I think that the probability calculation holds only if there is no correlation between different schedulers. I think however there might be an accidental correlation if you think about typical deployments.
Some details why I think accidental correlation is possible and even likely. Assume that: - we have similar and similarly busy machines running schedulers (likely) - time is synchronised between the machines (likely) - the machines have the same DAG folders mounted (or copied) and the same filesystem is used (this is exactly what multiple schedulers deployment is all about) - the schedulers start scanning at exactly the same time (crossing 0:00 second every full five minutes for example) - this I am not sure but I imagine this might be "typical" behaviour. - they process list of DAGs in exactly the same sequence (it looks like this is the case dag_processing <https://github.com/apache/airflow/blob/master/airflow/utils/dag_processing.py#L300> and models/__init__ <https://github.com/apache/airflow/blob/master/airflow/models/__init__.py#L567>: we use os.walk which uses os.listdir for which sequence of processing depends on the filesystem implementation <https://stackoverflow.com/questions/31534583/is-os-listdir-deterministic> and then we append files to the list) Then it's rather likely that the schedulers will be competing about the very same DAGs at the very beginning. Locking will change how quickly they process each DAG of course, but If the DAGs are of similar sizes it's also likely that the speed of scanning (DAGS/s) is similar for all schedulers. The schedulers will then catch-up with each other and might pretty much continuously compete for the same DAGs almost all the time. It can be mitigated super-easily by random sorting of the DAGs folder list after it is prepared (it's file-system dependent now so we do not rely on particular order) . Then the probability numbers will hold perfectly I think :) J. On Sat, Mar 2, 2019 at 2:41 PM Deng Xiaodong <xd.den...@gmail.com> wrote: > I’m thinking of which architecture would be ideal. > > > # Option-1: > The master-slave architecture would be one option. But leader-selection > will be very essential to consider, otherwise we have issue in terms of HA > again. > > > # Option-2: > Another option we may consider is to simply start multiple scheduler > instances (just using the current implementation, after modify & validate > the scheduler_lock on DagModel). > > - In this case, given we handle everything properly using locking, we > don’t need to worry too much about double-scheduling/triggering. > > - Another potential concern I had earlier is that different schedulers may > compete with each other and cause “waste” of scheduler resource. > After further thinking, I realise this is a typical Birthday Problem. > Given we have m DAGs, and n schedulers, at any moment, the probability > that all schedulers are working on different DAGs is m!/((m-n)! * (m^n)), > and the probability that there are schedulers competing on the same DAG > will be 1-m!/((m-n)! * (m^n)). > > Let’s say we have 200 DAGs and we start 2 schedulers. At any moment, the > probability that there is schedulers competing on the same DAG is only > 0.5%. If we run 2 schedulers against 300 DAGs, this probability is only > 0.33%. > (This probability will be higher if m/n is low. But users should not start > too many schedulers if they don’t have that many DAGs). > > Given the probability of schedulers competing is so low, my concern on > scheduler resource waste is not really valid. > > > > Based on these calculations/assessment, I think we can go for option-2, > i.e. we don’t make big change in the current implementation. Instead, we > ensure the scheduler_lock is working well and test intensively on running > multiple schedulers. Then we should be good to let users know that it’s > safe to run multiple schedulers. > > Please share your thoughts on this and correct me if I’m wrong in any > point above. Thanks. > > > XD > > > Reference: https://en.wikipedia.org/wiki/Birthday_problem < > https://en.wikipedia.org/wiki/Birthday_problem> > > > > On 2 Mar 2019, at 3:39 PM, Tao Feng <fengta...@gmail.com> wrote: > > > > Does the proposal use master-slave architecture(leader scheduler vs slave > > scheduler)? > > > > On Fri, Mar 1, 2019 at 5:32 PM Kevin Yang <yrql...@gmail.com> wrote: > > > >> Preventing double-triggering by separating DAG files different > schedulers > >> parse sounds easier and more intuitive. I actually removed one of the > >> double-triggering prevention logic here > >> < > >> > https://github.com/apache/airflow/pull/4234/files#diff-a7f584b9502a6dd19987db41a8834ff9L127 > >>> (expensive) > >> and > >> was relying on this lock > >> < > >> > https://github.com/apache/airflow/blob/master/airflow/models/__init__.py#L1233 > >>> > >> to > >> prevent double-firing and safe-guard our non-idempotent tasks( btw the > >> insert can be insert overwrite to be idempotent). > >> > >> Also tho in Airbnb we requeue tasks a lot, we haven't see double-firing > >> recently. > >> > >> Cheers, > >> Kevin Y > >> > >> On Fri, Mar 1, 2019 at 2:08 PM Maxime Beauchemin < > >> maximebeauche...@gmail.com> > >> wrote: > >> > >>> Forgot to mention: the intention was to use the lock, but I never > >>> personally got to do the second phase which would consist of skipping > the > >>> DAG if the lock is on, and expire the lock eventually based on a config > >>> setting. > >>> > >>> Max > >>> > >>> On Fri, Mar 1, 2019 at 1:57 PM Maxime Beauchemin < > >>> maximebeauche...@gmail.com> > >>> wrote: > >>> > >>>> My original intention with the lock was preventing "double-triggering" > >> of > >>>> task (triggering refers to the scheduler putting the message in the > >>> queue). > >>>> Airflow now has good "double-firing-prevention" of tasks (firing > >> happens > >>>> when the worker receives the message and starts the task), even if the > >>>> scheduler was to go rogue or restart and send multiple triggers for a > >>> task > >>>> instance, the worker(s) should only start one task instance. That's > >> done > >>> by > >>>> running the database assertions behind the conditions being met as > read > >>>> database transaction (no task can alter the rows that validate the > >>>> assertion while it's getting asserted). In practice it's a little > >> tricky > >>>> and we've seen rogue double-firing in the past (I have no idea how > >> often > >>>> that happens). > >>>> > >>>> If we do want to prevent double-triggerring, we should make sure that > 2 > >>>> schedulers aren't processing the same DAG or DagRun at the same time. > >>> That > >>>> would mean for the scheduler to not start the process of locked DAGs, > >> and > >>>> by providing a mechanism to expire the locks after some time. > >>>> > >>>> Has anyone experienced double firing lately? If that exist we should > >> fix > >>>> it, but also be careful around multiple scheduler double-triggering as > >> it > >>>> would make that problem potentially much worse. > >>>> > >>>> Max > >>>> > >>>> On Fri, Mar 1, 2019 at 8:19 AM Deng Xiaodong <xd.den...@gmail.com> > >>> wrote: > >>>> > >>>>> It’s exactly what my team is doing & what I shared here earlier last > >>> year > >>>>> ( > >>>>> > >>> > >> > https://lists.apache.org/thread.html/0e21230e08f07ef6f8e3c59887e9005447d6932639d3ce16a103078f@%3Cdev.airflow.apache.org%3E > >>>>> < > >>>>> > >>> > >> > https://lists.apache.org/thread.html/0e21230e08f07ef6f8e3c59887e9005447d6932639d3ce16a103078f@%3Cdev.airflow.apache.org%3E > >>>> > >>>>> ) > >>>>> > >>>>> It’s somehow a “hacky” solution (and HA is not addressed), and now > I’m > >>>>> thinking how we can have it more proper & robust. > >>>>> > >>>>> > >>>>> XD > >>>>> > >>>>>> On 2 Mar 2019, at 12:04 AM, Mario Urquizo <mario.urqu...@gmail.com> > >>>>> wrote: > >>>>>> > >>>>>> We have been running multiple schedulers for about 3 months. We > >>> created > >>>>>> multiple services to run airflow schedulers. The only difference is > >>>>> that > >>>>>> we have each of the schedulers pointed to a directory one level > >> deeper > >>>>> than > >>>>>> the DAG home directory that the workers and webapp use. We have seen > >>>>> much > >>>>>> better scheduling performance but this does not yet help with HA. > >>>>>> > >>>>>> DAGS_HOME: > >>>>>> {airflow_home}/dags (webapp & workers) > >>>>>> {airflow_home}/dags/group-a/ (scheduler1) > >>>>>> {airflow_home}/dags/group-b/ (scheduler2) > >>>>>> {airflow_home}/dags/group-etc/ (scheduler3) > >>>>>> > >>>>>> Not sure if this helps, just sharing in case it does. > >>>>>> > >>>>>> Thank you, > >>>>>> Mario > >>>>>> > >>>>>> > >>>>>> On Fri, Mar 1, 2019 at 9:44 AM Bolke de Bruin <bdbr...@gmail.com> > >>>>> wrote: > >>>>>> > >>>>>>> I have done quite some work on making it possible to run multiple > >>>>>>> schedulers at the same time. At the moment I don’t think there are > >>>>> real > >>>>>>> blockers actually to do so. We just don’t actively test it. > >>>>>>> > >>>>>>> Database locking is mostly in place (DagRuns and TaskInstances). > >> And > >>> I > >>>>>>> think the worst that can happen is that a task is scheduled twice. > >>> The > >>>>> task > >>>>>>> will detect this most of the time and kill one off if concurrent if > >>> not > >>>>>>> sequential then I will run again in some occasions. Everyone is > >>> having > >>>>>>> idempotent tasks right so no harm done? ;-) > >>>>>>> > >>>>>>> Have you encountered issues? Maybe work those out? > >>>>>>> > >>>>>>> Cheers > >>>>>>> Bolke. > >>>>>>> > >>>>>>> Verstuurd vanaf mijn iPad > >>>>>>> > >>>>>>>> Op 1 mrt. 2019 om 16:25 heeft Deng Xiaodong <xd.den...@gmail.com> > >>> het > >>>>>>> volgende geschreven: > >>>>>>>> > >>>>>>>> Hi Max, > >>>>>>>> > >>>>>>>> Following > >>>>>>> > >>>>> > >>> > >> > https://lists.apache.org/thread.html/0e21230e08f07ef6f8e3c59887e9005447d6932639d3ce16a103078f@%3Cdev.airflow.apache.org%3E > >>>>>>> < > >>>>>>> > >>>>> > >>> > >> > https://lists.apache.org/thread.html/0e21230e08f07ef6f8e3c59887e9005447d6932639d3ce16a103078f@%3Cdev.airflow.apache.org%3E > >>>>>> , > >>>>>>> I’m trying to prepare an AIP for supporting multiple-scheduler in > >>>>> Airflow > >>>>>>> (mainly for HA and Higher scheduling performance). > >>>>>>>> > >>>>>>>> Along the process of code checking, I found that there is one > >>>>> attribute > >>>>>>> of DagModel, “scheduler_lock”. It’s not used at all in current > >>>>>>> implementation, but it was introduced long time back (2015) to > >> allow > >>>>>>> multiple schedulers to work together ( > >>>>>>> > >>>>> > >>> > >> > https://github.com/apache/airflow/commit/2070bfc50b5aa038301519ef7c630f2fcb569620 > >>>>>>> < > >>>>>>> > >>>>> > >>> > >> > https://github.com/apache/airflow/commit/2070bfc50b5aa038301519ef7c630f2fcb569620 > >>>>>> > >>>>>>> ). > >>>>>>>> > >>>>>>>> Since you were the original author of it, it would be very helpful > >>> if > >>>>>>> you can kindly share why the multiple-schedulers implementation was > >>>>> removed > >>>>>>> eventually, and what challenges/complexity there were. > >>>>>>>> (You already shared a few valuable inputs in the earlier > >> discussion > >>>>>>> > >>>>> > >>> > >> > https://lists.apache.org/thread.html/d37befd6f04dbdbfd2a2d41722352603bc2e2f97fb47bdc5ba454d0c@%3Cdev.airflow.apache.org%3E > >>>>>>> < > >>>>>>> > >>>>> > >>> > >> > https://lists.apache.org/thread.html/d37befd6f04dbdbfd2a2d41722352603bc2e2f97fb47bdc5ba454d0c@%3Cdev.airflow.apache.org%3E > >>>>>> > >>>>>>> , mainly relating to hiccups around concurrency, cross DAG > >>>>> prioritisation & > >>>>>>> load on DB. Other than these, anything else you would like to > >>> advise?) > >>>>>>>> > >>>>>>>> I will also dive into the git history further to understand it > >>> better. > >>>>>>>> > >>>>>>>> Thanks. > >>>>>>>> > >>>>>>>> > >>>>>>>> XD > >>>>>>> > >>>>> > >>>>> > >>> > >> > > -- Jarek Potiuk Polidea <https://www.polidea.com/> | Principal Software Engineer M: +48 660 796 129 <+48660796129> E: jarek.pot...@polidea.com
