### Apache Airflow version

main (development)

### What happened

The DataprocCreateBatchOperator (Google provider) handles the case when a batch_id already exists in the Dataproc API by 'reattaching' to a potentially running job.  

Current reattachment logic uses the non-deferrable method even when the operator is in deferrable mode.  

### What you think should happen instead

The operator should reattach in deferrable mode. 

### How to reproduce

Create a DAG with a task of DataprocCreateBatchOperator that is long running.  Make DataprocCreateBatchOperator deferrable in the constructor.  

Restart local Airflow to simulate having to 'reattach' to a running job in Google Cloud Dataproc. 

The operator resumes using the running job but in the code path for the non-derferrable logic.  

### Operating System

macOS 13.4.1 (22F82)

### Versions of Apache Airflow Providers

Current main.

### Deployment

Official Apache Airflow Helm Chart

### Deployment details

_No response_

### Anything else

_No response_

### Are you willing to submit 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