**Description**

It appears that [`SparkSubmitHook`](https://airflow.apache.org/docs/stable/_api/airflow/contrib/operators/spark_submit_operator/index.html)'s [implementation](https://github.com/apache/airflow/blob/master/airflow/providers/apache/spark/hooks/spark_submit.py) of kerberos support is orthogonal to the `airflow kerberos` support. It requires us to specify a keytab in the task which will not work for us because our worker container intentionally does not have a volume mount for the keytab. This means we will have to modify SparkSubmit[Hook/Operator] to [use ticket cache](https://spark.apache.org/docs/latest/security.html#using-a-ticket-cache).

**Use case / motivation**

I want to use spark submit operator natively w/ ccache. 

**Proposed Changes **


I think this should be an addition of "use_krb5ccache" variable to hook and operator that defaults to 'False' for backwards compatibility.
When it is `True` we should add the following to the spark submit command construction:
```python3
if self.use_krb5ccache:
    if not os.getenv('KRB5CCNAME'):
        raise AirflowException("KRB5CCNAME environment variable not set while trying to us ticket from ccache.")
    connection_cmd += [
         "--conf",
         "spark.kerberos.renewal.credentials=ccache"
     ]
```

We should also fall back to use principal from security kerberos config if not specified in the task.
```
   self._principal = principal if principal else conf.get('kerberos', 'principal')
```

Note I've tested something similar via cluster policy as a workaround in my current project:
```python3
def spark_tasks_use_ccache(task: BaseOperator):
    """Configure SparkSubmitOperator tasks to use kerberos ticket cache."""
    if isinstance(task, SparkSubmitOperator):
        # pylint: disable=protected-access
        if task._conf:  # noqa
            task._conf["spark.kerberos.renewal.credentials"] = "ccache"  # noqa
        task._principal = conf.get('kerberos', 'principal')
```


cc: @mik-laj @potiuk WDYT about contributing this sort of thing back to airflow? should we change this in the hook? would it be interesting to contribute useful example cluster policies to airflow?
hook = SparkSubmitHook(conn_id="spark_standalone_cluster")
        log_lines = [
            "Submitting a request for the status of submission "
            "driver-20171128111415-0001 in spark://spark-standalone-master:6066",
            "17/11/28 11:15:37 INFO RestSubmissionClient: Server responded with SubmissionStatusResponse:",
            "{",
            '"action" : "SubmissionStatusResponse",',
            '"driverState" : "RUNNING",',
            '"serverSparkVersion" : "1.6.0",',
            '"submissionId" : "driver-20171128111415-0001",',
            '"success" : true,',
            '"workerHostPort" : "172.18.0.7:38561",',
            '"workerId" : "worker-20171128110741-172.18.0.7-38561"',
            "}",
        ]
        
        hook._process_spark_status_log(log_lines)
        
        assert hook._driver_status == "RUNNING"
    def test_process_spark_driver_status_log_bad_response(self):