### 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)

"""Delete a cluster in a project.
    :param region: Required. The Cloud Dataproc region in which to handle the request (templated).
    :param cluster_name: Required. The cluster name (templated).
    :param project_id: Optional. The ID of the Google Cloud project that the cluster belongs to (templated).
    :param cluster_uuid: Optional. Specifying the ``cluster_uuid`` means the RPC should fail
        if cluster with specified UUID does not exist.
    :param request_id: Optional. A unique id used to identify the request. If the server receives two
        ``DeleteClusterRequest`` requests with the same id, then the second request will be ignored and the
        first ``google.longrunning.Operation`` created and stored in the backend is returned.
    :param retry: A retry object used to retry requests. If ``None`` is specified, requests will not be
        retried.
    :param timeout: The amount of time, in seconds, to wait for the request to complete. Note that if
        ``retry`` is specified, the timeout applies to each individual attempt.
    :param metadata: Additional metadata that is provided to the method.
    :param gcp_conn_id: The connection ID to use connecting to Google Cloud.
    :param impersonation_chain: Optional service account to impersonate using short-term
        credentials, or chained list of accounts required to get the access_token
        of the last account in the list, which will be impersonated in the request.
        If set as a string, the account must grant the originating account
        the Service Account Token Creator IAM role.
        If set as a sequence, the identities from the list must grant
        Service Account Token Creator IAM role to the directly preceding identity, with first
        account from the list granting this role to the originating account (templated).
    :param deferrable: Run operator in the deferrable mode.
    :param polling_interval_seconds: Time (seconds) to wait between calls to check the cluster status.
    """
    template_fields: Sequence[str] = ("project_id", "region", "cluster_name", "impersonation_chain")
    def __init__(