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 😄  

IMPORTANT!!!

PLEASE CHECK "SIMILAR TO X EXISTING ISSUES" OPTION IF VISIBLE
NEXT TO "SUBMIT NEW ISSUE" BUTTON!!!

PLEASE CHECK IF THIS ISSUE HAS BEEN REPORTED PREVIOUSLY USING SEARCH!!!

Please complete the next sections or the issue will be closed.
These questions are the first thing we need to know to understand the context.

-->

**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
"""
    The base class for operators that launch job on DataProc.
    :param job_name: The job name used in the DataProc cluster. This name by default
        is the task_id appended with the execution data, but can be templated. The
        name will always be appended with a random number to avoid name clashes.
    :type job_name: str
    :param cluster_name: The name of the DataProc cluster.
    :type cluster_name: str
    :param project_id: The ID of the Google Cloud project the cluster belongs to,
        if not specified the project will be inferred from the provided GCP connection.
    :type project_id: str
    :param dataproc_properties: Map for the Hive properties. Ideal to put in
        default arguments (templated)
    :type dataproc_properties: dict
    :param dataproc_jars: HCFS URIs of jar files to add to the CLASSPATH of the Hive server and Hadoop
        MapReduce (MR) tasks. Can contain Hive SerDes and UDFs. (templated)
    :type dataproc_jars: list
    :param gcp_conn_id: The connection ID to use connecting to Google Cloud.
    :type gcp_conn_id: str
    :param delegate_to: The account to impersonate using domain-wide delegation of authority,
        if any. For this to work, the service account making the request must have
        domain-wide delegation enabled.
    :type delegate_to: str
    :param labels: The labels to associate with this job. Label keys must contain 1 to 63 characters,
        and must conform to RFC 1035. Label values may be empty, but, if present, must contain 1 to 63
        characters, and must conform to RFC 1035. No more than 32 labels can be associated with a job.
    :type labels: dict
    :param region: The specified region where the dataproc cluster is created.