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Queue / Pipeline Management

Merge pull request #218 from seomoz/vadim/fix-log-level

fix: log_level always reported
latest commit dc70b5041c
vadim-moz vadim-moz authored

qless Build Status

Qless is a powerful Redis-based job queueing system inspired by resque, but built on a collection of Lua scripts, maintained in the qless-core repo.

Philosophy and Nomenclature

A job is a unit of work identified by a job id or jid. A queue can contain several jobs that are scheduled to be run at a certain time, several jobs that are waiting to run, and jobs that are currently running. A worker is a process on a host, identified uniquely, that asks for jobs from the queue, performs some process associated with that job, and then marks it as complete. When it's completed, it can be put into another queue.

Jobs can only be in one queue at a time. That queue is whatever queue they were last put in. So if a worker is working on a job, and you move it, the worker's request to complete the job will be ignored.

A job can be canceled, which means it disappears into the ether, and we'll never pay it any mind ever again. A job can be dropped, which is when a worker fails to heartbeat or complete the job in a timely fashion, or a job can be failed, which is when a host recognizes some systematically problematic state about the job. A worker should only fail a job if the error is likely not a transient one; otherwise, that worker should just drop it and let the system reclaim it.


  1. Jobs don't get dropped on the floor -- Sometimes workers drop jobs. Qless automatically picks them back up and gives them to another worker
  2. Tagging / Tracking -- Some jobs are more interesting than others. Track those jobs to get updates on their progress. Tag jobs with meaningful identifiers to find them quickly in the UI.
  3. Job Dependencies -- One job might need to wait for another job to complete
  4. Stats -- qless automatically keeps statistics about how long jobs wait to be processed and how long they take to be processed. Currently, we keep track of the count, mean, standard deviation, and a histogram of these times.
  5. Job data is stored temporarily -- Job info sticks around for a configurable amount of time so you can still look back on a job's history, data, etc.
  6. Priority -- Jobs with the same priority get popped in the order they were inserted; a higher priority means that it gets popped faster
  7. Retry logic -- Every job has a number of retries associated with it, which are renewed when it is put into a new queue or completed. If a job is repeatedly dropped, then it is presumed to be problematic, and is automatically failed.
  8. Web App -- With the advent of a Ruby client, there is a Sinatra-based web app that gives you control over certain operational issues
  9. Scheduled Work -- Until a job waits for a specified delay (defaults to 0), jobs cannot be popped by workers
  10. Recurring Jobs -- Scheduling's all well and good, but we also support jobs that need to recur periodically.
  11. Notifications -- Tracked jobs emit events on pubsub channels as they get completed, failed, put, popped, etc. Use these events to get notified of progress on jobs you're interested in.

Enqueing Jobs

First things first, require qless and create a client. The client accepts all the same arguments that you'd use when constructing a redis client.

require 'qless'

# Connect to localhost
client =
# Connect to somewhere else
client = => '', :port => 1234)

Jobs should be classes or modules that define a perform method, which must accept a single job argument:

class MyJobClass
  def self.perform(job)
    # job is an instance of `Qless::Job` and provides access to
    #, a means to cancel the job (job.cancel), and more.

Now you can access a queue, and add a job to that queue.

# This references a new or existing queue 'testing'
queue = client.queues['testing']
# Let's add a job, with some data. Returns Job ID
queue.put(MyJobClass, :hello => 'howdy')
# => "0c53b0404c56012f69fa482a1427ab7d"
# Now we can ask for a job
job = queue.pop
# => <Qless::Job 0c53b0404c56012f69fa482a1427ab7d (MyJobClass / testing)>
# And we can do the work associated with it!

The job data must be serializable to JSON, and it is recommended that you use a hash for it. See below for a list of the supported job options.

The argument returned by queue.put is the job ID, or jid. Every Qless job has a unique jid, and it provides a means to interact with an existing job:

# find an existing job by it's jid
job =[jid]

# Query it to find out details about it:
job.klass # => the class of the job
job.queue # => the queue the job is in  # => the data for the job
job.history # => the history of what has happened to the job sofar
job.dependencies # => the jids of other jobs that must complete before this one
job.dependents # => the jids of other jobs that depend on this one
job.priority # => the priority of this job
job.tags # => array of tags for this job
job.original_retries # => the number of times the job is allowed to be retried
job.retries_left # => the number of retries left

# You can also change the job in various ways:
job.requeue("some_other_queue") # move it to a new queue
job.cancel # cancel the job
job.tag("foo") # add a tag
job.untag("foo") # remove a tag

Running A Worker

The Qless ruby worker was heavily inspired by Resque's worker, but thanks to the power of the qless-core lua scripts, it is much simpler and you are welcome to write your own (e.g. if you'd rather save memory by not forking the worker for each job).

As with resque...

  • The worker forks a child process for each job in order to provide resilience against memory leaks. Pass the RUN_AS_SINGLE_PROCESS environment variable to force Qless to not fork the child process. Single process mode should only be used in some test/dev environments.
  • The worker updates its procline with its status so you can see what workers are doing using ps.
  • The worker registers signal handlers so that you can control it by sending it signals.
  • The worker is given a list of queues to pop jobs off of.
  • The worker logs out put based on VERBOSE or VVERBOSE (very verbose) environment variables.
  • Qless ships with a rake task (qless:work) for running workers. It runs qless:setup before starting the main work loop so that users can load their environment in that task.
  • The sleep interval (for when there is no jobs available) can be configured with the INTERVAL environment variable.

Resque uses queues for its notion of priority. In contrast, qless has priority support built-in. Thus, the worker supports two strategies for what order to pop jobs off the queues: ordered and round-robin. The ordered reserver will keep popping jobs off the first queue until it is empty, before trying to pop job off the second queue. The round-robin reserver will pop a job off the first queue, then the second queue, and so on. You could also easily implement your own.

To start a worker, write a bit of Ruby code that instantiates a worker and runs it. You could write a rake task to do this, for example:

namespace :qless do
  desc "Run a Qless worker"
  task :work do
    # Load your application code. All job classes must be loaded.
    require 'my_app/environment'

    # Require the parts of qless you need
    require 'qless'
    require 'qless/job_reservers/ordered'
    require 'qless/worker'

    # Create a client
    client = => '', :port => 1234)

    # Get the queues you use
    queues = %w[ queue_1 queue_2 ].map do |name|

    # Create a job reserver; different reservers use different
    # strategies for which order jobs are popped off of queues
    reserver =

    # Create a forking worker that uses the given reserver to pop jobs.
    worker =

    # Start the worker!

The following signals are supported in the parent process:

  • TERM: Shutdown immediately, stop processing jobs.
  • INT: Shutdown immediately, stop processing jobs.
  • QUIT: Shutdown after the current job has finished processing.
  • USR1: Kill the forked child immediately, continue processing jobs.
  • USR2: Don't process any new jobs, and dump the current backtrace.
  • CONT: Start processing jobs again after a USR2

You should send these to the master process, not the child.

The child process supports the USR2 signal, whch causes it to dump its current backtrace.

Workers also support middleware modules that can be used to inject logic before, after or around the processing of a single job in the child process. This can be useful, for example, when you need to re-establish a connection to your database in each job.

Define a module with an around_perform method that calls super where you want the job to be processed:

module ReEstablishDBConnection
  def around_perform(job)

Then, mix-it into the worker class. You can mix-in as many middleware modules as you like:

require 'qless/worker'
Qless::Worker.class_eval do
  include ReEstablishDBConnection
  include SomeOtherAwesomeMiddleware

Per-Job Middlewares

Qless also supports middleware on a per-job basis, when you have some orthogonal logic to run in the context of some (but not all) jobs.

Per-job middlewares are defined the same as worker middlewares:

module ReEstablishDBConnection
  def around_perform(job)

To add them to a job class, you first have to make your job class middleware-enabled by extending it with Qless::Job::SupportsMiddleware, then extend your middleware modules:

class MyJobClass
  extend Qless::Job::SupportsMiddleware
  extend ReEstablishDBConnection
  extend MyOtherAwesomeMiddleware

  def self.perform(job)

Note that Qless::Job::SupportsMiddleware must be extended onto your job class before any other middleware modules.

Web Interface

Qless ships with a resque-inspired web app that lets you easily deal with failures and see what it is processing. If you're project has a rack-based ruby web app, we recommend you mount Qless's web app in it. Here's how you can do that with Rack::Builder in your

client = => "some-host", :port => 7000) do
  use SomeMiddleware

  map('/some-other-app') { run }
  map('/qless')          { run }

For an app using Rails 3+, check the router documentation for how to mount rack apps.

Job Dependencies

Let's say you have one job that depends on another, but the task definitions are fundamentally different. You need to bake a turkey, and you need to make stuffing, but you can't make the turkey until the stuffing is made:

queue        = client.queues['cook']
stuffing_jid = queue.put(MakeStuffing, {:lots => 'of butter'})
turkey_jid   = queue.put(MakeTurkey  , {:with => 'stuffing'}, :depends=>[stuffing_jid])

When the stuffing job completes, the turkey job is unlocked and free to be processed.


Some jobs need to get popped sooner than others. Whether it's a trouble ticket, or debugging, you can do this pretty easily when you put a job in a queue:

queue.put(MyJobClass, {:foo => 'bar'}, :priority => 10)

What happens when you want to adjust a job's priority while it's still waiting in a queue?

job =['0c53b0404c56012f69fa482a1427ab7d']
job.priority = 10
# Now this will get popped before any job of lower priority

Scheduled Jobs

If you don't want a job to be run right away but some time in the future, you can specify a delay:

# Run at least 10 minutes from now
queue.put(MyJobClass, {:foo => 'bar'}, :delay => 600)

This doesn't guarantee that job will be run exactly at 10 minutes. You can accomplish this by changing the job's priority so that once 10 minutes has elapsed, it's put before lesser-priority jobs:

# Run in 10 minutes
queue.put(MyJobClass, {:foo => 'bar'}, :delay => 600, :priority => 100)

Recurring Jobs

Sometimes it's not enough simply to schedule one job, but you want to run jobs regularly. In particular, maybe you have some batch operation that needs to get run once an hour and you don't care what worker runs it. Recurring jobs are specified much like other jobs:

# Run every hour
queue.recur(MyJobClass, {:widget => 'warble'}, 3600)
# => 22ac75008a8011e182b24cf9ab3a8f3b

You can even access them in much the same way as you would normal jobs:

job =['22ac75008a8011e182b24cf9ab3a8f3b']
# => < Qless::RecurringJob 22ac75008a8011e182b24cf9ab3a8f3b >

Changing the interval at which it runs after the fact is trivial:

# I think I only need it to run once every two hours
job.interval = 7200

If you want it to run every hour on the hour, but it's 2:37 right now, you can specify an offset which is how long it should wait before popping the first job:

# 23 minutes of waiting until it should go
queue.recur(MyJobClass, {:howdy => 'hello'}, 3600, :offset => 23 * 60)

Recurring jobs also have priority, a configurable number of retries, and tags. These settings don't apply to the recurring jobs, but rather the jobs that they create. In the case where more than one interval passes before a worker tries to pop the job, more than one job is created. The thinking is that while it's completely client-managed, the state should not be dependent on how often workers are trying to pop jobs.

  # Recur every minute
  queue.recur(MyJobClass, {:lots => 'of jobs'}, 60)
  # Wait 5 minutes
  # => 5 jobs got popped

Configuration Options

You can get and set global (read: in the context of the same Redis instance) configuration to change the behavior for heartbeating, and so forth. There aren't a tremendous number of configuration options, but an important one is how long job data is kept around. Job data is expired after it has been completed for jobs-history seconds, but is limited to the last jobs-history-count completed jobs. These default to 50k jobs, and 30 days, but depending on volume, your needs may change. To only keep the last 500 jobs for up to 7 days:

client.config['jobs-history'] = 7 * 86400
client.config['jobs-history-count'] = 500

Tagging / Tracking

In qless, 'tracking' means flagging a job as important. Tracked jobs have a tab reserved for them in the web interface, and they also emit subscribable events as they make progress (more on that below). You can flag a job from the web interface, or the corresponding code:['b1882e009a3d11e192d0b174d751779d'].track

Jobs can be tagged with strings which are indexed for quick searches. For example, jobs might be associated with customer accounts, or some other key that makes sense for your project.

queue.put(MyJobClass, {:tags => 'aplenty'}, :tags => ['12345', 'foo', 'bar'])

This makes them searchable in the web interface, or from code:

jids ='foo')

You can add or remove tags at will, too:

job =['b1882e009a3d11e192d0b174d751779d']
job.tag('howdy', 'hello')
job.untag('foo', 'bar')


Tracked jobs emit events on specific pubsub channels as things happen to them. Whether it's getting popped off of a queue, completed by a worker, etc. A good example of how to make use of this is in the qless-campfire or qless-growl. The jist of it goes like this, though: do |on|
  on.canceled  { |jid| puts "#{jid} canceled"   }
  on.stalled   { |jid| puts "#{jid} stalled"    }
  on.track     { |jid| puts "tracking #{jid}"   }
  on.untrack   { |jid| puts "untracking #{jid}" }
  on.completed { |jid| puts "#{jid} completed"  }
  on.failed    { |jid| puts "#{jid} failed"     }
  on.popped    { |jid| puts "#{jid} popped"     }
  on.put       { |jid| puts "#{jid} put"        }

Those familiar with redis pubsub will note that a redis connection can only be used for pubsub-y commands once listening. For this reason, invoking actually creates a second connection so that client can still be used as it normally would be: do |on|
  on.failed do |jid|
  puts "#{jid} failed in #{[jid].queue_name}"


When a worker is given a job, it is given an exclusive lock to that job. That means that job won't be given to any other worker, so long as the worker checks in with progress on the job. By default, jobs have to either report back progress every 60 seconds, or complete it, but that's a configurable option. For longer jobs, this may not make sense.

# Hooray! We've got a piece of work!
job = queue.pop
# How long until I have to check in?
# => 59
# Hey! I'm still working on it!
# => 1331326141.0
# Ok, I've got some more time. Oh! Now I'm done!

If you want to increase the heartbeat in all queues,

# Now jobs get 10 minutes to check in
client.config['heartbeat'] = 600
# But the testing queue doesn't get as long.
client.queues['testing'].heartbeat = 300

When choosing a heartbeat interval, realize that this is the amount of time that can pass before qless realizes if a job has been dropped. At the same time, you don't want to burden qless with heartbeating every 10 seconds if your job is expected to take several hours.

An idiom you're encouraged to use for long-running jobs that want to check in their progress periodically:

# Wait until we have 5 minutes left on the heartbeat, and if we find that
# we've lost our lock on a job, then honorably fall on our sword
if (job.ttl < 300) && !job.heartbeat
  return / die / exit


One nice feature of qless is that you can get statistics about usage. Stats are aggregated by day, so when you want stats about a queue, you need to say what queue and what day you're talking about. By default, you just get the stats for today. These stats include information about the mean job wait time, standard deviation, and histogram. This same data is also provided for job completion:

# So, how're we doing today?
stats = client.stats.get('testing')
# => { 'run' => {'mean' => ..., }, 'wait' => {'mean' => ..., }}


It's important to note that Redis doesn't allow access to the system time if you're going to be making any manipulations to data (which our scripts do). And yet, we have heartbeating. This means that the clients actually send the current time when making most requests, and for consistency's sake, means that your workers must be relatively synchronized. This doesn't mean down to the tens of milliseconds, but if you're experiencing appreciable clock drift, you should investigate NTP. For what it's worth, this hasn't been a problem for us, but most of our jobs have heartbeat intervals of 30 minutes or more.

Ensuring Job Uniqueness

As mentioned above, Jobs are uniquely identied by an id--their jid. Qless will generate a UUID for each enqueued job or you can specify one manually:

queue.put(MyJobClass, { :hello => 'howdy' }, :jid => 'my-job-jid')

This can be useful when you want to ensure a job's uniqueness: simply create a jid that is a function of the Job's class and data, it'll guaranteed that Qless won't have multiple jobs with the same class and data.

Setting Default Job Options

Qless::Queue#put accepts a number of job options (see above for their semantics):

  • jid
  • delay
  • priority
  • tags
  • retries
  • depends

When enqueueing the same kind of job with the same args in multiple places it's a pain to have to declare the job options every time. Instead, you can define default job options directly on the job class:

class MyJobClass
  def self.default_job_options(data)
    { :priority => 10, :delay => 100 }

queue.put(MyJobClass, { :some => "data" }, :delay => 10)

Individual jobs can still specify options, so in this example, the job would be enqueued with a priority of 10 and a delay of 10.

Testing Jobs

When unit testing your jobs, you will probably want to avoid the overhead of round-tripping them through redis. You can of course use a mock job object and pass it to your job class's perform method. Alternately, if you want a real full-fledged Qless::Job instance without round-tripping it through Redis, use

describe MyJobClass do
  let(:client) { }
  let(:job)    {, MyJobClass, :data => { "some" => "data" }) }

  it 'does something' do
    # make an assertion about what happened

The options hash passed to supports all the same options a normal job supports. See the source for a full list.


To bootstrap an environment, first have a redis.

Have rvm or rbenv. Then to install the dependencies:

rbenv install                 # rbenv only.  Install bundler if you need it.
bundle install
./exe/install_phantomjs       # Bring in phantomjs 1.7.0 for tests.
rbenv rehash                  # rbenv only
git submodule init
git submodule update
bundle exec rake core:build

To run the tests:

bundle exec rake spec

The locally installed redis will be flushed before and after each test run.

To change the redis instance used in tests, put the connection information into ./spec/redis.config.yml.

To contribute, fork the repo, use feature branches, run the tests and open PRs.

Mailing List

For questions and general Qless discussion, please join the Qless Mailing list.

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