How to implement a search function in nodejs

As we all know, modern network technology has reached an extremely developed level, and a large amount of information exists on the Internet, increasing every day with people's use. Therefore, search engines have become an essential tool for our daily use. In the field of back-end development, Node.js is one of the most popular and widely used technologies. Because it can easily handle a large number of concurrent requests. In this article, we will discuss how to use Node.js to build a powerful and scalable search engine.

Step 1: Install Node.js

First, we need to install Node.js on our system. This is obtained via the download page on the official website [nodejs.org](nodejs.org). After downloading, follow the regular steps to install and use the node command. Verify that the installation was successful by entering the following command:

node -v

Step 2: Create Project

We first create a new Node.js project and add some necessary files and modules for ease of use . This can be done in the command line interface with the following command:

mkdir search-engine && cd search-engine
npm init -y
touch index.js

In the project root directory, we created a new folder and entered that folder. We then use the npm init command to generate a new package.json file that lists our project’s code dependencies, authors, and other configuration. Once done, we create a main file called index.js, this is where we will write most of our search logic.

Step 3: Add the ElasticSearch module

In the Node.js project, we need to use the ElasticSearch module to perform search operations. This module provides many functions such as creating indexes, searching documents and deleting data, which can be configured and used according to the needs of the project. In order to use it, we need to install it using the following command:

npm install elasticsearch --save

Step 4: Implement the search function

We start to implement the search function by converting the found data into the document format in ElasticSearch . This can be done using the following code:

const data = [
    { title: '文章1', body: '8月6日讯 北京市公安局交通管理局昨日通报称，自2018年8月5日至8月6日...（略）...', id: 1 },
    { title: '文章2', body: '8月6日讯 北京市公安局交通管理局昨日通报称，自2018年8月5日至8月6日...（略）...', id: 2 },
    { title: '文章3', body: '8月6日讯 北京市公安局交通管理局昨日通报称，自2018年8月5日至8月6日...（略）...', id: 3 },
    { title: '文章4', body: '8月6日讯 北京市公安局交通管理局昨日通报称，自2018年8月5日至8月6日...（略）...', id: 4 },
    { title: '文章5', body: '8月6日讯 北京市公安局交通管理局昨日通报称，自2018年8月5日至8月6日...（略）...', id: 5 },
    { title: '文章6', body: '8月6日讯 北京市公安局交通管理局昨日通报称，自2018年8月5日至8月6日...（略）...', id: 6 },
]

data.forEach(({ title, body, id }) => {
        elasticClient.index({
            index,
            body: {
                id,
                title,
                body
            }
        })
    })

Now, we are ready to use ElasticSearch to perform search operations. We want to encapsulate the search process in a function called search. This function takes multiple parameters such as query string, document type, and number of results. The code to implement search is as follows:

async function search({ query, type, limit }) {
        const { body } = await elasticClient.search({
            index,
            type,
            body: {
                size: limit,
                query: {
                    match: {
                        title: {
                            query,
                            fuzziness: 2
                        }
                    }
                }
            }
        });

        return body.hits.hits.map(({ _source }) => _source);
    }

Now, we can implement a simple but powerful search engine in Node.js. It can be used for a variety of use cases such as web applications, internal enterprise search, and data analysis.

To sum up, Node.js is a powerful development tool that can help us build back-end systems that are highly scalable and capable of handling a large number of requests. By learning the usage of individual modules, we can build our own search engine to support our project needs. Node.js remains one of the best backend technologies to use because it excels at things like handling requests and performing searches. Through the study and practice of this article, I hope it will be helpful to readers in the development of search functions using Node.js.

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