Build a simple web crawler using Redis and JavaScript: How to quickly crawl data

Using Redis and JavaScript to build a simple web crawler: how to quickly crawl data

Introduction:
A web crawler is a program tool that obtains information from the Internet. It can automatically access web pages and parse them the data in it. Using web crawlers, we can quickly crawl large amounts of data to provide support for data analysis and business decisions. This article will introduce how to build a simple web crawler using Redis and JavaScript, and demonstrate how to quickly crawl data.

1. Environment preparation
   Before starting, we need to prepare the following environment:
2. Redis: used as the task scheduler and data storage of the crawler.
3. Node.js: Run JavaScript code.
4. Cheerio: A library for parsing HTML pages.
5. Crawler architecture design
   Our crawler will adopt a distributed architecture and be divided into two parts: task scheduler and crawler node.

• Task Scheduler: Responsible for adding URLs to be crawled to the Redis queue, and performing deduplication and priority settings as needed.
• Crawler node: Responsible for obtaining the URL to be crawled from the Redis queue, parsing the page, extracting data and storing it in Redis.

3. Task scheduler code example
   The task scheduler code example is as follows:

const redis = require('redis');
const client = redis.createClient();

// 添加待抓取的URL到队列
const enqueueUrl = (url, priority = 0) => {
  client.zadd('urls', priority, url);
}

// 从队列中获取待抓取的URL
const dequeueUrl = () => {
  return new Promise((resolve, reject) => {
    client.zrange('urls', 0, 0, (err, urls) => {
      if (err) reject(err);
      else resolve(urls[0]);
    })
  })
}

// 判断URL是否已经被抓取过
const isUrlVisited = (url) => {
  return new Promise((resolve, reject) => {
    client.sismember('visited_urls', url, (err, result) => {
      if (err) reject(err);
      else resolve(!!result);
    })
  })
}

// 将URL标记为已经被抓取过
const markUrlVisited = (url) => {
  client.sadd('visited_urls', url);
}

In the above code, we use Redis Sorted set and set data structure, ordered set urls is used to store URLs to be crawled, and set visited_urls is used to store URLs that have been crawled.

4. Crawler node code example
   The code example of the crawler node is as follows:

const request = require('request');
const cheerio = require('cheerio');

// 从指定的URL中解析数据
const parseData = (url) => {
  return new Promise((resolve, reject) => {
    request(url, (error, response, body) => {
      if (error) reject(error);
      else {
        const $ = cheerio.load(body);
        // 在这里对页面进行解析，并提取数据
        // ...

        resolve(data);
      }
    })
  })
}

// 爬虫节点的主逻辑
const crawler = async () => {
  while (true) {
    const url = await dequeueUrl();
    if (!url) break;

    if (await isUrlVisited(url)) continue;

    try {
      const data = await parseData(url);

      // 在这里将数据存储到Redis中
      // ...

      markUrlVisited(url);
    } catch (error) {
      console.error(`Failed to parse data from ${url}`, error);
    }
  }
}

crawler();

In the above code, we used the request library Send an HTTP request and use the cheerio library to parse the page. In the parseData function, we can use the cheerio library to parse the page and extract data according to the specific page structure and data extraction requirements. In the main logic of the crawler node, we loop to obtain the URL to be crawled from the Redis queue, and perform page parsing and data storage.

Summary:
By utilizing Redis and JavaScript, we can build a simple but powerful web crawler to quickly crawl large amounts of data. We can use the task scheduler to add the URL to be crawled to the Redis queue, and obtain the URL from the queue in the crawler node for page parsing and data storage. This distributed architecture can improve crawling efficiency, and through the data storage and high-performance features of Redis, large amounts of data can be easily processed.

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