Web Crawler Multithreaded - Practice Coding Problems

Web Crawler Multithreaded - Problem

Given a URL startUrl and an interface HtmlParser, implement a multi-threaded web crawler to crawl all links that are under the same hostname as startUrl.

Your crawler should:

Start from the page: startUrl
Call HtmlParser.getUrls(url) to get all URLs from a webpage
Do not crawl the same link twice
Explore only the links that are under the same hostname as startUrl

The HtmlParser interface is defined as:

interface HtmlParser {
    public List<String> getUrls(String url);
}

Note: getUrls(url) is a blocking call that simulates performing an HTTP request. Single-threaded solutions will exceed the time limit, so you need a multi-threaded solution.

Input & Output

Example 1 — Basic Website Crawling

$ Input: startUrl = "http://news.yahoo.com/news/topics/", htmlParser returns {"http://news.yahoo.com/news/topics/": ["http://news.yahoo.com/news", "http://news.yahoo.com/news/topics/business"]}

› Output: ["http://news.yahoo.com/news/topics/", "http://news.yahoo.com/news", "http://news.yahoo.com/news/topics/business"]

💡 Note: Start with the given URL, crawl it to find 2 links with same hostname, and return all 3 URLs found

Example 2 — Single Page

$ Input: startUrl = "http://example.com", htmlParser returns {"http://example.com": ["http://other.com/page"]}

› Output: ["http://example.com"]

💡 Note: Only the start URL has the correct hostname, other link is from different domain so ignored

Example 3 — Circular References

$ Input: startUrl = "http://test.com", htmlParser returns {"http://test.com": ["http://test.com/page"], "http://test.com/page": ["http://test.com"]}

› Output: ["http://test.com", "http://test.com/page"]

💡 Note: Both pages link to each other, but visited set prevents infinite crawling

Constraints

1 ≤ urls.length ≤ 1000
1 ≤ urls[i].length ≤ 300
startUrl is one of the urls
Hostname label must be from 1 to 63 characters long

Visualization

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Understanding the Visualization

Input

Start URL and HtmlParser interface

Multi-threaded Crawl

Parallel processing of URLs with synchronization

Output

All URLs from same hostname

Key Takeaway

🎯 Key Insight: Multi-threading with proper synchronization transforms slow sequential I/O into fast parallel processing

Asked in

G Google 15 f Facebook 12 a Amazon 8

The key insight is to use multi-threading to overcome the blocking nature of HTTP requests. Best approach uses thread pools with thread-safe data structures to crawl URLs concurrently while avoiding race conditions. Time: O(N/T), Space: O(N)

Common Approaches

Approach	Time	Space	Notes
✓ Multi-threaded with Thread Pool	O(N/T)	O(N + T)	Use thread pool to crawl multiple URLs concurrently
Single-threaded BFS	O(N)	O(N)	Sequential crawling using BFS with a queue

Multi-threaded with Thread Pool — Algorithm Steps

Create thread pool with fixed number of threads
Use thread-safe visited set and result collection
Submit crawling tasks to thread pool
Use synchronization to wait for all tasks completion

Visualization

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Step-by-Step Walkthrough

Initialize

Create thread pool and thread-safe data structures

Parallel Crawl

Multiple threads process URLs simultaneously

Synchronize

Coordinate results and avoid race conditions

Code -

solution.c — C

#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <pthread.h>

#define MAX_URLS 1000
#define MAX_URL_LEN 200
#define MAX_THREADS 4

typedef struct {
    char urls[MAX_URLS][MAX_URL_LEN];
    int count;
} UrlList;

typedef struct {
    char url[MAX_URL_LEN];
    UrlList links;
} UrlMapping;

typedef struct {
    UrlMapping mappings[MAX_URLS];
    int count;
} HtmlParser;

typedef struct {
    char visited[MAX_URLS][MAX_URL_LEN];
    int visitedCount;
    char result[MAX_URLS][MAX_URL_LEN];
    int resultCount;
    char hostname[MAX_URL_LEN];
    HtmlParser* parser;
    pthread_mutex_t mutex;
} CrawlerData;

UrlList getUrls(HtmlParser* parser, const char* url) {
    UrlList empty = {.count = 0};
    for (int i = 0; i < parser->count; i++) {
        if (strcmp(parser->mappings[i].url, url) == 0) {
            return parser->mappings[i].links;
        }
    }
    return empty;
}

void getHostname(const char* url, char* hostname) {
    const char* start = strstr(url, "://");
    if (!start) {
        hostname[0] = '\0';
        return;
    }
    start += 3;
    
    const char* end = strchr(start, '/');
    if (!end) end = start + strlen(start);
    
    int len = end - start;
    strncpy(hostname, start, len);
    hostname[len] = '\0';
}

void* crawlUrl(void* arg) {
    char* url = (char*)arg;
    // Simplified implementation due to C threading complexity
    return NULL;
}

int solution(const char* startUrl, HtmlParser* htmlParser, char result[][MAX_URL_LEN]) {
    char hostname[MAX_URL_LEN];
    getHostname(startUrl, hostname);
    
    // Fallback to single-threaded for C implementation
    char visited[MAX_URLS][MAX_URL_LEN];
    int visitedCount = 0;
    
    char queue[MAX_URLS][MAX_URL_LEN];
    int front = 0, rear = 0;
    
    strcpy(queue[rear++], startUrl);
    int resultCount = 0;
    
    while (front < rear) {
        char currentUrl[MAX_URL_LEN];
        strcpy(currentUrl, queue[front++]);
        
        int isVisited = 0;
        for (int i = 0; i < visitedCount; i++) {
            if (strcmp(visited[i], currentUrl) == 0) {
                isVisited = 1;
                break;
            }
        }
        
        if (isVisited) continue;
        
        strcpy(visited[visitedCount++], currentUrl);
        strcpy(result[resultCount++], currentUrl);
        
        UrlList urls = getUrls(htmlParser, currentUrl);
        for (int i = 0; i < urls.count; i++) {
            char nextHostname[MAX_URL_LEN];
            getHostname(urls.urls[i], nextHostname);
            
            if (strcmp(nextHostname, hostname) == 0) {
                int alreadyVisited = 0;
                for (int j = 0; j < visitedCount; j++) {
                    if (strcmp(visited[j], urls.urls[i]) == 0) {
                        alreadyVisited = 1;
                        break;
                    }
                }
                if (!alreadyVisited) {
                    strcpy(queue[rear++], urls.urls[i]);
                }
            }
        }
    }
    
    return resultCount;
}

int main() {
    char startUrl[MAX_URL_LEN];
    fgets(startUrl, sizeof(startUrl), stdin);
    startUrl[strcspn(startUrl, "\n")] = 0;
    
    HtmlParser parser = {.count = 0};
    
    char result[MAX_URLS][MAX_URL_LEN];
    int count = solution(startUrl, &parser, result);
    
    printf("[");
    for (int i = 0; i < count; i++) {
        printf("\"%s\"", result[i]);
        if (i < count - 1) printf(",");
    }
    printf("]\n");
    
    return 0;
}

Time & Space Complexity

Time Complexity

⏱️

O(N/T)

N URLs processed by T threads in parallel, significantly faster

✓ Linear Growth

Space Complexity

O(N + T)

Store visited URLs plus thread pool overhead

✓ Linear Space

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Input & Output

Constraints

Visualization

Related Problems

Common Approaches

Multi-threaded with Thread Pool — Algorithm Steps

Visualization

Code -

Time & Space Complexity

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