### Description

The Python Google Cloud Dataproc API version has been updated in Airflow to support filtering on the Dataproc Batches API.  The DataprocListBatchesOperator can be updated to make use of this filtering.  

Currently, DataprocListBatchesOperator returns, and populates xcom with every job run in the project.  This almost surely will fail as the return object is large and xcom storage is low, especially with MySQL. Filtering on job prefix and create_time are much more useful capabilities. 

### Use case/motivation

The ability to filter lists of GCP Dataproc Batches jobs.  

### 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)

"""Create a new Dataproc Cluster.
    :param cluster_name: The name of the DataProc cluster to create. (templated)
    :param project_id: The ID of the google cloud project in which
        to create the cluster. (templated)
    :param num_workers: The # of workers to spin up. If set to zero will
        spin up cluster in a single node mode
    :param storage_bucket: The storage bucket to use, setting to None lets dataproc
        generate a custom one for you
    :param init_actions_uris: List of GCS uri's containing
        dataproc initialization scripts
    :param init_action_timeout: Amount of time executable scripts in
        init_actions_uris has to complete
    :param metadata: dict of key-value google compute engine metadata entries
        to add to all instances
    :param image_version: the version of software inside the Dataproc cluster
    :param custom_image: custom Dataproc image for more info see
        https://cloud.google.com/dataproc/docs/guides/dataproc-images
    :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
    :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
    :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]``
    :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
    :param optional_components: List of optional cluster components, for more info see