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README.markdown

THIS FORK

This fork is intended to only run one fiber and does not use Fiber yielding to pick up jobs. This fork was created because the EM::Synchrony.sleep solution does not work well for sending Apple Push Notifications.

EM::Resque

EM::Resque is an addition to Resque for asynchronic processing of the background jobs created by Resque. It works like the original Resque worker, but runs inside an EventMachine and uses the same process instead of forking a new one for every job. It can run N workers inside one process, it packs all of them in Ruby fibers. The library is meant for small but IO-heavy jobs, which won't use much of CPU power in the running server.

Read the blog post Resque with EventMachine about solving our problems with this gem.

Use cases

EM::Resque is good for processing background jobs which are doing lots of IO. The evented nature of the reactor core is great when accessing third party services with HTTP or doing lots of database-intensive work. When combined with a connection pool to a SQL server it lets you easily control the amount of connections, being at the same time extremely scalable.

Overview

EM::Resque jobs are created and queued like with the synchronous version. When queued, one of the workers in the fiber pool will pick it up and process the job.

When making IO actions inside a job, it should never block the other workers. E.g. database operations etc. should be handled with libraries that support EventMachine to allow concurrent processing.

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

class Pinger
  @queue = :ping_publisher

  def self.perform(url)
    res = Result.new
    res.http_result = EventMachine::HttpRequest.new(url).get.response
    res.save
  end
end

The @queue class instance variable determines which queue Pinger 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 Pinger job on the ping_publisher queue, we might add this to our application's pre-existing Callback class:

class Callback
  def async_ping_publisher
    Resque.enqueue(Pinger, self.callback_url)
  end
end

Now when we call callback.async_ping_publisher in our application, a job will be created and placed on the ping_publisher queue.

For more use cases please refer the original Resque manual.

Let's start 100 async workers to work on ping_publisher jobs:

$ cd app_root
$ QUEUE=file_serve FIBERS=100 rake em_resque:work

This starts the EM::Resque process and loads 100 fibers with a worker inside each fiber and tells them to work off the ping_publisher queue. As soon as one of the workers is doing it's first IO action it will go to a "yield" mode to get data back from the IO and allow another one to start a new job. The event loop resumes the worker when it has some data back from the IO action.

The workers also reserve the jobs for them so the other workers won't touch them.

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.

Jobs

What should you run in the background with EM::Resque? Anything with lots of IO and which takes any time at all. Best use case is gathering data and sending pings to 3rd party services, which might or might not answer in a decent time.

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

  • Simple messaging between our frontend and backend softwares
  • Pinging publishers and affiliate networks

We're handling a tremendious amount of traffic with a bit over 100 workers, using a lot less of database connections, memory and cpu power compared to the synchronous and forking Resque or Delayed Job.

All the environment options from the original Resque work also in EM::Resque. There are also couple of more variables.

The amount of fibers

The number of fibers for the current process is set in FIBERS variable. One fiber equals one worker. They are all polling the same queue and terminated when the main process terminates. The default value is 1.

$ QUEUE=ping_publisher FIBERS=50 rake em_resque:work

Signals

EM:Resque workers respond to a few different signals:

  • QUIT / TERM / INT - Wait for workers to finish processing then exit

The Front End

EM::Resque uses the same frontend as Resque.

EM::Resque Dependencies

$ gem install bundler
$ bundle install

Installing EM::Resque

In a Rack app, as a gem

First install the gem.

$ gem install em-resque

Next include it in your application.

require 'em-resque'

Now start your application:

rackup config.ru

That's it! You can now create EM::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 'em-resque/tasks'

Now:

$ QUEUE=* FIBERS=50 rake em_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.

In a Rails 3 app, as a gem

EM::Resque is not supporting Rails with Rake at the moment. Needs more work.

To run EM::Resque with your Rails application, you need a specified script to load all the needed libraries and start the workers.

script/resque_async.rb

RAILS_ENV = ENV['RAILS_ENV'] || 'development_async'
RAILS_ROOT = Dir.pwd

require 'rubygems'
require 'yaml'
require 'uri'
require 'em-resque'
require 'em-resque/worker_machine'
require 'em-resque/task_helper'
require 'resque-retry'
require 'em-synchrony'
require 'em-synchrony/connection_pool'
require 'em-synchrony/mysql2'

Dir.glob(File.join(RAILS_ROOT, 'lib', 'async_worker', '**', '*.rb')).sort.each{|f| require File.expand_path(f)}

resque_config = YAML.load_file("#{RAILS_ROOT}/config/resque.yml")
proxy_config = YAML.load_file("#{RAILS_ROOT}/config/proxy.yml")
PROXY = proxy_config ? proxy_config[RAILS_ENV] : nil

opts = TaskHelper.parse_opts_from_env.merge(:redis => resque_config[RAILS_ENV])
EM::Resque::WorkerMachine.new(opts).start

You can start the script with the same environment variables as with the Rake task.

Now we have our own minimal ORM backed with em-powered mysql connection pool to handle our models, but there's a library in em-synchrony called em-activerecord which can be combined with async mysql2 library to handle sql connections inside the EventMachine.

Configuration

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

WorkerMachine has a redis parameter in the initializer, which can be given a string or a Redis object. This means if you're already using Redis in your app, EM::Resquec an re-use the existing connection. EM::Resque is using the non-blocking em-redis when given the host as a string. If using a Redis object, please use the non-blocking EM::Hiredis.

String: EM::Resque::WorkerMachine.new(opts.merge(:redis => 'localhost:6379'))

Redis: EM::Resque::WorkerMachine.new(opts.merge(:redis => $redis))

Namespaces

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][rs] library, which Resque uses by default to separate the keys it manages from other keys in your Redis server.

Simply use the EM::Resque.redis.namespace accessor:

EM::Resque.redis.namespace = "resque:SponsorPay"

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

Contributing

  1. Fork EM::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!

Meta

Author

Julius de Bruijn :: julius.bruijn@sponsorpay.com :: @pimeys

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