I'm looking at the GCP Dataproc operator and noticed that the `DataprocCreateClusterOperator` and `DataprocDeleteClusterOperator` require a `region` parameter, but other operators, like the `DataprocSubmitJobOperator` require a `location` parameter instead. I think it would be best to consistently enforce the parameter as `region`, because that's what is required in the protos for all of the [cluster CRUD operations](https://github.com/googleapis/python-dataproc/blob/master/google/cloud/dataproc_v1/proto/clusters.proto) and for [job submission](https://github.com/googleapis/python-dataproc/blob/d4b299216ad833f68ad63866dbdb2c8f2755c6b4/google/cloud/dataproc_v1/proto/jobs.proto#L741). `location` also feels too ambiguous imho, because it implies we could also pass a GCE zone, which in this case is either unnecessary or not supported (I can't remember which and it's too late in my Friday for me to double check 🙃 )

This might be similar to #13454 but I'm not 100% sure. If we think this is worth working on, I could maybe take this on as a PR, but it would be low priority for me, and if someone else wants to take it on, they should feel free to 😄  

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**Apache Airflow version**: 2.0.1


**Environment**:

running locally on a Mac with SQLite backend only running a unit test that makes sure the dag is compiled. Installed with Pip and the provided constraints file. 

**What happened**:

if you pass `location` in the `DataprocCreateClusterOperator` the DAG won't compile and will throw an error `airflow.exceptions.AirflowException: Argument ['region']`

As minimally and precisely as possible. Keep in mind we do not have access to your cluster or dags.


--->


airflow/providers/google/cloud/operators/dataproc.py
"""
    Start a Hadoop Job on a Cloud DataProc cluster.
    :param main_jar: The HCFS URI of the jar file containing the main class
        (use this or the main_class, not both together).
    :type main_jar: str
    :param main_class: Name of the job class. (use this or the main_jar, not both
        together).
    :type main_class: str
    :param arguments: Arguments for the job. (templated)
    :type arguments: list
    :param archives: List of archived files that will be unpacked in the work
        directory. Should be stored in Cloud Storage.
    :type archives: list
    :param files: List of files to be copied to the working directory
    :type files: list
    """
    template_fields = [
        'arguments',
        'job_name',
        'cluster_name',
        'region',
        'dataproc_jars',
        'dataproc_properties',
        'impersonation_chain',
    ]
    ui_color = '#0273d4'
    job_type = 'hadoop_job'
    def __init__(