### 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)

def bulk_write_to_db(
        cls,
        dags: Collection[DAG],
        processor_subdir: str | None = None,
        session=NEW_SESSION,
    ):
        """
        Ensure the DagModel rows for the given dags are up-to-date in the dag table in the DB, including
        calculated fields.
        Note that this method can be called for both DAGs and SubDAGs. A SubDag is actually a SubDagOperator.
        :param dags: the DAG objects to save to the DB
        :return: None
        """
        if not dags:
            return
        log.info("Sync %s DAGs", len(dags))
        dag_by_ids = {dag.dag_id: dag for dag in dags}
        dag_ids = set(dag_by_ids.keys())
        query = (
            session.query(DagModel)
            .options(joinedload(DagModel.tags, innerjoin=False))
            .filter(DagModel.dag_id.in_(dag_ids))
            .options(joinedload(DagModel.schedule_dataset_references))
            .options(joinedload(DagModel.task_outlet_dataset_references))
        )
        orm_dags: list[DagModel] = with_row_locks(query, of=DagModel, session=session).all()
        existing_dags = {orm_dag.dag_id: orm_dag for orm_dag in orm_dags}
        missing_dag_ids = dag_ids.difference(existing_dags)
        for missing_dag_id in missing_dag_ids:
            orm_dag = DagModel(dag_id=missing_dag_id)