### Description

expanding tasks in batches to allow mapped tasks spawn more than 1024 processes.

### Use case/motivation

Maximum length of a list is limited to 1024 by `max_map_length (AIRFLOW__CORE__MAX_MAP_LENGTH)`.
during scheduling of the new tasks, an UPDATE query is ran that tries to set all the new tasks at once.  Increasing `max_map_length` more than 4K makes airflow scheduler completely unresponsive.

Also, Postgres throws `stack depth limit exceeded` error which can be fixed by updating to a newer version and setting `max_stack_depth` higher. But it doesn't really matter because airflow scheduler freezes up.
 
As a workaround, I split the dag runs into subdag runs which works but it would be much nicer if we didn't have to worry about exceeding  `max_map_length`. 

### Related issues

It was discussed here:
[Increasing 'max_map_length' leads to SQL 'max_stack_depth' error with 5000 dags to be spawned #28478](https://github.com/apache/airflow/discussions/28478)

### 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)

context,
                expected_state,
            )
def clear_task_instances(
    tis: list[TaskInstance],
    session: Session,
    activate_dag_runs: None = None,
    dag: DAG | None = None,
    dag_run_state: DagRunState | Literal[False] = DagRunState.QUEUED,
) -> None:
    """
    Clears a set of task instances, but makes sure the running ones
    get killed.
    :param tis: a list of task instances
    :param session: current session
    :param dag_run_state: state to set DagRun to. If set to False, dagrun state will not
        be changed.
    :param dag: DAG object
    :param activate_dag_runs: Deprecated parameter, do not pass
    """
    job_ids = []
    
    task_id_by_key: dict[str, dict[str, dict[int, dict[int, set[str]]]]] = defaultdict(
        lambda: defaultdict(lambda: defaultdict(lambda: defaultdict(set)))
    )
    dag_bag = DagBag(read_dags_from_db=True)
    for ti in tis:
        if ti.state == TaskInstanceState.RUNNING:
            if ti.job_id: