### Apache Airflow Provider(s)

apache-spark

### Versions of Apache Airflow Providers

apache-airflow-providers-apache-spark==2.0.1

### Apache Airflow version

2.1.4

### Operating System

Amazon Linux 2

### Deployment

Virtualenv installation

### Deployment details

_No response_

### What happened

In the file `airflow/providers/apache/spark/hooks/spark_submit.py`, the function [_process_spark_status_log](https://github.com/apache/airflow/blob/main/airflow/providers/apache/spark/hooks/spark_submit.py#L516-L535) iterates through a `curl` response to get the driver state of a `SparkSubmitOperator` task.

If there's a transient network issue and there is no valid response from the cluster (e.g. timeout, etc.), there is no "driverState" in the `curl` response, which makes the driver state "UNKNOWN".

That state [exits the loop](https://github.com/apache/airflow/blob/main/airflow/providers/apache/spark/hooks/spark_submit.py#L573) and then makes the task to go on a [retry](https://github.com/apache/airflow/blob/main/airflow/providers/apache/spark/hooks/spark_submit.py#L464-L467), while the original task is actually still in a "RUNNING" state.

### What you expected to happen

I would expect the task not to go on a retry while the original task is running. The function `_process_spark_status_log` should probably ensure the `curl` response is valid before changing the driver state, e.g. check that there is a "submissionId"  in the response as well, otherwise leave the state to `None` and continue with the polling loop. A valid response would be something like this:
```
curl http://spark-host:6066/v1/submissions/status/driver-FOO-BAR

{
  "action" : "SubmissionStatusResponse",
  "driverState" : "RUNNING",
  "serverSparkVersion" : "2.4.6",
  "submissionId" : "driver-FOO-BAR,
  "success" : true,
  "workerHostPort" : "FOO:BAR",
  "workerId" : "worker-FOO-BAR-BAZ"
}
```
### How to reproduce

Use any DAG with a `SparkSubmitOperator` task on a Spark Standalone cluster where you can reset the network connection, or modify the `curl` command to return something other than the response above.

### 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)

airflow/providers/apache/spark/hooks/spark_submit.py
else:
                conn_data['master'] = conn.host
            
            extra = conn.extra_dejson
            conn_data['queue'] = extra.get('queue')
            conn_data['deploy_mode'] = extra.get('deploy-mode')
            conn_data['spark_home'] = extra.get('spark-home')
            conn_data['spark_binary'] = self._spark_binary or extra.get('spark-binary', "spark-submit")
            conn_data['namespace'] = extra.get('namespace')
        except AirflowException:
            self.log.info(
                "Could not load connection string %s, defaulting to %s", self._conn_id, conn_data['master']
            )
        if 'spark.kubernetes.namespace' in self._conf:
            conn_data['namespace'] = self._conf['spark.kubernetes.namespace']
        return conn_data
    def get_conn(self) -> Any:
        pass
    def _get_spark_binary_path(self) -> List[str]:
        
        
        
        if self._connection['spark_home']:
            connection_cmd = [
                os.path.join(self._connection['spark_home'], 'bin', self._connection['spark_binary'])
            ]
        else:
            connection_cmd = [self._connection['spark_binary']]
        return connection_cmd
    def _mask_cmd(self, connection_cmd: Union[str, List[str]]) -> str: