Building a real-time search engine with Redis and JavaScript: How to quickly respond to user queries-Redis-php.cn

Building a real-time search engine with Redis and JavaScript: How to quickly respond to user queries

王林

Release： 2023-07-29 11:53:10

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Using Redis and JavaScript to build a real-time search engine: How to quickly respond to user queries

Introduction:
In today's era of information explosion, users have increasingly higher requirements for the response speed of search engines, especially In real-time search scenarios. How to quickly respond to user queries has become an important issue faced by developers. This article will introduce how to use Redis and JavaScript to build a real-time search engine to achieve the goal of quickly responding to user queries.

Introduction
Redis is an open source in-memory database. Its high-speed read and write performance and flexible data structure make it one of the important components of real-time search engines. JavaScript is a scripting language widely used in front-end and back-end development. When used with Redis, it can realize the key functions of real-time search engines.
Preparation before building a search engine
In order to quickly respond to user query requests, you first need to store the data to be searched in Redis. Taking the product data in an e-commerce website as an example, the name, price and other information of the product can be stored in an ordered collection of Redis. The following is a sample code:

// 通过Redis连接池获取Redis实例
const redis = require("redis");
const client = redis.createClient();

// 添加商品到有序集合
client.zadd("products", 10, "iPhoneX");
client.zadd("products", 15, "iPad");
client.zadd("products", 8, "MacBook Pro");

// 查询有序集合中的商品
client.zrange("products", 0, -1, (error, result) => {
    if (error) throw error;
    console.log(result);
});

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Implementing the real-time query function
Next we need to implement the real-time query function, that is, when the user enters a keyword in the search box, the match will be returned in real time search results. In order to achieve this function, we can listen to user input events, then send keywords to Redis and obtain matching search results. The following is a sample code:

<!DOCTYPE html>
<html>
<head>
    <title>实时搜索引擎</title>
    <script src="https://cdn.jsdelivr.net/npm/redis/dist/redis-browser.js"></script>
    <script>
        // 通过Redis连接池获取Redis实例
        const redis = new Redis();

        // 监听用户输入事件
        const input = document.getElementById("search-input");
        input.addEventListener("input", (event) => {
            const keyword = event.target.value;

            // 根据关键字查询匹配的搜索结果

                if (error) throw error;
                console.log(result);
                // 显示搜索结果
                const resultDiv = document.getElementById("search-result");
                resultDiv.innerHTML = "";
                for (let i = 0; i < result.length; i++) {
                    const div = document.createElement("div");
                    div.innerText = result[i];
                    resultDiv.appendChild(div);
                }
            });
        });
    </script>
</head>
<body>
    <input id="search-input" type="text" placeholder="请输入关键字">
    <div id="search-result"></div>
</body>
</html>

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Through the above code, when the user enters a keyword in the input box, JavaScript will send a query request to Redis in real time and display the matching search results in the search results area.

Conclusion
Using Redis and JavaScript to build a real-time search engine can quickly respond to user query requests and provide a good search experience. This article introduces how to use Redis to store data and implement real-time query functions through JavaScript. I hope it will be helpful to developers building real-time search engines.

Summary:
This article introduces how to use Redis and JavaScript to build a real-time search engine, which covers sample code for storing data into Redis's ordered collection and how to implement real-time query functions. By properly utilizing Redis and JavaScript, we can build a real-time search engine that responds quickly to user queries. Of course, in actual projects, more complex business logic and performance optimization issues also need to be considered. I hope this article can inspire real-time search engine developers and enable them to continuously improve and optimize in practice.

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