**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
tries = sorted({ti.try_number for ti in tis})
        max_date = max(ti.execution_date for ti in tis) if tries else None
        chart.create_y_axis('yAxis', format='.02f', custom_format=False, label='Tries')
        chart.axislist['yAxis']['axisLabelDistance'] = '-15'
        session.commit()
        form = DateTimeWithNumRunsForm(
            data={
                'base_date': max_date or timezone.utcnow(),
                'num_runs': num_runs,
            }
        )
        chart.buildcontent()
        return self.render_template(
            'airflow/chart.html',
            dag=dag,
            root=root,
            form=form,
            chart=Markup(chart.htmlcontent),
            tab_title='Tries',
        )
    @expose('/landing_times')
    @auth.has_access(
        [
            (permissions.ACTION_CAN_READ, permissions.RESOURCE_DAG),
            (permissions.ACTION_CAN_READ, permissions.RESOURCE_TASK_INSTANCE),
        ]
    )
    @action_logging
    @provide_session
    def landing_times(self, session=None):