### 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)

#
#
from datetime import datetime
from typing import Optional
from pydantic import BaseModel as BaseModelPydantic
from airflow.jobs.base_job_runner import BaseJobRunner
def check_runner_initialized(job_runner: Optional[BaseJobRunner], job_type: str) -> BaseJobRunner:
    if job_runner is None:
        raise ValueError(f"In order to run {job_type} you need to initialize the {job_type}Runner first.")
    return job_runner
class JobPydantic(BaseModelPydantic):
    """Serializable representation of the Job ORM SqlAlchemyModel used by internal API"""
    id: Optional[int]
    dag_id: Optional[str]
    state: Optional[str]
    job_type: Optional[str]
    start_date: Optional[datetime]
    end_date: Optional[datetime]
    latest_heartbeat: datetime
    executor_class: Optional[str]
    hostname: Optional[str]
    unixname: Optional[str]
    
    heartrate: Optional[int]
    class Config:
        """Make sure it deals automatically with ORM classes of SQL Alchemy"""
        orm_mode = True