Design a web crawler in HLD - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to specify the main component responsible for fetching web pages.

HLD

The web crawler starts with the [1] component to download web pages.

Drag options to blanks, or click blank then click option'

AFetcher

BIndexer

CURL Scheduler

DParser

Attempts:

3 left

💡 Hint

Common Mistakes

Confusing the Fetcher with the Parser or Scheduler.

The Fetcher is the component that downloads web pages from the internet.

2fill in blank

medium

Complete the code to identify the component that manages the list of URLs to visit.

HLD

The [1] manages the queue of URLs that the crawler needs to visit next.

Drag options to blanks, or click blank then click option'

AParser

BFetcher

CURL Scheduler

DIndexer

Attempts:

3 left

💡 Hint

Common Mistakes

Mixing up the Scheduler with the Fetcher or Parser.

The URL Scheduler keeps track of URLs to crawl and controls the order of crawling.

3fill in blank

hard

Fix the error in the component that extracts links from downloaded pages.

HLD

The [1] extracts URLs and content from the fetched web pages.

Drag options to blanks, or click blank then click option'

AParser

BFetcher

CIndexer

DScheduler

Attempts:

3 left

💡 Hint

Common Mistakes

Confusing the Parser with the Fetcher or Indexer.

The Parser analyzes the page content and extracts links and data.

4fill in blank

hard

Fill both blanks to complete the description of the crawler's storage components.

HLD

The [1] stores the raw web pages, while the [2] stores the processed data for search.

Drag options to blanks, or click blank then click option'

AContent Repository

BURL Scheduler

CIndex

DFetcher

Attempts:

3 left

💡 Hint

Common Mistakes

Mixing storage roles or confusing with fetching components.

The Content Repository saves raw pages; the Index stores searchable data.

5fill in blank

hard

Fill all three blanks to complete the request flow in the crawler system.

HLD

First, the [1] selects a URL, then the [2] downloads the page, and finally the [3] extracts links and data.

Drag options to blanks, or click blank then click option'

AURL Scheduler

BFetcher

CParser

DIndexer

Attempts:

3 left

💡 Hint

Common Mistakes

Mixing the order or confusing components.

The Scheduler picks URLs, the Fetcher downloads pages, and the Parser extracts data.

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