### 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)

callback_tuples = self._schedule_all_dag_runs(guard, dag_runs, session)
        
        for dag_run, callback_to_run in callback_tuples:
            dag = self.dagbag.get_dag(dag_run.dag_id, session=session)
            if not dag:
                self.log.error("DAG '%s' not found in serialized_dag table", dag_run.dag_id)
                continue
            
            
            self._send_dag_callbacks_to_processor(dag, callback_to_run)
        with prohibit_commit(session) as guard:
            
            session.expunge_all()
            
            if self.job.executor.slots_available <= 0:
                
                self.log.debug("Executor full, skipping critical section")
                num_queued_tis = 0
            else:
                try:
                    timer = Stats.timer("scheduler.critical_section_duration")
                    timer.start()
                    
                    num_queued_tis = self._critical_section_enqueue_task_instances(session=session)
                    
                    
                    timer.stop(send=True)
                except OperationalError as e:
                    timer.stop(send=False)