### 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 task_dagrun_concurrency_limit is not None:
                        current_task_dagrun_concurrency = concurrency_map.task_dagrun_concurrency_map[
                            (task_instance.dag_id, task_instance.run_id, task_instance.task_id)
                        ]
                        if current_task_dagrun_concurrency >= task_dagrun_concurrency_limit:
                            self.log.info(
                                "Not executing %s since the task concurrency per DAG run for"
                                " this task has been reached.",
                                task_instance,
                            )
                            starved_tasks_task_dagrun_concurrency.add(
                                (task_instance.dag_id, task_instance.run_id, task_instance.task_id)
                            )
                            continue
                executable_tis.append(task_instance)
                open_slots -= task_instance.pool_slots
                concurrency_map.dag_active_tasks_map[dag_id] += 1
                concurrency_map.task_concurrency_map[(task_instance.dag_id, task_instance.task_id)] += 1
                concurrency_map.task_dagrun_concurrency_map[
                    (task_instance.dag_id, task_instance.run_id, task_instance.task_id)
                ] += 1
                pool_stats["open"] = open_slots
            is_done = executable_tis or len(task_instances_to_examine) < max_tis
            
            found_new_filters = (
                len(starved_pools) > num_starved_pools
                or len(starved_dags) > num_starved_dags
                or len(starved_tasks) > num_starved_tasks
                or len(starved_tasks_task_dagrun_concurrency) > num_starved_tasks_task_dagrun_concurrency
            )