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:
- A Ruby library for creating, querying, and processing jobs
- A Rake task for starting a worker which processes jobs
- 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. To see exceptions while developing,
use VERBOSE env variable, see details below under Logging.
For example, Resque ships with Airbrake support. To configure it, put the following into an initialisation file or into your rake job:
# send errors which occur in background jobs to redis and airbrake
require 'resque/failure/multiple'
require 'resque/failure/redis'
require 'resque/failure/airbrake'
Resque::Failure::Multiple.classes = [Resque::Failure::Redis, Resque::Failure::Airbrake]
Resque::Failure.backend = Resque::Failure::Multiple
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
If you want Resque to log to a file, in Rails do:
# config/initializers/resque.rb
Resque.logger = Logger.new(Rails.root.join('log', "#{Rails.env}_resque.log"))
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 process. 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 exitTERM
/INT
- Immediately kill child then exitUSR1
- Immediately kill child but don't exitUSR2
- Don't start to process any new jobsCONT
- 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.
When shutting down processes, Heroku sends every process a TERM signal at the
same time. By default this causes an immediate shutdown of any running job
leading to frequent Resque::TermException
errors. For short running jobs, a simple
solution is to give a small amount of time for the job to finish
before killing it.
To accomplish this set the following environment variables:
-
RESQUE_PRE_SHUTDOWN_TIMEOUT
- The time between the parent receiving a shutdown signal (TERM by default) and it sending that signal on to the child process. Designed to give the child process time to complete before being forced to die. -
TERM_CHILD
- Must be set forRESQUE_PRE_SHUTDOWN_TIMEOUT
to be used. After the timeout, if the child is still running it will raise aResque::TermException
and exit. -
RESQUE_TERM_TIMEOUT
- By default you have a few seconds to handleResque::TermException
in your job.RESQUE_TERM_TIMEOUT
andRESQUE_PRE_SHUTDOWN_TIMEOUT
must be lower than the heroku dyno timeout.
If your workers remain idle for too long they may lose their MySQL connection. Depending on your version of Rails, we recommend the following:
In your perform
method, add the following line:
class MyTask
def self.perform
ActiveRecord::Base.verify_active_connections!
# rest of your code
end
end
The Rails doc says the following about verify_active_connections!
:
Verify active connections and remove and disconnect connections associated with stale threads.
In your perform
method, instead of verify_active_connections!
, use:
class MyTask
def self.perform
ActiveRecord::Base.clear_active_connections!
# rest of your code
end
end
From the Rails docs on clear_active_connections!
:
Returns any connections in use by the current thread back to the pool, and also returns connections to the pool cached by threads that are no longer alive.
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: https://www.phusionpassenger.com/library/deploy/apache/deploy/ruby/ Nginx: https://www.phusionpassenger.com/library/deploy/nginx/deploy/ruby/
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.
$ 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'
If you're using Rails 5.x, include the following in lib/tasks/resque.rb:
require 'resque/tasks'
task 'resque:setup' => :environment
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/resque/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/resque/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 open an issue on this repo.
Want to hack on Resque?
First clone the repo and run the tests:
git clone git://github.com/resque/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.
Read CONTRIBUTING.md first.
Once you've made your great commits:
- Fork Resque
- Create a topic branch -
git checkout -b my_branch
- Push to your branch -
git push origin my_branch
- Create a Pull Request from your branch
- That's it!
This mailing list is no longer maintained. The archive can be found at http://librelist.com/browser/resque/.
- Code:
git clone git://github.com/resque/resque.git
- Home: http://github.com/resque/resque
- Docs: http://rubydoc.info/gems/resque
- Bugs: http://github.com/resque/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