### 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)

"""
        Verifies the DagRun by checking for removed tasks or tasks that are not in the
        database yet. It will set state to removed or add the task if required.
        :missing_indexes: A dictionary of task vs indexes that are missing.
        :param session: Sqlalchemy ORM Session
        """
        from airflow.settings import task_instance_mutation_hook
        
        
        hook_is_noop: Literal[True, False] = getattr(task_instance_mutation_hook, "is_noop", False)
        dag = self.get_dag()
        task_ids = self._check_for_removed_or_restored_tasks(
            dag, task_instance_mutation_hook, session=session
        )
        def task_filter(task: Operator) -> bool:
            return task.task_id not in task_ids and (
                self.is_backfill
                or task.start_date <= self.execution_date
                and (task.end_date is None or self.execution_date <= task.end_date)
            )
        created_counts: dict[str, int] = defaultdict(int)
        task_creator = self._get_task_creator(created_counts, task_instance_mutation_hook, hook_is_noop)
        
        tasks_to_create = (task for task in dag.task_dict.values() if task_filter(task))
        tis_to_create = self._create_tasks(tasks_to_create, task_creator, session=session)
        self._create_task_instances(self.dag_id, tis_to_create, created_counts, hook_is_noop, session=session)
    def _check_for_removed_or_restored_tasks(