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From Dan Davydov <ddavy...@twitter.com.INVALID>
Subject Re: [DISCUSS] AIP-12 Persist DAG into DB
Date Fri, 08 Mar 2019 16:56:28 GMT
>
> Personally I don’t understand why people are pushing for a JSON-based DAG
> representation

It sounds like you agree that DAGs should be serialized (just in the DB
instead of JSON), so will only address why JSON is better than MySQL (AKA
serializing at the DAG level vs the task level) as far as I can see, and
not why we need serialization. If you zoom out and look at all the use
cases of serialized DAGs, e.g. having the scheduler use them instead of
parsing DAGs directly, then it becomes clear that we need all appropriate
metadata in these DAGs, (operator params, DAG properties, etc), in which
case it's not clear how it will fit nicely into a DB table (unless you
wanted to do something like (parent_task_id, task_id, task_params), also
keep in mind that we will need to store different versions of each DAG in
the future so that we can ensure consistency in a dagrun, i.e. each task in
a dagrun uses the same version of a DAG.

I think some of our requirements should be:
1. The data model will lead to acceptable performance in all of its
consumers (scheduler, webserver, workers), i.e. no n+1 access patterns (my
biggest concern about serializing at task level as you propose vs at DAG
level)
2. We can have versioning of serialized DAGs
3. The ability to separate DAGs into their own data store (e.g. no reliance
on joins between the new table and the old one)
4. One source of truth/serialized representation for DAGs (currently we
have SimpleDAG)

If we can full-fill all of these requirements and serialize at the task
level rather than the DAG level in the DB, then I agree that probably makes
more sense.


> In the proposed PR’s we (Peter, Bas and me) aim to avoid re-parsing DAG
> files by querying all the required information from the database. In one or
> two cases this may however not be possible, in which case we might either
> have to fall back on the DAG file or add the missing information into the
> database. We can tackle these problems as we encounter them.

I think you would have the support of many of committers in removing any
use-cases that stand in the way of full serialization, that being said if
we need to remove features we need to do this carefully and thoughtfully,
and ideally with proposed alternatives/work-arounds to cover the removals.

The counter argument: this PR removes the need for the confusing "Refresh"
> button from the UI, and in general you only pay the cost for the expensive
> DAGs when you ask about them. (I don't know what/when we call the
> /pickle_info endpoint of the top of my head)

Probably worth splitting out into a separate thread, but I'm actually not
sure the refresh button does anything, I think we should double check... I
think about 2 years ago there was a commit made that made gunicorn
webservers automatically rotate underneath flask (each one would reparse
the DAGbag). Even if it works we should probably remove it since the
webserver refresh interval is pretty fast, and it just causes confusion to
users and implies that the DAGs are not refreshed automatically.

Do you mean https://json5.org/ or is this a typo? That might be okay for a
> nicer user front end, but the "canonical" version stored in the DB should
> be something "plainer" like just JSON.

I think he got this from my reply, and it was just an example, but you are
right, I agree JSON would be better than JSON5.

On Fri, Mar 8, 2019 at 8:53 AM Ash Berlin-Taylor <ash@apache.org> wrote:

> Comments inline.
>
> > On 8 Mar 2019, at 11:28, Kevin Yang <yrqls21@gmail.com> wrote:
> >
> > Hi all,
> > When I was preparing some work related to this AIP I found something
> very concerning. I noticed this JIRA ticket <
> https://issues.apache.org/jira/browse/AIRFLOW-3562> is trying to remove
> the dependency of dagbag from webserver, which is awesome--we wanted badly
> but never got to start work on. However when I looked at some subtasks of
> it, which try to remove dagbag dependency from each endpoint, I found the
> way we remove the dependency of dagbag is not very ideal. For example this
> PR <https://github.com/apache/airflow/pull/4867/files> will require us to
> parse the dag file each time we hit the endpoint.
>
> The counter argument: this PR removes the need for the confusing "Refresh"
> button from the UI, and in general you only pay the cost for the expensive
> DAGs when you ask about them. (I don't know what/when we call the
> /pickle_info endpoint of the top of my head)
>
> This end point may be one to hold off on (as it can ask for multiple dags)
> but there are some that def don't need a full dag bag or to even parse the
> dag file, the current DAG model has enough info.
>
> >
> >
> > If we go down this path, we indeed can get rid of the dagbag dependency
> easily, but we will have to 1. increase the DB load( not too concerning at
> the moment ), 2. wait the DAG file to be parsed before getting the page
> back, potentially multiple times. DAG file can sometimes take quite a while
> to parse, e.g. we have some framework DAG files generating large number of
> DAGs from some static config files or even jupyter notebooks and they can
> take 30+ seconds to parse. Yes we don't like large DAG files but people do
> see the beauty of code as config and sometimes heavily abuseleverage it.
> Assuming all users have the same nice small python file that can be parsed
> fast, I'm still a bit worried about this approach. Continuing on this path
> means we've chosen DagModel to be the serialized representation of DAG and
> DB columns to hold different properties--it can be one candidate but I
> don't know if we should settle on that now. I would personally prefer a
> more compact, e.g. JSON5, and easy to scale representation( such that
> serializing new fields != DB upgrade).
>
> Do you mean https://json5.org/ or is this a typo? That might be okay for
> a nicer user front end, but the "canonical" version stored in the DB should
> be something "plainer" like just JSON.
>
> I'm not sure that "serializing new fields != DB upgrade" is that big of a
> concern, as we don't add fields that often. One possible way of dealing
> with it if we do is to have a hybrid approach - a few distinct columns, but
> then a JSON blob. (and if we were only to support postgres we could just
> use JSONb. But I think our friends at Google may object ;) )
>
> Adding a new column in a DB migration with a default NULL shouldn't be an
> expensive operation, or difficult to achieve.
>
>
> >
> > In my imagination we would have to collect the list of dynamic features
> depending on unserializable fields of a DAG and start a discussion/vote on
> dropping support of them( I'm working on this but if anyone has already
> done so please take over), decide on the serialized representation of a DAG
> and then replace dagbag with it in webserver. Per previous discussion and
> some offline discussions with Dan, one future of DAG serialization that I
> like would look similar to this:
> >
>
> > https://imgur.com/ncqqQgc
>
> Something I've thought about before for other things was to embed an API
> server _into_ the scheduler - this would be useful for k8s healthchecks,
> native Prometheus metrics without needed statsd bridge, and could have
> endpoints to get information such as this directly.
>
> I was thinking it would be _in_ the scheduler process using either threads
> (ick. Python's still got a GIL doesn't it?) or using async/twisted etc.
> (not a side-car process like we have with the logs webserver for `airflow
> worker`).
>
> (This is possibly an unrelated discussion, but might be worth talking
> about?)
>
> > We can still discuss/vote which approach we want to take but I don't
> want the door to above design to be shut right now or we have to spend a
> lot effort switch path later.
> >
> > Bas and Peter, I'm very sorry to extend the discussion but I do think
> this is tightly related to the AIP and PRs behind it. And my sincere
> apology for bringing this up so late( I only pull the open PR list
> occasionally, if there's a way to subscribe to new PR event I'd love to
> know how).
>
> It's noisy, but you can subscribe to commits@airflow.apache.org (but be
> warned, this also includes all Jira tickets, edits of every comment on
> github etc.).
>
>
> >
> > Cheers,
> > Kevin Y
> >
> > On Thu, Feb 28, 2019 at 1:36 PM Peter van t Hof <pjrvanthof@gmail.com
> <mailto:pjrvanthof@gmail.com>> wrote:
> > Hi all,
> >
> > Just some comments one the point Bolke dit give in relation of my PR.
> >
> > At first, the main focus is: making the webserver stateless.
> >
> > > 1) Make the webserver stateless: needs the graph of the *current* dag
> >
> > This is the main goal but for this a lot more PR’s will be coming once
> my current is merged. For edges and graph view this is covered in my PR
> already.
> >
> > > 2) Version dags: for consistency mainly and not requiring parsing of
> the
> > > dag on every loop
> >
> > In my PR the historical graphs will be stored for each DagRun. This
> means that you can see if an older DagRun was the same graph structure,
> even if some tasks does not exists anymore in the current graph. Especially
> for dynamic DAG’s this is very useful.
> >
> > > 3) Make the scheduler not require DAG files. This could be done if the
> > > edges contain all information when to trigger the next task. We can
> then
> > > have event driven dag parsing outside of the scheduler loop, ie. by the
> > > cli. Storage can also be somewhere else (git, artifactory, filesystem,
> > > whatever).
> >
> > The scheduler is almost untouched in this PR. The only thing that is
> added is that this edges are saved to the database but the scheduling
> itself din’t change. The scheduler depends now still on the DAG object.
> >
> > > 4) Fully serialise the dag so it becomes transferable to workers
> >
> > It nice to see that people has a lot of idea’s about this. But as Fokko
> already mentioned this is out of scope for the issue what we are trying to
> solve. I also have some idea’s about this but I like to limit this PR/AIP
> to the webserver.
> >
> > For now my PR does solve 1 and 2 and the rest of the behaviour (like
> scheduling) is untouched.
> >
> > Gr,
> > Peter
> >
>
>

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