Please see e.g. Bull as an alternative. Thank you!
Kue is a priority job queue backed by redis, built for node.js.
PROTIP This is the latest Kue documentation, make sure to also read the changelist.
-
Latest release:
$ npm install kue
-
Master branch:
$ npm install http://github.com/Automattic/kue/tarball/master
- Delayed jobs
- Distribution of parallel work load
- Job event and progress pubsub
- Job TTL
- Optional retries with backoff
- Graceful workers shutdown
- Full-text search capabilities
- RESTful JSON API
- Rich integrated UI
- Infinite scrolling
- UI progress indication
- Job specific logging
- Powered by Redis
- Creating Jobs
- Jobs Priority
- Failure Attempts
- Failure Backoff
- Job TTL
- Job Logs
- Job Progress
- Job Events
- Queue Events
- Delayed Jobs
- Processing Jobs
- Processing Concurrency
- Pause Processing
- Updating Progress
- Graceful Shutdown
- Error Handling
- Queue Maintenance
- Redis Connection Settings
- User-Interface
- JSON API
- Parallel Processing With Cluster
- Securing Kue
- Testing
- Screencasts
- License
First create a job Queue
with kue.createQueue()
:
var kue = require('kue')
, queue = kue.createQueue();
Calling queue.create()
with the type of job ("email"), and arbitrary job data will return a Job
, which can then be save()
ed, adding it to redis, with a default priority level of "normal". The save()
method optionally accepts a callback, responding with an error
if something goes wrong. The title
key is special-cased, and will display in the job listings within the UI, making it easier to find a specific job.
var job = queue.create('email', {
title: 'welcome email for tj'
, to: 'tj@learnboost.com'
, template: 'welcome-email'
}).save( function(err){
if( !err ) console.log( job.id );
});
To specify the priority of a job, simply invoke the priority()
method with a number, or priority name, which is mapped to a number.
queue.create('email', {
title: 'welcome email for tj'
, to: 'tj@learnboost.com'
, template: 'welcome-email'
}).priority('high').save();
The default priority map is as follows:
{
low: 10
, normal: 0
, medium: -5
, high: -10
, critical: -15
};
By default jobs only have one attempt, that is when they fail, they are marked as a failure, and remain that way until you intervene. However, Kue allows you to specify this, which is important for jobs such as transferring an email, which upon failure, may usually retry without issue. To do this invoke the .attempts()
method with a number.
queue.create('email', {
title: 'welcome email for tj'
, to: 'tj@learnboost.com'
, template: 'welcome-email'
}).priority('high').attempts(5).save();
Job retry attempts are done as soon as they fail, with no delay, even if your job had a delay set via Job#delay
. If you want to delay job re-attempts upon failures (known as backoff) you can use Job#backoff
method in different ways:
// Honor job's original delay (if set) at each attempt, defaults to fixed backoff
job.attempts(3).backoff( true )
// Override delay value, fixed backoff
job.attempts(3).backoff( {delay: 60*1000, type:'fixed'} )
// Enable exponential backoff using original delay (if set)
job.attempts(3).backoff( {type:'exponential'} )
// Use a function to get a customized next attempt delay value
job.attempts(3).backoff( function( attempts, delay ){
//attempts will correspond to the nth attempt failure so it will start with 0
//delay will be the amount of the last delay, not the initial delay unless attempts === 0
return my_customized_calculated_delay;
})
In the last scenario, provided function will be executed (via eval) on each re-attempt to get next attempt delay value, meaning that you can't reference external/context variables within it.
Job producers can set an expiry value for the time their job can live in active state, so that if workers didn't reply in timely fashion, Kue will fail it with TTL exceeded
error message preventing that job from being stuck in active state and spoiling concurrency.
queue.create('email', {title: 'email job with TTL'}).ttl(milliseconds).save();
Job-specific logs enable you to expose information to the UI at any point in the job's life-time. To do so simply invoke job.log()
, which accepts a message string as well as variable-arguments for sprintf-like support:
job.log('$%d sent to %s', amount, user.name);
or anything else (uses util.inspect() internally):
job.log({key: 'some key', value: 10});
job.log([1,2,3,5,8]);
job.log(10.1);
Job progress is extremely useful for long-running jobs such as video conversion. To update the job's progress simply invoke job.progress(completed, total [, data])
:
job.progress(frames, totalFrames);
data can be used to pass extra information about the job. For example a message or an object with some extra contextual data to the current status.
Job-specific events are fired on the Job
instances via Redis pubsub. The following events are currently supported:
enqueue
the job is now queuedstart
the job is now runningpromotion
the job is promoted from delayed state to queuedprogress
the job's progress ranging from 0-100failed attempt
the job has failed, but has remaining attempts yetfailed
the job has failed and has no remaining attemptscomplete
the job has completedremove
the job has been removed
For example this may look something like the following:
var job = queue.create('video conversion', {
title: 'converting loki\'s to avi'
, user: 1
, frames: 200
});
job.on('complete', function(result){
console.log('Job completed with data ', result);
}).on('failed attempt', function(errorMessage, doneAttempts){
console.log('Job failed');
}).on('failed', function(errorMessage){
console.log('Job failed');
}).on('progress', function(progress, data){
console.log('\r job #' + job.id + ' ' + progress + '% complete with data ', data );
});
Note that Job level events are not guaranteed to be received upon process restarts, since restarted node.js process will lose the reference to the specific Job object. If you want a more reliable event handler look for Queue Events.
Note Kue stores job objects in memory until they are complete/failed to be able to emit events on them. If you have a huge concurrency in uncompleted jobs, turn this feature off and use queue level events for better memory scaling.
kue.createQueue({jobEvents: false})
Alternatively, you can use the job level function events
to control whether events are fired for a job at the job level.
var job = queue.create('test').events(false).save();
Queue-level events provide access to the job-level events previously mentioned, however scoped to the Queue
instance to apply logic at a "global" level. An example of this is removing completed jobs:
queue.on('job enqueue', function(id, type){
console.log( 'Job %s got queued of type %s', id, type );
}).on('job complete', function(id, result){
kue.Job.get(id, function(err, job){
if (err) return;
job.remove(function(err){
if (err) throw err;
console.log('removed completed job #%d', job.id);
});
});
});
The events available are the same as mentioned in "Job Events", however prefixed with "job ".
Delayed jobs may be scheduled to be queued for an arbitrary distance in time by invoking the .delay(ms)
method, passing the number of milliseconds relative to now. Alternatively, you can pass a JavaScript Date
object with a specific time in the future.
This automatically flags the Job
as "delayed".
var email = queue.create('email', {
title: 'Account renewal required'
, to: 'tj@learnboost.com'
, template: 'renewal-email'
}).delay(milliseconds)
.priority('high')
.save();
Kue will check the delayed jobs with a timer, promoting them if the scheduled delay has been exceeded, defaulting to a check of top 1000 jobs every second.
Processing jobs is simple with Kue. First create a Queue
instance much like we do for creating jobs, providing us access to redis etc, then invoke queue.process()
with the associated type.
Note that unlike what the name createQueue
suggests, it currently returns a singleton Queue
instance. So you can configure and use only a single Queue
object within your node.js process.
In the following example we pass the callback done
to email
, When an error occurs we invoke done(err)
to tell Kue something happened, otherwise we invoke done()
only when the job is complete. If this function responds with an error it will be displayed in the UI and the job will be marked as a failure. The error object passed to done, should be of standard type Error
.
var kue = require('kue')
, queue = kue.createQueue();
queue.process('email', function(job, done){
email(job.data.to, done);
});
function email(address, done) {
if(!isValidEmail(address)) {
//done('invalid to address') is possible but discouraged
return done(new Error('invalid to address'));
}
// email send stuff...
done();
}
Workers can also pass job result as the second parameter to done done(null,result)
to store that in Job.result
key. result
is also passed through complete
event handlers so that job producers can receive it if they like to.
By default a call to queue.process()
will only accept one job at a time for processing. For small tasks like sending emails this is not ideal, so we may specify the maximum active jobs for this type by passing a number:
queue.process('email', 20, function(job, done){
// ...
});
Workers can temporarily pause and resume their activity. That is, after calling pause
they will receive no jobs in their process callback until resume
is called. The pause
function gracefully shutdowns this worker, and uses the same internal functionality as the shutdown
method in Graceful Shutdown.
queue.process('email', function(job, ctx, done){
ctx.pause( 5000, function(err){
console.log("Worker is paused... ");
setTimeout( function(){ ctx.resume(); }, 10000 );
});
});
Note The ctx
parameter from Kue >=0.9.0
is the second argument of the process callback function and done
is idiomatically always the last
Note The pause
method signature is changed from Kue >=0.9.0
to move the callback function to the last.
For a "real" example, let's say we need to compile a PDF from numerous slides with node-canvas. Our job may consist of the following data, note that in general you should not store large data in the job it-self, it's better to store references like ids, pulling them in while processing.
queue.create('slideshow pdf', {
title: user.name + "'s slideshow"
, slides: [...] // keys to data stored in redis, mongodb, or some other store
});
We can access this same arbitrary data within a separate process while processing, via the job.data
property. In the example we render each slide one-by-one, updating the job's log and progress.
queue.process('slideshow pdf', 5, function(job, done){
var slides = job.data.slides
, len = slides.length;
function next(i) {
var slide = slides[i]; // pretend we did a query on this slide id ;)
job.log('rendering %dx%d slide', slide.width, slide.height);
renderSlide(slide, function(err){
if (err) return done(err);
job.progress(i, len, {nextSlide : i == len ? 'itsdone' : i + 1});
if (i == len) done()
else next(i + 1);
});
}
next(0);
});
Queue#shutdown([timeout,] fn)
signals all workers to stop processing after their current active job is done. Workers will wait timeout
milliseconds for their active job's done to be called or mark the active job failed
with shutdown error reason. When all workers tell Kue they are stopped fn
is called.
var queue = require('kue').createQueue();
process.once( 'SIGTERM', function ( sig ) {
queue.shutdown( 5000, function(err) {
console.log( 'Kue shutdown: ', err||'' );
process.exit( 0 );
});
});
Note that shutdown
method signature is changed from Kue >=0.9.0
to move the callback function to the last.
All errors either in Redis client library or Queue are emitted to the Queue
object. You should bind to error
events to prevent uncaught exceptions or debug kue errors.
var queue = require('kue').createQueue();
queue.on( 'error', function( err ) {
console.log( 'Oops... ', err );
});
Kue marks a job complete/failed when done
is called by your worker, so you should use proper error handling to prevent uncaught exceptions in your worker's code and node.js process exiting before in handle jobs get done.
This can be achieved in two ways:
- Wrapping your worker's process function in Domains
queue.process('my-error-prone-task', function(job, done){
var domain = require('domain').create();
domain.on('error', function(err){
done(err);
});
domain.run(function(){ // your process function
throw new Error( 'bad things happen' );
done();
});
});
Notice - Domains are deprecated from Nodejs with stability 0 and it's not recommended to use.
This is the softest and best solution, however is not built-in with Kue. Please refer to this discussion. You can comment on this feature in the related open Kue issue.
You can also use promises to do something like
queue.process('my-error-prone-task', function(job, done){
Promise.method( function(){ // your process function
throw new Error( 'bad things happen' );
})().nodeify(done)
});
but this won't catch exceptions in your async call stack as domains do.
- Binding to
uncaughtException
and gracefully shutting down the Kue, however this is not a recommended error handling idiom in javascript since you are losing the error context.
process.once( 'uncaughtException', function(err){
console.error( 'Something bad happened: ', err );
queue.shutdown( 1000, function(err2){
console.error( 'Kue shutdown result: ', err2 || 'OK' );
process.exit( 0 );
});
});
Kue currently uses client side job state management and when redis crashes in the middle of that operations, some stuck jobs or index inconsistencies will happen. The consequence is that certain number of jobs will be stuck, and be pulled out by worker only when new jobs are created, if no more new jobs are created, they stuck forever. So we strongly suggest that you run watchdog to fix this issue by calling:
queue.watchStuckJobs(interval)
interval
is in milliseconds and defaults to 1000ms
Kue will be refactored to fully atomic job state management from version 1.0 and this will happen by lua scripts and/or BRPOPLPUSH combination. You can read more here and here.
Queue object has two type of methods to tell you about the number of jobs in each state
queue.inactiveCount( function( err, total ) { // others are activeCount, completeCount, failedCount, delayedCount
if( total > 100000 ) {
console.log( 'We need some back pressure here' );
}
});
you can also query on an specific job type:
queue.failedCount( 'my-critical-job', function( err, total ) {
if( total > 10000 ) {
console.log( 'This is tOoOo bad' );
}
});
and iterating over job ids
queue.inactive( function( err, ids ) { // others are active, complete, failed, delayed
// you may want to fetch each id to get the Job object out of it...
});
however the second one doesn't scale to large deployments, there you can use more specific Job
static methods:
kue.Job.rangeByState( 'failed', 0, n, 'asc', function( err, jobs ) {
// you have an array of maximum n Job objects here
});
or
kue.Job.rangeByType( 'my-job-type', 'failed', 0, n, 'asc', function( err, jobs ) {
// you have an array of maximum n Job objects here
});
Note that the last two methods are subject to change in later Kue versions.
If you did none of above in Error Handling section or your process lost active jobs in any way, you can recover from them when your process is restarted. A blind logic would be to re-queue all stuck jobs:
queue.active( function( err, ids ) {
ids.forEach( function( id ) {
kue.Job.get( id, function( err, job ) {
// Your application should check if job is a stuck one
job.inactive();
});
});
});
Note in a clustered deployment your application should be aware not to involve a job that is valid, currently inprocess by other workers.
Jobs data and search indexes eat up redis memory space, so you will need some job-keeping process in real world deployments. Your first chance is using automatic job removal on completion.
queue.create( ... ).removeOnComplete( true ).save()
But if you eventually/temporally need completed job data, you can setup an on-demand job removal script like below to remove top n
completed jobs:
kue.Job.rangeByState( 'complete', 0, n, 'asc', function( err, jobs ) {
jobs.forEach( function( job ) {
job.remove( function(){
console.log( 'removed ', job.id );
});
});
});
Note that you should provide enough time for .remove
calls on each job object to complete before your process exits, or job indexes will leak
By default, Kue will connect to Redis using the client default settings (port defaults to 6379
, host defaults to 127.0.0.1
, prefix defaults to q
). Queue#createQueue(options)
accepts redis connection options in options.redis
key.
var kue = require('kue');
var q = kue.createQueue({
prefix: 'q',
redis: {
port: 1234,
host: '10.0.50.20',
auth: 'password',
db: 3, // if provided select a non-default redis db
options: {
// see https://github.com/mranney/node_redis#rediscreateclient
}
}
});
prefix
controls the key names used in Redis. By default, this is simply q
. Prefix generally shouldn't be changed unless you need to use one Redis instance for multiple apps. It can also be useful for providing an isolated testbed across your main application.
You can also specify the connection information as a URL string.
var q = kue.createQueue({
redis: 'redis://example.com:1234?redis_option=value&redis_option=value'
});
Since node_redis supports Unix Domain Sockets, you can also tell Kue to do so. See unix-domain-socket for your redis server configuration.
var kue = require('kue');
var q = kue.createQueue({
prefix: 'q',
redis: {
socket: '/data/sockets/redis.sock',
auth: 'password',
options: {
// see https://github.com/mranney/node_redis#rediscreateclient
}
}
});
Any node.js redis client library that conforms (or when adapted) to node_redis API can be injected into Kue. You should only provide a createClientFactory
function as a redis connection factory instead of providing node_redis connection options.
Below is a sample code to enable redis-sentinel to connect to Redis Sentinel for automatic master/slave failover.
var kue = require('kue');
var Sentinel = require('redis-sentinel');
var endpoints = [
{host: '192.168.1.10', port: 6379},
{host: '192.168.1.11', port: 6379}
];
var opts = options || {}; // Standard node_redis client options
var masterName = 'mymaster';
var sentinel = Sentinel.Sentinel(endpoints);
var q = kue.createQueue({
redis: {
createClientFactory: function(){
return sentinel.createClient(masterName, opts);
}
}
});
Note that all <0.8.x
client codes should be refactored to pass redis options to Queue#createQueue
instead of monkey patched style overriding of redis#createClient
or they will be broken from Kue 0.8.x
.
var Redis = require('ioredis');
var kue = require('kue');
// using https://github.com/72squared/vagrant-redis-cluster
var queue = kue.createQueue({
redis: {
createClientFactory: function () {
return new Redis.Cluster([{
port: 7000
}, {
port: 7001
}]);
}
}
});
The UI is a small Express application.
A script is provided in bin/
for running the interface as a standalone application
with default settings. You may pass in options for the port, redis-url, and prefix. For example:
node_modules/kue/bin/kue-dashboard -p 3050 -r redis://127.0.0.1:3000 -q prefix
You can fire it up from within another application too:
var kue = require('kue');
kue.createQueue(...);
kue.app.listen(3000);
The title defaults to "Kue", to alter this invoke:
kue.app.set('title', 'My Application');
Note that if you are using non-default Kue options, kue.createQueue(...)
must be called before accessing kue.app
.
You can also use Kue-UI web interface contributed by Arnaud Bénard
Along with the UI Kue also exposes a JSON API, which is utilized by the UI.
Query jobs, for example "GET /job/search?q=avi video":
["5", "7", "10"]
By default kue indexes the whole Job data object for searching, but this can be customized via calling Job#searchKeys
to tell kue which keys on Job data to create index for:
var kue = require('kue');
queue = kue.createQueue();
queue.create('email', {
title: 'welcome email for tj'
, to: 'tj@learnboost.com'
, template: 'welcome-email'
}).searchKeys( ['to', 'title'] ).save();
Search feature is turned off by default from Kue >=0.9.0
. Read more about this here. You should enable search indexes and add reds in your dependencies if you need to:
var kue = require('kue');
q = kue.createQueue({
disableSearch: false
});
npm install reds --save
Currently responds with state counts, and worker activity time in milliseconds:
{"inactiveCount":4,"completeCount":69,"activeCount":2,"failedCount":0,"workTime":20892}
Get a job by :id
:
{"id":"3","type":"email","data":{"title":"welcome email for tj","to":"tj@learnboost.com","template":"welcome-email"},"priority":-10,"progress":"100","state":"complete","attempts":null,"created_at":"1309973155248","updated_at":"1309973155248","duration":"15002"}
Get job :id
's log:
['foo', 'bar', 'baz']
Get jobs with the specified range :from
to :to
, for example "/jobs/0..2", where :order
may be "asc" or "desc":
[{"id":"12","type":"email","data":{"title":"welcome email for tj","to":"tj@learnboost.com","template":"welcome-email"},"priority":-10,"progress":0,"state":"active","attempts":null,"created_at":"1309973299293","updated_at":"1309973299293"},{"id":"130","type":"email","data":{"title":"welcome email for tj","to":"tj@learnboost.com","template":"welcome-email"},"priority":-10,"progress":0,"state":"active","attempts":null,"created_at":"1309975157291","updated_at":"1309975157291"}]
Same as above, restricting by :state
which is one of:
- active
- inactive
- failed
- complete
Same as above, however restricted to :type
and :state
.
Delete job :id
:
$ curl -X DELETE http://local:3000/job/2
{"message":"job 2 removed"}
Create a job:
$ curl -H "Content-Type: application/json" -X POST -d \
'{
"type": "email",
"data": {
"title": "welcome email for tj",
"to": "tj@learnboost.com",
"template": "welcome-email"
},
"options" : {
"attempts": 5,
"priority": "high"
}
}' http://localhost:3000/job
{"message": "job created", "id": 3}
You can create multiple jobs at once by passing an array. In this case, the response will be an array too, preserving the order:
$ curl -H "Content-Type: application/json" -X POST -d \
'[{
"type": "email",
"data": {
"title": "welcome email for tj",
"to": "tj@learnboost.com",
"template": "welcome-email"
},
"options" : {
"attempts": 5,
"priority": "high"
}
},
{
"type": "email",
"data": {
"title": "followup email for tj",
"to": "tj@learnboost.com",
"template": "followup-email"
},
"options" : {
"delay": 86400,
"attempts": 5,
"priority": "high"
}
}]' http://localhost:3000/job
[
{"message": "job created", "id": 4},
{"message": "job created", "id": 5}
]
Note: when inserting multiple jobs in bulk, if one insertion fails Kue will keep processing the remaining jobs in order. The response array will contain the ids of the jobs added successfully, and any failed element will be an object describing the error: {"error": "error reason"}
.
The example below shows how you may use Cluster to spread the job processing load across CPUs. Please see Cluster module's documentation for more detailed examples on using it.
When cluster .isMaster
the file is being executed in context of the master process, in which case you may perform tasks that you only want once, such as starting the web app bundled with Kue. The logic in the else
block is executed per worker.
var kue = require('kue')
, cluster = require('cluster')
, queue = kue.createQueue();
var clusterWorkerSize = require('os').cpus().length;
if (cluster.isMaster) {
kue.app.listen(3000);
for (var i = 0; i < clusterWorkerSize; i++) {
cluster.fork();
}
} else {
queue.process('email', 10, function(job, done){
var pending = 5
, total = pending;
var interval = setInterval(function(){
job.log('sending!');
job.progress(total - pending, total);
--pending || done();
pending || clearInterval(interval);
}, 1000);
});
}
This will create an email
job processor (worker) per each of your machine CPU cores, with each you can handle 10 concurrent email jobs, leading to total 10 * N
concurrent email jobs processed in your N
core machine.
Now when you visit Kue's UI in the browser you'll see that jobs are being processed roughly N
times faster! (if you have N
cores).
Through the use of app mounting you may customize the web application, enabling TLS, or adding additional middleware like basic-auth-connect
.
$ npm install --save basic-auth-connect
var basicAuth = require('basic-auth-connect');
var app = express.createServer({ ... tls options ... });
app.use(basicAuth('foo', 'bar'));
app.use(kue.app);
app.listen(3000);
Enable test mode to push all jobs into a jobs
array. Make assertions against
the jobs in that array to ensure code under test is correctly enqueuing jobs.
queue = require('kue').createQueue();
before(function() {
queue.testMode.enter();
});
afterEach(function() {
queue.testMode.clear();
});
after(function() {
queue.testMode.exit()
});
it('does something cool', function() {
queue.createJob('myJob', { foo: 'bar' }).save();
queue.createJob('anotherJob', { baz: 'bip' }).save();
expect(queue.testMode.jobs.length).to.equal(2);
expect(queue.testMode.jobs[0].type).to.equal('myJob');
expect(queue.testMode.jobs[0].data).to.eql({ foo: 'bar' });
});
IMPORTANT: By default jobs aren't processed when created during test mode. You can enable job processing by passing true to testMode.enter
before(function() {
queue.testMode.enter(true);
});
- Introduction to Kue
- API walkthrough to Kue
We love contributions!
When contributing, follow the simple rules:
- Don't violate DRY principles.
- Boy Scout Rule needs to have been applied.
- Your code should look like all the other code – this project should look like it was written by one person, always.
- If you want to propose something – just create an issue and describe your question with as much description as you can.
- If you think you have some general improvement, consider creating a pull request with it.
- If you add new code, it should be covered by tests. No tests – no code.
- If you add a new feature, don't forget to update the documentation for it.
- If you find a bug (or at least you think it is a bug), create an issue with the library version and test case that we can run and see what are you talking about, or at least full steps by which we can reproduce it.
(The MIT License)
Copyright (c) 2011 LearnBoost <tj@learnboost.com>
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the 'Software'), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
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