+1 on improving backfill. - The terminal interface was uselessly verbose. It was scrolling fast > enough to be unreadable.
I agree that backfill is currently too verbose. It simply logs to many things and it is hard to read. Often times, I only care about the number of tasks/dagruns that are in-progress/finished/not started. I had a PR <https://github.com/apache/airflow/pull/3478> that implements a progress bar for backfill but was not able to finish. Probably something that can help improve the backfill experience. - The backfill exceeded safe concurrency limits for the cluster and > could've easily brought it down if I'd left it running. Btw. backfill now respects pool limitation but we should probably looking into making it respect concurrency limit. Chao-Han > > On Mon, Mar 4, 2019 at 12:35 PM James Meickle <jmeic...@quantopian.com.invalid> wrote: > This is an old thread, but I wanted to bump it as I just had a really bad > experience using backfill. I'd been hesitant to even try backfills out > given what I've read about it, so I've just relied on the UI to "Clear" > entire tasks. However, I wanted to give it a shot the "right" way. Issues I > ran into: > > - The dry run flag didn't give good feedback about which dagruns and task > instances will be affected (and is very easy to typo as "--dry-run") > > - The terminal interface was uselessly verbose. It was scrolling fast > enough to be unreadable. > > - The backfill exceeded safe concurrency limits for the cluster and > could've easily brought it down if I'd left it running. > > - Tasks in the backfill were executed out of order despite the tasks having > `depends_on_past` > > - The backfill converted all existing DAGRuns to be backfill runs that the > scheduler later ignored, which is not how I would've expected this to work > (nor was it indicated in the dry run) > > I ended up having to do manual recovery work in the database to turn the > "backfill" runs back into scheduler runs, and then switch to using `airflow > clear`. I'm a heavy Airflow user and this took me an hour; it would've been > much worse for anyone else on my team. > > I don't have any specific suggestions here other than to confirm that this > feature needs an overhaul if it's to be recommended to anyone. > > On Fri, Jun 8, 2018 at 5:38 PM Maxime Beauchemin < > maximebeauche...@gmail.com> > wrote: > > > Ash I don't see how this could happen unless maybe the node doing the > > backfill is using another metadata database. > > > > In general we recommend for people to run --local backfills and have the > > default/sandbox template for `airflow.cfg` use a LocalExecutor with > > reasonable parallelism to make that behavior the default. > > > > Given the [not-so-great] state of backfill, I'm guessing many have been > > using the scheduler to do backfills. From that regard it would be nice to > > have CLI commands to generate dagruns or alter the state of existing ones > > > > Max > > > > On Fri, Jun 8, 2018 at 8:56 AM Ash Berlin-Taylor < > > ash_airflowl...@firemirror.com> wrote: > > > > > Somewhat related to this, but likely a different issue: > > > > > > I've just had a case where a long (7hours) running backfill task ended > up > > > running twice somehow. We're using Celery so this might be related to > > some > > > sort of Celery visibility timeout, but I haven't had a chance to be > able > > to > > > dig in to it in detail - it's 5pm on a Friday :D > > > > > > Has anyone else noticed anything similar? > > > > > > -ash > > > > > > > > > > On 8 Jun 2018, at 01:22, Tao Feng <fengta...@gmail.com> wrote: > > > > > > > > Thanks everyone for the feedback especially on the background for > > > backfill. > > > > After reading the discussion, I think it would be safest to add a > flag > > > for > > > > auto rerun failed tasks for backfill with default to be false. I have > > > > updated the pr accordingly. > > > > > > > > Thanks a lot, > > > > -Tao > > > > > > > > On Wed, Jun 6, 2018 at 1:47 PM, Mark Whitfield < > > > mark.whitfi...@nytimes.com> > > > > wrote: > > > > > > > >> I've been doing some work setting up a large, collaborative Airflow > > > >> pipeline with a group that makes heavy use of backfills, and have > been > > > >> encountering a lot of these issues myself. > > > >> > > > >> Other gripes: > > > >> > > > >> Backfills do not obey concurrency pool restrictions. We had been > > making > > > >> heavy use of SubDAGs and using concurrency pools to prevent > deadlocks > > > (why > > > >> does the SubDAG itself even need to occupy a concurrency slot if > none > > of > > > >> its constituent tasks are running?), but this quickly became > untenable > > > when > > > >> using backfills and we were forced to mostly abandon SubDAGs. > > > >> > > > >> Backfills do use DagRuns now, which is a big improvement. However, > > it's > > > a > > > >> common use case for us to add new tasks to a DAG and backfill to a > > date > > > >> specific to that task. When we do this, the BackfillJob will pick up > > > >> previous backfill DagRuns and re-use them, which is mostly nice > > because > > > it > > > >> keeps the Tree view neatly organized in the UI. However, it does not > > > reset > > > >> the start time of the DagRun when it does this. Combined with a > > > DAG-level > > > >> timeout, this means that the backfill job will activate a DagRun, > but > > > then > > > >> the run will immediately time out (since it still thinks it's been > > > running > > > >> since the previous backfill). This will cause tasks to deadlock > > > spuriously, > > > >> making backfills extremely cumbersome to carry out. > > > >> > > > >> *Mark Whitfield* > > > >> Data Scientist > > > >> New York Times > > > >> > > > >> > > > >> On Wed, Jun 6, 2018 at 3:33 PM Maxime Beauchemin < > > > >> maximebeauche...@gmail.com> > > > >> wrote: > > > >> > > > >>> Thanks for the input, this is helpful. > > > >>> > > > >>> To add to the list, there's some complexity around concurrency > > > management > > > >>> and multiple executors: > > > >>> I just hit this thing where backfill doesn't check DAG-level > > > concurrency, > > > >>> fires up 32 tasks, and `airlfow run` double-checks DAG-level > > > concurrency > > > >>> limit and exits. Right after backfill reschedules right away and so > > on, > > > >>> burning a bunch of CPU doing nothing. In this specific case it > seems > > > like > > > >>> `airflow run` should skip that specific check when in the context > of > > a > > > >>> backfill. > > > >>> > > > >>> Max > > > >>> > > > >>> On Tue, Jun 5, 2018 at 9:23 PM Bolke de Bruin <bdbr...@gmail.com> > > > wrote: > > > >>> > > > >>>> Thinking out loud here, because it is a while back that I did work > > on > > > >>>> backfills. There were some real issues with backfills: > > > >>>> > > > >>>> 1. Tasks were running in non deterministic order ending up in > > regular > > > >>>> deadlocks > > > >>>> 2. Didn’t create dag runs, making behavior inconsistent. Max dag > > runs > > > >>>> could not be enforced. Ui could really display it, lots of minor > > other > > > >>>> issues because of it. > > > >>>> 3. Behavior was different from the scheduler, while > subdagoperators > > > >>>> particularly make use of backfills at the moment. > > > >>>> > > > >>>> I think with 3 the behavior you are observing crept in. And given > 3 > > I > > > >>>> would argue a consistent behavior between the scheduler and the > > > >> backfill > > > >>>> mechanism is still paramount. Thus we should explicitly clear > tasks > > > >> from > > > >>>> failed if we want to rerun them. This at least until we move the > > > >>>> subdagoperator out of backfill and into the scheduler (which is > > > >> actually > > > >>>> not too hard). Also we need those command line options anyway. > > > >>>> > > > >>>> Bolke > > > >>>> > > > >>>> Verstuurd vanaf mijn iPad > > > >>>> > > > >>>>> Op 6 jun. 2018 om 01:27 heeft Scott Halgrim < > > > >> scott.halg...@zapier.com > > > >>> .INVALID> > > > >>>> het volgende geschreven: > > > >>>>> > > > >>>>> The request was for opposition, but I’d like to weigh in on the > > side > > > >> of > > > >>>> “it’s a better behavior [to have failed tasks re-run when cleared > > in a > > > >>>> backfill" > > > >>>>>> On Jun 5, 2018, 4:16 PM -0700, Maxime Beauchemin < > > > >>>> maximebeauche...@gmail.com>, wrote: > > > >>>>>> @Jeremiah Lowin <jlo...@gmail.com> & @Bolke de Bruin < > > > >>> bdbr...@gmail.com> > > > >>>> I > > > >>>>>> think you may have some context on why this may have changed at > > some > > > >>>> point. > > > >>>>>> I'm assuming that when DagRun handling was added to the backfill > > > >>> logic, > > > >>>> the > > > >>>>>> behavior just happened to change to what it is now. > > > >>>>>> > > > >>>>>> Any opposition in moving back towards re-running failed tasks > when > > > >>>> starting > > > >>>>>> a backfill? I think it's a better behavior, though it's a change > > in > > > >>>>>> behavior that we should mention in UPDATE.md. > > > >>>>>> > > > >>>>>> One of our goals is to make sure that a failed or killed > backfill > > > >> can > > > >>> be > > > >>>>>> restarted and just seamlessly pick up where it left off. > > > >>>>>> > > > >>>>>> Max > > > >>>>>> > > > >>>>>>> On Tue, Jun 5, 2018 at 3:25 PM Tao Feng <fengta...@gmail.com> > > > >> wrote: > > > >>>>>>> > > > >>>>>>> After discussing with Max, we think it would be great if > `airflow > > > >>>> backfill` > > > >>>>>>> could be able to auto pick up and rerun those failed tasks. > > > >>> Currently, > > > >>>> it > > > >>>>>>> will throw exceptions( > > > >>>>>>> > > > >>>>>>> > > > >>>> > > > >>> https://github.com/apache/incubator-airflow/blob/master/airf > > > >> low/jobs.py#L2489 > > > >>>>>>> ) > > > >>>>>>> without rerunning the failed tasks. > > > >>>>>>> > > > >>>>>>> But since it broke some of the previous assumptions for > backfill, > > > >> we > > > >>>> would > > > >>>>>>> like to get some feedback and see if anyone has any concerns(pr > > > >> could > > > >>>> be > > > >>>>>>> found at https://github.com/apache/incu > > > >> bator-airflow/pull/3464/files > > > >>> ). > > > >>>>>>> > > > >>>>>>> Thanks, > > > >>>>>>> -Tao > > > >>>>>>> > > > >>>>>>> On Thu, May 24, 2018 at 10:26 AM, Maxime Beauchemin < > > > >>>>>>> maximebeauche...@gmail.com> wrote: > > > >>>>>>> > > > >>>>>>>> So I'm running a backfill for what feels like the first time > in > > > >>> years > > > >>>>>>> using > > > >>>>>>>> a simple `airflow backfill --local` commands. > > > >>>>>>>> > > > >>>>>>>> First I start getting a ton of `logging.info` of each tasks > > that > > > >>>> cannot > > > >>>>>>> be > > > >>>>>>>> started just yet at every tick flooding my terminal with the > > > >> keyword > > > >>>>>>>> `FAILED` in it, looking like a million of lines like this one: > > > >>>>>>>> > > > >>>>>>>> [2018-05-24 14:33:07,852] {models.py:1123} INFO - Dependencies > > not > > > >>> met > > > >>>>>>> for > > > >>>>>>>> <TaskInstance: some_dag.some_task_id 2018-01-28 00:00:00 > > > >>> [scheduled]>, > > > >>>>>>>> dependency 'Trigger Rule' FAILED: Task's trigger rule > > > >> 'all_success' > > > >>> re > > > >>>>>>>> quires all upstream tasks to have succeeded, but found 1 > > > >>>> non-success(es). > > > >>>>>>>> upstream_tasks_state={'successes': 0L, 'failed': 0L, > > > >>>> 'upstream_failed': > > > >>>>>>>> 0L, > > > >>>>>>>> 'skipped': 0L, 'done': 0L}, upstream_task_ids=['some_other > > > >> _task_id'] > > > >>>>>>>> > > > >>>>>>>> Good thing I triggered 1 month and not 2 years like I actually > > > >> need, > > > >>>> just > > > >>>>>>>> the logs here would be "big data". Now I'm unclear whether > > there's > > > >>>>>>> anything > > > >>>>>>>> actually running or if I did something wrong, so I decide to > > kill > > > >>> the > > > >>>>>>>> process so I can set a smaller date range and get a better > > picture > > > >>> of > > > >>>>>>>> what's up. > > > >>>>>>>> > > > >>>>>>>> I check my logging level, am I in DEBUG? Nope. Just INFO. So I > > > >> take > > > >>> a > > > >>>>>>> note > > > >>>>>>>> that I'll need to find that log-flooding line and demote it to > > > >> DEBUG > > > >>>> in a > > > >>>>>>>> quick PR, no biggy. > > > >>>>>>>> > > > >>>>>>>> Now I restart with just a single schedule, and get an error > `Dag > > > >>>>>>> {some_dag} > > > >>>>>>>> has reached maximum amount of 3 dag runs`. Hmmm, I wish > backfill > > > >>> could > > > >>>>>>> just > > > >>>>>>>> pickup where it left off. Maybe I need to run an `airflow > clear` > > > >>>> command > > > >>>>>>>> and restart? Ok, ran my clear command, same error is showing > up. > > > >>> Dead > > > >>>>>>> end. > > > >>>>>>>> > > > >>>>>>>> Maybe there is some new `airflow clear --reset-dagruns` > option? > > > >>>> Doesn't > > > >>>>>>>> look like it... Maybe `airflow backfill` has some new switches > > to > > > >>>> pick up > > > >>>>>>>> where it left off? Can't find it. Am I supposed to clear the > DAG > > > >>> Runs > > > >>>>>>>> manually in the UI? This is a pre-production, in-development > > DAG, > > > >> so > > > >>>>>>> it's > > > >>>>>>>> not on the production web server. Am I supposed to fire up my > > own > > > >>> web > > > >>>>>>>> server to go and manually handle the backfill-related DAG > Runs? > > > >>>> Cannot to > > > >>>>>>>> my staging MySQL and do manually clear some DAG runs? > > > >>>>>>>> > > > >>>>>>>> So. Fire up a web server, navigate to my dag_id, delete the > DAG > > > >>> runs, > > > >>>> it > > > >>>>>>>> appears I can finally start over. > > > >>>>>>>> > > > >>>>>>>> Next thought was: "Alright looks like I need to go Linus on > the > > > >>>> mailing > > > >>>>>>>> list". > > > >>>>>>>> > > > >>>>>>>> What am I missing? I'm really hoping these issues specific to > > > >> 1.8.2! > > > >>>>>>>> > > > >>>>>>>> Backfilling is core to Airflow and should work very well. I > want > > > >> to > > > >>>>>>> restate > > > >>>>>>>> some reqs for Airflow backfill: > > > >>>>>>>> * when failing / interrupted, it should seamlessly be able to > > > >> pickup > > > >>>>>>> where > > > >>>>>>>> it left off > > > >>>>>>>> * terminal logging at the INFO level should be a clear, human > > > >>>> consumable, > > > >>>>>>>> indicator of progress > > > >>>>>>>> * backfill-related operations (including restarts) should be > > > >> doable > > > >>>>>>> through > > > >>>>>>>> CLI interactions, and not require web server interactions as > the > > > >>>> typical > > > >>>>>>>> sandbox (dev environment) shouldn't assume the existence of a > > web > > > >>>> server > > > >>>>>>>> > > > >>>>>>>> Let's fix this. > > > >>>>>>>> > > > >>>>>>>> Max > > > >>>>>>>> > > > >>>>>>> > > > >>>> > > > >>> > > > >> > > > > > > > > > -- Chao-Han Tsai
