### 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)

"""
        Enqueue task_instances which should have been set to queued with the executor.
        :param task_instances: TaskInstances to enqueue
        :param session: The session object
        """
        
        for ti in task_instances:
            if ti.dag_run.state in State.finished:
                ti.set_state(State.NONE, session=session)
                continue
            command = ti.command_as_list(
                local=True,
                pickle_id=ti.dag_model.pickle_id,
            )
            priority = ti.priority_weight
            queue = ti.queue
            self.log.info("Sending %s to executor with priority %s and queue %s", ti.key, priority, queue)
            self.job.executor.queue_command(
                ti,
                command,
                priority=priority,
                queue=queue,
            )
    def _critical_section_enqueue_task_instances(self, session: Session) -> int: