### 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)

else:
                
                
                
                
                
                data_interval_end = dag.get_run_data_interval(self).end
                true_delay = first_start_date - data_interval_end
                if true_delay.total_seconds() > 0:
                    Stats.timing(
                        f"dagrun.{dag.dag_id}.first_task_scheduling_delay", true_delay, tags=self.stats_tags
                    )
                    Stats.timing("dagrun.first_task_scheduling_delay", true_delay, tags=self.stats_tags)
        except Exception:
            self.log.warning("Failed to record first_task_scheduling_delay metric:", exc_info=True)
    def _emit_duration_stats_for_finished_state(self):
        if self.state == State.RUNNING:
            return
        if self.start_date is None:
            self.log.warning("Failed to record duration of %s: start_date is not set.", self)
            return
        if self.end_date is None:
            self.log.warning("Failed to record duration of %s: end_date is not set.", self)
            return
        duration = self.end_date - self.start_date
        timer_params = {"dt": duration, "tags": self.stats_tags}
        Stats.timing(f"dagrun.duration.{self.state.value}.{self.dag_id}", **timer_params)
        Stats.timing(f"dagrun.duration.{self.state.value}", **timer_params)
    @provide_session
    def verify_integrity(self, *, session: Session = NEW_SESSION) -> None: