### 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)

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"""This module contains a Google Cloud Dataproc hook."""
from __future__ import annotations
import time
import uuid
from typing import Any, Sequence
from google.api_core.client_options import ClientOptions
from google.api_core.exceptions import ServerError
from google.api_core.gapic_v1.method import DEFAULT, _MethodDefault
from google.api_core.operation import Operation
from google.api_core.operation_async import AsyncOperation
from google.api_core.operations_v1.operations_client import OperationsClient
from google.api_core.retry import Retry
from google.cloud.dataproc_v1 import (
    Batch,
    BatchControllerAsyncClient,
    BatchControllerClient,
    Cluster,
    ClusterControllerAsyncClient,
    ClusterControllerClient,
    Job,
    JobControllerAsyncClient,
    JobControllerClient,
    JobStatus,
    WorkflowTemplate,
    WorkflowTemplateServiceAsyncClient,
    WorkflowTemplateServiceClient,