### Description

The Databricks jobs 2.1 API has the ability to repair failed or skipped tasks in a Databricks workflow without having to rerun successful tasks for a given workflow run. It would be nice to be able to leverage this functionality via airflow operators.

### Use case/motivation

The primary motivation is the ability to be more efficient and only have to rerun failed or skipped tasks rather than the entire workflow if only 1 out of 10 tasks fail.

**Repair run API:**
https://docs.databricks.com/dev-tools/api/latest/jobs.html#operation/JobsRunsRepairfail

@alexott for visability

### Related issues

_No response_

### Are you willing to submit a 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)

"""
    Tests for DatabricksHook using async methodswhen auth is done with AAD token
    for SP as user inside workspace and using non-global Azure cloud (China, GovCloud, Germany)
    """
    @provide_session
    def setup_method(self, method, session=None):
        self.tenant_id = "3ff810a6-5504-4ab8-85cb-cd0e6f879c1d"
        self.ad_endpoint = "https://login.microsoftonline.de"
        self.client_id = "9ff815a6-4404-4ab8-85cb-cd0e6f879c1d"
        conn = session.query(Connection).filter(Connection.conn_id == DEFAULT_CONN_ID).first()
        conn.login = self.client_id
        conn.password = "secret"
        conn.extra = json.dumps(
            {
                "host": HOST,
                "azure_tenant_id": self.tenant_id,
                "azure_ad_endpoint": self.ad_endpoint,
            }
        )
        session.commit()
        self.hook = DatabricksHook(retry_args=DEFAULT_RETRY_ARGS)
    @pytest.mark.asyncio
    @mock.patch("airflow.providers.databricks.hooks.databricks_base.aiohttp.ClientSession.get")
    @mock.patch("airflow.providers.databricks.hooks.databricks_base.aiohttp.ClientSession.post")
    async def test_get_run_state(self, mock_post, mock_get):