**Apache Airflow version**: 2.0.0a2

**Kubernetes version (if you are using kubernetes)** (use `kubectl version`): v1.15.12

**Environment**:
- **OS** (e.g. from /etc/os-release): CentOS 7


**What happened**:

When using KubernetesExecutor, a single SIGTERM doesn't result in the scheduler actually exiting cleanly. However, it will exit after receiving a second SIGTERM.

The same behavior happens if you have an exception in the scheduler. An easy way to replicate it is to raise in `pod_mutation_hook`.

In practice, this means the scheduler doesn't get restarted by K8s after encountering a exception. Or, when terminating the scheduler pod, it sticks around until k8s ultimately sends it a SIGKILL after its grace period is up.

**What you expected to happen**:

The scheduler to exit after a single SIGTERM.

**How to reproduce it**:
The easiest way to reproduce it is to simply send a SIGKILL to your KubernetesExecutor scheduler pod:

```
$ kubectl exec {scheduler_pod_name} kill 1
```

Note, the pod stays running, while the logs report:

```
[2020-10-30 17:34:09,581] {scheduler_job.py:794} INFO - Exiting gracefully upon receiving signal 15
[2020-10-30 17:34:10,586] {process_utils.py:97} INFO - Sending Signals.SIGTERM to GPID 59
[2020-10-30 17:34:10,879] {process_utils.py:63} INFO - Process psutil.Process(pid=59, status='terminated', exitcode=0, started=
'17:33:23') (59) terminated with exit code 0
[2020-10-30 17:34:10,882] {process_utils.py:97} INFO - Sending Signals.SIGTERM to GPID 59
[2020-10-30 17:34:10,882] {scheduler_job.py:1329} INFO - Exited execute loop
```

Issue another `kill`:
```
$ kubectl exec {scheduler_pod_name} kill 1
```

And the pod will be restarted by k8s.

If you can't reproduce it, let me know and I'll try and get something running on kind.

**Anything else we need to know**:

The same behavior happens if you have an exception in the scheduler. An easy way to replicate it is to raise in a `pod_mutation_hook`.


tests/jobs/test_scheduler_job.py
empty_dir = mkdtemp()
        current_process = psutil.Process()
        old_children = current_process.children(recursive=True)
        self.scheduler_job = SchedulerJob(
            subdir=empty_dir, num_runs=1, executor=MockExecutor(do_update=False)
        )
        self.scheduler_job.run()
        shutil.rmtree(empty_dir)
        
        current_children = set(current_process.children(recursive=True)) - set(old_children)
        assert not current_children
    @mock.patch('airflow.jobs.scheduler_job.TaskCallbackRequest')
    @mock.patch('airflow.jobs.scheduler_job.Stats.incr')
    def test_process_executor_events(self, mock_stats_incr, mock_task_callback):
        dag_id = "test_process_executor_events"
        dag_id2 = "test_process_executor_events_2"
        task_id_1 = 'dummy_task'
        dag = DAG(dag_id=dag_id, start_date=DEFAULT_DATE, full_filepath="/test_path1/")
        dag2 = DAG(dag_id=dag_id2, start_date=DEFAULT_DATE, full_filepath="/test_path1/")
        task1 = DummyOperator(dag=dag, task_id=task_id_1)
        DummyOperator(dag=dag2, task_id=task_id_1)
        dag.fileloc = "/test_path1/"
        dag2.fileloc = "/test_path1/"
        executor = MockExecutor(do_update=False)
        task_callback = mock.MagicMock()
        mock_task_callback.return_value = task_callback
        self.scheduler_job = SchedulerJob(executor=executor)
        self.scheduler_job.processor_agent = mock.MagicMock()
        session = settings.Session()
        dag.sync_to_db(session=session)