### 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)

"""Returns BatchControllerAsyncClient"""
        client_options = None
        if region and region != "global":
            client_options = ClientOptions(api_endpoint=f"{region}-dataproc.googleapis.com:443")
        return BatchControllerAsyncClient(
            credentials=self.get_credentials(), client_info=CLIENT_INFO, client_options=client_options
        )
    def get_operations_client(self, region: str) -> OperationsClient:
        """Returns OperationsClient"""
        return self.get_template_client(region=region).transport.operations_client
    @GoogleBaseHook.fallback_to_default_project_id
    async def create_cluster(
        self,
        region: str,
        project_id: str,
        cluster_name: str,
        cluster_config: dict | Cluster | None = None,
        virtual_cluster_config: dict | None = None,
        labels: dict[str, str] | None = None,
        request_id: str | None = None,
        retry: Retry | _MethodDefault = DEFAULT,
        timeout: float | None = None,
        metadata: Sequence[tuple[str, str]] = (),
    ):
        """
        Creates a cluster in a project.
        :param project_id: Required. The ID of the Google Cloud project that the cluster belongs to.
        :param region: Required. The Cloud Dataproc region in which to handle the request.
        :param cluster_name: Name of the cluster to create