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From Ash Berlin-Taylor <...@apache.org>
Subject Re: Airflow DAG Serialisation
Date Tue, 30 Jul 2019 13:46:15 GMT
Hi Jon,

As part of this AIP(24) we aren't going to touch the scheduler any more than absolutely required,
but yes, better support of dynamic DAGs is _very much_ on Kaxil and I's hit list.

Our rough approach right now is to design the serialisation format well enough (including
versioning it so we can change it over time) such that we can change the scheduler to not
be as coupled with the dag parsing loop. But for the sake of small, reviewable PRs we'll do
it bit-by-bit.

-ash

On 2019/07/30 13:33:53, Jonathan Miles <jon@cybus.co.uk> wrote: 
> Another ask for the long-term list.
> 
>  From a superficial read of the code, it looks like this asynchronous 
> DAG loading approach could also be a stepping stone towards loading DAGs 
> in parallel? I've come across a case of someone dynamically generating a 
> DAG based on an external data source. Problem with that is when the data 
> source isn't available or is slow, it can block the loading of other 
> DAGs. Loading in parallel could isolate the failing or slow DAGs from 
> the good ones.
> 
> I suppose even with this patch, randomising the load order of DAGs could 
> also provide some basic protection against a small set of failing DAGs. 
> At least some would get updated.
> 
> Do the changes only affect the webserver or also loading in the scheduler?
> 
> Thanks,
> 
> Jon
> 
> On 29/07/2019 22:18, Zhou Fang wrote:
> > Hi Kevin,
> >
> > The problem that DAG parsing takes a long time can be solved by
> > Asynchronous DAG loading: https://github.com/apache/airflow/pull/5594
> >
> > The idea is the a background process parses DAG files, and sends DAGs to
> > webserver process every [webserver] dagbag_sync_interval = 10s.
> >
> > We have launched it in Composer, so our users can set webserver worker
> > restart interval to 1 hour (or longer). The background DAG parsing
> > processing refresh all DAGs per [webserver] = collect_dags_interval = 30s.
> >
> > If parsing all DAGs take 15min, you can see DAGs being gradually freshed
> > with this feature.
> >
> > Thanks,
> > Zhou
> >
> >
> > On Sat, Jul 27, 2019 at 2:43 AM Kevin Yang <yrqls21@gmail.com> wrote:
> >
> >> Nice job Zhou!
> >>
> >> Really excited, exactly what we wanted for the webserver scaling issue.
> >> Want to add another big drive for Airbnb to start think about this
> >> previously to support the effort: it can not only bring consistency between
> >> webservers but also bring consistency between webserver and
> >> scheduler/workers. It may be less of a problem if total DAG parsing time is
> >> small, but for us the total DAG parsing time is 15+ mins and we had to set
> >> the webserver( gunicorn subprocesses) restart interval to 20 mins, which
> >> leads to a worst case 15+20+15=50 mins delay between scheduler start to
> >> schedule things and users can see their deployed DAGs/changes...
> >>
> >> I'm not so sure about the scheduler performance improvement: currently we
> >> already feed the main scheduler process with SimpleDag through
> >> DagFileProcessorManager running in a subprocess--in the future we feed it
> >> with data from DB, which is likely slower( tho the diff should have
> >> negligible impact to the scheduler performance). In fact if we'd keep the
> >> existing behavior, try schedule only fresh parsed DAGs, then we may need to
> >> deal with some consistency issue--dag processor and the scheduler race for
> >> updating the flag indicating if the DAG is newly parsed. No big deal there
> >> but just some thoughts on the top of my head and hopefully can be helpful.
> >>
> >> And good idea on pre-rendering the template, believe template rendering was
> >> the biggest concern in the previous discussion. We've also chose the
> >> pre-rendering+JSON approach in our smart sensor API
> >> <
> >> https://cwiki.apache.org/confluence/display/AIRFLOW/AIP-17+Airflow+sensor+optimization
> >> and
> >> seems to be working fine--a supporting case for ur proposal ;) There's a
> >> WIP
> >> PR <https://github.com/apache/airflow/pull/5499> for it just in case you
> >> are interested--maybe we can even share some logics.
> >>
> >> Thumbs-up again for this and please don't heisitate to reach out if you
> >> want to discuss further with us or need any help from us.
> >>
> >>
> >> Cheers,
> >> Kevin Y
> >>
> >> On Sat, Jul 27, 2019 at 12:54 AM Driesprong, Fokko <fokko@driesprong.frl>
> >> wrote:
> >>
> >>> Looks great Zhou,
> >>>
> >>> I have one thing that pops in my mind while reading the AIP; should keep
> >>> the caching on the webserver level. As the famous quote goes: *"There are
> >>> only two hard things in Computer Science: cache invalidation and naming
> >>> things." -- Phil Karlton*
> >>>
> >>> Right now, the fundamental change that is being proposed in the AIP is
> >>> fetching the DAGs from the database in a serialized format, and not
> >> parsing
> >>> the Python files all the time. This will give already a great performance
> >>> improvement on the webserver side because it removes a lot of the
> >>> processing. However, since we're still fetching the DAGs from the
> >> database
> >>> in a regular interval, cache it in the local process, so we still have
> >> the
> >>> two issues that Airflow is suffering from right now:
> >>>
> >>>     1. No snappy UI because it is still polling the database in a regular
> >>>     interval.
> >>>     2. Inconsistency between webservers because they might poll in a
> >>>     different interval, I think we've all seen this:
> >>>     https://www.youtube.com/watch?v=sNrBruPS3r4
> >>>
> >>> As I also mentioned in the Slack channel, I strongly feel that we should
> >> be
> >>> able to render most views from the tables in the database, so without
> >>> touching the blob. For specific views, we could just pull the blob from
> >> the
> >>> database. In this case we always have the latest version, and we tackle
> >> the
> >>> second point above.
> >>>
> >>> To tackle the first one, I also have an idea. We should change the DAG
> >>> parser from a loop to something that uses inotify
> >>> https://pypi.org/project/inotify_simple/. This will change it from
> >> polling
> >>> to an event-driven design, which is much more performant and less
> >> resource
> >>> hungry. But this would be an AIP on its own.
> >>>
> >>> Again, great design and a comprehensive AIP, but I would include the
> >>> caching on the webserver to greatly improve the user experience in the
> >> UI.
> >>> Looking forward to the opinion of others on this.
> >>>
> >>> Cheers, Fokko
> >>>
> >>>
> >>>
> >>>
> >>>
> >>>
> >>>
> >>>
> >>> Op za 27 jul. 2019 om 01:44 schreef Zhou Fang
> >> <zhoufang@google.com.invalid
> >>>> :
> >>>> Hi Kaxi,
> >>>>
> >>>> Just sent out the AIP:
> >>>>
> >>>>
> >> https://cwiki.apache.org/confluence/display/AIRFLOW/AIP-24+DAG+Persistence+in+DB+using+JSON+for+Airflow+Webserver+and+%28optional%29+Scheduler
> >>>> Thanks!
> >>>> Zhou
> >>>>
> >>>>
> >>>> On Fri, Jul 26, 2019 at 1:33 PM Zhou Fang <zhoufang@google.com>
wrote:
> >>>>
> >>>>> Hi Kaxil,
> >>>>>
> >>>>> We are also working on persisting DAGs into DB using JSON for Airflow
> >>>>> webserver in Google Composer. We target at minimizing the change
to
> >> the
> >>>>> current Airflow code. Happy to get synced on this!
> >>>>>
> >>>>> Here is our progress:
> >>>>> (1) Serializing DAGs using Pickle to be used in webserver
> >>>>> It has been launched in Composer. I am working on the PR to upstream
> >>> it:
> >>>>> https://github.com/apache/airflow/pull/5594
> >>>>> Currently it does not support non-Airflow operators and we are
> >> working
> >>> on
> >>>>> a fix.
> >>>>>
> >>>>> (2) Caching Pickled DAGs in DB to be used by webserver
> >>>>> We have a proof-of-concept implementation, working on an AIP now.
> >>>>>
> >>>>> (3) Using JSON instead of Pickle in (1) and (2)
> >>>>> Decided to use JSON because Pickle is not secure and human readable.
> >>> The
> >>>>> serialization approach is very similar to (1).
> >>>>>
> >>>>> I will update the RP (https://github.com/apache/airflow/pull/5594)
> >> to
> >>>>> replace Pickle by JSON, and send our design of (2) as an AIP next
> >> week.
> >>>>> Glad to check together whether our implementation makes sense and
do
> >>>>> improvements on that.
> >>>>>
> >>>>> Thanks!
> >>>>> Zhou
> >>>>>
> >>>>>
> >>>>> On Fri, Jul 26, 2019 at 7:37 AM Kaxil Naik <kaxilnaik@gmail.com>
> >>> wrote:
> >>>>>> Hi all,
> >>>>>>
> >>>>>> We, at Astronomer, are going to spend time working on DAG
> >>> Serialisation.
> >>>>>> There are 2 AIPs that are somewhat related to what we plan to
work
> >> on:
> >>>>>>     - AIP-18 Persist all information from DAG file in DB
> >>>>>>     <
> >>>>>>
> >> https://cwiki.apache.org/confluence/display/AIRFLOW/AIP-18+Persist+all+information+from+DAG+file+in+DB
> >>>>>>     - AIP-19 Making the webserver stateless
> >>>>>>     <
> >>>>>>
> >> https://cwiki.apache.org/confluence/display/AIRFLOW/AIP-19+Making+the+webserver+stateless
> >>>>>> We plan to use JSON as the Serialisation format and store it
as a
> >> blob
> >>>> in
> >>>>>> metadata DB.
> >>>>>>
> >>>>>> *Goals:*
> >>>>>>
> >>>>>>     - Make Webserver Stateless
> >>>>>>     - Use the same version of the DAG across Webserver &
Scheduler
> >>>>>>     - Keep backward compatibility and have a flag (globally
& at DAG
> >>>> level)
> >>>>>>     to turn this feature on/off
> >>>>>>     - Enable DAG Versioning (extended Goal)
> >>>>>>
> >>>>>>
> >>>>>> We will be preparing a proposal (AIP) after some research and
some
> >>>> initial
> >>>>>> work and open it for the suggestions of the community.
> >>>>>>
> >>>>>> We already had some good brain-storming sessions with Twitter
folks
> >>>> (DanD
> >>>>>> &
> >>>>>> Sumit), folks from GoDataDriven (Fokko & Bas) & Alex
(from Uber)
> >> which
> >>>>>> will
> >>>>>> be a good starting point for us.
> >>>>>>
> >>>>>> If anyone in the community is interested in it or has some
> >> experience
> >>>>>> about
> >>>>>> the same and want to collaborate please let me know and join
> >>>>>> #dag-serialisation channel on Airflow Slack.
> >>>>>>
> >>>>>> Regards,
> >>>>>> Kaxil
> >>>>>>
> 

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