Swoole and Workerman's optimization methods for data partitioning and data replication in PHP and MySQL

Swoole and Workerman's optimization methods for data partitioning and data copies of PHP and MySQL require specific code examples

With the rapid development of the Internet and the widespread use of big data Applications have increasingly higher data processing capabilities and performance requirements for PHP and MySQL. In order to improve the operating efficiency and reliability of the system, data partitioning and data copies have become common optimization methods. As two popular server frameworks in the PHP field, Swoole and Workerman also provide related functions to optimize data processing performance. This article will introduce Swoole and Workerman's optimization methods for PHP and MySQL data partitioning and data copies, and give specific code examples.

1. Swoole’s optimization of data partitioning

1. Use Task to process and distribute data asynchronously

In Swoole, this can be achieved by creating a Task process The ability to process and distribute data asynchronously. This can avoid blocking in the main process and improve the concurrent processing capability of the entire system. The following is a simple sample code:

<?php
$serv = new SwooleServer("127.0.0.1", 9501, SWOOLE_PROCESS, SWOOLE_SOCK_TCP);

$serv->set(array(
    'worker_num' => 4,
    'task_worker_num' => 4,
));

$serv->on('Receive', function ($serv, $fd, $from_id, $data) {
    $task_id = $serv->task($data);
    echo "Dispatch AsyncTask: id=$task_id
";
});

$serv->on('Task', function ($serv, $task_id, $from_id, $data) {
    // 异步任务处理逻辑
    // 例如数据存储到MySQL中
    // 或者数据分区存储到不同的MySQL节点中
    echo "New AsyncTask[id=$task_id]".PHP_EOL;
    $serv->finish("$data -> OK");
});

$serv->on('Finish', function ($serv, $task_id, $data) {
    echo "AsyncTask[$task_id] Finish: $data".PHP_EOL;
});

$serv->start();

In the above code, we created 4 Worker processes and 4 Task processes to handle requests from the client. When data is received, the main process will distribute the task to one of the Task processes for asynchronous processing. In the Task process, data partitioning can be performed and the data can be stored in different MySQL nodes.

2. Using Swoole's coroutine feature

Swoole provides a coroutine mechanism that can simplify code for concurrent data processing. The following is a sample code that uses coroutines for data partition storage:

<?php
Coun(function() {
    $mysql = new SwooleCoroutineMySQL();

    $server = array(
        'host' => '127.0.0.1',
        'port' => 3306,
        'user' => 'root',
        'password' => '',
        'database' => 'test',
        'charset' => 'utf8mb4',
    );

    $mysql->connect($server);

    // 获取数据
    $res = $mysql->query("SELECT * FROM `table`");

    // 协程处理数据
    go(function() use ($res, $mysql) {
        foreach ($res as $row) {
            // 数据分区逻辑，将数据存储到不同的MySQL节点中
            $partition = $row['id'] % 4;
            $mysql->query("INSERT INTO `table_$partition` VALUES (...)");   
        }
    });
});

In the above code, we can use coroutines to perform concurrent MySQL queries and partition storage operations in the same thread, improving Data processing speed.

2. Workerman’s optimization of data copies

1. Using Redis to achieve data synchronization

In Workerman, you can use Redis as the middleware for data synchronization , realize the data copy function through the publish-subscribe mechanism. The following is a simple sample code:

<?php
require_once __DIR__ . '/vendor/autoload.php';

use WorkermanWorker;
use WorkermanLibTimer;
use PredisClient;

$worker = new Worker('tcp://0.0.0.0:2346');

// Redis配置
$redisConfig = [
    'scheme' => 'tcp',
    'host' => '127.0.0.1',
    'port' => 6379,
];

// Worker启动时执行的回调函数
$worker->onWorkerStart = function($worker) use ($redisConfig) {
    // 连接Redis
    $redis = new Client($redisConfig);

    // 定时器，每隔1秒向Redis发布一条消息
    Timer::add(1, function() use ($redis) {
        $redis->publish('data_channel', 'data');
    });
};

// 客户端连接时执行的回调函数
$worker->onConnect = function($connection) use ($redisConfig) {
    // 连接Redis
    $redis = new Client($redisConfig);

    // 订阅数据通道
    $redis->subscribe('data_channel', function($redis, $channel, $data) use ($connection) {
        // 数据副本逻辑，将数据发送给客户端
        $connection->send($data);
    });
};

Worker::runAll();

In the above code, we create a Worker process, connect to Redis at startup, and use a timer to publish a message to Redis every second. At the same time, when the client connects, it subscribes to the Redis data channel, and after receiving the message, the data is sent to the client, realizing the function of data copy.

To sum up, Swoole and Workerman provide corresponding functions in the optimization method of data partitioning and data copy in PHP and MySQL, by using Task asynchronous processing and coroutine features, and using Redis to achieve data synchronization. , which can improve the operating efficiency and reliability of the system. The code examples given above can be used as a reference to make appropriate adjustments and extensions according to actual business needs.

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