### 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)

if not _is_parent_process():
            
            return
        try:
            sig_name = signal.Signals(signum).name
        except Exception:
            sig_name = str(signum)
        self.log.info("%s\n%s received, printing debug\n%s", "-" * 80, sig_name, "-" * 80)
        self.job.executor.debug_dump()
        self.log.info("-" * 80)
    def is_alive(self, grace_multiplier: float | None = None) -> bool:
        """
        Whether the SchedulerJob is alive.
        We define alive as in a state of running and a heartbeat within the
        threshold defined in the ``scheduler_health_check_threshold`` config
        setting.
        ``grace_multiplier`` is accepted for compatibility with the parent class.
        """
        if grace_multiplier is not None:
            
            return self.job.is_alive(grace_multiplier=grace_multiplier)
        scheduler_health_check_threshold: int = conf.getint("scheduler", "scheduler_health_check_threshold")
        return (
            self.job.state == State.RUNNING
            and (timezone.utcnow() - self.job.latest_heartbeat).total_seconds()
            < scheduler_health_check_threshold
        )
    def __get_concurrency_maps(self, states: Iterable[TaskInstanceState], session: Session) -> ConcurrencyMap: