### 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)

if self.state == DagRunState.RUNNING:
            get_listener_manager().hook.on_dag_run_running(dag_run=self, msg=msg)
        elif self.state == DagRunState.SUCCESS:
            get_listener_manager().hook.on_dag_run_success(dag_run=self, msg=msg)
        elif self.state == DagRunState.FAILED:
            get_listener_manager().hook.on_dag_run_failed(dag_run=self, msg=msg)
        
        
        
    def _get_ready_tis(
        self,
        schedulable_tis: list[TI],
        finished_tis: list[TI],
        session: Session,
    ) -> tuple[list[TI], bool, bool]:
        old_states = {}
        ready_tis: list[TI] = []
        changed_tis = False
        if not schedulable_tis:
            return ready_tis, changed_tis, False
        
        
        additional_tis: list[TI] = []
        dep_context = DepContext(
            flag_upstream_failed=True,
            ignore_unmapped_tasks=True,  
            finished_tis=finished_tis,
        )
        def _expand_mapped_task_if_needed(ti: TI) -> Iterable[TI] | None: