System Design: Designing a Web Crawler

A Web Crawler (or spider) is an automated system that browses the World Wide Web in a methodical, automated manner to index content for search engines like Google or Bing.

1. Core Requirements

• Scalability: The crawler should be able to crawl billions of pages.
• Politeness: The crawler must respect robots.txt and not overwhelm a single server with requests.
• Deduplication: Avoiding crawling the same content multiple times.
• Freshness: Re-crawling updated pages while prioritizing important ones.

2. The URL Frontier

The URL Frontier is the most critical component. It is a data structure that stores all the URLs to be crawled.

• Prioritization: Prioritize high-authority domains (like .gov or .edu) or frequently updated news sites.
• Politeness Manager: Ensures that multiple threads are not hitting the same domain simultaneously. It uses a mapping of domain -> queue to maintain a delay between requests to the same server.

3. The Fetcher and DNS Resolver

• HTML Fetcher: Downloads the page content via HTTP.
• DNS Resolver: To avoid the latency of public DNS lookups, the crawler maintains a local DNS Cache of frequently visited IP addresses.

4. Content Deduplication (The "Fingerprint")

The web is full of duplicate content. To save storage and bandwidth:

• Fingerprinting: Instead of comparing full HTML, we use a hash function (like Simhash) to create a 64-bit fingerprint of the page content. If the hash already exists in our Seen Content DB, we discard the page.

5. URL Deduplication

Before adding a URL to the Frontier, we check if we've already crawled it.

• Bloom Filter: Use a Bloom Filter in RAM for a fast "No, I haven't seen this URL" check. If it's a "Maybe," we check the main URL Database on disk.

6. Distributed Architecture

• Worker Nodes: Multiple machines running the Fetcher and Parser logic.
• Messaging: Use Apache Kafka or RabbitMQ to distribute URLs from the Frontier to the worker nodes.
• Storage: Use a distributed NoSQL store like HBase or BigTable to store the crawled metadata and page summaries.

Summary

Building a web crawler is a massive distributed systems problem. By focusing on a robust URL Frontier, respecting Politeness, and implementing efficient Deduplication, you can build a system that indexes the vast complexity of the internet.