### Description

It would be nice if we could give the DatabricksSubmitRunOperator a pipeline name instead of a pipeline_id for cases when you do not already know the pipeline_id but do know the name. I'm not sure if there's an easy way to fetch a pipeline_id.

### Use case/motivation

Avoid hardcoding pipeline ID's, storing the ID's elsewhere, or fetching the pipeline list and filtering it manually if the pipeline name is known, but ID is not.

### 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)

of the ``DatabricksRunNowOperator`` directly. Note that there is exactly
    one named parameter for each top level parameter in the ``run-now``
    endpoint. In this method, your code would look like this: ::
        job_id=42
        notebook_params = {
            "dry-run": "true",
            "oldest-time-to-consider": "1457570074236"
        }
        python_params = ["douglas adams", "42"]
        jar_params = ["douglas adams", "42"]
        spark_submit_params = ["--class", "org.apache.spark.examples.SparkPi"]
        notebook_run = DatabricksRunNowOperator(
            job_id=job_id,
            notebook_params=notebook_params,
            python_params=python_params,
            jar_params=jar_params,
            spark_submit_params=spark_submit_params
        )
    In the case where both the json parameter **AND** the named parameters
    are provided, they will be merged together. If there are conflicts during the merge,
    the named parameters will take precedence and override the top level ``json`` keys.
    Currently the named parameters that ``DatabricksRunNowOperator`` supports are
        - ``job_id``
        - ``job_name``
        - ``json``
        - ``notebook_params``
        - ``python_params``
        - ``python_named_parameters``
        - ``jar_params``
        - ``spark_submit_params``