Worker threads#

Source Code: lib/worker_threads.js

The node:worker_threads module enables the use of threads that execute JavaScript in parallel. To access it:

import worker from 'node:worker_threads';'use strict';

const worker = require('node:worker_threads');copy

Workers (threads) are useful for performing CPU-intensive JavaScript operations. They do not help much with I/O-intensive work. The Node.js built-in asynchronous I/O operations are more efficient than Workers can be.

Unlike child_process or cluster, worker_threads can share memory. They do so by transferring ArrayBuffer instances or sharing SharedArrayBuffer instances.

import {
  Worker,
  isMainThread,
  parentPort,
  workerData,
} from 'node:worker_threads';

if (!isMainThread) {
  const { parse } = await import('some-js-parsing-library');
  const script = workerData;
  parentPort.postMessage(parse(script));
}

export default function parseJSAsync(script) {
  return new Promise((resolve, reject) => {
    const worker = new Worker(new URL(import.meta.url), {
      workerData: script,
    });
    worker.on('message', resolve);
    worker.on('error', reject);
    worker.on('exit', (code) => {
      if (code !== 0)
        reject(new Error(`Worker stopped with exit code ${code}`));
    });
  });
};'use strict';

const {
  Worker,
  isMainThread,
  parentPort,
  workerData,
} = require('node:worker_threads');

if (isMainThread) {
  module.exports = function parseJSAsync(script) {
    return new Promise((resolve, reject) => {
      const worker = new Worker(__filename, {
        workerData: script,
      });
      worker.on('message', resolve);
      worker.on('error', reject);
      worker.on('exit', (code) => {
        if (code !== 0)
          reject(new Error(`Worker stopped with exit code ${code}`));
      });
    });
  };
} else {
  const { parse } = require('some-js-parsing-library');
  const script = workerData;
  parentPort.postMessage(parse(script));
}copy

The above example spawns a Worker thread for each parseJSAsync() call. In practice, use a pool of Workers for these kinds of tasks. Otherwise, the overhead of creating Workers would likely exceed their benefit.

When implementing a worker pool, use the AsyncResource API to inform diagnostic tools (e.g. to provide asynchronous stack traces) about the correlation between tasks and their outcomes. See "Using AsyncResource for a Worker thread pool" in the async_hooks documentation for an example implementation.

Worker threads inherit non-process-specific options by default. Refer to Worker constructor options to know how to customize worker thread options, specifically argv and execArgv options.