**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 statistics."""
        dr = models.DagRun
        allowed_dag_ids = current_app.appbuilder.sm.get_accessible_dag_ids(g.user)
        dag_state_stats = session.query(dr.dag_id, dr.state, sqla.func.count(dr.state)).group_by(
            dr.dag_id, dr.state
        )