**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
"""Retrieve XCOM."""
        dag_id = request.args.get('dag_id')
        task_id = request.args.get('task_id')
        
        
        execution_date = request.args.get('execution_date')
        dttm = timezone.parse(execution_date)
        form = DateTimeForm(data={'execution_date': dttm})
        root = request.args.get('root', '')
        dm_db = models.DagModel
        ti_db = models.TaskInstance
        dag = session.query(dm_db).filter(dm_db.dag_id == dag_id).first()
        ti = session.query(ti_db).filter(ti_db.dag_id == dag_id and ti_db.task_id == task_id).first()
        if not ti:
            flash(f"Task [{dag_id}.{task_id}] doesn't seem to exist at the moment", "error")