### 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:
            ti = qry.one_or_none()
        if ti:
            
            self.start_date = ti.start_date
            self.end_date = ti.end_date
            self.duration = ti.duration
            self.state = ti.state
            
            self.try_number = ti.try_number
            self.max_tries = ti.max_tries
            self.hostname = ti.hostname
            self.unixname = ti.unixname
            self.job_id = ti.job_id
            self.pool = ti.pool
            self.pool_slots = ti.pool_slots or 1
            self.queue = ti.queue
            self.priority_weight = ti.priority_weight
            self.operator = ti.operator
            self.queued_dttm = ti.queued_dttm
            self.queued_by_job_id = ti.queued_by_job_id
            self.pid = ti.pid
            self.executor_config = ti.executor_config
            self.external_executor_id = ti.external_executor_id
            self.trigger_id = ti.trigger_id
            self.next_method = ti.next_method
            self.next_kwargs = ti.next_kwargs
        else:
            self.state = None
    def refresh_from_task(self, task: Operator, pool_override: str | None = None) -> None: