### 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
if self._yarn_application_id:
                kill_cmd = f"yarn application -kill {self._yarn_application_id}".split()
                env = {**os.environ, **(self._env or {})}
                if self._keytab is not None and self._principal is not None:
                    
                    
                    
                    renew_from_kt(self._principal, self._keytab, exit_on_fail=False)
                    env = os.environ.copy()
                    env["KRB5CCNAME"] = airflow_conf.get('kerberos', 'ccache')
                with subprocess.Popen(
                    kill_cmd, env=env, stdout=subprocess.PIPE, stderr=subprocess.PIPE
                ) as yarn_kill:
                    self.log.info("YARN app killed with return code: %s", yarn_kill.wait())
            if self._kubernetes_driver_pod:
                self.log.info('Killing pod %s on Kubernetes', self._kubernetes_driver_pod)
                
                try:
                    import kubernetes
                    client = kube_client.get_kube_client()
                    api_response = client.delete_namespaced_pod(
                        self._kubernetes_driver_pod,
                        self._connection['namespace'],
                        body=kubernetes.client.V1DeleteOptions(),
                        pretty=True,
                    )
                    self.log.info("Spark on K8s killed with response: %s", api_response)
                except kube_client.ApiException:
                    self.log.exception("Exception when attempting to kill Spark on K8s")