Optimizing SQL Query Performance with Complex Joins in Django 3.2
I'm not sure how to approach I'm experimenting with I am facing significant performance issues when executing a complex query with multiple joins in my Django 3.2 application. The query is returning a large dataset, and the response time is exceeding 10 seconds, which is unacceptable for my use case. Here’s a simplified version of the query I am using: ```python from django.db.models import Prefetch # Models class Author(models.Model): name = models.CharField(max_length=100) class Book(models.Model): title = models.CharField(max_length=100) author = models.ForeignKey(Author, on_delete=models.CASCADE) class Review(models.Model): book = models.ForeignKey(Book, on_delete=models.CASCADE) content = models.TextField() # Query queryset = Book.objects.prefetch_related( Prefetch('author'), Prefetch('review_set') ) ``` I have tried optimizing the query by using `select_related` for the author model, but it still results in slow performance: ```python queryset = Book.objects.select_related('author').prefetch_related('review_set') ``` Additionally, I am indexing the `book_id` field in the Review model, but the performance improvement has been negligible. I also analyzed the SQL query generated by Django and noticed that the joins are quite complex, generating a lot of data that I don't need. The SQL query looks something like this: ```sql SELECT b.*, a.*, r.* FROM book b JOIN author a ON b.author_id = a.id LEFT JOIN review r ON b.id = r.book_id ``` When I run this query directly in my PostgreSQL database, it takes about 3 seconds, but through Django, it’s much slower, likely due to the ORM overhead. I am looking for suggestions on how to further optimize this query. Should I consider raw SQL queries for this specific case, or are there better ways to structure my Django ORM queries to improve performance? Any insights or experiences with similar issues would be greatly appreciated! For reference, this is a production web app. Hoping someone can shed some light on this.