Optimizing legacy MongoDB queries in a Node.js application for better performance
Hey everyone, I'm running into an issue that's driving me crazy. I'm stuck trying to While refactoring an older Node.js application that interacts heavily with MongoDB, I've noticed some inefficiencies in how we're querying the database... Specifically, certain read operations are noticeably slow, especially when fetching large datasets. The queries seem to lack proper indexing, leading to full collection scans, which can be costly in terms of performance. For instance, consider the following query snippet: ```javascript const users = await User.find({ age: { $gte: 18 } }).sort({ createdAt: -1 }).limit(100); ``` This fetches users based on age and sorts them, but I suspect MongoDB isn't using indexes effectively here. I've tried creating a compound index on `age` and `createdAt`: ```javascript db.users.createIndex({ age: 1, createdAt: -1 }); ``` Yet, performance improvements are minor. I've also explored the aggregation pipeline, hoping to leverage its efficiency: ```javascript const users = await User.aggregate([ { $match: { age: { $gte: 18 } } }, { $sort: { createdAt: -1 } }, { $limit: 100 } ]); ``` This appears to be a bit faster, but I wonder if I'm missing other optimization techniques, such as more selective filters or restructuring the data model itself. Additionally, should we consider caching frequently accessed data with something like Redis to alleviate read pressure on MongoDB? Any insights on best practices for optimizing legacy database interactions in a Node.js environment would be greatly appreciated. I recently upgraded to Javascript 3.9. What's the correct way to implement this? This is my first time working with Javascript LTS. Has anyone dealt with something similar?