Home Backend Development PHP Tutorial How PHP and Unity3D implement multi-threaded data processing in Workerman

How PHP and Unity3D implement multi-threaded data processing in Workerman

Jul 18, 2023 am 09:31 AM
php Multithreading data processing workerman unityd

How PHP and Unity3D implement multi-threaded data processing in Workerman

Overview:
In web development and game development, the need to process large amounts of data is increasingly common. In order to improve the efficiency and response speed of data processing, multi-threaded data processing has become a common solution. This article will introduce how to implement multi-threaded data processing of PHP and Unity3D in Workerman and provide relevant code examples.

1. Introduction to Workerman
Workerman is a high-performance PHP development framework. One of its features is that it supports multi-process and multi-threading. It is mainly used to build high-performance network applications, such as chat servers, real-time communication servers, etc. Workerman adopts a non-blocking I/O model and can efficiently handle a large number of concurrent connections.

2. PHP multi-threaded data processing

  1. Installing extensions
    First, we need to install a PHP extension named "pthreads" to support multi-threading. It can be installed through PECL and execute the following command:

    sudo pecl install pthreads
  2. Write multi-threaded code

The following is a simple PHP multi-threaded data processing example:

<?php
class MyThread extends Thread {
    private $data;

    public function __construct($data) {
        $this->data = $data;
    }

    public function run() {
        // 处理数据
        $result = $this->processData($this->data);
        // 将结果写回主线程
        $this->synchronized(function($thread) use ($result) {
            $thread->result = $result;
        }, $this);
    }

    private function processData($data) {
        // 在此处编写真正的数据处理逻辑
        // 返回处理结果
    }
}

// 创建线程
$threads = [];
$data = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10];
foreach ($data as $item) {
    $thread = new MyThread($item);
    $threads[] = $thread;
    $thread->start();
}

// 等待所有线程结束并获取结果
$results = [];
foreach ($threads as $thread) {
    $thread->join();
    $results[] = $thread->result;
}

// 打印结果
print_r($results);

In the above code, we first created a class named MyThread, which inherits from the Thread class provided by the PHP multi-thread extension. Pass in the data to be processed in the constructor of the MyThread class, then write the specific data processing logic in the run() method, and save the result in resultAttributes. Then write the result back to the main thread through the synchronized method.

Next, we create a set of threads and assign the data to each thread. After each thread starts, it will execute the run() method. Finally, we wait for all threads to end through the join() method and obtain the final processing result.

  1. Using multi-threading in Workerman

Workerman supports multi-process and multi-threading and can be used to handle multi-threaded data processing of PHP and Unity3D. The following is a sample code:

<?php
// 引入Workerman的自动加载文件
require_once __DIR__ . '/workerman/Autoloader.php';

use WorkermanWorker;
use WorkermanLibTimer;
use WorkermanThreadWorker as ThreadWorker;

// 创建一个Worker监听端口,处理客户端请求
$worker = new Worker('tcp://0.0.0.0:2345');
$worker->count = 4;

$worker->onConnect = function ($connection) {
    echo "Client connected
";
};

$worker->onMessage = function ($connection, $data) {
    // 数据处理逻辑
    $result = processData($data);
    // 发送处理结果给客户端
    $connection->send($result);
};

// 创建多线程处理数据
$threadWorker = new ThreadWorker(4);

$threadWorker->onMessage = function ($task_id, $data) {
    // 数据处理逻辑
    $result = processData($data);
    // 获取任务ID,并将处理结果发送给主进程
    ThreadWorker::send($task_id, $result);
};

// 开始多线程工作
$threadWorker->start();

// 当有客户端连接时,将任务分配给多线程处理
$worker->onConnect = function($connection) {
    $task_id = $connection->id;
    $data = $connection->getRemoteIp();
    $threadWorker = new ThreadWorker();
    $threadWorker->name = 'Worker_' . $task_id;
    ThreadWorker::postMessage($threadWorker->id, $data, $task_id);
};

// 数据处理逻辑
function processData($data) {
    // 在此处编写真正的数据处理逻辑
    // 返回处理结果
}

// 运行worker
Worker::runAll();

In the above example, we first created a Worker instance to listen to client connection requests and process data when receiving messages. Then a multi-threaded Worker instance is created to process the data. Specific data processing logic is written in the onMessage callback function, and the processing results are sent to the main process.

In the data processing logic, we can write our own business logic according to actual needs and return the processing results.

3. Unity3D multi-threaded data processing

In Unity3D, most of the data processing logic can be processed in sub-threads to improve the response speed of the main thread. The following is a simple Unity3D multi-threaded data processing example:

using System.Collections;
using System.Collections.Generic;
using UnityEngine;
using System.Threading;

public class DataProcessing : MonoBehaviour
{
    private Thread thread;

    void Start()
    {
        thread = new Thread(DataProcess);
        thread.Start();
    }

    void DataProcess()
    {
        // 在此处编写数据处理逻辑
    }

    void OnDestroy()
    {
        if (thread != null && thread.IsAlive)
        {
            thread.Abort();
        }
    }
}

In the above example, we use C#’s System.Threading.Thread class to create a new thread and Write the data processing logic in it. In the OnDestroy method, we release the thread resources.

In practical applications, we can use thread pools, task queues and other technologies in data processing logic to manage threads and exchange data according to needs.

Summary:
Through the above code examples, we have learned how to implement multi-threaded data processing in PHP in Workerman and multi-threaded data processing in Unity3D. Multi-threaded data processing can improve the efficiency and response speed of data processing, and is suitable for scenarios where large amounts of data are processed. In practical applications, we can expand and optimize the code according to needs to improve the performance and stability of the system.

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