**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
'state',
        'job_type',
        'start_date',
        'end_date',
        'latest_heartbeat',
        'executor_class',
        'hostname',
        'unixname',
    ]
    search_columns = [
        'id',
        'dag_id',
        'state',
        'job_type',
        'start_date',
        'end_date',
        'latest_heartbeat',
        'executor_class',
        'hostname',
        'unixname',
    ]
    base_order = ('start_date', 'desc')
    base_filters = [['dag_id', DagFilter, lambda: []]]
    formatters_columns = {
        'start_date': wwwutils.datetime_f('start_date'),
        'end_date': wwwutils.datetime_f('end_date'),
        'hostname': wwwutils.nobr_f('hostname'),
        'state': wwwutils.state_f,
        'latest_heartbeat': wwwutils.datetime_f('latest_heartbeat'),
    }