Slow Query Performance with SQLAlchemy and PostgreSQL using JOINs
I can't seem to get I've hit a wall trying to I'm relatively new to this, so bear with me. I'm currently working on a Django application that utilizes SQLAlchemy to interact with a PostgreSQL database. I've encountered significant performance issues when executing a query that involves multiple JOINs across several tables. The query is taking upwards of 10 seconds to execute, which is far from ideal for the user experience. Here's a simplified version of the query I'm using: ```python from sqlalchemy.orm import sessionmaker from models import User, Post, Comment Session = sessionmaker(bind=engine) session = Session() results = session.query(User).join(Post).join(Comment).filter(User.id == 1).all() ``` The `User`, `Post`, and `Comment` tables have the following relationships: - `User` has many `Post` - `Post` has many `Comment` When I run this query directly in the PostgreSQL shell, it executes in a fraction of a second, which makes me think the issue lies in how SQLAlchemy is handling the JOINs or possibly the loading strategy. I've tried adding eager loading with `options` but it hasn't made a noticeable difference: ```python from sqlalchemy.orm import joinedload results = session.query(User).options(joinedload(User.posts).joinedload(Post.comments)).filter(User.id == 1).all() ``` Despite trying various indexing strategies on the database, I'm still seeing high execution times. I'm wondering if there are any specific configurations or patterns in SQLAlchemy that could help optimize the JOIN performance, especially when dealing with larger datasets. Any insights or recommendations would be greatly appreciated! Has anyone else encountered this? For context: I'm using Python on Debian. Could this be a known issue? I'd really appreciate any guidance on this.