### 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)

"""Render k8s pod yaml"""
        from kubernetes.client.api_client import ApiClient
        from airflow.kubernetes.kube_config import KubeConfig
        from airflow.kubernetes.kubernetes_helper_functions import create_pod_id  
        from airflow.kubernetes.pod_generator import PodGenerator
        kube_config = KubeConfig()
        pod = PodGenerator.construct_pod(
            dag_id=self.dag_id,
            run_id=self.run_id,
            task_id=self.task_id,
            map_index=self.map_index,
            date=None,
            pod_id=create_pod_id(self.dag_id, self.task_id),
            try_number=self.try_number,
            kube_image=kube_config.kube_image,
            args=self.command_as_list(),
            pod_override_object=PodGenerator.from_obj(self.executor_config),
            scheduler_job_id="0",
            namespace=kube_config.executor_namespace,
            base_worker_pod=PodGenerator.deserialize_model_file(kube_config.pod_template_file),
            with_mutation_hook=True,
        )
        sanitized_pod = ApiClient().sanitize_for_serialization(pod)
        return sanitized_pod
    def get_email_subject_content(