task assignment is quite "beefy" (sadly, or fortunately in your case, it 
favours consistence vs speed) : I don't see any reason why a single task 
gets picked up by ALL of the 12 workers at the same time if the backend 
isn't lying (i.e. slaves not replicating master data),.... if your mssql is 
"single", there shouldn't absolutely be those kind of problems...

Are you sure all are crunching the same exact task (i.e. same task id and 
uuid) ?

On Wednesday, August 17, 2016 at 2:47:11 PM UTC+2, Jason Solack wrote:
>
> I'm using nginx and MSSQL for the db
>
> On Wednesday, August 17, 2016 at 3:11:11 AM UTC-4, Niphlod wrote:
>>
>> nothing in particular. what backend are you using ?
>>
>> On Tuesday, August 16, 2016 at 8:35:17 PM UTC+2, Jason Solack wrote:
>>>
>>>         task = scheduler.queue_task(tab_run, 
>>> pvars=dict(tab_file_name=tab_file_name, the_form_file=the_form_file), 
>>> timeout=60 * 60 * 24, sync_output=2, immediate=False, 
>>> group_name=scheduler_group_name)
>>>
>>> anything look amiss here?
>>>
>>> On Tuesday, August 16, 2016 at 2:14:38 PM UTC-4, Dave S wrote:
>>>>
>>>>
>>>>
>>>> On Tuesday, August 16, 2016 at 9:38:09 AM UTC-7, Jason Solack wrote:
>>>>>
>>>>> Hello all, i am having a situation where my scheduled jobs are being 
>>>>> picked up by multiple workers.  My last task was picked up by all 12 
>>>>> workers and is crushing the machines.  This is a load balanced machine 
>>>>> with 
>>>>> 3 machine and 4 workers on each machine.  has anyone experienced 
>>>>> something 
>>>>> like this?
>>>>>
>>>>> Thanks for your help in advance!
>>>>>
>>>>> jason
>>>>>
>>>>
>>>> What does your queue_task() code look like?
>>>>
>>>> /dps
>>>>  
>>>>
>>>

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