Yeah, I actually thought this was a bug since it is difficult to reason
about!

We should change that

On Mon, 14 Sept 2026 at 18:46, Philippe Gagnon via dev <
[email protected]> wrote:

> I agree. The batching behavior is counter-intuitive.
> *✨ **Philippe Gagnon*
> *Meet for 30 mins 📅* <https://calendar.app.google/5qzgD9SadybUvSCv8>
>
>
> On Sat, Sep 12, 2026 at 7:26 AM Jarek Potiuk <[email protected]> wrote:
>
> > +1. Not batching. I think we should generally deprecate / remove the
> > auto-batching behavior as it is impossible to predict or control. If we
> > introduce batching, it should be configurable: specifying the number of
> > messages, the batching time windows etc. Unpredictable behaviour like
> this
> > is dangerous, especially if users start relying on it and it suddenly
> gets
> > impacted by unrelated things. In this case the big issue is that many
> > "noisy neighbour" cases can change the behaviour in unpredictable ways.
> You
> > might not even see the batching happening regularly - if events are
> > "slow-ish," - but suddenly you might suddenly start working when you
> > trigger a backfill for a completely different DAG, for example. That's a
> > recipe for disaster.
> >
> > On Sat, Sep 12, 2026 at 1:20 PM Jarek Potiuk <[email protected]> wrote:
> >
> > > NOTE: To Jake and others posting to devlist - as not everyone might be
> > > aware—please subscribe to devlist before posting (see "community" in
> > > https://airflow.apache.org).
> > >
> > > Otherwise we have to moderate your posts (only subscribers can write
> > > without moderation), and you might not see the answer when someone
> > replies
> > > to "dev@".
> > >
> > > J.
> > >
> > > On Fri, Sep 11, 2026 at 6:55 PM Jake McGrath via dev <
> > > [email protected]> wrote:
> > >
> > >> I agree with Constance that this is something that needs a bit more
> > >> discussion; this is something that I’ve bumped into a good bit lately,
> > >> specifically, with Asset-watching of S3.
> > >>
> > >> I like to think about this starting with the DAG. If my DAG has Tasks
> > >> within it that are only meant to parse a single file, then a single
> run
> > >> for
> > >> > 1 Asset Event would most likely break my DAG/not be properly
> handled.
> > >>
> > >> I do think there is a use-case for the existing “batching” sort of
> > >> behavior. However, I’d personally lean towards  NOT batching Asset
> > Events
> > >> by default.
> > >>
> > >>
> > >>
> > >>
> > >> On Sep 10, 2026 at 7:40:29 PM, Constance Martineau via dev <
> > >> [email protected]> wrote:
> > >>
> > >> > Hi all,
> > >> >
> > >> > Raising something that has been coming up over the past few years,
> > >> > especially recently with Asset Watchers: When a Dag is
> > asset-triggered,
> > >> the
> > >> > scheduler consumes every pending AssetEvent for that Dag in one loop
> > and
> > >> > creates a single DagRun for all of them
> > >> (_create_dag_runs_asset_triggered).
> > >> > If five files land and generate five events before the next
> scheduler
> > >> loop
> > >> > runs, you get one DagRun that consumes all five events, not five
> > >> separate
> > >> > DagRuns. Most users assume 1 event -> 1 DagRun and read the
> batchings
> > as
> > >> > Airflow dropping or missing events, and how much gets batched
> depends
> > on
> > >> > scheduler loop and Dag parallelism settings, not anything declared
> in
> > >> the
> > >> > Dag (see https://github.com/apache/airflow/issues/56750). This
> > >> behavior is
> > >> > intentional, dating back to when datasets shipped in 2.4, but the
> > >> > perception that "this is a bug" is real. This issue has come up as a
> > >> > specific point at Airflow Summit talks two years running, with
> > speakers
> > >> > assuming this was Airflow 2 flakiness that had since been fixed.
> > >> >
> > >> > It's not just a perception problem, either. Any asset-triggered Dag
> > that
> > >> > isn't explicitly written to iterate `dag_run.consumed_asset_events`
> > will
> > >> > silently under-process when multiple events land in the same run. It
> > >> looks
> > >> > like "1 run = 1 file" and quietly drops the rest. This isn't a
> > >> hypothetical
> > >> > scenario. The exact use-case that prompted this is that someone in
> one
> > >> of
> > >> > our client facing teams is building an S3 trigger on the
> AssetWatcher
> > >> > framework (there's no official S3 event trigger for this yet, the
> only
> > >> > documented AssetWatcher pattern today is SQS) that emits one event
> per
> > >> > updated file, with several files landing in the same scheduler loop.
> > >> > Because how many events get bundled depends on scheduler cadence and
> > >> > parallelism rather than anything declared in the Dag, this behavior
> is
> > >> also
> > >> > untestable. There's no way to write a CI test that reliably asserts
> "N
> > >> > events produce N runs".
> > >> >
> > >> > There's already community momentum here:
> > >> >
> > >> >   - #55956 <https://github.com/apache/airflow/issues/55956>
> proposes
> > a
> > >> >   `max_asset_events` param, milestoned for 3.4.0
> > >> >   - #56750
> > >> >   <
> > >> >
> > >>
> >
> https://medium.com/@MarinAgli1/a-look-into-airflow-data-aware-scheduling-and-dynamic-task-mapping-8c548d4ad79
> > >> > >
> > >> >   groups the related issues (#53896
> > >> >   <https://github.com/apache/airflow/issues/53896>, #56691
> > >> >   <https://github.com/apache/airflow/issues/56691>, #56050
> > >> >   <https://github.com/apache/airflow/issues/56050> and #47398
> > >> >   <https://github.com/apache/airflow/issues/47398>) and proposes a
> > >> >   Dag-level toggle (`asset_grouping`) rather than an all-or-nothing
> > >> global
> > >> >   switch.
> > >> >
> > >> > Regarding the question of whether this can only be a global config:
> I
> > >> don't
> > >> > think so. `_create_dag_runs_asset_triggered` already loops per-Dag
> and
> > >> only
> > >> > fetches that Dag's own pending events before building its DagRun,
> so a
> > >> > per-Dag opt-in is localized to that branch and shouldn't require
> > >> touching
> > >> > the shared code path every other asset-scheduled Dag depends on. I'd
> > >> model
> > >> > this the same way we already handle `catchup`: a Dag-level parameter
> > >> (like
> > >> > `asset_grouping`) that falls back to a global
> > >> `asset_grouping_by_default`
> > >> > in airflow configs when unset, mirroring `catchup` /
> > >> `catchup_by_default`.
> > >> > That gives Dag authors an explicit override where usage is genuinely
> > >> mixed,
> > >> > while still letting an org flip the behaviour fleet-wide for every
> Dag
> > >> that
> > >> > hasn't opted in, without touching Dag code. SCrocky's issue for
> > example
> > >> > Idescribes running both patterns side by side in the same
> deployment.
> > >> >
> > >> > Where I want actual discussion: What should
> > `asset_grouping_by_default`
> > >> > ship as? Every proposal so far (including ours) assumes it has to
> > >> default
> > >> > to today's batched behaviour, to avoid a breaking change. I want to
> > make
> > >> > the case for defaulting it to `False` (1 event -> 1 DagRun) instead,
> > >> > because the cost asymmetric.
> > >> >
> > >> >   - If we default to unbatched and someone was relying on batching,
> > the
> > >> >   worst case is an extra DagRun. They were never able to control the
> > >> batch
> > >> >   size to begin with as it depends on the scheduler cadence and
> > >> > parallelism,
> > >> >   not anything declared in the Dag, so their code already has to
> > >> tolerate a
> > >> >   variable number of events per run. An occasional extra run is just
> > >> more
> > >> > of
> > >> >   the same variance they already had to handle, not a new failure
> > mode.
> > >> >   - If we keep batching as the default, everyone who wants per-event
> > >> >   semantics, which judging by the summit and this thread is most
> > >> people's
> > >> >   mental model, has to actively work around it. They need to inspect
> > how
> > >> > many
> > >> >   events landed in a run and add conditional/expansion logic to
> split
> > >> them
> > >> >   back out, which is exactly the workaround we're discussing
> > internally
> > >> > right
> > >> >   now. This imposes real, ongoing complexity on the majority to
> > protect
> > >> a
> > >> >   minority's default.
> > >> >
> > >> > I don't think this is a close call.
> > >> >
> > >> > I'm not trying to let perfect be the enemy of good. If we can only
> get
> > >> > consensus on an opt-in with today's default, that's still a real
> > >> > improvement, but I'd rather we make the case for the better default
> > >> before
> > >> > settling for that.
> > >> >
> > >> > Curious what others thing, especially anyone closer to #56750
> > >> > <
> > >> >
> > >>
> >
> https://medium.com/@MarinAgli1/a-look-into-airflow-data-aware-scheduling-and-dynamic-task-mapping-8c548d4ad79
> > >> > >
> > >> > .
> > >> >
> > >> > Thanks,
> > >> > Constance
> > >> >
> > >> >
> > >> > --
> > >> >
> > >> > Constance Martineau
> > >> >
> > >> > Staff Product Manager
> > >> >
> > >> > Email: [email protected]
> > >> >
> > >> > Time zone: US Eastern (EST UTC-5 / EDT UTC-4)
> > >> >
> > >>
> > >
> >
>

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