SameerMesiah97 opened a new issue, #61467:
URL: https://github.com/apache/airflow/issues/61467
### Apache Airflow Provider(s)
dbt-cloud
### Versions of Apache Airflow Providers
`apache-airflow-providers-dbt-cloud==4.6.4`
### Apache Airflow version
main
### Operating System
Debian GNU/Linux 12 (bookworm)
### Deployment
Other
### Deployment details
_No response_
### What happened
When using `DbtCloudRunJobOperator` in **deferrable mode** with
`execution_timeout` set, the Airflow task times out but the underlying dbt
Cloud job continues running.
In non-deferrable mode, exceeding `execution_timeout` causes both the task
to fail and the dbt Cloud job to be cancelled. In deferrable mode, the task
fails due to timeout, but the external job is not stopped, which can result in
long-running or orphaned dbt Cloud jobs.
This creates inconsistent behavior between deferrable and non-deferrable
execution modes.
### What you think should happen instead
`execution_timeout` should be enforced consistently regardless of execution
mode.
When a deferrable `DbtCloudRunJobOperator` exceeds `execution_timeout`:
* The Airflow task should fail due to execution timeout
* The associated dbt Cloud job should be cancelled
This ensures predictable timeout behavior and prevents leaked dbt Cloud jobs.
### How to reproduce
1. Configure a dbt Cloud connection in Airflow.
2. Create a dbt Cloud job that runs longer than 30 seconds (the
`execution_timeout` used in this reproduction).
3. Create the following DAG (replace <JOB_ID> wiht the ID of your DBT Cloud
Job).
```python
from airflow import DAG
from airflow.providers.dbt.cloud.operators.dbt import DbtCloudRunJobOperator
from datetime import datetime, timedelta
with DAG(
dag_id="dbt_deferrable_execution_timeout_repro",
start_date=datetime(2024, 1, 1),
schedule=None,
catchup=False,
) as dag:
run_dbt = DbtCloudRunJobOperator(
task_id="run_dbt",
job_id=<JOB_ID>,
wait_for_termination=True,
deferrable=True,
execution_timeout=timedelta(seconds=30),
)
```
4. Trigger the DAG and wait for the task to exceed `execution_timeout`.
**Observed Behavior**
* The Airflow task fails due to execution timeout.
* The dbt Cloud job continues running and is not cancelled.
### Anything else
This inconsistency makes `execution_timeout` unreliable for deferrable dbt
Cloud jobs and can lead to unintended dbt Cloud resource usage. While
deferrable operators execute via the triggerer rather than a worker process,
this does not preclude enforcing `execution_timeout ` semantics. The
expectation is that task-level timeout behavior remains consistent across
execution modes, even if the underlying enforcement mechanism differs..
### Are you willing to submit PR?
- [x] Yes I am willing to submit a PR!
### Code of Conduct
- [x] I agree to follow this project's [Code of
Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)
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