### 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)

return TaskReturnCode.DEFERRED
        except AirflowSkipException as e:
            
            
            if e.args:
                self.log.info(e)
            if not test_mode:
                self.refresh_from_db(lock_for_update=True, session=session)
            self.state = State.SKIPPED
        except AirflowRescheduleException as reschedule_exception:
            self._handle_reschedule(actual_start_date, reschedule_exception, test_mode, session=session)
            session.commit()
            return None
        except (AirflowFailException, AirflowSensorTimeout) as e:
            
            
            self.handle_failure(e, test_mode, context, force_fail=True, session=session)
            session.commit()
            raise
        except AirflowException as e:
            if not test_mode:
                self.refresh_from_db(lock_for_update=True, session=session)
            
            
            
            if self.state in State.finished:
                self.clear_next_method_args()
                session.merge(self)
                session.commit()
                return None