Currently, the celery executor imports the `Task` model for the Celery database backend directly:

https://github.com/apache/airflow/blob/2dd4e96045d4a7f45cc8c06df3d25c4f1479392c/airflow/executors/celery_executor.py#L38

However, Celery, being highly customisable, uses `self.task_cls` in the backend implementation; this defaults to either `Task` or `TaskExtended` depending on the Celery configuration, see [`celery.backends.database:66`](https://github.com/celery/celery/blob/406f04a082949ac42ec7a4af94fed896c515aaa4/celery/backends/database/__init__.py#L66):

> ```python
>     task_cls = Task
> ```

and [`celery.backends.database:76,77`](https://github.com/celery/celery/blob/406f04a082949ac42ec7a4af94fed896c515aaa4/celery/backends/database/__init__.py#L76-L77):

> ```python
>         if self.extended_result:
>             self.task_cls = TaskExtended
> ```

Airflow should support this flexibility, and instead of importing a fixed class just use `backend.task_cls`, so in `_get_many_from_db_backend` just use:

```python
        Task = app.backend.task_cls
        with session_cleanup(session):
            tasks = session.query(Task).filter(Task.task_id.in_(task_ids)).all()
```

I suppose there is one downside to this: `TaskExtended` fetches a few more columns per task, but given that the result of `task.to_dict()` is passed to `backend.meta_from_decoded()`, which could also have been customised to make use of information contained in a custom model, that's neither here nor there. It would be the price anyone using the `result_extended` option would need to pay elsewhere anyway.
airflow/executors/celery_executor.py
num_process = min(len(async_results), self._sync_parallelism)
        with Pool(processes=num_process) as sync_pool:
            chunksize = max(1, math.floor(math.ceil(1.0 * len(async_results) / self._sync_parallelism)))
            task_id_to_states_and_info = sync_pool.map(
                fetch_celery_task_state, async_results, chunksize=chunksize
            )
            states_and_info_by_task_id: MutableMapping[str, EventBufferValueType] = {}
            for task_id, state_or_exception, info in task_id_to_states_and_info:
                if isinstance(state_or_exception, ExceptionWithTraceback):
                    self.log.error(  
                        CELERY_FETCH_ERR_MSG_HEADER + ":%s\n%s\n",
                        state_or_exception.exception,
                        state_or_exception.traceback,
                    )
                else:
                    states_and_info_by_task_id[task_id] = state_or_exception, info
        return states_and_info_by_task_id