By Andrew Williams
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Reason: Ubuntu 12.04 reached end of life (EOL) on April 28, 2017 and no longer receives security patches or updates. This guide is no longer maintained.
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Memcached is a very fast in-memory object caching system that can make Rails run much faster with very few changes.
This tutorial assumes you have already installed Ruby on Rails and Memcached. If not, the tutorials are linked below:
It also assumes that you have your Rails application up and running and ready to optimize using Memcached.
The first thing we will have to do is install Mike Perham's Dalli Gem:
gem install dalli
If you use Bundler, then add
gem 'dalli' to your Gemfile and run
This will be our super fast and feature packed way of interacting with Memcached.
The first step to configuring Rails to use memcached is to edit your
config/environments/production.rb and add this line to tell Rails to use Dalli:
config.cache_store = :dalli_store
Next, we will tell ActionController to perform caching. Add this line to the same file:
config.action_controller.perform_caching = true
Now, restart your Rails application as you normally would.
To take advantage of the changes we've just made, the Rails application will need to be updated. There are two major ways to take advantage of the speed up memcached will give you.
The easiest way to take advantage of memcached is to add a Cache-Control header to one of your actions. This will let Rack::Cache store the result of that action in memcached for you. If you had the following action in
def slow_action sleep 15 # todo - print something here end
We can add the following line to tell Rack::Cache to store the result for five minutes:
def slow_action expires_in 5.minutes sleep 15 # todo - print something here end
Now, when you execute this action the second time, you'll see that it's significantly faster. Rails only has to execute it once every five minutes to update Rack::Cache.
Please note that this will set the Cache-Control header to public. If you have certain actions that only one user should see, use
expires_in 5.minutes, :public => false. You will also have to determine what the appropriate time is to cache your responses, this varies from application to application.
If you would like to learn more about HTTP Caching, check out Mark Nottingham's Caching Tutorial for Web Authors and Webmasters.
If you have a very expensive operation or object that you must create each time, you can store and retrieve it in memcached. Let's say your action looks like this:
def slow_action slow_object = create_slow_object end
We can store the result in memcached by changing the action like this:
def slow_action slow_object = Rails.cache.fetch(:slow_object) do create_slow_object end end
Rails will ask memcached for the object with a key of 'slow_object'; if it doesn't find that object, it will execute the block given and write the object back into it.
Fragment caching is a Rails feature that lets you choose which parts of your application are the most dynamic and need to be optimized. You can easily cache any part of a view surrounding it in a
<% # app/views/managers/index.html.erb %> <% cache manager do %> Manager's Direct Reports: <%= render manager.employees %> <% end %> <% # app/views/employees/_employee.html.erb %> <% cache employee do %> Employee Name: <%= employee.name %> <%= render employee.incomplete_tasks %> <% end %> <% # app/views/tasks/_incomplete_tasks.html.erb %> <% cache task do %> Task: <%= task.title %> Due Date: <%= task.due_date %> <% end %>
The above technique is called Russian Doll caching alluding to the traditional Russian nesting dolls. Rails will then cache these fragments to memcached and since we added the model into the
cache statement this cache object's key will change when the object changes. The problem this creates though is when a task gets updated:
Since we are nesting cache objects inside of cache objects, Rails won't know to expire the cache fragments that rely on this model. This is where the ActiveRecord
touch keyword comes in handy:
class Employee < ActiveRecord::Base belongs_to :manager, touch: true end class Todo < ActiveRecord::Base belongs_to :employee, touch: true end
Now when a
Todo model is updated, it will expire its cache fragments plus notify the
Employee model that it should update its fragments too. Then the
Employee fragment will notify the
Manager model and after this, the cache expiration process is complete.
There is one additional problem that Russian Doll caching creates for us. When deploying a new application, Rails doesn't know when to check that a view template has changed. If we update our task listing view partial:
<% # app/views/tasks/_incomplete_tasks.html.erb %> <% cache task do %> Task: <%= task.title %> Due Date: <%= task.due_date %> <p><%= task.notes %></p> <% end %>
Rails won't expire the cache fragments that use view partial. Before you would have to add version numbers to your
cache statements but now there is a gem called cache_digests that automatically adds in an MD5 hash of the template file to the cache key. If you update the partial and restart your application, the cache key will no longer match since the MD5 of the view template file has changed and Rails will render that template again. It also handles the dependencies between template files so, in the above example, it will expire all our cache objects up the dependency chain if the
_incomplete_tasks.html.erb is updated.
This feature is automatically included in Rails version 4.0. To use this gem in your Rails 3 project, type the following command:
gem install cache_digests
Or if you use Bundler, add this line to your Gemfile:
The Dalli Ruby Gem is very powerful and takes care of spreading keys across a cluster of memcached servers, which distributes the load and increases your memcached capacity. If you have multiple web servers in your web tier, you can install memcached on each of those servers and add them all to your
config.cache_store = :dalli_store, 'web1.example.com', 'web2.example.com', 'web3.example.com'
This will use consistent hashing to spread the keys across the available memcached servers.
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Thanks, Great tutorial.
Great tutorial. Clean and objective. Well done.
This easy an easy guide for setting up memcached. Thanks!
@pafahim - there’s no way to store a “validation rule” in memcache. even if you could, you still have to do the actual processing. i would recommend, if you have this much data to validate, to offload the request to something like delayed_job or resque. also, if you can hand-write validations in plain ruby instead of using rails validation bits (just for the upload/import, of course), you wouldn’t have to load a new ar object for each row. you can look into using something like a service object (http://stevelorek.com/service-objects.html) to handle the validation. as far as inserting records, you can pass in an array of hashes to .create of any model, which will insert all the records as one database call, instead of hundreds of database calls, which will save you a tremendous amount of time.
Thanks for your blog. Can we validate request input data using memcache ? Actually I am facing scenario in which user uploading CSV file which can have hundreds of rows and to validate each row using ActiveRecord taking long time.
Please can you reply me below question:-
excellent tutorial, you’re amazing
Nice article, thanks!