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How to implement nodejs multi-threading

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2023-05-08 09:09:062501browse

Node.js is one of the more popular back-end programming languages. Its event-driven, non-blocking I/O features make it more efficient than other languages.

Especially when achieving high concurrency, the advantages of Node.js' event-driven and non-blocking I/O are particularly prominent, which can provide a more efficient running method for our programs.

But in some cases, the single-threaded running mode may actually become an insurmountable bottleneck, such as when processing CPU-intensive tasks, although Node.js has adopted asynchronous non-blocking I /O model to solve I/O-intensive problems and reduce code complexity. However, when using multi-tasking libraries like MPI, you still need to implement a multi-threading solution. However, the single-threaded model of Node.js does not support multi-threading, so other methods need to be used to implement multi-threading solutions.

In this article, we will introduce some of the solutions you can use to implement multi-threading in Node.js, and under what circumstances they are most effective.

  1. Child Process

The Child Process module in Node.js provides a way to create a child process and implement a multi-threading solution through the child process. Each child process can execute in its own thread, thus avoiding the problem of blocking in the main process.

Using the Child Process module, we can perform some CPU-intensive tasks in the child process, and can choose different strategies for task allocation and data interaction. The following is an example of using Child Process to implement multi-threaded addition:

const { fork } = require('child_process');

// 创建子进程
const worker = fork('./worker');

// 向子进程发送数据
worker.send({a: 1, b: 2});

// 接收来自子进程的数据
worker.on('message', result => {
  console.log(result);
})

// 错误处理
worker.on('error', err => {
  console.log(err);
})

In this example, we first use the Child Process module to create a child process, and then send data to the child through the worker.send() method Process, the child process returns the result to the main process after completing the calculation and receives the return value through the worker.on('message') method. This enables multi-threaded calculations.

  1. Worker Threads

Node.js provides another way to implement multi-threading: Worker Threads, which allows us to start a sub-thread independent of the main thread, This sub-thread can perform some time-consuming tasks, thereby avoiding the problem of blocking the main thread in the single-threaded model.

Unlike Child Process, Worker Threads completely share memory. They can run JavaScript code in an independent environment without worrying about data sharing.

The following is an example of using Worker Threads to implement multi-threaded addition:

const { Worker } = require('worker_threads');

function runService() {
  // 创建 Worker 线程
  const worker = new Worker(`
    const add = (a, b) => a + b;
    const { parentPort } = require('worker_threads');

    // 接收来自主线程的数据
    parentPort.on('message', message => {
      // 子线程执行加法运算
      const result = add(message.a, message.b);

      // 将结果发送给主线程
      parentPort.postMessage(result);
    });
  `);

  return worker;
}

// 启动 Worker 线程
const worker = runService();

// 向 Worker 线程发送数据
worker.postMessage({ a: 1, b: 2 });

// 接收来自 Worker 线程的数据
worker.on('message', result => {
  console.log(result);
});

// 错误处理
worker.on('error', err => {
  console.log(err);
});

Here, we use Worker Threads to create an independent sub-thread environment, and the sub-thread runs Our calculation logic. Send data to the child thread through the worker.postMessage() method, and receive the calculation results returned by the child thread through the worker.on('message') method. In this way we achieve multi-threaded computing.

  1. Cluster

Another solution for implementing multi-threading in Node.js is to use the Cluster module of Node.js. The Cluster module achieves load balancing by distributing connections among multiple processes. In other words, using multiple processes can significantly improve system performance when processing time-consuming tasks.

In some cases, the Cluster module may be more suitable than Child Process and Worker Threads for handling data parallelism issues. To use the Cluster module, you need to follow the following steps:

const cluster = require('cluster');
const http = require('http');

if (cluster.isMaster) {
  // 获取 CPU 的核心数
  const numCPUs = require('os').cpus().length;

  // fork 子进程
  for (let i = 0; i < numCPUs; i++) {
    cluster.fork();
  }

  // 处理 worker exit 事件
  cluster.on('exit', (worker, code, signal) => {
    console.info(`Worker ${worker.process.pid} died`);
  });
} else {
  const server = http.createServer((req, res) => {
    res.writeHead(200);
    res.end(`hello world from ${process.pid}`);
  });

  server.listen(8000, () => {
    console.info(`Server running at http://localhost:8000/ in worker process with pid ${process.pid}`);
  });
}

In this example, we first determine whether it is the main process. If so, fork multiple child processes and listen to the exit event of each child process to facilitate errors. Notify the main process for processing. Otherwise, an HTTP service is created in the child process and the pid of the current child process is specified by the parameter passed in the listen method.

Summary

The above are the three main solutions for implementing multi-threading in Node.js, Child Process, Worker Threads and Cluster. The first two are more suitable for use when processing CPU-intensive tasks, and the latter The latter is more suitable for use and load balancing when handling network connection tasks. Of course, there are other solutions, such as using Web Workers or using lower-level C libraries to implement multi-threading, etc.

When using the above solutions, you need to pay attention to some details, such as the correctness of data and shared memory issues, etc., but with the help of these solutions, we can also provide efficient and scalable Node.js applications. processing power for better performance.

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