Unleashing Parallel Processing with Node.js Worker Threads
Worker Threads enable true parallelism in Node.js, perfect for CPU-intensive tasks. Let's dive in.
Why Worker Threads?
- Parallel execution of JavaScript code
- Shared memory capabilities
- Ideal for CPU-bound operations
Basic Usage
const { Worker, isMainThread, parentPort } = require('worker_threads'); if (isMainThread) { const worker = new Worker(__filename); worker.on('message', (msg) => console.log('From worker:', msg)); worker.postMessage('Hello, Worker!'); } else { parentPort.on('message', (msg) => { console.log('From main:', msg); parentPort.postMessage('Hello, Main!'); }); }
Passing Data
- Structured Clone Algorithm (default)
- Transferable objects
- SharedArrayBuffer for zero-copy transfers
const { Worker } = require('worker_threads'); const worker = new Worker('./worker.js'); const sharedBuffer = new SharedArrayBuffer(4); const arr = new Int32Array(sharedBuffer); arr[0] = 123; worker.postMessage({ sharedBuffer });
Worker Pools
const { StaticPool } = require('node-worker-threads-pool'); const pool = new StaticPool({ size: 4, task: (n) => n * 2 }); async function runTasks() { const results = await Promise.all([ pool.exec(10), pool.exec(20), pool.exec(30) ]); console.log(results); // [20, 40, 60] } runTasks().catch(console.error);
Best Practices
- Use for CPU-intensive tasks, not I/O operations
- Implement proper error handling
- Carefully manage shared resources to avoid race conditions
- Consider using worker pools for better resource management
Performance Considerations
- Thread creation has overhead; reuse workers when possible
- Balance number of workers with available CPU cores
- Minimize data transfer between threads
Pitfalls to Avoid
- Overusing for simple tasks (threading has overhead)
- Neglecting to terminate workers when done
- Assuming automatic load balancing (you must manage this)
Worker Threads shine for parallel processing of CPU-intensive tasks. Use wisely to supercharge your Node.js applications.
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