### Description

Add Databricks Cluster API in Databricks Hook


### Use case/motivation

Databricks provider lacks [Cluster API](https://docs.databricks.com/dev-tools/api/latest/clusters.html) access to allow
to CRUD cluster as well as manage clusters (start/restart/delete/...)
Those API are very convenient to control clusters (get status, force shutdown...) and to optimize some specific flows (scale cluster in advance when a coming need is detected )

### Related issues

none

### 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)

"""
        Retrieves job_id from run_id.
        :param run_id: id of the run
        :return: Job id for given Databricks run
        """
        json = {"run_id": run_id}
        response = self._do_api_call(GET_RUN_ENDPOINT, json)
        return response["job_id"]
    def get_run_state(self, run_id: int) -> RunState:
        """
        Retrieves run state of the run.
        Please note that any Airflow tasks that call the ``get_run_state`` method will result in
        failure unless you have enabled xcom pickling.  This can be done using the following
        environment variable: ``AIRFLOW__CORE__ENABLE_XCOM_PICKLING``
        If you do not want to enable xcom pickling, use the ``get_run_state_str`` method to get
        a string describing state, or ``get_run_state_lifecycle``, ``get_run_state_result``, or
        ``get_run_state_message`` to get individual components of the run state.
        :param run_id: id of the run
        :return: state of the run
        """
        json = {"run_id": run_id}
        response = self._do_api_call(GET_RUN_ENDPOINT, json)
        state = response["state"]
        return RunState(**state)
    async def a_get_run_state(self, run_id: int) -> RunState: