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In-depth analysis of the multi-process model of swoole development function

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Release: 2023-08-06 09:37:53
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In-depth analysis of the multi-process model of Swoole development function

Introduction:
In high concurrency situations, the traditional single-process and single-thread model often cannot meet the needs, so the multi-process model has become a a common solution. Swoole is a multi-process-based PHP extension that provides a simple, easy-to-use, efficient and stable multi-process development framework. This article will deeply explore the implementation principles of the Swoole multi-process model and analyze it with code examples.

  1. Introduction to Swoole multi-process model
    In Swoole, we can create sub-processes through the swoole_process class to implement the multi-process model. Each child process has an independent memory space and can perform its own tasks. The main process is responsible for managing the life cycle of the child process, distributing tasks, and handling the exit of the child process. Child processes can exchange data via IPC (inter-process communication) or shared memory.
  2. Advantages of the Swoole multi-process model
    Compared with the traditional model, the Swoole multi-process model has the following advantages:
    (1) Share the pressure of the main process: child processes can accept and process requests , reduce the burden on the main process and improve the concurrency capability of the system.
    (2) Fast response: Swoole's multi-process model can handle multiple requests at the same time, improving the system's response speed.
    (3) Better utilization of hardware resources: On a multi-core CPU machine, each sub-process can be bound to a different CPU core to improve the operating efficiency of the system.
  3. Implementation of Swoole multi-process model
    The following is a sample code that uses Swoole to implement a multi-process model:
<?php
$worker_num = 4; // 创建 4 个子进程
$workers = [];

// 创建子进程
for ($i = 0; $i < $worker_num; $i++) {
    $process = new swoole_process('process_callback');
    $pid = $process->start();
    $workers[$pid] = $process; // 将子进程对象保存起来
}

// 子进程逻辑处理函数
function process_callback(swoole_process $worker)
{
    // 子进程逻辑代码
    // ...
}

// 主进程监听子进程退出事件
foreach ($workers as $pid => $process) {
    swoole_event_add($process->pipe, function ($pipe) use ($process) {
        $data = $process->read(); // 读取子进程发送过来的数据
        // 对数据进行处理
        // ...
    });
}

// 主进程等待子进程退出
swoole_process::wait();
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In the above code, we first create the specified number of Subprocesses, then create these subprocesses through the swoole_process class, and save the subprocess objects. Each child process will execute the logic code of the process_callback function.

Next, the main process listens to the pipe events of the sub-process through the swoole_event_add method. When the sub-process has data written to the pipe, the main process will receive the notification and read it in the callback function. Get the data sent by the child process. The main process can perform corresponding processing according to the content of the data.

Finally, the main process waits for all child processes to exit through the swoole_process::wait() method.

  1. Summary
    In this article, we have an in-depth exploration of the implementation principles of the Swoole multi-process model and give code examples. By using Swoole's multi-process model, we can effectively improve the concurrency and response speed of the system, make better use of hardware resources, and provide an effective solution for high-concurrency scenarios.

It should be noted that when using Swoole's multi-process model, we need to fully understand the mechanism of inter-process communication to avoid data conflicts or competition. In addition, you also need to pay attention to controlling the number of child processes to avoid wasting system resources caused by too many child processes.

I hope this article will be helpful in understanding the Swoole multi-process model and provide readers with a reference for better developing high-concurrency and high-performance systems.

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