**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
"""Default filters for model"""
        return (
            super()  
            .get_query()
            .filter(or_(models.DagModel.is_active, models.DagModel.is_paused))
            .filter(~models.DagModel.is_subdag)
        )
    def get_count_query(self):
        """Default filters for model"""
        return (
            super()  
            .get_count_query()
            .filter(models.DagModel.is_active)
            .filter(~models.DagModel.is_subdag)
        )
    @auth.has_access(
        [
            (permissions.ACTION_CAN_READ, permissions.RESOURCE_DAG),
        ]
    )
    @provide_session
    @expose('/autocomplete')
    def autocomplete(self, session=None):