uranusjr commented on code in PR #68517:
URL: https://github.com/apache/airflow/pull/68517#discussion_r4204069269
##########
airflow-core/src/airflow/jobs/scheduler_job_runner.py:
##########
@@ -2931,41 +2958,54 @@ def _create_dag_runs_asset_triggered(
len(queued_adrqs),
triggered_date,
)
- dag_run = dag.create_dagrun(
- run_id=DagRun.generate_run_id(
- run_type=DagRunType.ASSET_TRIGGERED,
logical_date=None, run_after=triggered_date
- ),
- logical_date=None,
- data_interval=None,
- run_after=triggered_date,
- run_type=DagRunType.ASSET_TRIGGERED,
- triggered_by=DagRunTriggeredByType.ASSET,
- state=DagRunState.QUEUED,
- creating_job_id=self.job.id,
- session=session,
- )
+ if dag.timetable.batch_asset_events:
+ event_runs = iter([(triggered_date, asset_events)])
+ else:
+ event_runs = ((timezone.coerce_datetime(ev.timestamp),
[ev]) for ev in asset_events)
Review Comment:
The scheduler now branches on `timetable.batch_asset_events` in several
places. Grouping events into runs should be the timetable's decision. Maybe we
should have a method on the timetable
```python
def group_asset_events(
self,
events,
triggered_date,
) -> Iterable[tuple[datetime, list[AssetEvent]]]
```
for the scheduler to use?
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