**Description**

For a DAG that looks like this:

```
A >> B
```

If A fails, B goes into "upstream_failed" state. If a user then marks A "success", B will remain in "upstream_failed" state. It will not automatically start running. This scenario often happens if the failure of A is dealt with outside of Airflow and the user does not want Airflow to run A again. But he usually expect Airflow to run B after A is marked "success".

**Use case / motivation**

After A is marked "success", its downstream tasks B should be cleared automatically and get ready to be scheduled. To avoid changing this behaviour completely, there can be a toggle button next to "Success" that lets the user decide if he wants Airflow to automatically clear downstream tasks that are in "upstream_failed" state.
airflow/www/views.py
'dag_id': wwwutils.dag_link,
    }
class TaskRescheduleModelView(AirflowModelView):
    """View to show records from Task Reschedule table"""
    route_base = '/taskreschedule'
    datamodel = AirflowModelView.CustomSQLAInterface(models.TaskReschedule)  
    related_views = [DagRunModelView]
    class_permission_name = permissions.RESOURCE_TASK_RESCHEDULE
    method_permission_name = {
        'list': 'read',
    }
    base_permissions = [
        permissions.ACTION_CAN_READ,
        permissions.ACTION_CAN_ACCESS_MENU,
    ]
    list_columns = [
        'id',
        'dag_id',
        'task_id',
        'execution_date',
        'try_number',
        'start_date',
        'end_date',
        'duration',
        'reschedule_date',
    ]
    search_columns = ['dag_id', 'task_id', 'execution_date', 'start_date', 'end_date', 'reschedule_date']
    base_order = ('id', 'desc')
    base_filters = [['dag_id', DagFilter, lambda: []]]
    def duration_f(self):