### 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)

tis = self.get_task_instances(session=session, state=State.task_states)
        self.log.debug("number of tis tasks for %s: %s task(s)", self, len(tis))
        def _filter_tis_and_exclude_removed(dag: DAG, tis: list[TI]) -> Iterable[TI]:
            """Populate ``ti.task`` while excluding those missing one, marking them as REMOVED."""
            for ti in tis:
                try:
                    ti.task = dag.get_task(ti.task_id)
                except TaskNotFound:
                    if ti.state != State.REMOVED:
                        self.log.error("Failed to get task for ti %s. Marking it as removed.", ti)
                        ti.state = State.REMOVED
                        session.flush()
                else: