### 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)

ti.state,
                state,
                try_number,
                ti.max_tries,
                ti.job_id,
                ti.pool,
                ti.queue,
                ti.priority_weight,
                ti.operator,
                ti.queued_dttm,
                ti.queued_by_job_id,
                ti.pid,
            )
            
            
            
            
            
            
            
            
            ti_queued = ti.try_number == buffer_key.try_number and ti.state == TaskInstanceState.QUEUED
            ti_requeued = ti.queued_by_job_id != self.job.id or self.job.executor.has_task(ti)
            if ti_queued and not ti_requeued:
                Stats.incr(
                    "scheduler.tasks.killed_externally",
                    tags={"dag_id": ti.dag_id, "task_id": ti.task_id},
                )
                msg = (
                    "Executor reports task instance %s finished (%s) although the "