rails-performance

Rails Performance Optimization

Guidance for optimizing Rails application performance including database queries, caching, background processing, and profiling.

N+1 Query Prevention

Detect N+1 queries by checking for association access inside loops. Resolve with eager loading:

# BAD: N+1 — each iteration queries the database
users.each { |u| u.posts.count }

# GOOD: Eager load with includes
users = User.includes(:posts)
users.each { |u| u.posts.size }  # No additional queries

Method	Query Style	Use When
includes	Auto (smart)	Default choice for eager loading
preload	Separate queries	Multiple has_many, avoiding cartesian
eager_load	Single LEFT JOIN	Filtering/ordering by association
joins	INNER JOIN	Filtering only, not accessing data

Enable strict loading in development to surface N+1 issues as errors:

# config/environments/development.rb
config.active_record.strict_loading_by_default = true

For detailed eager loading patterns, Bullet gem setup, and strict loading configuration, read references/eager-loading.md.

Database Optimization

Indexing

Add indexes for foreign keys, WHERE clause columns, ORDER BY columns, and composite queries:

add_index :posts, :user_id
add_index :users, :email, unique: true
add_index :orders, [:status, :created_at]

Query Patterns

# Select only needed columns
User.select(:id, :name, :email)

# Use pluck for arrays of values (skips model instantiation)
User.where(active: true).pluck(:email)

# Check existence efficiently
User.where(email: email).exists?  # Not .count > 0

# Batch process large datasets
User.find_each(batch_size: 1000) { |u| u.process! }

# Bulk operations
User.where(active: false).update_all(deleted_at: Time.current)

Counter Caches

Avoid repeated counting queries by maintaining a cached count column:

class Post < ApplicationRecord
  belongs_to :user, counter_cache: true
end
# user.posts_count reads the column — no query

Pagination

Paginate all large collections to avoid loading entire tables:

# Pagy (recommended — faster, lower memory)
@pagy, @users = pagy(User.all, items: 25)

# Kaminari
@users = User.page(params[:page]).per(25)

For indexing strategies, EXPLAIN analysis, bulk operations, and advanced query patterns, read references/database-optimization.md.

Caching Strategies

Fragment Caching

Cache expensive view partials:

<% cache @article do %>
  <%= render @article %>
<% end %>

<%# Collection caching %>
<%= render partial: 'article', collection: @articles, cached: true %>

Low-Level Caching

Cache arbitrary data with automatic expiration:

Rails.cache.fetch('popular_posts', expires_in: 1.hour, race_condition_ttl: 10.seconds) do
  Post.popular.limit(10).to_a
end

HTTP Caching

Return 304 Not Modified when content has not changed:

def show
  @article = Article.find(params[:id])
  if stale?(@article)
    respond_to { |format| format.html }
  end
end

Cache Store Configuration

# Redis (recommended for production)
config.cache_store = :redis_cache_store, {
  url: ENV['REDIS_URL'],
  expires_in: 1.day,
  namespace: 'myapp_cache'
}

# Solid Cache (Rails 8+ — database-backed)
config.cache_store = :solid_cache_store

For Russian Doll caching, cache key design, invalidation patterns, and detailed store options, read references/caching-strategies.md.

Background Jobs

Move slow operations out of the request cycle:

class OrdersController < ApplicationController
  def create
    @order = Order.create!(order_params)
    ProcessOrderJob.perform_later(@order.id)
    SendConfirmationEmailJob.perform_later(@order.id)
    redirect_to @order, notice: 'Order placed!'
  end
end

Offload to background jobs: email sending, external API calls, report generation, file processing, and any operation exceeding ~100ms.

Streaming Large Responses

For large exports (CSV, JSON), stream the response to avoid buffering in memory:

def export
  headers['Content-Type'] = 'text/csv'
  headers['Content-Disposition'] = 'attachment; filename="users.csv"'

  self.response_body = Enumerator.new do |yielder|
    yielder << "name,email\n"
    User.find_each(batch_size: 1000) do |user|
      yielder << "#{user.name},#{user.email}\n"
    end
  end
end

Combine find_each (batch loading) with an Enumerator (streaming output) to export large datasets without memory bloat or request timeouts.

Profiling

rack-mini-profiler

Add a timing badge to every page showing SQL queries, rendering time, and memory:

gem 'rack-mini-profiler'
# Press Alt+P to show/hide. Append ?pp=flamegraph for flamegraphs.

Benchmark Comparisons

Benchmark.bm do |x|
  x.report('includes') { User.includes(:posts).to_a }
  x.report('preload')  { User.preload(:posts).to_a }
end

For MemoryProfiler, derailed_benchmarks, ActiveSupport::Notifications, and production monitoring setup, read references/profiling-tools.md.

Performance Checklist

Database

• Indexes on foreign keys and frequently queried columns
• No N+1 queries (use includes/preload)
• Select only needed columns
• find_each for large dataset processing
• Pagination on all listings

Caching

• Fragment caching for expensive view partials
• Collection caching with cached: true
• HTTP caching headers (stale?/expires_in)
• Redis or Solid Cache in production

Background Processing

• Heavy operations in background jobs
• Email sending async
• External API calls async
• Large exports use streaming responses

Quick Reference

Problem	Solution
N+1 queries	includes(:association)
Slow counting	Counter cache
Large datasets	find_each + pagination
Slow views	Fragment caching
Slow operations	Background jobs
Missing indexes	add_index migration
Heavy queries	Select only needed columns
Large exports	find_each + streaming

Additional Resources

Reference Files

For detailed patterns and techniques, consult:

• references/eager-loading.md — N+1 detection, includes vs preload vs eager_load, Bullet gem, strict loading
• references/database-optimization.md — Indexing strategies, EXPLAIN analysis, batch processing, bulk operations, counter caches
• references/caching-strategies.md — Russian Doll caching, low-level cache keys, HTTP caching, cache store configuration, invalidation patterns
• references/profiling-tools.md — rack-mini-profiler, Benchmark, MemoryProfiler, derailed_benchmarks, ActiveSupport::Notifications