**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
if ti is not None:
            num_logs = ti.next_try_number - 1
            if ti.state == State.UP_FOR_RESCHEDULE:
                
                num_logs += 1
        logs = [''] * num_logs
        root = request.args.get('root', '')
        return self.render_template(
            'airflow/ti_log.html',
            logs=logs,
            dag=dag_model,
            title="Log by attempts",
            dag_id=dag_id,
            task_id=task_id,
            execution_date=execution_date,
            form=form,
            root=root,
            wrapped=conf.getboolean('webserver', 'default_wrap'),
        )
    @expose('/redirect_to_external_log')
    @auth.has_access(
        [
            (permissions.ACTION_CAN_READ, permissions.RESOURCE_DAG),
            (permissions.ACTION_CAN_READ, permissions.RESOURCE_TASK_INSTANCE),
            (permissions.ACTION_CAN_READ, permissions.RESOURCE_TASK_LOG),
        ]
    )
    @action_logging
    @provide_session
    def redirect_to_external_log(self, session=None):