### 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)

instance is returned. If the task to pull is mapped, an iterator (not a
        list) yielding XComs from mapped task instances is returned. In either
        case, ``default`` (*None* if not specified) is returned if no matching
        XComs are found.
        When pulling multiple tasks (i.e. either ``task_id`` or ``map_index`` is
        a non-str iterable), a list of matching XComs is returned. Elements in
        the list is ordered by item ordering in ``task_id`` and ``map_index``.
        """
        if dag_id is None:
            dag_id = self.dag_id
        query = XCom.get_many(
            key=key,
            run_id=self.run_id,
            dag_ids=dag_id,
            task_ids=task_ids,
            map_indexes=map_indexes,
            include_prior_dates=include_prior_dates,
            session=session,
        )
        
        
        
        
        if (task_ids is None or isinstance(task_ids, str)) and not isinstance(map_indexes, Iterable):
            first = query.with_entities(
                XCom.run_id, XCom.task_id, XCom.dag_id, XCom.map_index, XCom.value
            ).first()
            if first is None:  
                return default
            if map_indexes is not None or first.map_index < 0: