### Apache Airflow version

Other Airflow 2 version (please specify below)

### What happened

Airflow version: 2.3.4 (Composer 2.1.12)

I've been using the DataprocCreateBatchOperator with the deferrable=True option. It worked well for the past few months, but an error started appearing on June 21, 2023, at 16:51 UTC. The error message is as follows:
```
grpc.aio._call.AioRpcError: <AioRpcError of RPC that terminated with:
	status = StatusCode.INVALID_ARGUMENT
	details = "Request contains an invalid argument."
	debug_error_string = "UNKNOWN:Error received from peer ipv4:74.125.69.95:443 {grpc_message:"Request contains an invalid argument.", grpc_status:3, created_time:"2023-06-21T16:51:22.992951359+00:00"}"
```

### What you think should happen instead

The name argument in the [hook code](https://github.com/apache/airflow/blob/main/airflow/providers/google/cloud/hooks/dataproc.py#L1746) follows the format "projects/PROJECT_ID/regions/DATAPROC_REGION/batches/BATCH_ID". However, according to the [Google Cloud DataProc API Reference](https://cloud.google.com/dataproc-serverless/docs/reference/rpc/google.cloud.dataproc.v1#google.cloud.dataproc.v1.GetBatchRequest), it should be in the format "projects/PROJECT_ID/locations/DATAPROC_REGION/batches/BATCH_ID .

### How to reproduce

just run a dataproc operator like this
```
create_batch = DataprocCreateBatchOperator(
        task_id="create_batch",
        batch_id="batch_test",
        deferrable=True,
)
```

### Operating System

Ubuntu 20.04

### Versions of Apache Airflow Providers

_No response_

### Deployment

Google Cloud Composer

### Deployment details

Composer 2.1.12

### Anything else

_No response_

### 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)

main = "main"
        self.builder.set_main(main_class=None, main_jar=main)
        assert main == self.builder.job["job"][self.job_type]["main_jar_file_uri"]
    def test_set_python_main(self):
        main = "main"
        self.builder.set_python_main(main)
        assert main == self.builder.job["job"][self.job_type]["main_python_file_uri"]
    @pytest.mark.parametrize(
        "job_name",
        [
            pytest.param("name", id="simple"),
            pytest.param("name_with_dash", id="name with underscores"),
            pytest.param("group.name", id="name with dot"),
            pytest.param("group.name_with_dash", id="name with dot and underscores"),
        ],
    )
    @mock.patch(DATAPROC_STRING.format("uuid.uuid4"))
    def test_set_job_name(self, mock_uuid, job_name):
        uuid = "test_uuid"
        expected_job_name = f"{job_name}_{uuid[:8]}".replace(".", "_")
        mock_uuid.return_value = uuid
        self.builder.set_job_name(job_name)
        assert expected_job_name == self.builder.job["job"]["reference"]["job_id"]
        assert len(self.builder.job["job"]["reference"]["job_id"]) == len(job_name) + 9
    def test_build(self):
        assert self.builder.job == self.builder.build()