System Design: Web Crawler

Learn about the web crawler service.

Introduction

A web crawler is an internet bot that systematically scoursTo go or move swiftly about, over, or through in search of something. the World Wide Web (WWW) for content, starting its operation from a pool of seed URLs. This process of acquiring content from the WWW is called the crawling process. The crawler further saves the content in data stores, ensuring the data is available for later use. Efficient storage and subsequent retrieval of this data are integral to designing a robust system.

The core functionality of a web crawler involves fetching web pages, parsing their content and metadata, and extracting new URLs or lists of URLs for further crawling. This is the first step performed by search engines. The output of the crawling process serves as input for subsequent stages such as:

  • Data cleaning

  • Indexing

  • Relevance scoring using algorithms like PageRank

  • URL frontier management

  • Analytics

This specific design problem is focused on web crawlers’ System Design and excludes explanations of the later stages of indexing, ranking in search engines, etc. To learn about some of these subsequent stages, refer to our chapter on distributed search.

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An overview of the web crawler system
An overview of the web crawler system

Benefits of a Web Crawler

Web crawlers offer various utilities beyond data collection:

  • Web page testing: Web crawlers test the validity of the links and structures of HTML pages.

  • Web page monitoring: We use web crawlers to monitor the content or structure updates on web pages.

  • Site mirroring: Web crawlers are an effective way to mirrorMirroring is like making a dynamic carbon copy of a website. Mirroring refers to network services available by any protocol, such as HTTP or FTP. The URLs of these sites differ from the original sites, but the content is similar or almost identical. popular websites.

  • Copyright infringement check: Web crawlers fetch and parse page content and check for copyright infringement issues.

Challenges of a Web Crawler System Design

While designing a web crawler, several challenges arise:

  • Crawler traps: Infinite loops caused by dynamic links or calendar pages.

  • Duplicate content: Crawling the same web pages repeatedly wastes resources.

  • Rate limiting: Fetching too many pages from a single domain can lead to server overload. We need load balancing to balance the loads on web servers or application servers.

  • DNS lookup latency: Frequent domain name system (DNS) lookups increase latency.

  • Scalability: Handling large-scale crawling is challenging and demands a distributed system that can process millions of seed URLs and distribute load across multiple web servers.

Designing a web crawler is a common System Design interview question to test candidates’ understanding of components like HTML fetcher, extractor, scheduler, etc. The interviewer can ask the following interesting questions:

  • How would you design a web crawler system that can handle large datasets, and how would you incorporate Redis for caching and Amazon web services (AWS) for scalability?

  • How would you handle request timeouts and manage rate limits set by websites?

  • What optimization strategies would you use for components like parser, fetcher, etc., for large-scale use cases like those at FAANG?

  • How metrics like response time, cache hit rate, etc., help evaluate web crawlers’ performance to crawl large datasets for aggregation.

Let’s now discuss how we will design a web crawler system.

How will we design a Web crawler?

In this chapter, we will explore a comprehensive approach to designing a web crawler system, ensuring both scalability and fault tolerance. This chapter consists of four lessons that encompass the overall design of the web crawler system:

  1. Requirements: This lesson enlists the functional and non-functional requirements of the system and estimates calculations for various system parameters.

  2. Design: This lesson analyzes a bottom-up approach for a web-crawling service. We get a detailed overview of all the individual components, leading to a combined operational mechanism to meet the requirements, along with APIs for communication with servers and data structure for storing data.

  3. Improvements: This lesson provides all the design improvements required to counter shortcomings, especially the crawler traps. These crawler traps include links with query parameters, internal links redirection, links holding infinite calendar pages, links for dynamic content generation, and links containing cyclic directories.

  4. Evaluation: This lesson provides an in-depth evaluation of our design choices to check if they meet all the standards and requirements we expect from our design.

Let’s begin with defining the requirements of a web crawler system.