### 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 self.job_template:
            self.job = self.job_template.build()
            if self.job is None:
                raise Exception("The job should be set here.")
            self.dataproc_job_id = self.job["job"]["reference"]["job_id"]
            self.log.info("Submitting %s job %s", self.job_type, self.dataproc_job_id)
            job_object = self.hook.submit_job(
                project_id=self.project_id, job=self.job["job"], region=self.region
            )
            job_id = job_object.reference.job_id
            self.log.info("Job %s submitted successfully.", job_id)
            
            DataprocLink.persist(
                context=context, task_instance=self, url=DATAPROC_JOB_LOG_LINK, resource=job_id
            )
            if self.deferrable:
                self.defer(
                    trigger=DataprocSubmitTrigger(
                        job_id=job_id,
                        project_id=self.project_id,
                        region=self.region,
                        delegate_to=self.delegate_to,
                        gcp_conn_id=self.gcp_conn_id,
                        impersonation_chain=self.impersonation_chain,
                        polling_interval_seconds=self.polling_interval_seconds,
                    ),
                    method_name="execute_complete",