Fix Bullet::Notification::UnoptimizedQueryError: USE eager loading detected Post => [:comments] in Rails

An N+1 query occurs when your code loads a collection and then makes a separate database query for each item's associations. This drastically slows page loads as the number of records grows. Fix it by using includes, preload, or eager_load to batch-load the associated records in a single query.

Reading the Stack Trace

Here's what each line means:

• app/views/posts/index.html.erb:5: The view iterates over posts and accesses post.comments on each iteration, triggering individual queries.
• app/controllers/posts_controller.rb:8:in `index': The controller loads posts without eager loading the comments association.
• activerecord (7.1.3) lib/active_record/relation.rb:860:in `exec_queries': ActiveRecord executes a separate query for each post's comments instead of batching.

Common Causes

# app/controllers/posts_controller.rb
def index
  @posts = Post.all
end

# app/views/posts/index.html.erb
<% @posts.each do |post| %>
  <p><%= post.comments.count %> comments</p>
<% end %>

@posts = Post.includes(:comments)
# But view also accesses comment.user which is not preloaded
<% post.comments.each do |comment| %>
  <p><%= comment.user.name %></p>
<% end %>

<% @posts.each do |post| %>
  <p><%= post.comments.count %></p>  <!-- COUNT query per post -->
<% end %>

The Fix

Adding .includes(:comments) tells ActiveRecord to load all comments for all posts in a single query using a LEFT OUTER JOIN or a separate IN query, eliminating the N+1 problem.

def index
  @posts = Post.all
end

def index
  @posts = Post.includes(:comments).order(created_at: :desc)
end

Testing the Fix

require 'rails_helper'

RSpec.describe PostsController, type: :controller do
  describe 'GET #index' do
    it 'eager loads comments to avoid N+1' do
      posts = create_list(:post, 3)
      posts.each { |p| create_list(:comment, 2, post: p) }

      expect {
        get :index
      }.to make_database_queries(count: 2..3)
    end

    it 'returns all posts' do
      create_list(:post, 3)
      get :index
      expect(assigns(:posts).size).to eq(3)
    end
  end
end

Run your tests:

bundle exec rspec spec/controllers/posts_controller_spec.rb

Pushing Through CI/CD

git checkout -b fix/rails-n-plus-one
git add app/controllers/posts_controller.rb
git commit -m "fix: add includes(:comments) to eliminate N+1 query"
git push origin fix/rails-n-plus-one

Your CI config should look something like this:

name: CI
on:
  pull_request:
    branches: [main]
jobs:
  test:
    runs-on: ubuntu-latest
    services:
      postgres:
        image: postgres:16
        env:
          POSTGRES_PASSWORD: postgres
        ports: ['5432:5432']
    steps:
      - uses: actions/checkout@v4
      - uses: ruby/setup-ruby@v1
        with:
          ruby-version: '3.3'
          bundler-cache: true
      - run: bin/rails db:setup
      - run: bundle exec rspec

The Full Manual Process: 18 Steps

Here's every step you just went through to fix this one bug:

1. Notice the error alert or see it in your monitoring tool
2. Open the error dashboard and read the stack trace
3. Identify the file and line number from the stack trace
4. Open your IDE and navigate to the file
5. Read the surrounding code to understand context
6. Reproduce the error locally
7. Identify the error source
8. Write the fix
9. Run the test suite locally
10. Fix any failing tests
11. Write new tests covering the edge case
12. Run the full test suite again
13. Create a new git branch
14. Commit and push your changes
15. Open a pull request
16. Wait for code review
17. Merge and deploy to production
18. Monitor production to confirm the error is resolved

Total time: 30-60 minutes. For one bug.

gem install bugstack

require 'bugstack'

Bugstack.init(api_key: ENV['BUGSTACK_API_KEY'])

Deploying the Fix (Manual Path)

1. Add includes to the controller query.
2. Enable Bullet gem in development and test to detect future N+1 queries.
3. Run the test suite and confirm query count is reduced.
4. Open a pull request.
5. Merge and monitor query performance in production.

Frequently Asked Questions