### 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)

if not self.graceful_decommission_timeout:
            return None
        timeout = None
        match = re.match(r"^(\d+)([smdh])$", self.graceful_decommission_timeout)
        if match:
            if match.group(2) == "s":
                timeout = int(match.group(1))
            elif match.group(2) == "m":
                val = float(match.group(1))
                timeout = int(timedelta(minutes=val).total_seconds())
            elif match.group(2) == "h":
                val = float(match.group(1))
                timeout = int(timedelta(hours=val).total_seconds())
            elif match.group(2) == "d":
                val = float(match.group(1))
                timeout = int(timedelta(days=val).total_seconds())
        if not timeout:
            raise AirflowException(
                "DataprocClusterScaleOperator "
                " should be expressed in day, hours, minutes or seconds. "
                " i.e. 1d, 4h, 10m, 30s"
            )
        return {"seconds": timeout}
    def execute(self, context: Context) -> None: