### 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)

self,
        dag_run: DagRun,
        session: Session,
    ) -> DagCallbackRequest | None:
        """
        Make scheduling decisions about an individual dag run.
        :param dag_run: The DagRun to schedule
        :return: Callback that needs to be executed
        """
        callback: DagCallbackRequest | None = None
        dag = dag_run.dag = self.dagbag.get_dag(dag_run.dag_id, session=session)
        dag_model = DM.get_dagmodel(dag_run.dag_id, session)
        if not dag or not dag_model:
            self.log.error("Couldn't find DAG %s in DAG bag or database!", dag_run.dag_id)
            return callback
        if (
            dag_run.start_date
            and dag.dagrun_timeout
            and dag_run.start_date < timezone.utcnow() - dag.dagrun_timeout
        ):
            dag_run.set_state(DagRunState.FAILED)
            unfinished_task_instances = (
                session.query(TI)
                .filter(TI.dag_id == dag_run.dag_id)
                .filter(TI.run_id == dag_run.run_id)
                .filter(TI.state.in_(State.unfinished))