Resque

Resque (pronounced like "rescue") is a Redis-backed library for creating background jobs, placing those jobs on multiple queues, and processing them later.

Background jobs can be any Ruby class or module that responds to perform. Your existing classes can easily be converted to background jobs or you can create new classes specifically to do work. Or, you can do both.

Resque is heavily inspired by DelayedJob (which rocks) and comprises three parts:

1. A Ruby library for creating, querying, and processing jobs
2. A Rake task for starting a worker which processes jobs
3. A Sinatra app for monitoring queues, jobs, and workers.

Resque workers can be distributed between multiple machines, support priorities, are resilient to memory bloat / "leaks," are optimized for REE (but work on MRI and JRuby), tell you what they're doing, and expect failure.

Resque queues are persistent; support constant time, atomic push and pop (thanks to Redis); provide visibility into their contents; and store jobs as simple JSON packages.

The Resque frontend tells you what workers are doing, what workers are not doing, what queues you're using, what's in those queues, provides general usage stats, and helps you track failures.

For the backstory, philosophy, and history of Resque's beginnings, please see the blog post.

Resque allows you to create jobs and place them on a queue, then, later, pull those jobs off the queue and process them.

Resque jobs are Ruby classes (or modules) which respond to the perform method. Here's an example:

class Archive
  @queue = :file_serve

  def self.perform(repo_id, branch = 'master')
    repo = Repository.find(repo_id)
    repo.create_archive(branch)
  end
end

The @queue class instance variable determines which queue Archive jobs will be placed in. Queues are arbitrary and created on the fly - you can name them whatever you want and have as many as you want.

To place an Archive job on the file_serve queue, we might add this to our application's pre-existing Repository class:

class Repository
  def async_create_archive(branch)
    Resque.enqueue(Archive, self.id, branch)
  end
end

Now when we call repo.async_create_archive('masterbrew') in our application, a job will be created and placed on the file_serve queue.

Later, a worker will run something like this code to process the job:

klass, args = Resque.reserve(:file_serve)
klass.perform(*args) if klass.respond_to? :perform

Which translates to:

Archive.perform(44, 'masterbrew')

Let's start a worker to run file_serve jobs:

$ cd app_root
$ QUEUE=file_serve rake resque:work

This starts one Resque worker and tells it to work off the file_serve queue. As soon as it's ready it'll try to run the Resque.reserve code snippet above and process jobs until it can't find any more, at which point it will sleep for a small period and repeatedly poll the queue for more jobs.

Workers can be given multiple queues (a "queue list") and run on multiple machines. In fact they can be run anywhere with network access to the Redis server.

What should you run in the background? Anything that takes any time at all. Slow INSERT statements, disk manipulating, data processing, etc.

At GitHub we use Resque to process the following types of jobs:

• Warming caches
• Counting disk usage
• Building tarballs
• Building Rubygems
• Firing off web hooks
• Creating events in the db and pre-caching them
• Building graphs
• Deleting users
• Updating our search index

As of writing we have about 35 different types of background jobs.

Keep in mind that you don't need a web app to use Resque - we just mention "foreground" and "background" because they make conceptual sense. You could easily be spidering sites and sticking data which needs to be crunched later into a queue.

Jobs are persisted to queues as JSON objects. Let's take our Archive example from above. We'll run the following code to create a job:

repo = Repository.find(44)
repo.async_create_archive('masterbrew')

The following JSON will be stored in the file_serve queue:

{
    'class': 'Archive',
    'args': [ 44, 'masterbrew' ]
}

Because of this your jobs must only accept arguments that can be JSON encoded.

So instead of doing this:

Resque.enqueue(Archive, self, branch)

do this:

Resque.enqueue(Archive, self.id, branch)

This is why our above example (and all the examples in examples/) uses object IDs instead of passing around the objects.

While this is less convenient than just sticking a marshaled object in the database, it gives you a slight advantage: your jobs will be run against the most recent version of an object because they need to pull from the DB or cache.

If your jobs were run against marshaled objects, they could potentially be operating on a stale record with out-of-date information.

Want something like DelayedJob's send_later or the ability to use instance methods instead of just methods for jobs? See the examples/ directory for goodies.

We plan to provide first class async support in a future release.

If a job raises an exception, it is logged and handed off to the Resque::Failure module. Failures are logged either locally in Redis or using some different backend.

For example, Resque ships with Hoptoad support.

Keep this in mind when writing your jobs: you may want to throw exceptions you would not normally throw in order to assist debugging.

Resque workers are rake tasks that run forever. They basically do this:

start
loop do
  if job = reserve
    job.process
  else
    sleep 5 # Polling frequency = 5 
  end
end
shutdown

Starting a worker is simple. Here's our example from earlier:

$ QUEUE=file_serve rake resque:work

By default Resque won't know about your application's environment. That is, it won't be able to find and run your jobs - it needs to load your application into memory.

If we've installed Resque as a Rails plugin, we might run this command from our RAILS_ROOT:

$ QUEUE=file_serve rake environment resque:work

This will load the environment before starting a worker. Alternately we can define a resque:setup task with a dependency on the environment rake task:

task "resque:setup" => :environment

GitHub's setup task looks like this:

task "resque:setup" => :environment do
  Grit::Git.git_timeout = 10.minutes
end

We don't want the git_timeout as high as 10 minutes in our web app, but in the Resque workers it's fine.

Workers support basic logging to STDOUT. If you start them with the VERBOSE env variable set, they will print basic debugging information. You can also set the VVERBOSE (very verbose) env variable.

$ VVERBOSE=1 QUEUE=file_serve rake environment resque:work

There are scenarios where it's helpful to record the PID of a resque worker process. Use the PIDFILE option for easy access to the PID:

$ PIDFILE=./resque.pid QUEUE=file_serve rake environment resque:work

(Only supported with ruby >= 1.9). There are scenarios where it's helpful for the resque worker to run itself in the background (usually in combination with PIDFILE). Use the BACKGROUND option so that rake will return as soon as the worker is started.

$ PIDFILE=./resque.pid BACKGROUND=yes QUEUE=file_serve \
    rake environment resque:work

You can pass an INTERVAL option which is a float representing the polling frequency. The default is 5 seconds, but for a semi-active app you may want to use a smaller value.

$ INTERVAL=0.1 QUEUE=file_serve rake environment resque:work

Resque doesn't support numeric priorities but instead uses the order of queues you give it. We call this list of queues the "queue list."

Let's say we add a warm_cache queue in addition to our file_serve queue. We'd now start a worker like so:

$ QUEUES=file_serve,warm_cache rake resque:work

When the worker looks for new jobs, it will first check file_serve. If it finds a job, it'll process it then check file_serve again. It will keep checking file_serve until no more jobs are available. At that point, it will check warm_cache. If it finds a job it'll process it then check file_serve (repeating the whole process).

In this way you can prioritize certain queues. At GitHub we start our workers with something like this:

$ QUEUES=critical,archive,high,low rake resque:work

Notice the archive queue - it is specialized and in our future architecture will only be run from a single machine.

At that point we'll start workers on our generalized background machines with this command:

$ QUEUES=critical,high,low rake resque:work

And workers on our specialized archive machine with this command:

$ QUEUE=archive rake resque:work

If you want your workers to work off of every queue, including new queues created on the fly, you can use a splat:

$ QUEUE=* rake resque:work

Queues will be processed in alphabetical order.

At GitHub we use god to start and stop multiple workers. A sample god configuration file is included under examples/god. We recommend this method.

If you'd like to run multiple workers in development mode, you can do so using the resque:workers rake task:

$ COUNT=5 QUEUE=* rake resque:workers

This will spawn five Resque workers, each in its own thread. Hitting ctrl-c should be sufficient to stop them all.

On certain platforms, when a Resque worker reserves a job it immediately forks a child process. The child processes the job then exits. When the child has exited successfully, the worker reserves another job and repeats the process.

Why?

Because Resque assumes chaos.

Resque assumes your background workers will lock up, run too long, or have unwanted memory growth.

If Resque workers processed jobs themselves, it'd be hard to whip them into shape. Let's say one is using too much memory: you send it a signal that says "shutdown after you finish processing the current job," and it does so. It then starts up again - loading your entire application environment. This adds useless CPU cycles and causes a delay in queue processing.

Plus, what if it's using too much memory and has stopped responding to signals?

Thanks to Resque's parent / child architecture, jobs that use too much memory release that memory upon completion. No unwanted growth.

And what if a job is running too long? You'd need to kill -9 it then start the worker again. With Resque's parent / child architecture you can tell the parent to forcefully kill the child then immediately start processing more jobs. No startup delay or wasted cycles.

The parent / child architecture helps us keep tabs on what workers are doing, too. By eliminating the need to kill -9 workers we can have parents remove themselves from the global listing of workers. If we just ruthlessly killed workers, we'd need a separate watchdog process to add and remove them to the global listing - which becomes complicated.

Workers instead handle their own state.

Here's a parent / child pair doing some work:

$ ps -e -o pid,command | grep [r]esque
92099 resque: Forked 92102 at 1253142769
92102 resque: Processing file_serve since 1253142769

You can clearly see that process 92099 forked 92102, which has been working since 1253142769.

(By advertising the time they began processing you can easily use monit or god to kill stale workers.)

When a parent process is idle, it lets you know what queues it is waiting for work on:

$ ps -e -o pid,command | grep [r]esque
92099 resque: Waiting for file_serve,warm_cache

Resque workers respond to a few different signals:

• QUIT - Wait for child to finish processing then exit
• TERM / INT - Immediately kill child then exit
• USR1 - Immediately kill child but don't exit
• USR2 - Don't start to process any new jobs
• CONT - Start to process new jobs again after a USR2

If you want to gracefully shutdown a Resque worker, use QUIT.

If you want to kill a stale or stuck child, use USR1. Processing will continue as normal unless the child was not found. In that case Resque assumes the parent process is in a bad state and shuts down.

If you want to kill a stale or stuck child and shutdown, use TERM

If you want to stop processing jobs, but want to leave the worker running (for example, to temporarily alleviate load), use USR2 to stop processing, then CONT to start it again.

If your workers remain idle for too long they may lose their MySQL connection. If that happens we recommend using this Gist.

Resque comes with a Sinatra-based front end for seeing what's up with your queue.

If you've installed Resque as a gem running the front end standalone is easy:

$ resque-web

It's a thin layer around rackup so it's configurable as well:

$ resque-web -p 8282

If you have a Resque config file you want evaluated just pass it to the script as the final argument:

$ resque-web -p 8282 rails_root/config/initializers/resque.rb

You can also set the namespace directly using resque-web:

$ resque-web -p 8282 -N myapp

or set the Redis connection string if you need to do something like select a different database:

$ resque-web -p 8282 -r localhost:6379:2

Using Passenger? Resque ships with a config.ru you can use. See Phusion's guide:

Apache: http://www.modrails.com/documentation/Users%20guide%20Apache.html#_deploying_a_rack_based_ruby_application Nginx: http://www.modrails.com/documentation/Users%20guide%20Nginx.html#deploying_a_rack_app

If you want to load Resque on a subpath, possibly alongside other apps, it's easy to do with Rack's URLMap:

require 'resque/server'

run Rack::URLMap.new \
  "/"       => Your::App.new,
  "/resque" => Resque::Server.new

Check examples/demo/config.ru for a functional example (including HTTP basic auth).

You can also mount Resque on a subpath in your existing Rails 3 app by adding require 'resque/server' to the top of your routes file or in an initializer then adding this to routes.rb:

mount Resque::Server.new, :at => "/resque"

How does Resque compare to DelayedJob, and why would you choose one over the other?

• Resque supports multiple queues
• DelayedJob supports finer grained priorities
• Resque workers are resilient to memory leaks / bloat
• DelayedJob workers are extremely simple and easy to modify
• Resque requires Redis
• DelayedJob requires ActiveRecord
• Resque can only place JSONable Ruby objects on a queue as arguments
• DelayedJob can place any Ruby object on its queue as arguments
• Resque includes a Sinatra app for monitoring what's going on
• DelayedJob can be queried from within your Rails app if you want to add an interface

If you're doing Rails development, you already have a database and ActiveRecord. DelayedJob is super easy to setup and works great. GitHub used it for many months to process almost 200 million jobs.

Choose Resque if:

• You need multiple queues
• You don't care / dislike numeric priorities
• You don't need to persist every Ruby object ever
• You have potentially huge queues
• You want to see what's going on
• You expect a lot of failure / chaos
• You can setup Redis
• You're not running short on RAM

Choose DelayedJob if:

• You like numeric priorities
• You're not doing a gigantic amount of jobs each day
• Your queue stays small and nimble
• There is not a lot failure / chaos
• You want to easily throw anything on the queue
• You don't want to setup Redis

In no way is Resque a "better" DelayedJob, so make sure you pick the tool that's best for your app.

Resque requires Redis 0.900 or higher.

Resque uses Redis' lists for its queues. It also stores worker state data in Redis.

If you're on OS X, Homebrew is the simplest way to install Redis:

$ brew install redis
$ redis-server /usr/local/etc/redis.conf

You now have a Redis daemon running on 6379.

Resque includes Rake tasks (thanks to Ezra's redis-rb) that will install and run Redis for you:

$ git clone git://github.com/defunkt/resque.git
$ cd resque
$ rake redis:install dtach:install
$ rake redis:start

Or, if you don't have admin access on your machine:

$ git clone git://github.com/defunkt/resque.git
$ cd resque
$ PREFIX=<your_prefix> rake redis:install dtach:install
$ rake redis:start

You now have Redis running on 6379. Wait a second then hit ctrl-\ to detach and keep it running in the background.

The demo is probably the best way to figure out how to put the parts together. But, it's not that hard.

$ gem install bundler
$ bundle install

First install the gem.

$ gem install resque

Next include it in your application.

require 'resque'

Now start your application:

rackup config.ru

That's it! You can now create Resque jobs from within your app.

To start a worker, create a Rakefile in your app's root (or add this to an existing Rakefile):

require 'your/app'
require 'resque/tasks'

Now:

$ QUEUE=* rake resque:work

Alternately you can define a resque:setup hook in your Rakefile if you don't want to load your app every time rake runs.

First install the gem.

$ gem install resque

Next include it in your application.

$ cat config/initializers/load_resque.rb
require 'resque'

Now start your application:

$ ./script/server

That's it! You can now create Resque jobs from within your app.

To start a worker, add this to your Rakefile in RAILS_ROOT:

require 'resque/tasks'

Now:

$ QUEUE=* rake environment resque:work

Don't forget you can define a resque:setup hook in lib/tasks/whatever.rake that loads the environment task every time.

$ ./script/plugin install git://github.com/defunkt/resque

That's it! Resque will automatically be available when your Rails app loads.

To start a worker:

$ QUEUE=* rake environment resque:work

Don't forget you can define a resque:setup hook in lib/tasks/whatever.rake that loads the environment task every time.

First include it in your Gemfile.

$ cat Gemfile
...
gem 'resque'
...

Next install it with Bundler.

$ bundle install

Now start your application:

$ rails server

That's it! You can now create Resque jobs from within your app.

To start a worker, add this to a file in lib/tasks (ex: lib/tasks/resque.rake):

require 'resque/tasks'

Now:

$ QUEUE=* rake environment resque:work

Don't forget you can define a resque:setup hook in lib/tasks/whatever.rake that loads the environment task every time.

You may want to change the Redis host and port Resque connects to, or set various other options at startup.

Resque has a redis setter which can be given a string or a Redis object. This means if you're already using Redis in your app, Resque can re-use the existing connection.

String: Resque.redis = 'localhost:6379'

Redis: Resque.redis = $redis

For our rails app we have a config/initializers/resque.rb file where we load config/resque.yml by hand and set the Redis information appropriately.

Here's our config/resque.yml:

development: localhost:6379
test: localhost:6379
staging: redis1.se.github.com:6379
fi: localhost:6379
production: redis1.ae.github.com:6379

And our initializer:

rails_root = ENV['RAILS_ROOT'] || File.dirname(__FILE__) + '/../..'
rails_env = ENV['RAILS_ENV'] || 'development'

resque_config = YAML.load_file(rails_root + '/config/resque.yml')
Resque.redis = resque_config[rails_env]

Easy peasy! Why not just use RAILS_ROOT and RAILS_ENV? Because this way we can tell our Sinatra app about the config file:

$ RAILS_ENV=production resque-web rails_root/config/initializers/resque.rb

Now everyone is on the same page.

Also, you could disable jobs queueing by setting 'inline' attribute. For example, if you want to run all jobs in the same process for cucumber, try:

Resque.inline = ENV['RAILS_ENV'] == "cucumber"

For a list of available plugins see http://wiki.github.com/defunkt/resque/plugins.

If you'd like to write your own plugin, or want to customize Resque using hooks (such as Resque.after_fork), see docs/HOOKS.md.

If you're running multiple, separate instances of Resque you may want to namespace the keyspaces so they do not overlap. This is not unlike the approach taken by many memcached clients.

This feature is provided by the redis-namespace library, which Resque uses by default to separate the keys it manages from other keys in your Redis server.

Simply use the Resque.redis.namespace accessor:

Resque.redis.namespace = "resque:GitHub"

We recommend sticking this in your initializer somewhere after Redis is configured.

Resque ships with a demo Sinatra app for creating jobs that are later processed in the background.

Try it out by looking at the README, found at examples/demo/README.markdown.

If you're using god to monitor Resque, we have provided example configs in examples/god/. One is for starting / stopping workers, the other is for killing workers that have been running too long.

If you're using monit, examples/monit/resque.monit is provided free of charge. This is not used by GitHub in production, so please send patches for any tweaks or improvements you can make to it.

Please add them to the FAQ or ask on the Mailing List. The Mailing List is explained further below

Want to hack on Resque?

First clone the repo and run the tests:

git clone git://github.com/defunkt/resque.git
cd resque
rake test

If the tests do not pass make sure you have Redis installed correctly (though we make an effort to tell you if we feel this is the case). The tests attempt to start an isolated instance of Redis to run against.

Also make sure you've installed all the dependencies correctly. For example, try loading the redis-namespace gem after you've installed it:

$ irb
>> require 'rubygems'
=> true
>> require 'redis/namespace'
=> true

If you get an error requiring any of the dependencies, you may have failed to install them or be seeing load path issues.

Feel free to ping the mailing list with your problem and we'll try to sort it out.

Read the Contributing wiki page first.

Once you've made your great commits:

1. Fork Resque
2. Create a topic branch - git checkout -b my_branch
3. Push to your branch - git push origin my_branch
4. Create a Pull Request from your branch
5. That's it!

To join the list simply send an email to resque@librelist.com. This will subscribe you and send you information about your subscription, including unsubscribe information.

The archive can be found at http://librelist.com/browser/resque/.

• Code: git clone git://github.com/defunkt/resque.git
• Home: http://github.com/defunkt/resque
• Docs: http://defunkt.github.com/resque/
• Bugs: http://github.com/defunkt/resque/issues
• List: resque@librelist.com
• Chat: irc://irc.freenode.net/resque
• Gems: http://gemcutter.org/gems/resque

This project uses Semantic Versioning.

Chris Wanstrath :: chris@ozmm.org :: @defunkt