> Timetable is a synonym of ’Schedule’ I'm not a native speaker and I don't get it easily as a synonym.
To be honest the "timetable" sounds like a complex piece of software. Personally I experienced that people use schedule and schedule_interval interchangeably. Additionally, schedule being more linked to scheduler imho is an advantage because it suggests some connection between these two. I feel that by introducing timetable we will bring yet more complexity to airflow vocabulary. And I personally would treat it as yet another moving part of an already complex system. I think we can move forward with this feature. We renamed "functional DAGs" to "Taskflow API" so, naming is not a blocker. If we can't get consensus we can always ask the users - they will use the feature. Best, Tomek On Fri, 12 Mar 2021 at 01:15, James Timmins <[email protected]> wrote: > *Timetable vs Schedule* > Re Timetable. I agree that if this was a greenfield project, it might make > sense to use Schedule. But as it stands, we need to find the right balance > between the most specific name and being sufficiently unique that it’s easy > to work with in code and, perhaps most importantly, easy to find when > searching on Google and in the Airflow Docs. > > There are more than 10,000 references to `schedule*` in the Airflow > codebase. `schedule` and `scheduler` are also identical to most search > engines/libraries, since they have the same stem, `schedule`. This means > that when a user Googles `Airflow Schedule`, they will get back intermixed > results of the Schedule class and the Scheduler. > > Timetable is a synonym of ’Schedule’, so it passes the accuracy test, > won’t ever be ambiguous in code, and is distinct in search results. > > *Should "interval-less DAGs” have data_interval_start and end available in > the context?* > I think they should be present so it’s consistent across DAGs. Let’s not > make users think too hard about what values are available in what context. > What if someone sets the interval to 0? What if sometimes the interval is > 0, and sometimes it’s 1 hour? Rather than changing the rules depending on > usage, it’s easiest to have one rule that the users can depend upon. > > *Re set_context_variables()* > What context is being defined here? The code comment says "Update or set > new context variables to become available in task templates and operators.” > The Timetable seems like the wrong place for variables that will get passed > into task templates/operators, unless this is actually a way to pass > Airflow macros into the Timetable context. In which case I fully support > this. If not, we may want to add this functionality. > > James > On Mar 11, 2021, 9:40 AM -0800, Kaxil Naik <[email protected]>, wrote: > > Yup I have no strong opinions on either so happy to keep it TimeTable or > if there is another suggestion. > > Regards, > Kaxil > > On Thu, Mar 11, 2021 at 5:00 PM James Timmins <[email protected]> > wrote: > >> Respectfully, I strongly disagree with the renaming of Timetable to >> Schedule. Schedule and Scheduler aren't meaningfully different, which can >> lead to a lot of confusion. Even as a native English speaker, and someone >> who works on Airflow full time, I routinely need to ask for clarification >> about what schedule-related concept someone is referring to. I foresee >> Schedule and Scheduler as two distinct yet closely related concepts >> becoming a major source of confusion. >> >> If folks dislike Timetable, we could certainly change to something else, >> but let's not use something so similar to existing Airflow classes. >> >> -James >> >> On Thu, Mar 11, 2021 at 2:13 AM Ash Berlin-Taylor <[email protected]> wrote: >> >>> Summary of changes so far on the AIP: >>> >>> My proposed rename of DagRun.execution_date is now DagRun.schedule_date >>> (previously I had proposed run_date. Thanks dstandish!) >>> >>> Timetable classes are renamed to Schedule classes (CronSchedule etc), >>> similarly the DAG argument is now schedule (reminder: schedule_interval >>> will not be removed or deprecated, and will still be the way to use >>> "simple" expressions) >>> >>> -ash >>> >>> On Wed, 10 Mar, 2021 at 14:15, Ash Berlin-Taylor <[email protected]> wrote: >>> >>> Could change Timetable To Schedule -- that would mean the DAG arg >>> becomes `schedule=CronSchedule(...)` -- a bit close to the current >>> `schedule_interval` but I think clear enough difference. >>> >>> I do like the name but my one worry with "schedule" is that Scheduler >>> and Schedule are very similar, and might be be confused with each other for >>> non-native English speakers? (I defer to others' judgment here, as this is >>> not something I can experience myself.) >>> >>> @Kevin Yang <[email protected]> @Daniel Standish <[email protected]> any >>> final input on this AIP? >>> >>> >>> >>> On Tue, 9 Mar, 2021 at 16:59, Kaxil Naik <[email protected]> wrote: >>> >>> Hi Ash and all, >>> >>> >>> What do people think of this? Worth it? Too complex to reason about what >>>> context variables might exist as a result? >>> >>> >>> I think I wouldn't worry about it right now or maybe not as part of this >>> AIP. Currently, in one of the Github Issue, a user mentioned that it is not >>> straightforward to know what is inside the context dictionary- >>> https://github.com/apache/airflow/issues/14396. So maybe we can tackle >>> this issue separately once the AbstractTimetable is built. >>> >>> Should "interval-less DAGs" (ones using "CronTimetable" in my proposal >>>> vs "DataTimetable") have data_interval_start and end available in the >>>> context? >>> >>> >>> hmm.. I would say No but then it contradicts my suggestion to remove >>> context dict from this AIP. If we are going to use it in scheduler then >>> yes, where data_interval_start = data_interval_end from CronTimetable. >>> >>> Does anyone have any better names than TimeDeltaTimetable, >>>> DataTimetable, and CronTimetable? (We can probably change these names right >>>> up until release, so not important to get this correct *now*.) >>> >>> >>> No strong opinion here. Just an alternate suggestion can >>> be TimeDeltaSchedule, DataSchedule and CronSchedule >>> >>> >>>> Should I try to roll AIP-30 >>>> <https://cwiki.apache.org/confluence/display/AIRFLOW/AIP-30%3A+State+persistence> >>>> in >>>> to this, or should we make that a future addition? (My vote is for future >>>> addition) >>> >>> >>> I would vote for Future addition too. >>> >>> Regards, >>> Kaxil >>> >>> On Sat, Mar 6, 2021 at 11:05 AM Ash Berlin-Taylor <[email protected]> >>> wrote: >>> >>>> I think, yes, AIP-35 or something like it would happily co-exist with >>>> this proposal. >>>> >>>> @Daniel <[email protected]> and I have been discussing this a bit >>>> on Slack, and one of the questions he asked was if the concept of >>>> data_interval should be moved from DagRun as James and I suggested down on >>>> to the individual task: >>>> >>>> suppose i have a new dag hitting 5 api endpoints and pulling data to >>>> s3. suppose that yesterday 4 of them succeeded but one failed. today, 4 of >>>> them should pull from yesterday. but the one that failed should pull from 2 >>>> days back. so even though these normally have the same interval, today they >>>> should not. >>>> >>>> >>>> My view on this is two fold: one, this should primarily be handled by >>>> retries on the task, and secondly, having different TaskIstances in the >>>> same DagRun have different data intervals would be much harder to reason >>>> about/design the UI around, so for those reasons I still think interval >>>> should be a DagRun-level concept. >>>> >>>> (He has a stalled AIP-30 where he proposed something to address this >>>> kind of "watermark" case, which we might pick up next after this AIP is >>>> complete) >>>> >>>> One thing we might want to do is extend the interface of >>>> AbstractTimetable to be able to add/update parameters in the context dict, >>>> so the interface could become this: >>>> >>>> class AbstractTimetable(ABC): >>>> @abstractmethod >>>> def next_dagrun_info( >>>> date_last_automated_dagrun: Optional[pendulum.DateTime], >>>> >>>> session: Session, >>>> ) -> Optional[DagRunInfo]: >>>> """ >>>> Get information about the next DagRun of this dag after >>>> ``date_last_automated_dagrun`` -- the >>>> execution date, and the earliest it could be scheduled >>>> >>>> :param date_last_automated_dagrun: The max(execution_date) of >>>> existing >>>> "automated" DagRuns for this dag (scheduled or backfill, >>>> but not >>>> manual) >>>> """ >>>> >>>> @abstractmethod >>>> def set_context_variables(self, dagrun: DagRun, context: Dict[str, >>>> Any]) -> None: >>>> """ >>>> Update or set new context variables to become available in >>>> task templates and operators. >>>> """ >>>> >>>> >>>> What do people think of this? Worth it? Too complex to reason about >>>> what context variables might exist as a result? >>>> >>>> *Outstanding question*: >>>> >>>> - Should "interval-less DAGs" (ones using "CronTimetable" in my >>>> proposal vs "DataTimetable") have data_interval_start and end available >>>> in >>>> the context? >>>> - Does anyone have any better names than TimeDeltaTimetable, >>>> DataTimetable, and CronTimetable? (We can probably change these names >>>> right >>>> up until release, so not important to get this correct *now*.) >>>> - Should I try to roll AIP-30 >>>> >>>> <https://cwiki.apache.org/confluence/display/AIRFLOW/AIP-30%3A+State+persistence> >>>> in to this, or should we make that a future addition? (My vote is for >>>> future addition) >>>> >>>> >>>> I'd like to start voting on this AIP next week (probably on Tuesday) as >>>> I think this will be a powerful feature that eases confusing to new users. >>>> >>>> -Ash >>>> >>>> >>>> On Tue, 2 Mar, 2021 at 23:05, Alex Inhert <[email protected]> >>>> wrote: >>>> >>>> Is this AIP going to co-exist with AIP-35 "Add Signal Based Scheduling >>>> To Airflow"? >>>> I think streaming was also discussed there (though it wasn't really the >>>> use case). >>>> >>>> >>>> 02.03.2021, 22:10, "Ash Berlin-Taylor" <[email protected]>: >>>> >>>> Hi Kevin, >>>> >>>> Interesting idea. My original idea was actually for "interval-less >>>> DAGs" (i.e. ones where it's just "run at this time") would not have >>>> data_interval_start or end, but (while drafting the AIP) we decided that it >>>> was probably "easier" if those values were always datetimes. >>>> >>>> That said, I think having the DB model have those values be nullable >>>> would future proof it without needing another migration to change it. Do >>>> you think this is worth doing now? >>>> >>>> I haven't (yet! It's on my list) spent any significant time thinking >>>> about how to make Airflow play nicely with streaming jobs. If anyone else >>>> has ideas here please share them >>>> >>>> -ash >>>> >>>> On Sat, 27 Feb, 2021 at 16:09, Kevin Yang <[email protected]> wrote: >>>> >>>> Hi Ash and James, >>>> >>>> This is an exciting move. What do you think about using this >>>> opportunity to extend Airflow's support to streaming like use cases? I.e >>>> DAGs/tasks that want to run forever like a service. For such use cases, >>>> schedule interval might not be meaningful, then do we want to make the date >>>> interval param optional to DagRun and task instances? That sounds like a >>>> pretty major change to the underlying model of Airflow, but this AIP is so >>>> far the best opportunity I saw that can level up Airflow's support for >>>> streaming/service use cases. >>>> >>>> >>>> Cheers, >>>> Kevin Y >>>> >>>> On Fri, Feb 26, 2021 at 8:56 AM Daniel Standish <[email protected]> >>>> wrote: >>>> >>>> Very excited to see this proposal come through and love the direction >>>> this has gone. >>>> >>>> Couple comments... >>>> >>>> *Tree view / Data completeness view* >>>> >>>> When you design your tasks with the canonical idempotence pattern, the >>>> tree view shows you both data completeness and task execution history >>>> (success / failure etc). >>>> >>>> When you don't use that pattern (which is my general preference), tree >>>> view is only task execution history. >>>> >>>> This change has the potential to unlock a data completeness view for >>>> canonical tasks. It's possible that the "data completeness view" can >>>> simply be the tree view. I.e. somehow it can use these new classes to know >>>> what data was successfully filled and what data wasn't. >>>> >>>> To the extent we like the idea of either extending / plugging / >>>> modifying tree view, or adding a distinct data completeness view, we might >>>> want to anticipate the needs of that in this change. And maybe no >>>> alteration to the proposal would be needed but just want to throw the idea >>>> out there. >>>> >>>> *Watermark workflow / incremental processing* >>>> >>>> A common pattern in data warehousing is pulling data incrementally from >>>> a source. >>>> >>>> A standard way to achieve this is at the start of the task, select max >>>> `updated_at` in source table and hold on to that value for a minute. This >>>> is your tentative new high watermark. >>>> Now it's time to pull your data. If your task ran before, grab last >>>> high watermark. If not, use initial load value. >>>> If successful, update high watermark. >>>> >>>> On my team we implemented this with a stateful tasks / stateful >>>> processes concept (there's a dormant draft AIP here >>>> <https://cwiki.apache.org/confluence/display/AIRFLOW/AIP-30%3A+State+persistence>) >>>> and a WatermarkOperator that handled the boilerplate*. >>>> >>>> Again here, I don't have a specific suggestion at this moment. But I >>>> wanted to articulate this workflow because it is common and it wasn't >>>> immediately obvious to me in reading AIP-39 how I would use it to implement >>>> it. >>>> >>>> AIP-39 makes airflow more data-aware. So if it can support this kind >>>> of workflow that's great. @Ash Berlin-Taylor <[email protected]> do >>>> you have thoughts on how it might be compatible with this kind of thing as >>>> is? >>>> >>>> --- >>>> >>>> * The base operator is designed so that Subclasses only need to >>>> implement two methods: >>>> - `get_high_watermark`: produce the tentative new high watermark >>>> ' `watermark_execute`: analogous to implementing poke in a sensor, >>>> this is where your work is done. `execute` is left to the base class, and >>>> it orchestrates (1) getting last high watermark or inital load value and >>>> (2) updating new high watermark if job successful. >>>> >>>>
