CASE STUDY

Web Crawler

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How to use this case study

SDE-2 / Mid

Study the full Web Crawler case study. Focus on understanding the core components and how they interact. Focus on sections 1-3: requirements, API design, and high-level architecture. Understand the URL frontier, politeness policy, and deduplication.

SDE-3 / Senior

Study the full Web Crawler case study. Focus on understanding the core components and how they interact. Be ready to discuss the distributed URL frontier design, how to handle 10K pages/sec crawl rate, and the content fingerprinting for deduplication.

Staff / Principal

Study the full Web Crawler case study. Focus on understanding the core components and how they interact. Be prepared to discuss the crawl scheduling algorithm, how to handle JavaScript-rendered pages, and the distributed architecture for 10B+ pages. Discuss the robots.txt parsing and compliance system.

# Web Crawler \

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0) Problem Restatement\

Design a distributed web crawler that can efficiently traverse the internet, download web pages, extract links, and index content for a search engine. The core challenges are avoiding duplicate crawling, respecting politeness policies, handling failures, and scaling to billions of pages.\

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1) Requirements\

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1.1 Functional\

  • Crawl web pages starting from seed URLs.\
  • Extract and follow links from downloaded pages.\
  • Store page content and metadata.\
  • Respect robots.txt and politeness policies.\
  • Support incremental and recurring crawls (freshness).\
  • Handle different content types (HTML, PDF, images, etc.).\
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1.2 Non-Functional\

  • Scalability: Crawl billions of pages across millions of domains.\
  • Politeness: Avoid overloading servers (rate limiting per domain). Example: If you crawl *example.com/page1*, wait 1 second before crawling *example.com/page2*. But you can simultaneously crawl *other-site.com/page1* (different domain)\
  • Robustness: Handle failures, malformed HTML, redirects, timeouts.\
  • Efficiency: High throughput (thousands of pages/sec).\
  • Freshness: Re-crawl important pages regularly.\
  • Deduplication: Avoid crawling duplicate URLs and content.\
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1.3 Scale Estimates\

  • Total pages: 10 billion pages to crawl.\
  • Crawl rate: 10,000 pages/second.\
  • Avg page size: 100 KB.\
  • Storage: 10B × 100 KB = 1 PB (raw HTML).\
  • Recrawl interval: Monthly for most pages, hours/days for critical content.\
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2) High-Level Architecture\

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2.1 Overview\

  • Frontier (URL queue) → Crawler WorkersDNS ResolverDownloaderContent ProcessorStorage (HTML, metadata, index).\
  • Key challenges: URL deduplication, politeness enforcement, distributed coordination, failure recovery.\
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2.2 Architecture Diagram\

```mermaid\

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config:\

layout: elk\

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flowchart TB\

%% Seed URLs and Frontier\

Seeds[\

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