Swoole practice: building a high-performance queue system

With the rapid development of the Internet, various high-concurrency scenarios are becoming more and more common. In these scenarios, traditional queuing systems often experience performance bottlenecks and cannot meet real-time requirements. In order to solve this problem, Swoole, as an event-driven high-performance network communication framework, has become a very good choice. In this article, we will discuss how to use Swoole to build a high-performance queuing system to meet the challenges in high-concurrency business scenarios.

1. What is a queue system

First of all, we need to understand what a queue system is. A queue system is a data structure used to store tasks or messages that need to be processed and processed in a certain order. Normally, the queue system uses the FIFO (first in, first out) method to process tasks or messages. When a task or message is put into the queue, it becomes the tail of the queue. When the task or message needs to be processed, it is processed from the head of the queue. Queue systems are usually used to handle high-load, high-concurrency, and high-availability business scenarios, such as e-commerce platforms, social platforms, game platforms, etc.

2. Introduction to Swoole

Swoole is an event-driven, high-performance network communication framework based on PHP, with features such as coroutines, asynchronous IO, multi-process, and multi-threads. It can help PHP applications achieve better performance and scalability in high-concurrency business scenarios. Swoole has become the most popular high-performance network communication framework in the PHP language. Swoole has built-in asynchronous TCP/UDP network programming, asynchronous file system, coroutine network server, asynchronous tasks, distributed deployment, asynchronous SQLite and other functions. Compared with traditional PHP applications, applications developed using Swoole can achieve faster response speed, less resource usage, higher concurrency capabilities and other advantages.

3. Use Swoole to build a queue system

Based on the above introduction, we can use Swoole to build a high-performance queue system. The specific steps are as follows:

1. Design the queue structure

Since the queue system mainly uses FIFO to process tasks or messages, we need to design a queue structure that conforms to FIFO rules. Queue structures can be implemented using data structures such as arrays and linked lists.

2. Implementing an asynchronous task queue based on Swoole

In the process of using Swoole to build a queue system, we need to implement an asynchronous task queue. The asynchronous task queue is different from the ordinary task queue. When using the asynchronous task queue for task processing, the system will not block waiting for the completion of the task. This approach can improve system throughput and efficiency.

3. Use Swoole to implement queue consumers and producers

In a queue system, consumers and producers are required. The producer is additionally responsible for pushing tasks into the queue, and the consumer is responsible for removing tasks from the queue and executing them. When using Swoole to build a queue system, we can use coroutines to implement consumers and producers.

4. Use Swoole to implement distributed queues

For high concurrency business requirements, we may need to build a distributed queue system. This kind of queue system can distribute the tasks in the queue to multiple servers for processing to speed up the processing of tasks. When using Swoole to build a distributed queue system, you can use the distributed deployment function provided by Swoole to achieve this.

The above are the basic steps for using Swoole to build a high-performance queue system. Next, we will take an e-commerce website as an example to explain in detail how to use Swoole to build a high-performance queue system.

4. Use Swoole to build the order processing queue of the e-commerce website

In the e-commerce website, order processing is a very important business. In order to cope with high-concurrency and high-load business scenarios, we can use Swoole to build a high-performance order processing queue. The following are the specific steps:

1. Design the order processing queue structure

We can use arrays to implement the order processing queue and use the FIFO principle for task processing.

// 订单处理队列结构
$orderQueue = array();

2. Implement asynchronous task queue based on Swoole

Using the Task Worker function provided by Swoole, an asynchronous task queue can be implemented.

// Swoole异步任务队列
$serv = new SwooleServer("127.0.0.1", 9501);
$serv->set(array(
    'task_worker_num' => 4,
));

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

$serv->on('task', function ($serv, $task_id, $from_id, $data) use ($orderQueue) {
    $orderQueue[] = $data;
    echo "New Task: id=$task_id, data=$data
";
});

$serv->on('finish', function ($serv, $task_id, $data) {
    echo "Task Finished: id=$task_id, data=$data
";
});

$serv->start();

3. Use Swoole to implement queue consumers and producers

On the consumer side, we can use coroutines to process tasks. On the producer side, we just push the task into the queue.

// 消费者
Coun(function () use ($orderQueue) {
    while (true) {
        if (!empty($orderQueue)) {
            $order = array_shift($orderQueue);
            // 处理订单
            echo "Processing Order: $order
";
        }
        Co::sleep(0.1);
    }
});

// 生产者
for ($i = 1; $i <= 10000; $i++) {
    $data = "Order $i";
    $client = new SwooleClient(SWOOLE_SOCK_TCP, SWOOLE_SOCK_ASYNC);
    $client->on("connect", function($cli) use ($data){
        $cli->send($data . PHP_EOL);
    });
    $client->connect('127.0.0.1', 9501, 0.5);
}

4. Use Swoole to implement distributed queues

In order to cope with higher concurrency, we can use the distributed function provided by Swoole to process tasks on multiple servers.

// 生产者端
for ($i = 1; $i <= 10000; $i++) {
    $data = "Order $i";
    $server_list = array(
        array('host'=>'192.168.0.100', 'port'=>9501),
        array('host'=>'192.168.0.101', 'port'=>9501),
        array('host'=>'192.168.0.102', 'port'=>9501),
        array('host'=>'192.168.0.103', 'port'=>9501),
    );
    $client = new SwooleClient(SWOOLE_SOCK_TCP, SWOOLE_SOCK_ASYNC);
    $client->on("connect", function($cli) use ($data) {
        $cli->send($data . PHP_EOL);
    });
    $client->connect($server_list[array_rand($server_list)]['host'],
                     $server_list[array_rand($server_list)]['port'], 0.5);
}

// 服务端
$serv = new SwooleServer("127.0.0.1", 9501);

$serv->set(array(
    'task_worker_num' => 4,
    'worker_num' => 4,
    'task_ipc_mode' => 3,
    'message_queue_key' => 0x70001001,
));

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

$serv->on('task', function ($serv, $task_id, $from_id, $data) use ($orderQueue) {
    $orderQueue[] = $data;
    echo "New Task: id=$task_id, data=$data
";
    $serv->finish($data);
});

$serv->on('finish', function ($serv, $task_id, $data) {
    echo "Task Finished: id=$task_id, data=$data
";
});

$serv->start();

Through the above code, we can successfully use Swoole to build a high-performance order processing queue. This queue system can not only cope with high concurrency and high load scenarios, but also supports distributed deployment. We can build more complex and efficient business scenarios by optimizing this basic queue system.

5. Summary

This article mainly discusses how to use Swoole to build a high-performance queue system to cope with high-concurrency and high-load business scenarios. Through the above example, we introduced in detail the asynchronous task queue, consumer and producer based on Swoole, as well as the construction method of the distributed queue. I hope this article will help readers understand and use Swoole to build a high-performance queue system.

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