### 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)

"""
        Update task with rendered template fields for presentation in UI.
        If task has already run, will fetch from DB; otherwise will render.
        """
        from airflow.models.renderedtifields import RenderedTaskInstanceFields
        rendered_task_instance_fields = RenderedTaskInstanceFields.get_templated_fields(self, session=session)
        if rendered_task_instance_fields:
            self.task = self.task.unmap(None)
            for field_name, rendered_value in rendered_task_instance_fields.items():
                setattr(self.task, field_name, rendered_value)
            return
        try:
            
            from airflow.utils.log.secrets_masker import redact
            self.render_templates()
            for field_name in self.task.template_fields:
                rendered_value = getattr(self.task, field_name)
                setattr(self.task, field_name, redact(rendered_value, field_name))
        except (TemplateAssertionError, UndefinedError) as e:
            raise AirflowException(
                "Webserver does not have access to User-defined Macros or Filters "
                "when Dag Serialization is enabled. Hence for the task that have not yet "
                "started running, please use 'airflow tasks render' for debugging the "
                "rendering of template_fields."
            ) from e
    @provide_session
    def get_rendered_k8s_spec(self, session: Session = NEW_SESSION):