### 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)

mark_success=self.mark_success,
            ignore_all_deps=self.ignore_all_deps,
            ignore_depends_on_past=self.ignore_depends_on_past,
            wait_for_past_depends_before_skipping=self.wait_for_past_depends_before_skipping,
            ignore_task_deps=self.ignore_task_deps,
            ignore_ti_state=self.ignore_ti_state,
            job_id=str(self.job.id),
            pool=self.pool,
            external_executor_id=self.external_executor_id,
        ):
            self.log.info("Task is not able to be run")
            return None
        return_code = None
        try:
            self.task_runner.start()
            heartbeat_time_limit = conf.getint("scheduler", "scheduler_zombie_task_threshold")
            
            
            
            
            
            
            
            
            while not self.terminating:
                
                
                
                max_wait_time = max(
                    0,