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
:param init_action_timeout: Amount of time executable scripts in
        init_actions_uris has to complete
    :type init_action_timeout: str
    :param metadata: dict of key-value google compute engine metadata entries
        to add to all instances
    :type metadata: dict
    :param image_version: the version of software inside the Dataproc cluster
    :type image_version: str
    :param custom_image: custom Dataproc image for more info see
        https://cloud.google.com/dataproc/docs/guides/dataproc-images
    :type custom_image: str
    :param custom_image_project_id: project id for the custom Dataproc image, for more info see
        https://cloud.google.com/dataproc/docs/guides/dataproc-images
    :type custom_image_project_id: str
    :param custom_image_family: family for the custom Dataproc image,
        family name can be provide using --family flag while creating custom image, for more info see
        https://cloud.google.com/dataproc/docs/guides/dataproc-images
    :type custom_image_family: str
    :param autoscaling_policy: The autoscaling policy used by the cluster. Only resource names
        including projectid and location (region) are valid. Example:
        ``projects/[projectId]/locations/[dataproc_region]/autoscalingPolicies/[policy_id]``
    :type autoscaling_policy: str
    :param properties: dict of properties to set on
        config files (e.g. spark-defaults.conf), see
        https://cloud.google.com/dataproc/docs/reference/rest/v1/projects.regions.clusters#SoftwareConfig
    :type properties: dict
    :param optional_components: List of optional cluster components, for more info see
        https://cloud.google.com/dataproc/docs/reference/rest/v1/ClusterConfig#Component
    :type optional_components: list[str]
    :param num_masters: The # of master nodes to spin up