ferruzzi commented on code in PR #50957:
URL: https://github.com/apache/airflow/pull/50957#discussion_r2138330321
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airflow-core/src/airflow/api_fastapi/core_api/datamodels/dag_run.py:
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@@ -68,6 +69,7 @@ class DAGRunResponse(BaseModel):
end_date: datetime | None
data_interval_start: datetime | None
data_interval_end: datetime | None
+ deadlines: list[DeadlineResponse] | None
Review Comment:
I brought it up on the dev call last week and we're going to make (a
variation on) the change you suggested. Here's what the lifespan of a Deadline
will be, using Dagrun as an example:
- When a new Dagrun is created:
- If the dag has a deadline, calculate the value and store it along with
the dag_id, run_id, etc in the `deadline` table
- When a dagrun finishes:
- If (and only if) the current time is before the calculated deadline,
then remove the deadline from the `deadline` table
- The scheduler loop will query the deadline table to see if any deadlines
have expired
- If yes then the callback is sent to the Triggerer to process
- once the callback is run, the Triggerer will move the failed deadline
to a new table (working name is just `missed_deadlines`?)
So `deadlines` table will have all upcoming and unprocessed deadlines.
`missed_deadlines` table will have all expired deadlines which have been
resolved. If the serialized DAG has a deadline and it is in neither table,
then it will be assumed that it completed successfully.
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