### 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)

min(
                        (
                            heartbeat_time_limit
                            - (timezone.utcnow() - self.job.latest_heartbeat).total_seconds() * 0.75
                        ),
                        self.job.heartrate if self.job.heartrate is not None else heartbeat_time_limit,
                    ),
                )
                return_code = self.task_runner.return_code(timeout=max_wait_time)
                if return_code is not None:
                    self.handle_task_exit(return_code)
                    return return_code
                perform_heartbeat(
                    job=self.job, heartbeat_callback=self.heartbeat_callback, only_if_necessary=False
                )
                
                
                
                time_since_last_heartbeat = (timezone.utcnow() - self.job.latest_heartbeat).total_seconds()
                if time_since_last_heartbeat > heartbeat_time_limit:
                    Stats.incr("local_task_job_prolonged_heartbeat_failure", 1, 1)
                    self.log.error("Heartbeat time limit exceeded!")
                    raise AirflowException(
                        f"Time since last heartbeat({time_since_last_heartbeat:.2f}s) exceeded limit "
                        f"({heartbeat_time_limit}s)."
                    )
            return return_code
        finally:
            self.on_kill()
    def handle_task_exit(self, return_code: int) -> None: