Massive data storage and paging query optimization in PHP flash sale system

Mass data storage and paging query optimization in PHP flash sale system

1. Introduction
With the rapid development of the e-commerce industry, various promotional activities have become An important means to attract users, and flash sales, as a highly concentrated type of online promotion activity, place extremely high requirements on the performance and stability of the system. Among them, massive data storage and paging query optimization are one of the keys to building an efficient flash sale system. This article will introduce how to perform massive data storage and paging query optimization in the PHP flash sale system, and provide specific code examples.

2. Massive data storage
The massive data in the flash sale system mainly includes product information, user orders, etc. For product information, we can use a database to store it. Commonly used database software includes MySQL, Redis, etc. When storing product information, the following optimization strategies can be adopted:

1. Data redundancy: In order to improve the concurrent processing capability of the system, part of the product information, such as product name, price and other commonly used fields, can be redundant. This can reduce the query operations on persistent storage and speed up the system's response speed.
2. Cache data: Use a cache server such as Redis to cache product information. By setting a reasonable expiration time and cache update strategy, you can reduce the load on the database and improve the system's reading speed.

For data such as user orders and flash sale purchase records, due to frequent read and write operations, you can consider using NoSQL databases such as MongoDB, Cassandra, etc. for storage. This type of database has high concurrent reading and writing capabilities and massive data storage capabilities, which can meet the needs of the flash sale system.

3. Paging query optimization
In the flash sale system, users often need to browse and purchase products through paging queries. For paging queries of massive data, we can use the following optimization strategies:

1. Paging processing: By using database paging query statements, such as the LIMIT statement in MySQL, the specified number of pages can be directly returned on the server side data without returning all data. A large amount of data processing and transmission on the server side is avoided.
2. Front-end data rendering: Use front-end technologies such as Ajax to send paging query requests to the server, and then render the returned data into the page. This can distribute the processing and transmission of data to the client and reduce the server load.
3. Data cache: For frequently queried data, you can use a cache server such as Redis for caching. Cache data in memory to speed up queries.

The following is an example that shows how to optimize paging queries in the PHP flash kill system:

<?php

// 分页查询商品列表
function getGoodsByPage($page, $pagesize) {
    $start = ($page - 1) * $pagesize;
    $end = $start + $pagesize - 1;

    // 使用缓存服务器获取商品列表数据
    $redis = new Redis();
    $redis->connect('127.0.0.1', 6379);
    $goodsList = $redis->lrange('goods_list', $start, $end);

    // 假设需要获取商品的详细信息
    $goodsInfoList = [];
    foreach ($goodsList as $goodsId) {
        // 从数据库中查询商品详细信息
        $goodsInfo = getGoodsInfoById($goodsId);

        $goodsInfoList[] = $goodsInfo;
    }

    return $goodsInfoList;
}

// 查询商品详细信息
function getGoodsInfoById($goodsId) {
    // 查询缓存中是否存在商品信息
    $redis = new Redis();
    $redis->connect('127.0.0.1', 6379);
    $goodsInfo = $redis->hget('goods_info', $goodsId);

    // 如果缓存中不存在，则从数据库中查询商品信息
    if (!$goodsInfo) {
        // 查询数据库
        $mysql = new mysqli('localhost', 'username', 'password', 'database');
        $sql = "SELECT * FROM goods WHERE id = $goodsId";
        $result = $mysql->query($sql);
        $row = $result->fetch_assoc();

        $goodsInfo = json_encode($row);

        // 将商品信息存储到缓存中
        $redis->hset('goods_info', $goodsId, $goodsInfo);
    }

    return json_decode($goodsInfo, true);
}

?>

Through the above optimization strategies and code examples, the PHP flash kill system can be made It can achieve higher performance and response speed when storing and paging massive data.

4. Summary
Massive data storage and paging query optimization are crucial to building an efficient PHP flash sale system. Through reasonable data storage strategies and paging query optimization, the system's concurrent processing capabilities and user experience can be improved, and the system's stability can be increased. At the same time, it is also necessary to select appropriate databases and cache servers based on specific business needs and system scale to ensure system performance and scalability.

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