### 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_to_reset_or_adopt = with_row_locks(
                        query, of=TI, session=session, **skip_locked(session=session)
                    ).all()
                    to_reset = self.job.executor.try_adopt_task_instances(tis_to_reset_or_adopt)
                    reset_tis_message = []
                    for ti in to_reset:
                        reset_tis_message.append(repr(ti))
                        ti.state = State.NONE
                        ti.queued_by_job_id = None
                    for ti in set(tis_to_reset_or_adopt) - set(to_reset):
                        ti.queued_by_job_id = self.job.id
                    Stats.incr("scheduler.orphaned_tasks.cleared", len(to_reset))
                    Stats.incr("scheduler.orphaned_tasks.adopted", len(tis_to_reset_or_adopt) - len(to_reset))
                    if to_reset:
                        task_instance_str = "\n\t".join(reset_tis_message)
                        self.log.info(
                            "Reset the following %s orphaned TaskInstances:\n\t%s",
                            len(to_reset),
                            task_instance_str,
                        )
                    
                    
                    session.flush()
                except OperationalError:
                    session.rollback()
                    raise
        return len(to_reset)
    @provide_session
    def check_trigger_timeouts(self, session: Session = NEW_SESSION) -> None: