### 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)

return prune_dict({"dag_id": self.dag_id, "task_id": self.task_id})
    @staticmethod
    def insert_mapping(run_id: str, task: Operator, map_index: int) -> dict[str, Any]:
        """:meta private:"""
        return {
            "dag_id": task.dag_id,
            "task_id": task.task_id,
            "run_id": run_id,
            "_try_number": 0,
            "hostname": "",
            "unixname": getuser(),
            "queue": task.queue,
            "pool": task.pool,
            "pool_slots": task.pool_slots,
            "priority_weight": task.priority_weight_total,
            "run_as_user": task.run_as_user,
            "max_tries": task.retries,
            "executor_config": task.executor_config,
            "operator": task.task_type,
            "map_index": map_index,
        }
    @reconstructor
    def init_on_load(self) -> None:
        """Initialize the attributes that aren't stored in the DB"""
        
        self._log = logging.getLogger("airflow.task")
        self.test_mode = False  
    @hybrid_property
    def try_number(self):