**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
"""Mark DagRun failed."""
        dag_id = request.form.get('dag_id')
        execution_date = request.form.get('execution_date')
        confirmed = request.form.get('confirmed') == 'true'
        origin = get_safe_url(request.form.get('origin'))
        return self._mark_dagrun_state_as_failed(dag_id, execution_date, confirmed, origin)
    @expose('/dagrun_success', methods=['POST'])
    @auth.has_access(
        [
            (permissions.ACTION_CAN_READ, permissions.RESOURCE_DAG),
            (permissions.ACTION_CAN_EDIT, permissions.RESOURCE_DAG_RUN),
        ]
    )
    @action_logging
    def dagrun_success(self):
        """Mark DagRun success"""
        dag_id = request.form.get('dag_id')
        execution_date = request.form.get('execution_date')
        confirmed = request.form.get('confirmed') == 'true'
        origin = get_safe_url(request.form.get('origin'))
        return self._mark_dagrun_state_as_success(dag_id, execution_date, confirmed, origin)
    def _mark_task_instance_state(