### Description

Ability to clear or mark task groups as success/failure and have that propagate to the tasks within that task group. Sometimes there is a need to adjust the status of tasks within a task group, which can get unwieldy depending on the number of tasks in that task group. A great quality of life upgrade, and something that seems like an intuitive feature, would be the ability to clear or change the status of all tasks at their taskgroup level through the UI.

### Use case/motivation

In the event a large number of tasks, or a whole task group in this case, need to be cleared or their status set to success/failure this would be a great improvement. For example, a manual DAG run triggered through the UI or the API that has a number of task sensors or tasks that otherwise don't matter for that DAG run - instead of setting each one as success by hand, doing so for each task group would be great.

### Related issues

_No response_

### Are you willing to submit a PR?

- [ ] Yes I am willing to submit a PR!

### Code of Conduct

- [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

num_of_all_dags = status_count_paused
            else:
                current_dags = all_dags
                num_of_all_dags = all_dags_count
            sort_column = DagModel.__table__.c.get(arg_sorting_key)
            if sort_column is not None:
                if arg_sorting_direction == "desc":
                    sort_column = sort_column.desc()
                current_dags = current_dags.order_by(sort_column)
            dags = current_dags.options(joinedload(DagModel.tags)).offset(start).limit(dags_per_page).all()
            user_permissions = g.user.perms
            can_create_dag_run = (
                permissions.ACTION_CAN_CREATE,
                permissions.RESOURCE_DAG_RUN,
            ) in user_permissions
            dataset_triggered_dag_ids = {dag.dag_id for dag in dags if dag.schedule_interval == "Dataset"}
            if dataset_triggered_dag_ids:
                dataset_triggered_next_run_info = get_dataset_triggered_next_run_info(
                    dataset_triggered_dag_ids, session=session
                )
            else:
                dataset_triggered_next_run_info = {}
            for dag in dags:
                dag.can_edit = get_airflow_app().appbuilder.sm.can_edit_dag(dag.dag_id, g.user)
                dag.can_trigger = dag.can_edit and can_create_dag_run
                dag.can_delete = get_airflow_app().appbuilder.sm.can_delete_dag(dag.dag_id, g.user)
            dagtags = session.query(func.distinct(DagTag.name)).all()
            tags = [
                {"name": name, "selected": bool(arg_tags_filter and name in arg_tags_filter)}
                for name, in dagtags