Design a web crawler in HLD - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Architecture

intermediate

Identify the main components of a web crawler architecture

Which of the following lists correctly represents the essential components of a scalable web crawler system?

A Parser, Renderer, User Tracker, URL Frontier, Logger

B User Interface, Database, Cache, Logger, Scheduler

C Load Balancer, API Gateway, Authentication, Fetcher, Parser

D URL Frontier, Fetcher, Parser, URL Filter, Storage

💡 Hint

Think about the components that handle URL management, downloading pages, and storing data.

A web crawler needs to manage URLs to visit (URL Frontier), download pages (Fetcher), extract links and content (Parser), filter URLs to avoid duplicates or unwanted sites (URL Filter), and store the data (Storage).

❓ scaling

intermediate

Scaling the URL Frontier in a distributed crawler

What is the best approach to scale the URL Frontier component to handle billions of URLs efficiently?

A Partition URLs by domain and distribute queues across multiple servers

B Store all URLs in a relational database with ACID transactions

C Use a centralized queue stored on a single server with large memory

D Keep URLs in local files on each crawler node without coordination

💡 Hint

Consider how to avoid bottlenecks and balance load across servers.

Partitioning URLs by domain and distributing queues allows parallel processing and avoids a single bottleneck, making the system scalable.

❓ tradeoff

advanced

Tradeoffs in politeness and crawling speed

Which option best describes the tradeoff between politeness (respecting website rules) and crawling speed in a web crawler?

A Ignoring robots.txt and crawling aggressively increases speed but risks IP bans

B Politeness has no impact on crawling speed or system design

C Crawling slowly with delays respects politeness but reduces throughput

D Using multiple IPs allows fast crawling without any politeness concerns

💡 Hint

Think about how respecting website rules affects how fast you can crawl.

Respecting politeness means adding delays between requests to the same site, which reduces crawling speed but avoids overloading servers or getting banned.

🧠 Conceptual

advanced

Handling duplicate content in web crawling

What is the most effective method to detect and avoid storing duplicate pages in a web crawler system?

A Use hash functions on page content and compare hashes

B Compare full page content byte-by-byte before storing

C Store all pages and remove duplicates later manually

D Ignore duplicates and rely on URL uniqueness only

💡 Hint

Think about a fast way to check if content is the same without storing everything twice.

Using hash functions like MD5 or SHA on page content allows quick comparison to detect duplicates without storing full content multiple times.

❓ estimation

expert

Estimating storage needs for a large-scale web crawler

If a web crawler downloads 1 billion pages per year, each averaging 500 KB, what is the approximate storage needed per year (in terabytes) to store raw pages without compression?

A Approximately 180 TB

B Approximately 500 TB

C Approximately 15 TB

D Approximately 1000 TB

💡 Hint

Calculate total bytes: pages × size, then convert to terabytes (1 TB = 10^12 bytes).

1 billion pages × 500 KB = 10^9 × 500 × 10^3 bytes = 5 × 10^14 bytes. 5 × 10^14 / 10^12 = 500 TB.

Practice

1. What is the primary role of a web crawler in system design?

easy

A. To manage user authentication on websites

B. To display web pages to users

C. To automatically visit and collect data from websites

D. To store user preferences for websites

Solution

1. Step 1: Understand the function of a web crawler

   A web crawler is designed to visit websites automatically and collect data for indexing or analysis.

2. Step 2: Differentiate from other web functions

   Displaying pages, managing authentication, or storing preferences are not tasks of a crawler but of browsers or web servers.

3. Final Answer:

   To automatically visit and collect data from websites -> Option C

4. Quick Check:

   Web crawler = data collection [OK]

Hint: Crawler means automatic website data collection [OK]

Common Mistakes:

• Confusing crawler with browser functionality
• Thinking crawler manages user data
• Mixing crawler with server-side tasks

2. Which component is essential for managing the list of URLs to visit in a web crawler?

easy

A. User Interface

B. URL Frontier

C. Data Storage

D. HTML Parser

Solution

1. Step 1: Identify the URL management part

   The URL Frontier is the component that keeps track of URLs to be visited next in a crawler.

2. Step 2: Exclude unrelated components

   HTML Parser processes page content, Data Storage saves data, and User Interface is unrelated to URL management.

3. Final Answer:

   URL Frontier -> Option B

4. Quick Check:

   URL list manager = URL Frontier [OK]

Hint: URL list is managed by URL Frontier [OK]

Common Mistakes:

• Confusing parser with URL manager
• Thinking storage manages URLs
• Assuming UI handles crawling logic

3. Consider a crawler fetching pages with a politeness delay of 2 seconds per domain. If it visits 5 domains concurrently, how many pages can it fetch in 10 seconds?

medium

A. 50 pages

B. 10 pages

C. 5 pages

D. 25 pages

Solution

1. Step 1: Calculate pages per domain in 10 seconds

   With 2 seconds delay, each domain can be fetched 10 / 2 = 5 times in 10 seconds.

2. Step 2: Multiply by number of domains

   5 domains * 5 pages each = 25 pages total.

3. Final Answer:

   25 pages -> Option D

4. Quick Check:

   5 domains * 5 pages = 25 [OK]

Hint: Pages = (time/delay) * domains [OK]

Common Mistakes:

• Multiplying delay by domains incorrectly
• Ignoring concurrency in calculation
• Using total time as pages directly

4. A web crawler's URL Frontier is implemented as a simple queue. What problem might arise with this design?

medium

A. It may revisit the same URLs multiple times

B. It will fetch pages too quickly without delay

C. It cannot parse HTML content correctly

D. It will store data inefficiently

Solution

1. Step 1: Understand queue behavior in URL management

   A simple queue does not track visited URLs, so duplicates can be added and revisited.

2. Step 2: Identify consequences

   This causes repeated crawling of same pages, wasting resources.

3. Final Answer:

   It may revisit the same URLs multiple times -> Option A

4. Quick Check:

   Queue alone lacks duplicate check [OK]

Hint: Queue alone misses duplicate URL checks [OK]

Common Mistakes:

• Confusing queue with parser or storage issues
• Assuming queue controls fetch speed
• Thinking queue affects data storage

5. You want to design a scalable web crawler that respects website politeness and avoids overloading servers. Which approach best achieves this?

hard

A. Use distributed crawling with domain-based rate limiting and URL deduplication

B. Fetch all URLs as fast as possible without delay to maximize speed

C. Store all URLs in a single server queue without concurrency control

D. Ignore robots.txt and crawl all pages aggressively

Solution

1. Step 1: Identify scalability and politeness needs

   Distributed crawling allows scaling; domain-based rate limiting ensures politeness; URL deduplication prevents repeated visits.

2. Step 2: Evaluate other options

   Fetching fast without delay overloads servers; single queue limits scalability; ignoring robots.txt is unethical and risky.

3. Final Answer:

   Use distributed crawling with domain-based rate limiting and URL deduplication -> Option A

4. Quick Check:

   Distributed + rate limit + deduplication = scalable polite crawler [OK]

Hint: Combine distribution, rate limits, and deduplication [OK]

Common Mistakes:

• Ignoring politeness rules
• Centralizing all URLs causing bottlenecks
• Disregarding robots.txt rules