### 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)

"""
        Returns edge information for the given pair of tasks if present, and
        an empty edge if there is no information.
        """
        
        empty = cast(EdgeInfoType, {})
        if self.edge_info:
            return self.edge_info.get(upstream_task_id, {}).get(downstream_task_id, empty)
        else:
            return empty
    def set_edge_info(self, upstream_task_id: str, downstream_task_id: str, info: EdgeInfoType):
        """
        Sets the given edge information on the DAG. Note that this will overwrite,
        rather than merge with, existing info.
        """
        self.edge_info.setdefault(upstream_task_id, {})[downstream_task_id] = info
    def validate_schedule_and_params(self):
        """
        Validates & raise exception if there are any Params in the DAG which neither have a default value nor
        have the null in schema['type'] list, but the DAG have a schedule_interval which is not None.
        """
        if not self.timetable.can_run:
            return
        for k, v in self.params.items():
            
            if not v.has_value and ("type" not in v.schema or "null" not in v.schema["type"]):
                raise AirflowException(
                    "DAG Schedule must be None, if there are any required params without default values"
                )
    def iter_invalid_owner_links(self) -> Iterator[tuple[str, str]]: