### 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 self.next_method:
                timeout_seconds = (
                    task_to_execute.execution_timeout - (timezone.utcnow() - self.start_date)
                ).total_seconds()
            else:
                timeout_seconds = task_to_execute.execution_timeout.total_seconds()
            try:
                
                if timeout_seconds <= 0:
                    raise AirflowTaskTimeout()
                
                with timeout(timeout_seconds):
                    result = execute_callable(context=context)
            except AirflowTaskTimeout:
                task_to_execute.on_kill()
                raise
        else:
            result = execute_callable(context=context)
        with create_session() as session:
            if task_to_execute.do_xcom_push:
                xcom_value = result
            else:
                xcom_value = None
            if xcom_value is not None:  
                self.xcom_push(key=XCOM_RETURN_KEY, value=xcom_value, session=session)
            self._record_task_map_for_downstreams(task_orig, xcom_value, session=session)
        return result
    @provide_session
    def _defer_task(self, session: Session, defer: TaskDeferred) -> None: