### 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)

self,
        state: Iterable[TaskInstanceState | None] | None = None,
        session: Session = NEW_SESSION,
    ) -> list[TI]:
        """Returns the task instances for this dag run"""
        tis = (
            session.query(TI)
            .options(joinedload(TI.dag_run))
            .filter(
                TI.dag_id == self.dag_id,
                TI.run_id == self.run_id,
            )
        )
        if state:
            if isinstance(state, str):
                tis = tis.filter(TI.state == state)
            else:
                
                if State.NONE in state:
                    if all(x is None for x in state):
                        tis = tis.filter(TI.state.is_(None))
                    else:
                        not_none_state = [s for s in state if s]
                        tis = tis.filter(or_(TI.state.in_(not_none_state), TI.state.is_(None)))
                else:
                    tis = tis.filter(TI.state.in_(state))
        if self.dag and self.dag.partial: