### 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)

return self._replace(tis=[t for t in self.tis if t.state in State.unfinished])
        start_dttm = timezone.utcnow()
        self.last_scheduling_decision = start_dttm
        with Stats.timer(
            f"dagrun.dependency-check.{self.dag_id}",
            tags=self.stats_tags,
        ):
            dag = self.get_dag()
            info = self.task_instance_scheduling_decisions(session)
            tis = info.tis
            schedulable_tis = info.schedulable_tis
            changed_tis = info.changed_tis
            finished_tis = info.finished_tis
            unfinished = _UnfinishedStates.calculate(info.unfinished_tis)
            if unfinished.should_schedule:
                are_runnable_tasks = schedulable_tis or changed_tis
                
                if not are_runnable_tasks:
                    are_runnable_tasks, changed_by_upstream = self._are_premature_tis(
                        unfinished.tis, finished_tis, session
                    )
                    if changed_by_upstream:  
                        unfinished = unfinished.recalculate()
        leaf_task_ids = {t.task_id for t in dag.leaves}