A node.js client and worker library for the Faktory job server. The client allows you to push jobs and communicate with the Faktory server and the worker fetches background jobs from the Faktory server and processes them.
Faktory server compatibility: ~v1.6.1
npm install faktory-worker
const faktory = require("faktory-worker");
(async () => {
const client = await faktory.connect();
await client.job("ResizeImage", { id: 333, size: "thumb" }).push();
await client.close(); // reuse client if possible! remember to disconnect!
})().catch((e) => console.error(e));A job is a payload of keys and values according to the faktory job payload specification. Any keys provided will be passed to the faktory server during PUSH. A jid (uuid) is created automatically for your job when using this library. See the spec for more options and defaults.
const faktory = require("faktory-worker");
(async () => {
const client = await faktory.connect();
let job1 = client.job("ResizeImage", { id: 333, size: "thumb" });
let job2 = client.job("ResizeImage", { id: 334, size: "thumb" });
let rejected = await client.pushBulk([job1, job2]);
// rejected is a dictionary of [jid]: { payload, reason } if any failed to enqueue
for (const [jid, { payload, reason }] of Object.entries(rejected)) {
console.error(`Faild to push job for image ${payload.args[0].id}`);
}
await client.close(); // reuse client if possible! remember to disconnect!
})().catch((e) => console.error(e));faktory link: https://github.com/contribsys/faktory/blob/main/Changes.md#160
const faktory = require("faktory-worker");
faktory.register("ResizeImage", async ({ id, size }) => {
const image = await Image.find(id);
await image.resize(size);
});
faktory.work().catch((error) => {
console.error(`worker failed to start: ${error}`);
process.exit(1);
});A job function can be a sync or async function. Simply return a promise or use await in your async function to perform async tasks during your job. If you return early or don't await properly, the job will be ACKed when the function returns.
faktory.work() traps INT and TERM signals so that it can gracefully shut down and finish any in-progress jobs before the options.timeout is reached.
By default, faktory_worker_node will listen to a default queue. If you'd like to use multiple queues, specify them in options.queues when instantiating a Worker or via --queue when using the CLI.
Queues can be specified in two ways: strictly ordered and weighted random.
To specify queues to be worked on in a strict order (empty one, then the next, etc), use an array of queue names for options.queues.
faktory.work({ queues: ["immediately", "afterwards"] });In the previous example, all jobs are be fetched and started from the immediately queue before any are fetched and started from the afterwards queue.
To specify queues to be worked on randomly, use an object of [queueName: string]: number entries. To ensure that some queues are processed more frequently than others, use a higher weight number for that queue. Weights are relative. 100, 200, and 300 is no different than 1, 2, and 3, respectively.
faktory.work({ queues: { critical: 10, default: 1 } });In the example above, the critical queue, weighted 10, will have roughly 10 jobs processed for every 1 job processed in the default queue. For equal weighting (just random queue processing), see below:
faktory.work({ queues: { useast: 1, uswest: 1 } });In the example above, useast and uswest have equal weights are worked on concurrently.
A Faktory Worker emits several events that can be used to handle errors. When a job function throws an error, it is caught and the job is FAILed. You can listen for a fail event to do something with these errors (like send a message to an error aggregator).
An error event is emitted when an unexpected error occurs in the this library. If no listener is registered for the error event, a default handler is added.
const worker = await faktory.work();
worker.on("fail", ({ job, error }) => {
// report job error somewhere
});Faktory middleware works just like koa middleware. You can register a middleware function (async or sync) with .use. Middleware is called for every job that is performed. Always return a promise, await next(), or return next(); to allow execution to continue down the middleware chain.
const faktory = require("faktory-worker");
faktory.use(async (ctx, next) => {
const start = process.hrtime();
await next();
const time = process.hrtime(start);
console.info("%s took %ds %dms", ctx.job.jobtype, time[0], time[1] / 1e6);
});
faktory.work();faktory-worker comes with two helper scripts:
node_modules/.bin/faktory-work
Starts one worker. Use --help for more information.
and
node_modules/.bin/faktory-cluster
You can override the default options for a faktory worker by providing an object to the faktory.work() method or the Worker() constructor.
Here are the defaults:
await faktory.work({
host: process.env.FAKTORY_URL || "127.0.0.1",
// default: 7419 -- can extracted from FAKTORY_URL env var
port: 7419,
// can extracted from FAKTORY_URL env var
password: undefined,
// this is a max number of jobs the worker will have
// in progress at any time
concurrency: 20,
// the queues the worker will process—remember to preserve default if overriding this
// default fetching behavior is **Strictly Ordered**
queues: ["default"],
// the number of milliseconds jobs have to complete after
// receiving a graceful shutdown signal. After this timeout, in-progress jobs may be abruptly stopped.
timeout: 8 * 1000,
// the worker id to use in the faktory-server connection
// for this process. must be unique per process.
wid: uuid().first(8),
// labels for the faktory worker process to see in the UI
labels: [],
});Use DEBUG=faktory* to see related debug log lines.
- How do I specify the Faktory server location?
By default, it will connect to tcp://127.0.0.1:7419.
Use FAKTORY_URL to specify the URL, e.g. tcp://faktory.example.com:12345 or use FAKTORY_PROVIDER to specify the environment variable which contains the URL: FAKTORY_PROVIDER=FAKTORYTOGO_URL. This level of
indirection is useful for SaaSes, Heroku Addons, etc.
- How do I access the job payload in my function?
The function passed to register can be a thunk. The registered function will receive the job args and if that function returns a function, that returned function will be called and provided the execution context (ctx) which contains the raw job payload at ctx.job, containing all custom props and other metadata of the job payload.
faktory.register("JobWithHeaders", (...args) => async ({ job }) => {
const [email] = args;
I18n.locale = job.custom.locale;
log(job.custom.txid);
await sendEmail(email);
});- How do I add middleware to the job execution stack?
Because many jobs may share the same dependencies, the faktory job processor holds a middleware stack of functions that will execute before the job function does. You can add middleware to this stack by calling faktory.use and providing a function to be called. The middleware execution in faktory-worker works exactly the same as koa.
Here's an example of passing a pooled connection to every faktory job that's executed.
const { createPool } = require("generic-pool"); // any pool or connection library works
const faktory = require("faktory");
const pool = createPool({
create() {
return new Client();
},
destroy(client) {
return client.disconnect();
},
});
faktory.use(async (ctx, next) => {
ctx.db = await pool.acquire();
try {
// middleware *must* return next() or await next()
// this invokes the downstream middleware (including your job fn)
await next();
} finally {
// return connection to pool
pool.release(ctx.db);
}
});
faktory.register("TouchRecord", (id) => async ({ db }) => {
const record = await db.find(id);
await record.touch();
});- Customizable logger
- Pro features
- CLI: Require jobs from folder and automatically register
- Mutate API
- Connection pooling
- Handle signals from server heartbeat response
- Middleware
- CLI
- Heartbeat
- Tests
- Authentication
- Fail jobs
- Add'l client commands API
- Labels
Install docker.
bin/server will run the faktory server in a docker container. The server is available at 127.0.0.1:7419
Use DEBUG=faktory* to see debug output from this library.
A faktory server must be running locally. Use bin/server to start one.
The tests can be run via npm test—they will be executed by ava.
Josh Bielick, @jbielick