**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
"""Duration calculation."""
        end_date = self.get('end_date')  
        duration = self.get('duration')  
        if end_date and duration:
            return timedelta(seconds=duration)
        return None
    formatters_columns = {
        'dag_id': wwwutils.dag_link,
        'task_id': wwwutils.task_instance_link,
        'start_date': wwwutils.datetime_f('start_date'),
        'end_date': wwwutils.datetime_f('end_date'),
        'execution_date': wwwutils.datetime_f('execution_date'),
        'reschedule_date': wwwutils.datetime_f('reschedule_date'),
        'duration': duration_f,
    }
class TaskInstanceModelView(AirflowModelView):
    """View to show records from TaskInstance table"""
    route_base = '/taskinstance'
    datamodel = AirflowModelView.CustomSQLAInterface(models.TaskInstance)  
    class_permission_name = permissions.RESOURCE_TASK_INSTANCE
    method_permission_name = {
        'list': 'read',
        'action_clear': 'edit',
        'action_set_running': 'edit',
        'action_set_failed': 'edit',