**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
"""Shows landing times."""
        default_dag_run = conf.getint('webserver', 'default_dag_run_display_number')
        dag_id = request.args.get('dag_id')
        dag = current_app.dag_bag.get_dag(dag_id)
        base_date = request.args.get('base_date')
        num_runs = request.args.get('num_runs', default=default_dag_run, type=int)
        if base_date:
            base_date = timezone.parse(base_date)
        else:
            base_date = dag.get_latest_execution_date() or timezone.utcnow()
        dates = dag.date_range(base_date, num=-abs(num_runs))
        min_date = dates[0] if dates else timezone.utc_epoch()
        root = request.args.get('root')
        if root:
            dag = dag.sub_dag(task_ids_or_regex=root, include_upstream=True, include_downstream=False)
        chart_height = wwwutils.get_chart_height(dag)
        chart = nvd3.lineChart(name="lineChart", x_is_date=True, height=chart_height, width="1200")
        y_points = {}
        x_points = {}
        for task in dag.tasks:
            task_id = task.task_id
            y_points[task_id] = []
            x_points[task_id] = []
            for ti in task.get_task_instances(start_date=min_date, end_date=base_date):
                ts = ti.execution_date
                if dag.schedule_interval and dag.following_schedule(ts):