**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 dag run for a given execution date if it exists, otherwise
        none.
        :param execution_date: The execution date of the DagRun to find.
        :param session:
        :return: The DagRun if found, otherwise None.
        """
        dagrun = (
            session.query(DagRun)
            .filter(DagRun.dag_id == self.dag_id, DagRun.execution_date == execution_date)
            .first()
        )
        return dagrun
    @provide_session
    def get_dagruns_between(self, start_date, end_date, session=None):