**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
task_dict['start_date'] = task_dict['start_date'] or end_date
            task_dict['state'] = State.FAILED
            task_dict['operator'] = task.task_type
            task_dict['try_number'] = try_count
            task_dict['extraLinks'] = task.extra_links
            tasks.append(task_dict)
        data = {
            'taskNames': [ti.task_id for ti in tis],
            'tasks': tasks,
            'height': len(tis) * 25 + 25,
        }
        session.commit()
        return self.render_template(
            'airflow/gantt.html',
            dag=dag,
            execution_date=dttm.isoformat(),
            form=form,
            data=data,
            base_date='',
            root=root,
        )
    @expose('/extra_links')
    @auth.has_access(
        [
            (permissions.ACTION_CAN_READ, permissions.RESOURCE_DAG),
            (permissions.ACTION_CAN_READ, permissions.RESOURCE_TASK_INSTANCE),
        ]
    )
    @action_logging
    def extra_links(self):