### 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)

pools = Pool.slots_stats(lock_rows=True, session=session)
        
        
        pool_slots_free = sum(max(0, pool["open"]) for pool in pools.values())
        if pool_slots_free == 0:
            self.log.debug("All pools are full!")
            return []
        max_tis = min(max_tis, pool_slots_free)
        starved_pools = {pool_name for pool_name, stats in pools.items() if stats["open"] <= 0}
        
        concurrency_map = self.__get_concurrency_maps(states=EXECUTION_STATES, session=session)
        
        num_starving_tasks_total = 0
        
        starved_dags: set[str] = set()
        starved_tasks: set[tuple[str, str]] = set()
        starved_tasks_task_dagrun_concurrency: set[tuple[str, str, str]] = set()
        pool_num_starving_tasks: dict[str, int] = Counter()
        for loop_count in itertools.count(start=1):
            num_starved_pools = len(starved_pools)
            num_starved_dags = len(starved_dags)
            num_starved_tasks = len(starved_tasks)
            num_starved_tasks_task_dagrun_concurrency = len(starved_tasks_task_dagrun_concurrency)
            
            
            
            query = (
                session.query(TI)
                .with_hint(TI, "USE INDEX (ti_state)", dialect_name="mysql")