return res.get()
Code using starmap:
arguments = [(i, 4, j) for i in array1 for j in array2]
~generate.starmap(arguments)
Upvotes: 1
Views: 2633
Reputation: 21
All I needed to do was to make a chain, as below:
res = chain(generate(i, 2, j)for i in array1 for j in array2)()
return res.get()
and then run celery with a additional argument that sets the maximum number of threads
celery -A tasks worker --concurrency=1
Upvotes: 1
Reputation: 15926
if the tasks are truly independent, you should be using .si
and not .s
:
tasks = chain(generate.si(i, 5, j) for i in array1 for j in array2)
res = tasks()
return res.get()
Upvotes: 1