👀 Views: 83 💬 Answers: 1 📅 Created: 2025-09-13

postgresql performance linux sql

I'm dealing with I'm stuck on something that should probably be simple. Hey everyone, I'm running into an issue that's driving me crazy. Hey everyone, I'm running into an issue that's driving me crazy. Recently started working with a React-based application that heavily relies on a PostgreSQL database for data retrieval. As the user base grows, I've noticed some performance bottlenecks, especially when fetching large datasets. Specifically, queries that pull user data with multiple joins take considerably longer than anticipated, which degrades the user experience. To address this, I tried indexing some of the common fields involved in these joins, yet the performance improvement was minimal. Here's an example of one of the queries: ```sql SELECT users.id, users.name, orders.amount FROM users JOIN orders ON users.id = orders.user_id WHERE orders.created_at > NOW() - INTERVAL '1 week' ORDER BY orders.created_at DESC; ``` I ran `EXPLAIN ANALYZE` on the query and observed that the join operation is particularly slow. The output indicated that the sequential scan on the `orders` table was the main culprit. To tackle this, I attempted to partition the `orders` table based on the `created_at` field, but that involved a lot of restructuring. In addition, I explored using `LIMIT` and `OFFSET` to paginate results, which helped a bit, but I fear that as the dataset grows, so will the delay. I also considered caching strategies with Redis, but integrating that into our existing architecture is proving a bit challenging. What are some best practices for optimizing this kind of query in a Linux environment? Are there specific configurations in PostgreSQL I should look into, or perhaps different ways to structure the data model to enhance performance? What's the best practice here? What's the best practice here? Hoping someone can shed some light on this. This issue appeared after updating to Sql latest. Is there a simpler solution I'm overlooking? This is happening in both development and production on Ubuntu 22.04. What's the best practice here?