4.0 KiB
4.0 KiB
title, impact, impactDescription, tags
| title | impact | impactDescription | tags |
|---|---|---|---|
| Prevent N+1 Query Problems | HIGH | Reduces API calls from N+1 to 1-2, dramatically faster page loads | query, performance, n-plus-one, optimization |
Prevent N+1 Query Problems
N+1 queries occur when you fetch a list of records, then make additional requests for each record's related data. This pattern causes severe performance issues at scale.
Incorrect (N+1 patterns):
// Classic N+1: fetching related data in a loop
async function getPostsWithDetails() {
const posts = await pb.collection('posts').getList(1, 20); // 1 query
for (const post of posts.items) {
// N additional queries!
post.author = await pb.collection('users').getOne(post.author);
post.category = await pb.collection('categories').getOne(post.category);
}
// Total: 1 + 20 + 20 = 41 queries for 20 posts
}
// N+1 with Promise.all (faster but still N+1)
async function getPostsParallel() {
const posts = await pb.collection('posts').getList(1, 20);
await Promise.all(posts.items.map(async post => {
post.author = await pb.collection('users').getOne(post.author);
}));
// Still 21 API calls, just parallel
}
// Hidden N+1 in rendering
function PostList({ posts }) {
return posts.map(post => (
<PostCard
post={post}
author={useAuthor(post.author)} // Each triggers a fetch!
/>
));
}
Correct (eliminate N+1):
// Solution 1: Use expand for relations
async function getPostsWithDetails() {
const posts = await pb.collection('posts').getList(1, 20, {
expand: 'author,category,tags'
});
// All data in one request
posts.items.forEach(post => {
console.log(post.expand?.author?.name);
console.log(post.expand?.category?.name);
});
// Total: 1 query
}
// Solution 2: Batch fetch related records
async function getPostsWithAuthorsBatch() {
const posts = await pb.collection('posts').getList(1, 20);
// Collect unique author IDs
const authorIds = [...new Set(posts.items.map(p => p.author))];
// Single query for all authors (use pb.filter for safe binding)
const filter = authorIds.map(id => pb.filter('id = {:id}', { id })).join(' || ');
const authors = await pb.collection('users').getList(1, authorIds.length, {
filter
});
// Create lookup map
const authorMap = Object.fromEntries(
authors.items.map(a => [a.id, a])
);
// Attach to posts
posts.items.forEach(post => {
post.authorData = authorMap[post.author];
});
// Total: 2 queries regardless of post count
}
// Solution 3: Use view collection for complex joins
// Create a view that joins posts with authors:
// SELECT p.*, u.name as author_name, u.avatar as author_avatar
// FROM posts p LEFT JOIN users u ON p.author = u.id
async function getPostsFromView() {
const posts = await pb.collection('posts_with_authors').getList(1, 20);
// Single query, data already joined
}
// Solution 4: Back-relations with expand
async function getUserWithPosts(userId) {
const user = await pb.collection('users').getOne(userId, {
expand: 'posts_via_author' // All posts by this user
});
console.log('Posts by user:', user.expand?.posts_via_author);
// 1 query gets user + all their posts
}
Detecting N+1 in your code:
// Add request logging to detect N+1
let requestCount = 0;
pb.beforeSend = (url, options) => {
requestCount++;
console.log(`Request #${requestCount}: ${options.method} ${url}`);
return { url, options };
};
// Monitor during development
async function loadPage() {
requestCount = 0;
await loadAllData();
console.log(`Total requests: ${requestCount}`);
// If this is >> number of records, you have N+1
}
Prevention checklist:
- Always use
expandfor displaying related data - Never fetch related records in loops
- Batch fetch when expand isn't available
- Consider view collections for complex joins
- Monitor request counts during development
Reference: PocketBase Expand