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Golang asynchronous task/job queue with Redis, SQS, IronMQ, and in-memory backends

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Installation

taskq supports 2 last Go versions and requires a Go version with modules support. So make sure to initialize a Go module:

go mod init github.com/my/repo

And then install taskq/v3 (note v3 in the import; omitting it is a popular mistake):

go get github.com/frain-dev/taskq/v3

Features

  • Redis, SQS, IronMQ, and in-memory backends.
  • Automatically scaling number of goroutines used to fetch (fetcher) and process messages (worker).
  • Global rate limiting.
  • Global limit of workers.
  • Call once - deduplicating messages with same name.
  • Automatic retries with exponential backoffs.
  • Automatic pausing when all messages in queue fail.
  • Fallback handler for processing failed messages.
  • Message batching. It is used in SQS and IronMQ backends to add/delete messages in batches.
  • Automatic message compression using snappy / s2.

Quickstart

I recommend that you split your app into the two parts:

  • An API that accepts requests from customers and adds tasks to the queues.
  • A Worker that fetches tasks from the queues and processes them.

This way you can:

  • Isolate API and worker from each other.
  • Scale API and worker separately.
  • Have different configs for API and worker (like timeouts).

There is an api_worker example that demonstrates this approach using Redis as a backend:

cd example/api_worker
go run worker/worker.go
go run api/api.go

You start by choosing a backend to use - in our case Redis:

package api_worker

var QueueFactory = redisq.NewFactory()

Using that factory you create a queue that contains tasks:

var MainQueue = QueueFactory.RegisterQueue(&taskq.QueueOptions{
    Name:  "api-worker",
    Redis: Redis, // go-redis client
})

Using the queue you create a task with handler that does some useful work:

var CountTask = taskq.RegisterTask(&taskq.TaskOptions{
    Name: "counter",
    Handler: func() error {
        IncrLocalCounter()
        return nil
    },
})

Then in an API binary you use tasks to add messages/jobs to queues:

ctx := context.Background()
for {
    // call task handler without any args
    err := api_worker.MainQueue.Add(api_worker.CountTask.WithArgs(ctx))
    if err != nil {
        log.Fatal(err)
    }
}

And in a worker binary you start processing queues:

err := api_worker.MainQueue.Start(context.Background())
if err != nil {
    log.Fatal(err)
}

API overview

t := myQueue.RegisterTask(&taskq.TaskOptions{
    Name:    "greeting",
    Handler: func(name string) error {
        fmt.Println("Hello", name)
        return nil
    },
})

// Say "Hello World".
err := myQueue.Add(t.WithArgs(context.Background(), "World"))
if err != nil {
    panic(err)
}

// Say "Hello World" with 1 hour delay.
msg := t.WithArgs(ctx, "World")
msg.Delay = time.Hour
_ = myQueue.Add(msg)

// Say "Hello World" once.
for i := 0; i < 100; i++ {
    msg := t.WithArgs(ctx, "World")
    msg.Name = "hello-world" // unique
    _ = myQueue.Add(msg)
}

// Say "Hello World" once with 1 hour delay.
for i := 0; i < 100; i++ {
    msg := t.WithArgs(ctx, "World")
    msg.Name = "hello-world"
    msg.Delay = time.Hour
    _ = myQueue.Add(msg)
}

// Say "Hello World" once in an hour.
for i := 0; i < 100; i++ {
    msg := t.WithArgs(ctx, "World").OnceInPeriod(time.Hour)
    _ = myQueue.Add(msg)
}

// Say "Hello World" for Europe region once in an hour.
for i := 0; i < 100; i++ {
    msg := t.WithArgs(ctx, "World").OnceInPeriod(time.Hour, "World", "europe")
    _ = myQueue.Add(msg)
}

Message deduplication

If a Message has a Name then this will be used as unique identifier and messages with the same name will be deduplicated (i.e. not processed again) within a 24 hour period (or possibly longer if not evicted from local cache after that period). Where Name is omitted then non deduplication occurs and each message will be processed. Task's WithMessage and WithArgs both produces messages with no Name so will not be deduplicated. OnceWithArgs sets a name based off a consistent hash of the arguments and a quantised period of time (i.e. 'this hour', 'today') passed to OnceWithArgs a period. This guarantees that the same function will not be called with the same arguments during `period'.

Handlers

A Handler and FallbackHandler are supplied to RegisterTask in the TaskOptions.

There are three permitted types of signature:

  1. A zero-argument function
  2. A function whose arguments are assignable in type from those which are passed in the message
  3. A function which takes a single *Message argument

If a task is registered with a handler that takes a Go context.Context as its first argument then when that handler is invoked it will be passed the same Context that was passed to Consumer.Start(ctx). This can be used to transmit a signal to abort to all tasks being processed:

var AbortableTask = MainQueue.RegisterTask(&taskq.TaskOptions{
    Name: "SomethingLongwinded",
    Handler: func(ctx context.Context) error {
        for range time.Tick(time.Second) {
            select {
                case <-ctx.Done():
                    return ctx.Err()
                default:
                    fmt.Println("Wee!")
            }
        }
        return nil
    },
})

Custom message delay

If error returned by handler implements Delay() time.Duration interface then that delay is used to postpone message processing.

type RateLimitError string

func (e RateLimitError) Error() string {
    return string(e)
}

func (RateLimitError) Delay() time.Duration {
    return time.Hour
}

func handler() error {
    return RateLimitError("calm down")
}

Tracing

taskq supports tracing out-of-the-box using OpenTelemetry API. To instrument a queue, use the following code:

import "github.com/vmihailenco/taskq/extra/taskqotel/v3"

consumer := queue.Consumer()
consumer.AddHook(&taskqotel.OpenTelemetryHook{})

or using a taskq.Factory:

factory.Range(func(q taskq.Queue) bool {
    consumer := q.Consumer()
    consumer.AddHook(&taskqext.OpenTelemetryHook{})

    return true
})

We recommend using Uptrace.dev as a tracing backend.

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Golang asynchronous task/job queue with Redis, SQS, IronMQ, and in-memory backends

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