### 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._find_zombies,
        )
        timers.call_regular_interval(60.0, self._update_dag_run_state_for_paused_dags)
        timers.call_regular_interval(
            conf.getfloat("scheduler", "task_queued_timeout_check_interval"),
            self._fail_tasks_stuck_in_queued,
        )
        timers.call_regular_interval(
            conf.getfloat("scheduler", "parsing_cleanup_interval"),
            self._orphan_unreferenced_datasets,
        )
        if self._standalone_dag_processor:
            timers.call_regular_interval(
                conf.getfloat("scheduler", "parsing_cleanup_interval"),
                self._cleanup_stale_dags,
            )
        for loop_count in itertools.count(start=1):
            with Stats.timer("scheduler.scheduler_loop_duration") as timer:
                if self.using_sqlite and self.processor_agent:
                    self.processor_agent.run_single_parsing_loop()
                    
                    
                    self.log.debug("Waiting for processors to finish since we're using sqlite")
                    self.processor_agent.wait_until_finished()
                with create_session() as session:
                    num_queued_tis = self._do_scheduling(session)
                    self.job.executor.heartbeat()
                    session.expunge_all()
                    num_finished_events = self._process_executor_events(session=session)
                if self.processor_agent: