Design a web crawler in HLD - System Design Guide

Problem Statement

When a system tries to gather information from the web, it can easily get overwhelmed by the huge number of pages and links. Without a structured way to visit and collect data, it may miss important pages, revisit the same pages repeatedly, or overload websites with too many requests at once.

Solution

A web crawler systematically visits web pages by starting from a set of seed URLs, fetching their content, extracting links, and adding new links to a queue for future visits. It uses a scheduler to manage the order of URLs, respects website rules to avoid overloading, and stores visited URLs to prevent repeated crawling.

Architecture

Seed URLs

→URL Scheduler

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↓

Visited URL Store

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URL Frontier

URL Frontier

This diagram shows the flow of URLs starting from seed URLs, moving through scheduling, fetching, parsing, and storing visited URLs, with extracted links feeding back into the URL frontier for continuous crawling.

Trade-offs

✓ Pros

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Efficiently manages large-scale web crawling by scheduling and queueing URLs.

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Prevents repeated visits to the same page by tracking visited URLs.

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Respects website load by controlling request rates and obeying robots.txt rules.

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Modular design allows easy scaling and maintenance.

✗ Cons

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Requires significant storage and memory to track visited URLs and manage queues at scale.

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Complexity increases with handling dynamic content and JavaScript-heavy sites.

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Latency can increase due to politeness delays and network variability.

When needing to crawl millions of web pages regularly with respect to website policies and when data freshness and coverage are important.

For small-scale or one-time data collection where a simple script suffices and overhead of a full crawler is unnecessary.

Real World Examples

Google

Google uses a distributed web crawler to index billions of web pages efficiently while respecting site rules and managing huge URL queues.

Bing

Bing's crawler prioritizes URLs based on freshness and importance to keep its search index updated and relevant.

Amazon

Amazon uses web crawlers to monitor competitor pricing and product availability by systematically visiting e-commerce sites.

Alternatives

Focused Crawler

Crawls only pages related to specific topics or keywords instead of the entire web.

Use when: When you need targeted data collection and want to reduce resource usage by ignoring irrelevant pages.

Incremental Crawler

Crawls only pages that have changed since the last crawl to save bandwidth and processing.

Use when: When data freshness is critical and full recrawling is too costly.

Deep Web Crawler

Designed to access content behind forms or requiring interaction, unlike standard crawlers that follow links.

Use when: When you need to extract data from dynamic or hidden web content.

Summary

A web crawler systematically visits web pages by managing URLs through scheduling, fetching, parsing, and storing.

It prevents overload and repeated visits by tracking visited URLs and respecting website rules.

This design supports large-scale, efficient, and polite data collection from the web.