Performance Degradation in Django with Large QuerySets and Prefetch Related
Could someone explain I'm not sure how to approach I'm a bit lost with I'm experiencing important performance optimization in my Django application (version 3.2) when dealing with large QuerySets combined with `prefetch_related`... The application frequently hangs when executing queries involving related models. For instance, I'm trying to retrieve a list of `Author` objects, each with a prefetch of their `Book` objects, but the response time can exceed 10 seconds for around 500 authors, which is unacceptable in my production environment. Here's a snippet of my query: ```python from myapp.models import Author, Book # Attempting to optimize fetching of authors and their books authors = Author.objects.prefetch_related('books').all() ``` I've also tried limiting the number of authors retrieved by using `.only()` and applied pagination, but it hasn't improved the performance significantly: ```python # Limiting fields to retrieve only necessary data authors = Author.objects.only('name').prefetch_related('books').all()[:100] ``` Despite these efforts, I'm still seeing long load times. I monitored the database queries using Django Debug Toolbar and noticed that the number of queries executed spikes significantly when prefetching even a small number of related records. Additionally, I'm using PostgreSQL 13, and I suspect there might be a configuration scenario as the database can process simple queries quickly. The query plan shows a few sequential scans that I wasn't expecting. Here's the relevant output: ``` Explain analyze: Seq Scan on author (cost=0.00..42.00 rows=1000 width=32) ``` Could there be something wrong with my database configuration, or is there another optimization technique that I'm missing? Any insights on enhancing the performance of `prefetch_related` in Django would be greatly appreciated. Any suggestions would be helpful. My development environment is Windows 10. This issue appeared after updating to Python 3.9. This is my first time working with Python LTS. What's the best practice here?