WARNING: This project is mostly experimental and the API is subject to change.
This package implements thread pools using node 10.5's new worker thread API (see: https://nodejs.org/api/worker_threads.html).
surrial
) for serializationWorker threads are usually expensive to create, a thread pool maintains the threads and allows you to submit work on the fly, without having to pay the cost of recreating threads.
With node's new worker_thread
API, threads in the pool can pass messages to each other and read and write to shared memory.
Full API documentation can be found here: https://psastras.github.io/node-threadpool/api/modules/executors.html.
If you're familiar with Java's thread pool API, this should be very familiar:
import { Executors } from "node-threadpool";
const pool = Executors.newFixedThreadPool(1);
const result = pool.submit(async () => "hello world");
console.log(await result); // prints "hello world"
Requires node 10.5+. You must run node with the --experimental-worker
flag enabled.
NODE_OPTIONS=--experimental-worker ./server.js
or
node --experimental-worker ./server.js
To install:
yarn add node-threadpool
or
npm install node-threadpool
Import node-threadpool
:
import { Executors } from "node-threadpool";
Executors contains methods to create different thread pools.
Create a thread pool by calling one of these methods:
// creates a thread pool with 4 threads
const pool = Executors.newFixedThreadPool(4);
Then submit work to the pool with the submit
method. This method takes in a function with no arguments that returns a Promise. The submit
method itself returns a Promise which is resolved when the function has been executed.
// these execute in parallel (as long as the pool size >= 2)
const result1 = pool.submit(async () => "done 1");
const result2 = pool.submit(async () => "done 2");
console.log(await result1); // joins and prints "done1"
console.log(await result2); // joins and prints "done2"
See the documentation for full API details.
Note: if you're not using async / await, Promise based functions work just as well.
You may only access data within the runnable function's context. For example, this is an error:
const hello = "hello";
await pool.submit(async () => hello);
Instead, use the optional data
object when submitting the function:
const hello = "hello";
await pool.submit(async (data) => data, hello);
Similarly you must require third party modules from inside the run method:
await pool.submit(async () => {
const fs = require('fs');
fs.readFileSync('README');
});
const pool = Executors.newFixedThreadPool(4);
const result = pool.submit(async () => "hello world");
console.log(await result); // prints "hello world"
const pool = Executors.newSingleThreadedExecutor();
const map = new Map();
map.set("key", "value");
const data = {
map
};
const result = pool.submit(async d => d.map.get("key"), data);
console.log(await result); // prints "value"
const buffer = new SharedArrayBuffer(1 * Int32Array.BYTES_PER_ELEMENT);
const array = new Int32Array(sharedBuffer);
// theres no lock, so in order to write safely we'll use one thread for this toy example
// see the next example for atomic usage
const pool = Executors.newSingleThreadedExecutor();
// set the data in the shared buffer to 42
await pool.submit(async d => (new Int32Array(d)[0] = 42), buffer);
// read the data from the shared buffer
const result = pool.submit(async d => new Int32Array(d)[0], buffer);
console.log(await result); // prints 42
const buffer = new SharedArrayBuffer(1 * Int32Array.BYTES_PER_ELEMENT);
const array = new Int32Array(buffer);
const pool = Executors.newSingleThreadedExecutor();
const result = pool.submit(async d => {
const view = new Int32Array(d);
Atomics.wait(view, 0, 0); // wait here until the value is no longer 0
return Atomics.load(view, 0);
}, buffer);
Atomics.store(array, 0, 1); // change the value from 0, unblocking the worker thread
console.log(await result); // prints 1
MIT Licensed, see the LICENSE file.
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