**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 logs including metadata."""
        dag_id = request.args.get('dag_id')
        task_id = request.args.get('task_id')
        execution_date = request.args.get('execution_date')
        try_number = request.args.get('try_number', type=int)
        metadata = request.args.get('metadata')
        metadata = json.loads(metadata)
        response_format = request.args.get('format', 'json')
        
        if not metadata:
            metadata = {}
        
        try:
            execution_date = timezone.parse(execution_date)
        except ValueError: