ehm, missing something here: worker(s) do(es) auto-assignments of tasks. there's no web2py involved in assigning task to a particular worker. Said that, I'd run one worker if there are no requisites like "I need function1 and function2 to run concurrently", in which case, start 2 workers, they'll split the jobs.
On Friday, November 9, 2012 7:59:04 AM UTC+1, Amit wrote: > > Hi, > I have more than 10 functions which has to be executed by Scheduler and > each task has assigned different time ( for e.g...one has to execute on > every 15 minutes, other one has to executes on every 24 hrs etc... ) to > execute, so in my CustomScheduler.py module : I wiil have 10 different > statements like below: > > > db.scheduler_task.validate_and_insert( > function_name='func1', > args='[]', > repeats = 0, # run indefinately > period = 3600, # every 1h > timeout = 120, # should take less than 120 seconds > ) > > > > db.scheduler_task.validate_and_insert( > function_name='func2', > args='[]', > repeats = 0, # run indefinately > period = 900, # every 15 min > timeout = 120, # should take less than 120 seconds > ) > > My doubt is what will be the better optimized approach to assign those > 10 tasks to Scheduler: > > 1. Create only one worker using *web2py -K appname* command for all > tasks, which will further takes care of running all tasks at designated > time OR > 2. Create 10 different workers means execute above command 10 times and > then web2py takes care of assigning the task to each worker. > > which will be the best optimized way to use web2py scheduler? > > Regards, > Amit > > --
