**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
]
    )
    @action_logging
    def delete(self):
        """Deletes DAG."""
        from airflow.api.common.experimental import delete_dag
        from airflow.exceptions import DagFileExists, DagNotFound
        dag_id = request.values.get('dag_id')
        origin = get_safe_url(request.values.get('origin'))
        try:
            delete_dag.delete_dag(dag_id)
        except DagNotFound:
            flash(f"DAG with id {dag_id} not found. Cannot delete", 'error')
            return redirect(request.referrer)
        except DagFileExists:
            flash(f"Dag id {dag_id} is still in DagBag. Remove the DAG file first.", 'error')
            return redirect(request.referrer)
        flash(f"Deleting DAG with id {dag_id}. May take a couple minutes to fully disappear.")
        
        return redirect(origin)
    @expose('/trigger', methods=['POST', 'GET'])
    @auth.has_access(
        [
            (permissions.ACTION_CAN_EDIT, permissions.RESOURCE_DAG),
            (permissions.ACTION_CAN_CREATE, permissions.RESOURCE_DAG_RUN),
        ]
    )
    @action_logging
    @provide_session
    def trigger(self, session=None):