**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/models/dag.py
"""
        Returns the number of active "running" dag runs
        :param external_trigger: True for externally triggered active dag runs
        :type external_trigger: bool
        :param session:
        :return: number greater than 0 for active dag runs
        """
        
        query = (
            session.query(func.count())
            .filter(DagRun.dag_id == self.dag_id)
            .filter(DagRun.state == State.RUNNING)
        )
        if external_trigger is not None:
            query = query.filter(
                DagRun.external_trigger == (expression.true() if external_trigger else expression.false())
            )
        return query.scalar()
    @provide_session
    def get_dagrun(self, execution_date, session=None):