### Apache Airflow version

main (development)

### What happened

The provider operator for Google Cloud Dataproc Batches has two bugs: 

1. The running [operator](https://github.com/apache/airflow/blob/main/airflow/providers/google/cloud/operators/dataproc.py#L2123-L2124) returns successful even if the job transitions to State.CANCELLED or State.CANCELLING 
2. It [attempts](https://github.com/apache/airflow/blob/main/airflow/providers/google/cloud/operators/dataproc.py#L2154) to 'reattach' to a potentially running job if it AlreadyExists, but it sends the wrong type since 'result' is a Batch and needs Operation

### What you think should happen instead

A new hook that polls for batch job completion.  There is precedent for it in traditional dataproc with 'wait_for_job'.

### How to reproduce

Use the Breeze environment and a DAG that runs DataprocCreateBatchOperator.  Allow the first instance to start. 

Use the gcloud CLI to cancel the job. 

`gcloud dataproc batches cancel <batch_id> --project <project_id> --region <region>`

Observe that the task completes successfully after a 3-5 minute timeout, even though the job was cancelled. 

Run the task again with the same batch_id.  Observe the ValueError where it expects Operation but receives Batch



### Operating System

Darwin 5806 21.6.0 Darwin Kernel Version 21.6.0: Mon Aug 22 20:17:10 PDT 2022; root:xnu-8020.140.49~2/RELEASE_X86_64 x86_64

### Versions of Apache Airflow Providers

Same as dev (main) version. 

### Deployment

Other Docker-based deployment

### Deployment details

Observable in the Breeze environment, when running against real Google Infrastructure. 

### Anything else

Every time. 

### 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.protobuf.duration_pb2 import Duration
from google.protobuf.field_mask_pb2 import FieldMask
from airflow.exceptions import AirflowException
from airflow.providers.google.common.consts import CLIENT_INFO
from airflow.providers.google.common.hooks.base_google import GoogleBaseHook
from airflow.version import version as airflow_version
class DataProcJobBuilder:
    """A helper class for building Dataproc job."""
    def __init__(
        self,
        project_id: str,
        task_id: str,
        cluster_name: str,
        job_type: str,
        properties: dict[str, str] | None = None,
    ) -> None:
        name = f"{task_id.replace('.', '_')}_{uuid.uuid4()!s:.8}"
        self.job_type = job_type
        self.job: dict[str, Any] = {
            "job": {
                "reference": {"project_id": project_id, "job_id": name},
                "placement": {"cluster_name": cluster_name},
                "labels": {"airflow-version": "v" + airflow_version.replace(".", "-").replace("+", "-")},
                job_type: {},
            }
        }
        if properties is not None:
            self.job["job"][job_type]["properties"] = properties
    def add_labels(self, labels: dict | None = None) -> None: