victorymakes opened a new pull request, #69442:
URL: https://github.com/apache/airflow/pull/69442
## Summary
`DatabricksSubmitRunOperator` and `DatabricksRunNowOperator` both implement
`on_kill()` to cancel the Databricks run when an Airflow task is killed
(SIGTERM or `execution_timeout`). `DatabricksTaskBaseOperator` — the base for
`DatabricksTaskOperator` and `DatabricksNotebookOperator` — is missing the same
implementation, so Databricks jobs continue running after the Airflow task is
killed, orphaning compute resources and incurring unnecessary cloud spend.
`DatabricksWorkflowTaskGroup` received `on_kill()` in #42115; this PR closes
the remaining gap for standalone task operators.
## Changes
- Adds `on_kill()` to `DatabricksTaskBaseOperator` using
`self.databricks_run_id`, which is:
- initialised to `None` in `__init__` (no `AttributeError` risk)
- set by `_launch_job()` the moment the run is submitted — earlier than
any polling or permission calls
- Adds unit tests covering both the cancel and no-op paths
## Testing
```
pytest
providers/databricks/tests/unit/databricks/operators/test_databricks.py -k
"on_kill"
```
##### Was generative AI tooling used to co-author this PR?
- [x] Yes — Claude Code (Sonnet 4.6)
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