### 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)

from google.api_core.gapic_v1.method import DEFAULT, _MethodDefault
from google.api_core.retry import Retry, exponential_sleep_generator
from google.cloud.dataproc_v1 import Batch, Cluster, ClusterStatus, JobStatus
from google.protobuf.duration_pb2 import Duration
from google.protobuf.field_mask_pb2 import FieldMask
from airflow.exceptions import AirflowException, AirflowProviderDeprecationWarning
from airflow.providers.google.cloud.hooks.dataproc import DataprocHook, DataProcJobBuilder
from airflow.providers.google.cloud.hooks.gcs import GCSHook
from airflow.providers.google.cloud.links.dataproc import (
    DATAPROC_BATCH_LINK,
    DATAPROC_BATCHES_LINK,
    DATAPROC_CLUSTER_LINK,
    DATAPROC_JOB_LOG_LINK,
    DATAPROC_WORKFLOW_LINK,
    DATAPROC_WORKFLOW_TEMPLATE_LINK,
    DataprocLink,
    DataprocListLink,
)
from airflow.providers.google.cloud.operators.cloud_base import GoogleCloudBaseOperator
from airflow.providers.google.cloud.triggers.dataproc import (
    DataprocBatchTrigger,
    DataprocClusterTrigger,
    DataprocDeleteClusterTrigger,
    DataprocSubmitTrigger,
    DataprocWorkflowTrigger,
)
from airflow.utils import timezone
if TYPE_CHECKING:
    from airflow.utils.context import Context
class ClusterGenerator: