### 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)

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        current_try_number = self.try_number - 1
        additional_context: dict[str, Any] = {
            "exception": exception,
            "exception_html": exception_html,
            "try_number": current_try_number,
            "max_tries": self.max_tries,
        }
        if use_default:
            default_context = {"ti": self, **additional_context}
            jinja_env = jinja2.Environment(
                loader=jinja2.FileSystemLoader(os.path.dirname(__file__)), autoescape=True
            )
            subject = jinja_env.from_string(default_subject).render(**default_context)
            html_content = jinja_env.from_string(default_html_content).render(**default_context)
            html_content_err = jinja_env.from_string(default_html_content_err).render(**default_context)
        else:
            
            
            
            dag = self.task.get_dag()
            if dag:
                jinja_env = dag.get_template_env(force_sandboxed=True)
            else:
                jinja_env = SandboxedEnvironment(cache_size=0)
            jinja_context = self.get_template_context()
            context_merge(jinja_context, additional_context)
            def render(key: str, content: str) -> str: