### 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)

info = dag_run.task_instance_scheduling_decisions(session)
            skippable_task_ids = {
                task_id for task_id in partial_dag.task_ids if task_id not in task.downstream_task_ids
            }
            schedulable_tis = [
                ti
                for ti in info.schedulable_tis
                if ti.task_id not in skippable_task_ids
                and not (
                    ti.task.inherits_from_empty_operator
                    and not ti.task.on_execute_callback
                    and not ti.task.on_success_callback
                    and not ti.task.outlets
                )
            ]
            for schedulable_ti in schedulable_tis:
                if not hasattr(schedulable_ti, "task"):
                    schedulable_ti.task = task.dag.get_task(schedulable_ti.task_id)
            num = dag_run.schedule_tis(schedulable_tis, session=session)
            self.log.info("%d downstream tasks scheduled from follow-on schedule check", num)
            session.flush()
        except OperationalError as e:
            
            self.log.info(
                "Skipping mini scheduling run due to exception: %s",
                e.statement,
                exc_info=True,
            )
            session.rollback()
    def get_relevant_upstream_map_indexes(