**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
return self.render_template(
            'airflow/graph.html',
            dag=dag,
            form=form,
            width=request.args.get('width', "100%"),
            height=request.args.get('height', "800"),
            execution_date=dttm.isoformat(),
            state_token=wwwutils.state_token(dt_nr_dr_data['dr_state']),
            doc_md=doc_md,
            arrange=arrange,
            operators=sorted({op.task_type: op for op in dag.tasks}.values(), key=lambda x: x.task_type),
            root=root or '',
            task_instances=task_instances,
            tasks=tasks,
            nodes=nodes,
            edges=edges,
            show_external_log_redirect=task_log_reader.supports_external_link,
            external_log_name=external_log_name,
            dag_run_state=dt_nr_dr_data['dr_state'],
        )
    @expose('/duration')
    @auth.has_access(
        [
            (permissions.ACTION_CAN_READ, permissions.RESOURCE_DAG),
            (permissions.ACTION_CAN_READ, permissions.RESOURCE_TASK_INSTANCE),
        ]
    )
    @action_logging  
    @provide_session  
    def duration(self, session=None):