### 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)

qry = session.query(cls)
        dag_ids = [dag_id] if isinstance(dag_id, str) else dag_id
        if dag_ids:
            qry = qry.filter(cls.dag_id.in_(dag_ids))
        if is_container(run_id):
            qry = qry.filter(cls.run_id.in_(run_id))
        elif run_id is not None:
            qry = qry.filter(cls.run_id == run_id)
        if is_container(execution_date):
            qry = qry.filter(cls.execution_date.in_(execution_date))
        elif execution_date is not None:
            qry = qry.filter(cls.execution_date == execution_date)
        if execution_start_date and execution_end_date:
            qry = qry.filter(cls.execution_date.between(execution_start_date, execution_end_date))
        elif execution_start_date:
            qry = qry.filter(cls.execution_date >= execution_start_date)
        elif execution_end_date:
            qry = qry.filter(cls.execution_date <= execution_end_date)
        if state:
            qry = qry.filter(cls.state == state)
        if external_trigger is not None:
            qry = qry.filter(cls.external_trigger == external_trigger)
        if run_type:
            qry = qry.filter(cls.run_type == run_type)
        if no_backfills:
            qry = qry.filter(cls.run_type != DagRunType.BACKFILL_JOB)
        return qry.order_by(cls.execution_date).all()
    @classmethod
    @provide_session
    def find_duplicate(