A persistent and flexible background jobs library for go.

Jobs is powered by Redis and supports the following features:

• A job can encapsulate any arbitrary functionality. A job can do anything which can be done in a go function.
• A job can be one-off (only executed once) or recurring (scheduled to execute at a specific interval).
• A job can be retried a specified number of times if it fails.
• A job is persistent, with protections against power loss and other worst case scenarios. (See the Guarantees section below)
• Work on jobs can be spread amongst any number of concurrent workers across any number of machines.
• Provided it is persisted to disk, every job will be executed at least once, and in ideal network conditions will be executed exactly once. (See the Guarantees section below)
• You can query the database to find out e.g. the number of jobs that are currently executing or how long a particular job took to execute.
• Any job that permanently fails will have its error captured and stored.

Jobs is intended to be used in web applications. It is useful for cases where you need to execute some long-running code, but you don't want your users to wait for the code to execute before rendering a response. A good example is sending a welcome email to your users after they sign up. You can use Jobs to schedule the email to be sent asynchronously, and render a response to your user without waiting for the email to be sent. You could use a goroutine to accomplish the same thing, but in the event of a server restart or power loss, the email might never be sent. Jobs guarantees that the email will be sent at some time and allows you to spread the work between different machines.

Jobs is being actively developed and is well-tested. However, since it is still a young library, it is not recommended for use in mission-critical production applications at this time. It is probably fine to use for low-traffic hobby sites, and in fact we encourage its use in those settings to help polish the API and find missing features and hidden bugs. Pull requests and issue reports are much appreciated :)

Jobs follows semantic versioning but offers no guarantees of backwards compatibility until version 1.0. Keep in mind that breaking changes might occur. We will do our best to make the community aware of any non-trivial breaking changes beforehand.

Jobs requires Go version >= 1.2. If you do not already have it, follow these instructions:

• Install Go
• Follow the instructions for setting up your go workspace

Jobs requires access to a Redis database. If you plan to have multiple worker pools spread out across different machines, they should all connect to the same Redis database. If you only want to run one worker pool, it is safe to install Redis locally and run it on the same machine. In either case, if you need to install Redis, follow these instructions:

• Install Redis.
• Follow the instructions in the section called Installing Redis more properly.
• Make sure you understand how Redis Persistence works and have edited your config file to get your desired persistence. We recommend using both RDB and AOF and setting fsync to either "always" or "everysec".

After that, you can install Jobs like you would any other go package: go get github.com/albrow/jobs. If you want to update the package later, use go get -u github.com/albrow/jobs. Then you can import Jobs like you would any other go package by adding import github.com/albrow/jobs to your go source file.

You can configure the connection to Redis by editing Config.Db. Here are the options:

• Address is the address of the redis database to connect to. Default is "localhost:6379".
• Network is the type of network to use to connect to the redis database Default is "tcp".
• Database is the redis database number to use for storing all data. Default is 0.
• Password is a password to use for connecting to a redis database via the AUTH command. If empty, Jobs will not attempt to authenticate. Default is "" (an empty string).

You should edit Config.Db during program initialization, before running Pool.Start or scheduling any jobs. Here's an example of how to configure Jobs to use databse #10 and authenticate with the password "foobar":

func main() {
	// Configure database options at the start of your application
	jobs.Config.Db.Database = 10
	jobs.Config.Db.Password = "foobar"
}

Jobs must be organized into discrete types. Here's an example of how to register a job which sends a welcome email to users:

// We'll specify that we want the job to be retried 3 times before finally failing
welcomeEmailJobs, err := jobs.RegisterType("welcomeEmail", 3, func(user *User) error {
	msg := fmt.Sprintf("Hello, %s! Thanks for signing up for foo.com.", user.Name)
	if err := emails.Send(user.EmailAddress, msg); err != nil {
		// The returned error will be captured by a worker, which will then log the error
		// in the database and trigger up to 3 retries.
		return err
	}
})

The final argument to the RegisterType function is a HandlerFunc which will be executed when the job runs. HandlerFunc must be a function which accepts either zero or one arguments and returns an error.

After registering a job type, you can schedule a job using the Schedule or ScheduleRecurring methods like so:

// The priority argument lets you choose how important the job is. Higher
// priority jobs will be executed first.
job, err := welcomeEmailJobs.Schedule(100, time.Now(), &User{EmailAddress: "[email protected]"})
if err != nil {
	// Handle err
}

You can use the Job object returned by Schedule or ScheduleRecurring to check on the status of the job or cancel it manually.

You can schedule any number of worker pools across any number of machines, provided every machine agrees on the definition of the job types. If you want, you can start a worker pool on the same machines that are scheduling jobs, or you can have each worker pool running on a designated machine. Since each pool is assigned an id based on a unique hardware identifier, you must only run one worker pool per machine.

To create a new pool with the default configuration, just pass in nil:

pool, err := jobs.NewPool(nil)
if err != nil {
	// Handle err
}

You can also specify a different configuration by passing in *PoolConfig. Any zero values in the config you pass in will fallback to the default values. So here's how you could start a pool with 10 workers and a batch size of 10, while letting the other options remain the default.

pool, err := jobs.NewPool(&jobs.PoolConfig{
	NumWorkers: 10,
	BatchSize: 10,
})
if err != nil {
	// Handle err
}

After you have created a pool, you can start it with the Start method. Once started, the pool will continuously query the database for new jobs and delegate those jobs to workers. Any program that calls Pool.Start() should also wait for the workers to finish before exiting. You can do so by wrapping Close and Wait in a defer statement. Typical usage looks something like this:

func main() {
	pool, err := jobs.NewPool(nil)
	if err != nil {
		// Handle err
	}
	defer func() {
		pool.Close()
		if err := pool.Wait(); err != nil {
			// Handle err
		}
	}()
	if err := pool.Start(); err != nil {
		// Handle err
	}
}

You can also call Close and Wait at any time to manually stop the pool from executing new jobs. In this case, any jobs that are currently being executed will still finish.

To run the tests, make sure you have Redis running and accepting unix socket connections on the address /tmp/redis.sock. The tests will use database #14. WARNING: After each test is run, database #14 will be completely erased, so make sure you do not have any important data stored there.

To run the tests just run go test . If anything fails, please report an issue and describe what happened.

See Contributing.md

Since jobs is powered by Redis, there is a chance that you can lose data with the default Redis configuration. To get the best persistence guarantees, you should set Redis to use both AOF and RDB persistence modes and set fsync to "always". With these settings, Redis is more or less as persistent as a database like postgres. If want better performance and are okay with a slightly greater chance of losing data (i.e. jobs not executing), you can set fsync to "everysec".

Read more about Redis persistence.

Jobs is carefully written using Redis transactions and lua scripting so that all database changes are atomic. If Redis crashes in the middle of a transaction or script execution, it is possible that your AOF file can become corrupted. If this happens, Redis will refuse to start until the AOF file is fixed. It is relatively easy to fix the problem with the redis-check-aof tool, which will remove the partial transaction from the AOF file. In effect, this guarantees that modifications of the database are atomic, even in the event of a power loss or hard reset, with the caveat that you may need to use the redis-check-aof tool in the worst case scenario.

Read more about Redis transactions and scripts.

Jobs guarantees that a job will be executed at least once, provided it has been persisted on disk. (See the section on Persistence directly above). A job can only picked up by one pool at a time because a pool atomically pops (gets and immediately moves) the next available jobs from the database. A job can only be executed by one worker at a time because the jobs are delegated to workers via a shared channel. Each worker pool checks on the health of all the other pools when it starts. If a pool crashes or is otherwise disconnected, any jobs it had grabbed from the database that did not yet finish will be re-queued and picked up by a different pool.

This is in no way an exhaustive list, but here are some known examples of scenarios that may cause a job to be executed more than once:

1. If there is a power failure or hard reset while a worker is in the middle of executing a job, the job may be stuck in a half-executed state. Since there is no way to know how much of the job was successfully completed, the job will be re-queued and picked up by a different pool, where it may be partially or fully executed more than once.
2. If a pool becomes disconnected, it will be considered stale and its jobs will be re-queued and reclaimed by a different pool. However, if the stale pool is able to partly or fully execute jobs without a reliable internet connection, any jobs belonging to the stale pool might be executed more than once. You can increase the StaleTimeout parameter for a pool to make this scenario less likely.

Jobs is licensed under the MIT License. See the LICENSE file for more information.