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More Rails: Beyond Backend:

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What is even better than having a really fast web server, framework, programming language that creates your web page? Not having to create and load the page at all because it's already there in a cache.

After working through this guide:

  • you will know that many different caches influence your web app:
    • HTTP caching
    • Fragment caching
    • ActiveRecord QueryCache
    • Caches inside the Database
  • you will be able to configure rails for caching
  • you will be able to measure if a change you made improved the performance of your rails app

DEMO: You can study the demo for the example described here

  • if it's currently online.

1 What is Caching

In computing we are faced with vastly different access speeds for different media:

  • reading a megabyte of data from another host on the internet might take seconds
  • loading the same data from a local ssd takes only 200 µs
  • reading the data from main memory takes 9 µs.

Given these numbers it makes sense to keep a local copy of data that we might use again soon. Better to read it from ssd or memory the second time we need it!

In general english usage a cache is stuff hidden in a secret place. But in computing a cache is "auxiliary memory from which high-speed retrieval is possible".

When you load a webpage into your browser there are many level of caches influencing this process. We will look at some of the caches that we can influence as web developers.

2 Measuring Performance

As we already discussed in the chapter on the asset pipeline it is important to measure the performance of your app before you try to optimize anyhing.

In this chapter we will learn about new tools for measuring what happens on the server.

Let's start with a very general rule of thumb for performance:

We want the whole web page to load within a second. We expect to need about half of that (500ms) for loading extra assets like javascript files, css, images. We will set aside another 200ms for shipping data across the network, which leaves us with 300ms time to render out the first HTML document from our Rails App.

2.1 rack-mini-profiler

This gem helps you analyze where your Rails App spends time.

See RailsCast #368 for a good introduction.

The Mini Profiler only measures the server side: the time spent in the rails app to generate the webpage. So we need to compare the numbers Mini Profiler gives us to the 300ms threshold defined above.

2.2 Example App

We will use a portfolio site as an example app. All the screenshots above already show this example app. You can study the demo on heroku, there all the caching is already implemented.

3 HTTP Caching

HTTP Caching is built into the HTTP protocol. There are several headers in both the HTTP-request and HTTP-response that influence if the browser will cache a resource for later and how long it will keep the resource in the cache.

The Asset Pipeline handles setting the right headers for images, css and javascript by default. See the chapter on the asset pipeline.

For the HTML and JSON output rendered by our rails views we assume that most of them should not be cached by the browser as a whole. For HTML and JSON server side caching is a better approach.

4 Fragment Caching

Fragement caching is a feature of the Rails Framework. Looking at the views and partials that are rendered, you can mark some fragments of the output to be cached for later.

To decide which fragments can be cached and which parts of the view have to be computed anew every time you need to know about the application.

4.1 Configure Caching

Fragment Caching is deactivated by default in the development environment. You have to activate it if you want to try this out in development:

# on the command line
$ rails dev:cache
Development mode is now being cached.

You have to decide on a cache store. This store can be any "key-value" store. For production the simplest method when using just one web server is in-memory.

# in the file config/environments/production.rb

   require 'active_support/core_ext/numeric/bytes'
   config.cache_store = :memory_store, { size: 64.megabytes }

When using several web servers you need a cache store that can be shared between them like memcached or redis.

In development, to get a quick impression of what is saved to the cache it is helpful to use the file_store:

# in the file config/environments/development.rb
    # config.cache_store = :memory_store
    config.cache_store = :file_store, "#{Rails.root}/tmp/file_store"
    config.public_file_server.headers = {
      'Cache-Control' => 'public, max-age=172800'

4.2 Caching a View

The first image of miniprofiler above showed the rendering of the show-action in the project controller.

At first glance rendering the view takes too long: 450ms. We could dig into the details, but let's try a simple approach first: cache the whole view.

add this around the whole project view:

<% cache @project do %>
<% end %>

The result is stunning: from 450ms down to 45ms:

4.2.1 How caching works

So what happens here? When the view is rendered for the first time, it will be rendered normally and still take around 450ms. In the log file you will see a message like this:

Write fragment views/projects/1679-20140722193808000000000/0db0955317bafa37cc34ffcb7567a874 (19.1ms)

This shows the key that is used for the fragment.

The key depends on both the object we specified (here @project), and on the view fragment. In this example '1679' is the id of @project, and '20140722193808000000000' is the current value of its updated_at attribute. The last part of the key is a hash of the view fragment inside the cache block.

So if either the object or the view changes, a new key will be generated, and nothing will be found in the cache. The view will be rendered from scratch.

When the view is rendered for the second time, you find the following message in the log file:

Read fragment views/projects/1679-20140722193808000000000/0db0955317bafa37cc34ffcb7567a874 (1.9ms)

Here the cache is read out, which is a lot faster then rendering.

So which parts of the Rail Stack have we skipped by using the fragment cache?

Really only part of the view. The whole stack was traversed from Routing to Controller to View.

4.2.2 Peeking into the cache

You can also read from the cache in the rails console:


The result is a string with 14716 bytes of html (too long to show here).

When using file_store you can also find the cache in the directory you specified. A two level directory structure will be generated for the cache files, for example:

$ ls  tmp/file_store/*/*/*

4.2.3 Changing the model

Now let's check if the cache is really invalidated when the underlying model changes. Load the project "Origin" in your web browser: http://localhost:3000/projects/2015-origin

In the rails console you can find the corresponding model, and change an attribute:

project = Project.find_by_title('Origin')
project.description = project.description + " and some new information"

Now reload the browser to make sure that a new version of the page is rendered. Reload again to check if the new version is cached.

4.3 Caching smaller fragements

If you look at the homepage of the demo you can see that the list of project under "Bachelorprojekte" is different every time you reload the page. There are 9 projects in all, but only 5 will be picked randomly and will be displayed.

If we want to keep this feature caching the whole homepage will not work: once the homepage is cached, a reload of the page will show the exact same page. The same five projects will appear on the homepage indefinetly.

There are two approaches to this:

a) We could change our expectations for the random display: We could decide that the same 5 projects should be shown for a whole day, and only on the next day new projects should be picked.

This would work for our example app.

b) a second approach would be to not cache the whole homepage, but only the display of an individual project. This means going down to the projects/_project partial, and caching that.

This second approach is useful not just for our "random projects".

Think of the "activity stream" on the facebook hompage: it will look differently for each user, and each time the page is loaded. But it consists of smaller fragments which can be cached: the individual status message, or event, or photo can be reused.

4.3.1 Caching a partial

In the file projects/_project.html.erb we switch on caching.

When you add the code, make sure that you specify the correct object. If not, you might up loading the same partial again and again:

problem with fragement caching

If you implement it correctly each rendering of the partial should be faster now:

successful fragement caching

In Rails 5 you can speed up the rendering even more. If you look at the fronts/show view you can see that the project partial is rendered through a collection:

<%= render :partial => "projects/project", :collection => @sample %>

In Rails 5 you can add caching here:

<%= render :partial => "projects/project", :collection => @sample, :cached => true %>

Now instead of fetching each partial from the cache one by one rails will do a multi-fetch, which is faster. But our example app is written in Rails 4, so this does not work yet.

See Deshmane(2016)

4.3.2 Side Effects

An unexpected side effect of caching the partial can be seen in the edition view: this view also uses the projects/_project partial, so it too will profit from the caching.

4.4 Russian Doll Caching

In the previous step we implemented caching for the projects/_project partial, which is also used in the editions/show view. Now let's add caching to this view also:

<% cache @edition do %>
<% end %>

This change will again speed up the display of the page:

russian doll caching

But now we have problem: if we change one of the projects inside this edition, the cache for the partial would be recreated. But this never gets triggered, because the cache for the whole edition is still valid:

project = Project.find_by_title('Origin')
project.title = 'Orange'

If you reload the page now, you can still see the project named "Origin", not "Orange".

The problem here is a missing dependency: our cache entry only depends on the edition, not on the projects contained in the edition.

We can declare the full dependency by supplying an array of objects to the cache helper method:

<% cache [@edition,@edition.projects] do %>
<% end %>

If you reload the page now, you can see that a much longer cache key is generated:

Write fragment views/editions/16-20160202125058000000000/projec
ts/1622-20141216101932000000000 /projects/1658-2015060105552300

This key works for all changes in an edition:

  • changing an attribute of the edition will change the updated_at attribute also, and will change the key
  • changing an attribute of one of the projects will change the corresponding updated_at attribute also, and will change the key
  • adding a new project to the edition will make the key longer
  • removing a project from the edition will make the key shorter

In the example below the title of one of the projects was changed: You can see in rack-mini-profiler that only one of the partials was recreated, all the other partials were loaded from cache. The next time the same page was rendered the edition cache was reused.

russian doll caching at work: changes when a project changes

4.5 The limits of fragment caching

Caching is really helpful for pages that are accessed a lot. In our example app this might be true for the homepage and maybe the editions. But there are hundreds of projects in the portfolio. Each individual project page will only get very few hits. Which means that chances are high that the page will not already be in the cache when it is requested.

So caching cannot be the solution to all performance problems. We need to take a closer look at the first render of a page to find where we are wasting time. To do this it makes sense to switch off caching in development:

# on the command line
$ rails dev:cache
Development mode is no longer being cached.

4.6 Final Thought on Caching in Rails

If you find that the backend framework causes a performance problem you should be able to narrow down the problem and fix it using different methods. You should be able to:

  • configure caching in development and production
  • use caching for fragments that depend on one or several objects
  • use caching with partials and collections
  • recognize russion doll caching and debug it if necessary

5 ActiveRecord and DB

Accessing the database takes a long time - compared to all the computation that is done in ruby code itself. So looking at the Database, and the ORM we use to access the database, might make sense for performance optimisation.

5.1 Ignore this

If you find SHOW FULL FIELDS queries in your log file or in rack-mini-profiler, you can ignore them. These queries are used by activerecord to find out which attributes an object has. In production these will only occur when the first object of a type is loaded, so you can savely ignore them.

5.2 QueryCache

If you look into the log file logs/development.log you will see all the SQL queries made to the database, and also some that are not really sent to the database.

Here are some lines from a log file:

Started GET "/projects/2014-yokaisho" for ::1 at 2017-04-20 04:40:10 +0200
Processing by ProjectsController#show as HTML
  Parameters: {"id"=>"2014-yokaisho"}
  User Load (6.9ms)  SELECT  `users`.* FROM `users` WHERE `users`.`id` = 953 LIMIT 1
  CACHE (0.1ms)  SELECT  `users`.* FROM `users` WHERE `users`.`id` = 953 LIMIT 1  [["id", 953]]
  CACHE (0.0ms)  SELECT  `users`.* FROM `users` WHERE `users`.`id` = 953 LIMIT 1  [["id", 953]]
  CACHE (0.1ms)  SELECT  `users`.* FROM `users` WHERE `users`.`id` = 953 LIMIT 1  [["id", 953]]

What we can see here is that the Data for user 953 was loaded four times. Somewhere in our rails app we call User.find(953) or similar ActiveRecord methods four times.

But only the first time a SQL requests is really sent to the database. Loading the data from the database took 6.9 ms here.

The next three times the same user was loaded, it was loaded from the ActiveRecord QueryCache, which only took 0.1ms or less.

The default behaviour is that rails loads each model only once for each HTTP request. For the next HTTP request the QueryCache is cleard. So one request-responce cycle is the lifespan of the cached object.

If you ever run into problems with the QueryCache, you can always reload a model explicitly:

user = User.find(953)
# will do SQL request

user = User.find(953)
# will use the query cache

# bust the query cache, do a real SQL query

5.3 indexes in the db

When we query the database by id we will get a rapid response: the primary key is always accessed through an index.

But in this app the main way of identifying a resource is through a "friendly url". For example the project show action is not accessed through the conventional route


but through


In the miniprofiler we can see, that this translates to the SQL query

SELECT * FROM projects WHERE slug='2014-anton-eine-multimediale-inszenierung'

There should be an index on columns slug!

We can check if this is the case in the database console:

mysql> DESCRIBE SELECT * FROM projects WHERE slug='2014-anton-eine-multimediale-inszenierung'
    -> ;
| id | select_type | table    | partitions | type  | possible_keys          | key                    | key_len | ref   | rows | filtered | Extra |
|  1 | SIMPLE      | projects | NULL       | const | index_projects_on_slug | index_projects_on_slug | 768     | const |    1 |   100.00 | NULL  |
1 row in set, 1 warning (0,12 sec)

Yes, there is an index that is used for this query. Contrast this with the output of DESCRIBE when there is no index:

mysql> DESCRIBE SELECT * FROM projects WHERE publicationdate='2014-07-22';
| id | select_type | table    | partitions | type | possible_keys | key  | key_len | ref  | rows | filtered | Extra       |
|  1 | SIMPLE      | projects | NULL       | ALL  | NULL          | NULL | NULL    | NULL |  695 |    10.00 | Using where |
1 row in set, 1 warning (0,12 sec)

5.4 n+1 queries

When analysing the SQL queries a rails project generates you will often find this situation: you have a one-to-many relationship, for example: a project has many users. When displaying the project with all of its users you see n+1 queries. In our example app this happens:

SELECT * FROM `projects` WHERE `slug` = '2014-yokaisho' ORDER BY `projects`.`id` ASC LIMIT 1
SELECT * FROM `projects_roles_users` WHERE `project_id` IN (1622)
SELECT * FROM `users` WHERE `id` = 1033 LIMIT 1
SELECT * FROM `users` WHERE `id` = 1018 LIMIT 1
SELECT * FROM `users` WHERE `id` = 901 LIMIT 1
SELECT * FROM `users` WHERE `id` = 938 LIMIT 1
SELECT * FROM `users` WHERE `id` = 945 LIMIT 1
SELECT * FROM `users` WHERE `id` = 977 LIMIT 1
SELECT * FROM `users` WHERE `id` = 953 LIMIT 1
SELECT * FROM `users` WHERE `id` = 652 LIMIT 1
SELECT * FROM `users` WHERE `id` = 940 LIMIT 1

Here 9 users belong to the project. They are loaded using 9 requests. This is inefficient! If we were coding SQL by hand, we could get the same data using one query with a join.

We can use rack-mini-profiler to find the code line that generated the request:

finding the source code for a sql request

In this example, the ActiveRecord method that generate the first request is in project_controller.rb, line 26

@project = Project.friendly.find(params[:id])

Later, in the view and partials, the relationships from @project to users is accessed.

@project.users.each do |user| ...

To get ActiveRecord to automatically load all the users for the project at once we can change this one line in the controller:

@project = Project.includes(:users).friendly.find(params[:id])

After this change we find a lot less SQL requests:

SELECT * FROM `projects` WHERE `slug` = '2014-yokaisho' ORDER BY `projects`.`id` ASC LIMIT 1
SELECT * FROM `projects_roles_users` WHERE `project_id` IN (1622)
SELECT * FROM `users` WHERE `id` IN (1033, 1018, 901, 938, 945, 977, 953, 652, 940)

This makes a measurable difference:

compare render times with and withoud include

In the demo app, the project model has associations not only with the user model, but with many other models too. If we include them all, we end up with a sizable reduction in SQL queries:

@project = Project.includes(:users, :roles, :assets, :urls, :tags).friendly.find(params[:id])

compare render times with many includes

5.5 view in the database

The last method of speeding up the database access is called a view. The word view here has nothing to do with MVC in Rails, but is a technical term used in databases.

Let's look at a problem where a database view might be a solution:

For the collaborators/_show partial a lot of SQL queries are created.

The collaborator partial shows information about one team member: the thumbnail, the name, their degree program(s) and the role(s) they had in the project.

collaborator partial

The information about the degree programs is found in 2 different tables:

  • studycourses
  • agegroups_studycourses_departments_users

To display "MMT Bachelor 2010, MMT Master 2014" for Mr. Huber the helper method print_studycourses is used. We can try out this helper method in the rails console:

> user = User.find(901)
  User Load (0.5ms)  SELECT  `users`.* FROM `users` WHERE `users`.`id` = 901 LIMIT 1
> ApplicationController.helpers.print_studycourses(user)
  Enrollment Load (0.5ms)  SELECT `agegroups_studycourses_departments_users`.* FROM `agegroups_studycourses_departments_users` WHERE `agegroups_studycourses_departments_users`.`user_id` = 901
  Studycourse Load (0.3ms)  SELECT  `studycourses`.* FROM `studycourses` WHERE `studycourses`.`id` = 3 LIMIT 1
  Agegroup Load (0.4ms)  SELECT  `agegroups`.* FROM `agegroups` WHERE `agegroups`.`id` = 3 LIMIT 1
  Studycourse Load (0.4ms)  SELECT  `studycourses`.* FROM `studycourses` WHERE `studycourses`.`id` = 5 LIMIT 1
  Agegroup Load (0.4ms)  SELECT  `agegroups`.* FROM `agegroups` WHERE `agegroups`.`id` = 19 LIMIT 1

Here information from three database tables is combined.

5.5.1 creating a database view

In the database console we can build a simple select statement with two joins to get the same information:

mysql> SELECT user_id, concat(, ' ', year) AS name
FROM agegroups_studycourses_departments_users x
LEFT JOIN studycourses ON (
LEFT JOIN agegroups ON (
WHERE user_id=901;
| user_id | name              |
|     901 | MMT Bachelor 2010 |
|     901 | MMT Master 2014   |
2 rows in set (0,01 sec)

We can use the select statement to create a view:

mysql> CREATE VIEW degree_programs AS
SELECT user_id, concat(, ' ', year) AS name
FROM agegroups_studycourses_departments_users x
LEFT JOIN studycourses ON (
LEFT JOIN agegroups ON (;
Query OK, 0 rows affected (0,06 sec)

The select statment with the two joins can now be used like a simple table called degree_programs in the database when creating new sql queries.

mysql> SELECT * from degree_programs WHERE user_id=901 ;
| user_id | name              |
|     901 | MMT Bachelor 2010 |
|     901 | MMT Master 2014   |
2 rows in set (0,00 sec)

5.5.2 model and relationships for the view

In Rails we can define a model for a database view:

class DegreeProgram < ApplicationRecord
  belongs_to :user

  def to_s

And add a relationship from user:

class User < ApplicationRecord
  has_many :degree_programs

back in the rails console we can now use this new model:

> user = User.find(901)
  User Load (0.5ms)  SELECT  `users`.* FROM `users` WHERE `users`.`id` = 901 LIMIT 1
> user.degree_programs.join(', ')
  DegreeProgram Load (0.6ms)  SELECT `degree_programs`.* FROM `degree_programs` WHERE `degree_programs`.`user_id` = 901
=> "MMT Bachelor 2010, MMT Master 2014"

And in a final step we can refactor the helper method print_studycourses

  def print_studycourses(student)
    student.degree_programs.join(', ')

This reduces the number of SQL statements to one per collaborator partial:


If we add a relationship from projects to degree_program (actually: three has_many through: steps to get from projects to collaborators, and from collaborators to users, and from users to degree_programs), we can also include degree_programs in our includes statement when loading the project:

@project = Project.includes(:users, :roles, :assets, :urls, :tags, :degree_programs).friendly.find(params[:id])

This way we end up with only very few sql queries, and a big performance improvement:

final state of the app

5.5.3 create view in production

To deploy the view to production, you need to create it with a migration:

class CreateViewDegreeProgram < ActiveRecord::Migration
  def up
    execute <<-SQL
      CREATE VIEW degree_programs AS
      SELECT user_id, concat(, ' ', year) AS name
      FROM agegroups_studycourses_departments_users x
      LEFT JOIN studycourses ON (
      LEFT JOIN agegroups ON (
  def down
    execute 'DROP VIEW degree_programs'

5.5.4 uses and limitations of view

In this case the view might be a first step towards refactoring the database. We just have too many tables in the database that are not really needed.

We can rewrite the rails app step by step to use only the new view, and not the database tables it is supposed to replace. After we have changed all the rails code, we can drop the view, and create a table with the same data instead. Then we can drop the original tables and are finished with the database refactoring.

In other cases you might use a view permanently: If you need both the underlying, more complex data, and the simplified data in the view. Reports with aggregated data, top 10 lists, queries that use complex database expressions, or tables with a reduced set of attributes would be good examples for using a view.

For data that is accessed a lot, but changes very seldom, you can us a materialized view. In a normal view each access to the view triggers the underlying sql requests. In a materialized view the data is copied over to the view once. Like any other caching method this needs more memory, but gives faster access.

5.6 final thoughts

ActiveRecord was a big help when writing this app. But it cannot find the best SQL Query for every situation and it cannot improve the database. As a developer you have to keep an eye on your ORM, and check now and again if the SQL queries that the ORM creates make sense and are efficient. You should

  • be aware of the QueryCache, know how to use it and how to break out of it
  • use indexes in the db for slow queries
  • recognize n+1 queries and avoid them by using includes
  • use view in the database to isolate complex sql and to add caching if needed