**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
'log_url',
    ]
    order_columns = [
        item for item in list_columns if item not in ['try_number', 'log_url', 'external_executor_id']
    ]
    search_columns = [
        'state',
        'dag_id',
        'task_id',
        'execution_date',
        'hostname',
        'queue',
        'pool',
        'operator',
        'start_date',
        'end_date',
        'queued_dttm',
    ]
    edit_columns = [
        'state',
        'dag_id',
        'task_id',
        'execution_date',
        'start_date',
        'end_date',
    ]
    edit_form = TaskInstanceEditForm
    base_order = ('job_id', 'asc')
    base_filters = [['dag_id', DagFilter, lambda: []]]
    def log_url_formatter(self):