**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
"""Mark Dag Blocked."""
        allowed_dag_ids = current_app.appbuilder.sm.get_accessible_dag_ids(g.user)
        
        selected_dag_ids = {unquote(dag_id) for dag_id in request.form.getlist('dag_ids') if dag_id}
        if selected_dag_ids:
            filter_dag_ids = selected_dag_ids.intersection(allowed_dag_ids)
        else:
            filter_dag_ids = allowed_dag_ids
        if not filter_dag_ids:
            return wwwutils.json_response([])
        
        dags = (
            session.query(DagRun.dag_id, sqla.func.count(DagRun.id))
            .filter(DagRun.state == State.RUNNING)
            .filter(DagRun.dag_id.in_(filter_dag_ids))
            .group_by(DagRun.dag_id)
        )
        
        payload = []
        for dag_id, active_dag_runs in dags:
            max_active_runs = 0
            dag = current_app.dag_bag.get_dag(dag_id)
            if dag:
                
                max_active_runs = dag.max_active_runs