A durable job queuing and worker system for Clojure backed by PostgreSQL.
Use Proletarian for asynchronously executing tasks in the background. It's useful for offloading long-running tasks from the request thread in user-facing web applications. What kind of tasks? Anything that uses external services, and anything that takes more than a few milliseconds:
If you're already using PostgreSQL as your main database, there are some very nice advantages to having your job queue in PostgreSQL as well:
Here is a basic example, showing the creation of a queue worker in one namespace, and the enqueuing of a job in another namespace:
(ns your-app.workers
"You'll probably want to use a component state library (Component, Integrant,
Mount, or some such) for managing the worker state. For this example we're
just def-ing the worker. The queue worker constructor function takes
a javax.sql.DataSource as its first (and only required) argument. You
probably already have a data-source at hand in your application already. Here
we'll use next.jdbc to get one from a JDBC connection URL."
(:require [next.jdbc :as jdbc]
[proletarian.worker :as worker]))
(def email-worker
(let [ds (jdbc/get-datasource "jdbc:postgresql://...")]
(worker/create-queue-worker ds)))
(worker/start! email-worker)
(ns your-app.handlers
"Let's say this is a namespace where you handle web requests. We're going to
handle the request, write something to the database, and enqueue a job.
We'll do this in a transaction with a little bit of help from next.jdbc."
(:require [next.jdbc :as jdbc]
[proletarian.job :as job]))
(defn some-handler [system request]
(jdbc/with-transaction [tx (:db system)]
;; Do some business logic here
;; Write some result to the database
;; Enqueue the job:
(job/enqueue! tx ::confirmation-email
{:email email-address, :other-data-1 :foo, :other-data-2 :bar})
;; Return a response
response))
;; Implement the proletarian.job/handle! multimethod for the job type.
(defmethod job/handle! ::confirmation-email
[context job-type {:keys [email-address other-data-1 other-data-2]}]
;; Send the mail and do other time-consuming work here.
)
Add Proletarian to your deps.edn
file:
msolli/proletarian {:mvn/version "1.0.29-alpha"}
Or to your project.clj
for Leiningen:
[msolli/proletarian "1.0.29-alpha"]
Proletarian works with your existing PostgreSQL database. It uses
the SKIP LOCKED
feature that was introduced with PostgreSQL 9.5,
so there's a hard requirement of at least version 9.5.
Proletarian works with any Clojure database library (next.jdbc, clojure.java.jdbc) you might be using, and does not itself depend on any such library.
You'll have to create two database tables, one for queueing jobs, and one for
keeping a record of finished jobs. These are defined in database/tables.sql
in this repository, along with a PostgreSQL
schema to contain
them, and an index.
Before using the library, you must install these tables in your database. There
are many ways you can do this. You are probably already using a migration
library like Flyway or
Migratus. Copy the contents of the
database/tables.sql
file into a migration file. You can change the PostgreSQL
schema and table names, but then you'll need to provide the
:proletarian/job-table
and :proletarian/archived-job-table
options to
create-queue-worker
and enqueue!
.
This repository contains a few examples that demonstrates features and usage patterns. You can run these by cloning this repo, execute a script to set up an example Proletarian database, and then run the examples from your terminal. All the details are in the example docs:
A queue worker is a process that works off a given named queue. It can have one or more worker threads, working in parallel. The worker threads pick jobs off a queue and run them. While there are jobs to be processed, the workers will work on them continuously until the queue is empty. Then they will poll the queue at a configurable interval.
There is a default queue, :proletarian/default
, which is the one used by
job/enqueue!
and worker/create-queue-worker
if no queue is specified in the
options.
You can create as many queue workers as you like, consuming jobs from different queues. The jobs will all live in the same table, but are differentiated by the queue name. The parameters you provide when setting up the queue workers, like the polling interval and the number of worker threads (ie. the number of parallel worker instances that are polling the queue and working on jobs), will in effect control the priority of the jobs on the different queues.
A queue worker is local to one machine only. If you have several machines acting as job processing instances, they will each have queue worker processes running. The parallelization factor for a given queue will be the number of queue worker processes (on different machines) multiplied by the number of threads in each queue worker.
The job handler for a job-type is the function that the Proletarian queue worker invokes when a job of that type is pulled off the queue.
You implement the job handler by implementing the proletarian.job/handle!
multimethod with the job-type as dispatch-value. The job-type is a Clojure
keyword (optionally namespaced). You provide this as the second argument to
proletarian.job/enqueue!
when enqueueing a job.
(require '[proletarian.job :as job])
(defn do-something! [db-conn foo]
;; Do stuff here
;; Enqueue a job:
(job/enqueue! db-conn ::the-job-type foo)
)
(defmethod job/handle! ::the-job-type
[context job-type payload]
;; Do the work here.
;; The value of payload is whatever was passed as third argument to
;; job/enqueue! (the value of foo in do-something! in this case).
)
Proletarian goes to great lengths to ensure that no jobs are lost due to exceptions, network errors, database failure, computers catching fire or other facts of life. It relies on PostgreSQL transactions to protect the integrity of the jobs tables while polling and running jobs. A job will not be removed from the queue until it has finished successfully. It is moved to the archive table in the same transaction.
The guarantee is that Proletarian will run each job at least once. There are failure scenarios where a job can run and finish successfully, but the database operations in the transaction that moves the job off the queue can't be completed. These are unlikely events, like the database going offline at just the moment before the job was to be moved to the archive table. Should this happen, the job will get picked up and run again when the queue worker comes online again (or by a different thread or machine, depending on your setup).
The flip side of the at least once guarantee is that your job handler must be idempotent, or your business rules must tolerate that the effects of your job handler happen more than once (in some unlikely cases).
Jobs that throw an exception (a java.lang.Exception
or subclass, but not other
instances of Throwable
) will be retried according to their retry strategy.
The default retry strategy is to not retry.
You define a retry strategy for a job-type by implementing
the proletarian.job/retry-strategy
multimethod
with the job-type as dispatch-value. The queue worker calls this multimethod
when an exception is caught for a job handler. The job and the exception is
passed as arguments. You can use these to make informed decisions about how to
proceed. The exception might for example contain information on when to retry an
HTTP call (from a Retry-After
HTTP header). In most cases, however, a simple static retry strategy will
suffice.
The retry strategy is a Clojure map with the keys :retries
and :delays
. See
comment in code below for explanation.
(require '[proletarian.job :as job])
(defmethod job/handle! ::the-job-type
[context job-type payload]
;; Do stuff that might throw an exception here
)
(defmethod job/retry-strategy ::the-job-type
[job throwable]
{:retries 4
:delays [1000 5000]}
;; This retry strategy specifies that the job should be retried up to four
;; times, for a total of five attempts. The first retry should happen
;; one second after the first attempt failed. The remaining attempts should
;; happen five seconds after the previous attempt failed.
;; After four retries, if the job was still failing, it is not retried
;; anymore. It is moved to the archived-job-table with a failure status.
)
The queue worker, once started, will run until its stop!
function is called.
You should call this when you want to bring down your system. If you set the
install-jvm-shutdown-hook?
option to true, Proletarian will install a JVM
shutdown hook using java.lang.Runtime.addShutdownHook
that will call the stop!
function.
When the shutdown sequence starts, threads in the queue worker thread pool will receive an interrupt. How these interrupts are handled depends on where in the poll/run cycle each worker thread is. If a worker thread is polling, it will simply stop polling. If the worker thread is busy running a job, it's the job's responsibility to handle interrupts.
Most of the time, if you have jobs that run quickly (less than a few seconds), you can simply ignore interrupts. Your job will finish, and the worker thread will not pick up any more jobs.
On the other hand, if your job takes a long time to finish, you should handle interrupts one of two ways:
InterruptedException
. If your job calls (directly or
indirectly) a method that throws InterruptedException
(such as Object.wait
, Thread.sleep
, and Thread.join
), you can wrap your
job handler code in a try/catch that catches InterruptedException
. Do this
if you can meaningfully finish the job this way, or if you don't want the job
to be run again when the queue worker starts up again.Thread.isInterrupted()
. If you have CPU-intensive work that takes a
lot of time, you could chunk the work such that you can read the interrupt
status in-between chunks, and finish the job gracefully if interrupted.In general, if you stick to enqueuing jobs that require only a few seconds to run and that are safe to be run again (they are idempotent), then you can ignore interrupts.
There is lots more to be said about this topic. There is an article by Brian Goetz that goes into great detail on how to implement cancelable tasks.
If you have specific questions, or even advice you want to share regarding this topic, please open an issue.
Many thanks for Christian Johansen for help with designing the library and database schema.
Hat tip to the creators of MessageDB for how to do the example database install scripts.
Copyright © 2020-2021 Martin Solli
Distributed under the Eclipse Public License, same as Clojure.
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