So after more investigation we are seeing that our load balanced server with processes runnin on all three machines are causing a lot of deadlocks in MSSQL. Have you seen that before?
On Friday, August 19, 2016 at 2:40:35 AM UTC-4, Niphlod wrote: > > yep. your worker setup clearly can't stably be connected to your backend. > > On Thursday, August 18, 2016 at 7:41:38 PM UTC+2, Jason Solack wrote: >> >> so after some digging what i'm seeing is the sw.insert(...) is not >> committing and the mybackedstatus is None, this happens 5 times and then >> the worker appears and almost instantly disappers. There are no errors. i >> tried manually doing a db.executesql but i'm having trouble getting >> self.w_stats converted to something i can insert via sql. >> >> another things i'm noticing is my "distribution" in w_stats is None... >> >> Any ideas as to why this is happening? >> >> On Thursday, August 18, 2016 at 12:21:26 PM UTC-4, Jason Solack wrote: >>> >>> doing that now, what i'm seeing is some problems here: >>> >>> # record heartbeat >>> mybackedstatus = db(sw.worker_name == self >>> .worker_name).select().first() >>> if not mybackedstatus: >>> sw.insert(status=ACTIVE, worker_name=self.worker_name, >>> first_heartbeat=now, last_heartbeat=now, >>> group_names=self.group_names, >>> worker_stats=self.w_stats) >>> self.w_stats.status = ACTIVE >>> self.w_stats.sleep = self.heartbeat >>> mybackedstatus = ACTIVE >>> >>> mybackedstatus is consistently coming back as "None" i'm guessing there >>> is an error somewhere in that try block and the db commit is being rolled >>> back >>> >>> i'm using MSSQL and nginx... currently upgrading web2py to see it >>> continues >>> >>> >>> >>> On Thursday, August 18, 2016 at 10:44:28 AM UTC-4, Niphlod wrote: >>>> >>>> turn on workers debugging level and grep for errors. >>>> >>>> On Thursday, August 18, 2016 at 4:38:31 PM UTC+2, Jason Solack wrote: >>>>> >>>>> I think we have this scenario happening: >>>>> >>>>> >>>>> https://groups.google.com/forum/#%21searchin/web2py/task_id%7csort:relevance/web2py/AYH5IzCIEMo/hY6aNplbGX8J >>>>> >>>>> our workers seems to be restarting quickly and we're trying to figure >>>>> out why >>>>> >>>>> On Thursday, August 18, 2016 at 3:55:55 AM UTC-4, Niphlod wrote: >>>>>> >>>>>> small recap.......a single worker is tasked with assigning tasks (the >>>>>> one with is_ticker=True) and then that task is picked up only by the >>>>>> assigned worker (you can see it on the >>>>>> scheduler_task.assigned_worker_name >>>>>> column of the task). >>>>>> There's no way the same task (i.e. a scheduler_task "row") is >>>>>> executed while it is RUNNING (i.e. processed by some worker). >>>>>> The process running the task is stored also in >>>>>> scheduler_run.worker_name. >>>>>> >>>>>> <tl;dr> you shouldn't EVER have scheduler_run records with the same >>>>>> task_id and 12 different worker_name all in the RUNNING status. >>>>>> >>>>>> For a single task to be processed by ALL 12 workers at the same >>>>>> time... is quite impossible, if everything is running smoothly. And >>>>>> frankly >>>>>> I can't fathom any scenario in which it is possible. >>>>>> >>>>>> >>>>>> On Wednesday, August 17, 2016 at 6:25:41 PM UTC+2, Jason Solack wrote: >>>>>>> >>>>>>> I only see the task_id in the scheduler_run table, it seems to be >>>>>>> added as many times as it can while the run is going... a short run >>>>>>> will >>>>>>> add just 2 of the workers and stop adding them once the initial run is >>>>>>> completed >>>>>>> >>>>>>> On Wednesday, August 17, 2016 at 11:15:52 AM UTC-4, Niphlod wrote: >>>>>>>> >>>>>>>> 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 >>>>>>>>>>>> >>>>>>>>>>>> >>>>>>>>>>> -- Resources: - http://web2py.com - http://web2py.com/book (Documentation) - http://github.com/web2py/web2py (Source code) - https://code.google.com/p/web2py/issues/list (Report Issues) --- You received this message because you are subscribed to the Google Groups "web2py-users" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. For more options, visit https://groups.google.com/d/optout.
