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worker_threads_clusters
Advanced tools
Split CPU-intensive tasks on multiple servers through node worker_threads.
Split CPU-intensive tasks on multiple servers (nodes) through node worker_threads.
npm install worker_threads_clusters
Node.js offers a feature called worker_threads
that allows you to launch other node files as threads on the main node program. This can be useful for running programs that might block the event loop or for running CPU-intensive programs.
This package takes that concept one step further by allowing you to spawn workers on different servers (referred to as clusters). This way, you can run CPU-intensive tasks on server clusters and then get the response on the main server without any complicated back-end work.
const { Client } = require('worker_threads_clusters');
// nodeBehavior is how what node should be picked
// 'random' | 'incremental' | 'balancing'
/*
random - pick a random node
incremental - use the nodes in order, first worker on first node, 2nd worker on 2nd node, etc and it keeps resetting back to first worker and continues the cycle
balancing - it will fetch the cpu(s) usage of all the nodes and choose the best one to spawn the worker based on the usage percentage
*/
const c = new Client({ nodeBehavior: 'random' });
// connection transport is done through HTTP (udp support coming soon)
c.addNode('http://username:password@node1.clusters.local');
c.addNode('http://username:password@node2.clusters.local');
c.addNode('http://username:password@node3.clusters.local');
c.addNode('http://username:password@node4.clusters.local');
c.addNode('http://username:password@node5.clusters.local');
(async () => {
// a node is first chosen
// then the "run.js" file gets bundled with esbuild and uploaded to the node
// worker will then be launched on node
const worker = await c.spawnWorker('run.js');
worker.on('online', () => console.log('worker is online'));
worker.on('error', () => console.log('error'));
worker.on('exit', () => console.log('exit'));
worker.on('message', (data) => console.log('recieved message:', data));
setInterval(()=>{
worker.postMessage('balls');
}, 1000)
})();
const { Server } = require('worker_threads_clusters');
const s = new Server({
auth: {
username: 'username',
password: 'password'
},
port: 80,
log: true // Whether or not it should console.log when important stufff happens (default = true)
});
s.start();
// the server will automatically start processing requests from clients
const { isMainThread, parentPort } = require('worker_threads');
if(!isMainThread) {
console.log("yooooo i'm alive!!!!")
parentPort.on("message", (data) => {
// messages can be sent and recieved
console.log('got message:', data);
parentPort.send(data);
});
doSomethingReallyIntensiveCpuTask();
} else {
console.log("run me through a worker, smh")
}
Pull requests and stars are always welcome. For bugs and feature requests, please create an issue.
Running and reviewing unit tests is a great way to get familiarized with a library and its API. You can install dependencies and run tests with the following command:
$ npm install && npm test
Soon
This is sort of an unfinished project. Right now, everything mentioned previously is fully implemented and new things are coming soon.
Copyright © 2022, Hackermon. Released under the MIT License.
FAQs
Split CPU-intensive tasks on multiple servers through node worker_threads.
The npm package worker_threads_clusters receives a total of 3 weekly downloads. As such, worker_threads_clusters popularity was classified as not popular.
We found that worker_threads_clusters demonstrated a not healthy version release cadence and project activity because the last version was released a year ago. It has 1 open source maintainer collaborating on the project.
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