### 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)

dagrun = _get_previous_dagrun_success()
            if dagrun is None:
                return None
            return timezone.coerce_datetime(dagrun.start_date)
        @cache
        def get_yesterday_ds() -> str:
            return (logical_date - timedelta(1)).strftime("%Y-%m-%d")
        def get_yesterday_ds_nodash() -> str:
            return get_yesterday_ds().replace("-", "")
        @cache
        def get_tomorrow_ds() -> str:
            return (logical_date + timedelta(1)).strftime("%Y-%m-%d")
        def get_tomorrow_ds_nodash() -> str:
            return get_tomorrow_ds().replace("-", "")
        @cache
        def get_next_execution_date() -> pendulum.DateTime | None:
            
            
            
            
            if dag_run.external_trigger:
                return logical_date
            if dag is None:
                return None
            next_info = dag.next_dagrun_info(data_interval, restricted=False)
            if next_info is None:
                return None
            return timezone.coerce_datetime(next_info.logical_date)
        def get_next_ds() -> str | None: