### 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)

"""
    The base class for operators that launch job on DataProc.
    :param region: The specified region where the dataproc cluster is created.
    :param job_name: The job name used in the DataProc cluster. This name by default
        is the task_id appended with the execution data, but can be templated. The
        name will always be appended with a random number to avoid name clashes.
    :param cluster_name: The name of the DataProc cluster.
    :param project_id: The ID of the Google Cloud project the cluster belongs to,
        if not specified the project will be inferred from the provided GCP connection.
    :param dataproc_properties: Map for the Hive properties. Ideal to put in
        default arguments (templated)
    :param dataproc_jars: HCFS URIs of jar files to add to the CLASSPATH of the Hive server and Hadoop
        MapReduce (MR) tasks. Can contain Hive SerDes and UDFs. (templated)
    :param gcp_conn_id: The connection ID to use connecting to Google Cloud.
    :param delegate_to: The account to impersonate using domain-wide delegation of authority,
        if any. For this to work, the service account making the request must have
        domain-wide delegation enabled.
    :param labels: The labels to associate with this job. Label keys must contain 1 to 63 characters,
        and must conform to RFC 1035. Label values may be empty, but, if present, must contain 1 to 63