**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 log."""
        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})
        dag_model = DagModel.get_dagmodel(dag_id)
        ti = (
            session.query(models.TaskInstance)
            .filter(
                models.TaskInstance.dag_id == dag_id,
                models.TaskInstance.task_id == task_id,
                models.TaskInstance.execution_date == dttm,
            )
            .first()
        )
        num_logs = 0