The Arduous Life of a Web Crawler – Challenges in Web Crawling
Ever wondered how Google can display a million search results in less than a second? Its because Google has indexed all the pages in their library so that it can return relevant results based on user’s search query. However, the web is dynamic, and thousands of content is uploaded each day. So they would have […]READ MORE >>
Ever wondered how Google can display a million search results in less than a second? Its because Google has indexed all the pages in their library so that it can return relevant results based on user’s search query. However, the web is dynamic, and thousands of content is uploaded each day. So they would have to continually refresh their indexes and go through all the millions of pages to find a relevant result. On the outlook, it seems like an impossible task, but thanks to web crawlers it is possible. The web crawler functions as an automated script, which browses the internet systematically. They look at the keyword in the page, the external and internal links, and kind of content before returning information to the search engine. It’s fascinating how these web crawlers do all the work in the background and make it look so simple. However, it is not as easy as it looks, as there are multiple challenges faced by programmers in web crawling.
The web is a dynamic space which doesn’t have a set standard for data formats and structures. Collecting data in a format that can be understood by machines can be a challenge due to the lack of uniformity. For instance, a webpage can be created using HTML, CSS, Java, PHP, or XML. The process of data extraction becomes challenging when web crawlers need structured data on a massive scale. The problem gets amplified when the web crawlers have to extract data from thousands of web sources pertaining to a specific schema.
Maintain database freshness
Majority of the web publisher like bloggers and news agency update their content on a daily or hourly basis. The crawler has to download all these pages to provide updated information to the user. The problem arises when the crawler starts downloading all such pages as it puts unnecessary pressure on the internet traffic. Programmers can develop a strategy, where web crawling is done only on pages which update their content frequently.
Bandwidth and impact on web servers
One of the biggest challenges or limitations faced by web crawlers is the high consumption rate of network bandwidth. This can particularly happen when the web crawler downloads many irrelevant web pages. To maintain the freshness of the database, crawlers adopt a polling method or use multiple crawlers, which consumes a lot of bandwidth. If a web crawler is frequently visiting websites, then the performance of the web servers will be severely impacted.
Absence of context
Web crawling uses numerous strategies to download the content that is relevant to user’s query. The crawler focuses on a particular topic; however, in some cases, the crawler may not be able to find relevant content. As a result, the crawler starts downloading a large number of irrelevant pages. As a result, programmers need to find out crawling techniques that focus on content that closely resembles the search query.
The rise of anti-scraping tools
Today, web developers have tools such as ScrapeSheild and ScrapeSentry that can differentiate bots from humans. Using such tools, web developers can manipulate content shown to bots and humans, and also restrict bots from scraping the website. Although practiced on a small scale, if crawlers continue to disregard robots.txt file and keep hitting the target server, it can cause DDoS to the websites.
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