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Design a Web Crawler

Overview​

A web crawler (also called a robot or spider) is used to discover and collect content from the web such as:

  • Web pages
  • Images
  • Videos
  • PDFs

It starts with a set of URLs and recursively follows links to discover more content.

Use Cases​

1. Search Engine Indexing​

  • Build searchable index of web pages
  • Example: Googlebot

2. Web Archiving​

  • Preserve web data for future use

3. Web Mining​

  • Extract insights (e.g., financial reports)

4. Web Monitoring​

  • Detect copyright or trademark violations

Basic Algorithm​

  1. Start with seed URLs
  2. Download web pages
  3. Extract URLs from pages
  4. Add new URLs to queue
  5. Repeat

🧠 Step 1: Requirements & Scope​

  • Purpose: Search engine indexing
  • Scale: 1 billion pages/month
  • Content: HTML only
  • Handle updates: Yes
  • Storage: 5 years
  • Deduplication: Required

Characteristics of a Good Crawler​

  • Scalability
  • Robustness
  • Politeness
    • Meaning not getting rate-limited
  • Extensibility
    • for now we are supporting html but we should be easily able to extend for image/vedios as well

Back-of-the-Envelope Estimation​

  • QPS ≈ 400
  • Peak QPS ≈ 800
  • Storage (5 years) ≈ 30 PB

High-Level Design Components​

  • Seed URLs
  • URL Frontier
  • HTML Downloader
  • DNS Resolver
  • Content Parser
  • Content Seen (Deduplication)
  • Content Storage
  • URL Extractor
  • URL Filter
  • URL Seen
  • URL Storage

Workflow​

  1. Add seed URLs → URL Frontier
  2. Fetch URLs → Downloader
  3. Resolve DNS → Download HTML
  4. Parse content
  5. Check duplicate content
  6. Store if new
  7. Extract links
  8. Filter URLs
  9. Check if URL seen
  10. Add new URLs to frontier

Deep Dive​

BFS vs DFS​

  • BFS preferred
    • as we pick this as because of FIFO order and also help in implementation
    • we also keep in mind priority of webpage based on page rank, traffic and all
  • DFS can go too deep

URL Frontier Goals​

It is a data structure which stores urls to be downloaded next

  • Politeness
  • Priority
  • Freshness

Politeness​

  • Avoid too many requests per host
  • Use host-based queues

Priority​

  • Based on importance (PageRank, traffic)
  • Multiple priority queues

Freshness​

  • Recrawl based on update frequency

Storage Strategy​

  • Disk for scale
  • Memory for speed

HTML Downloader​

Robots.txt​

  • Respect crawl rules
  • Cache results

Performance Optimizations​

  • Distributed crawling
  • DNS caching
  • Locality
  • Timeouts

Handling Problematic Content​

Duplicate Content​

  • Use hashing

Spider Traps​

  • Limit URL depth
  • Detect abnormal patterns

Data Noise​

  • Filter spam, ads