### 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)

from airflow.utils.session import provide_session
if sys.version_info < (3, 8):
    from asynctest import mock
    from asynctest.mock import CoroutineMock as AsyncMock
else:
    from unittest import mock
    from unittest.mock import AsyncMock
TASK_ID = "databricks-operator"
DEFAULT_CONN_ID = "databricks_default"
NOTEBOOK_TASK = {"notebook_path": "/test"}
SPARK_PYTHON_TASK = {"python_file": "test.py", "parameters": ["--param", "123"]}
NEW_CLUSTER = {"spark_version": "2.0.x-scala2.10", "node_type_id": "r3.xlarge", "num_workers": 1}
CLUSTER_ID = "cluster_id"
RUN_ID = 1
JOB_ID = 42
JOB_NAME = "job-name"
DEFAULT_RETRY_NUMBER = 3
DEFAULT_RETRY_ARGS = dict(
    wait=tenacity.wait_none(),
    stop=tenacity.stop_after_attempt(DEFAULT_RETRY_NUMBER),
)
HOST = "xx.cloud.databricks.com"
HOST_WITH_SCHEME = "https://xx.cloud.databricks.com"
LOGIN = "login"
PASSWORD = "password"
TOKEN = "token"
RUN_PAGE_URL = "https://XX.cloud.databricks.com/#jobs/1/runs/1"
LIFE_CYCLE_STATE = "PENDING"
STATE_MESSAGE = "Waiting for cluster"
ERROR_MESSAGE = "error message from databricks API"