Cracking the System Design: How Search Engines Deliver Results | DARSHAN CHOPRA | Oct 2024

The Components that Power a Search Engine

A search engine is like access to the giant library of the Internet. It gives you the list of the best resources on the web for your search. A search engine is powered by several key components that work together to crawl, index and rank the web content as per the user queries. Let’s have a quick overview on the main components of search engines:

1. Query Rewriting — This component pre-processes the query. It corrects all the grammatical, spelling errors in the query and updates the query to an understandable format.
2. Query Understanding — This component interprets the user’s request and tries to understand the intent of the user’s query. It considers a set of parameters for this process like location, search history to fine tune the search engine’s results page. It uses Natural Language Processing (NLP) to interpret and understand the context of the user’s query.
3. Web Crawlers (Spiders/Bots) — These are automated programs that crawl/browse the web pages and discover new and updated web pages. The crawlers retrieve the content from the web pages which includes images, texts, metadata and links.
4. Indexing — After the crawling process the massive amount of data gets stored in a database called index. It is like a library where the search engine stores and organizes the retrieved data for enabling a fast retrieval when a user queries for something. Thus, reduces the search space of an engine.
5. Search Algorithms — These are complex mathematical expressions, machine learning models that determine how to rank the content?, how to retrieve the content from the index when a user provides a query? These algorithms can consider a set of parameters for this like user’s intent, keywords, relevance, freshness of the content, location etc.
6. Ranking — After determining what to retrieve. It is important to decide the order in which the content should be listed. To solve this problem the concept of ranking system was introduced. Ranking process rank’s the pages as per their importance, relevance to a user’s query. This is influenced by various factors such as page’s content quality, number of backlinks, page speed etc.
7. Machine Learning & Artificial Intelligence — Nowadays, AI & ML models power the modern search engines by learning from the user’s behavior e.g., clicks, bounce rates, successful session completions etc. To continuously improve the search accuracy & ranking. Google’s RankBrain is one of the examples of an AI system that improves the search as per the user’s interactions.

These are the components that power a search engine and enables a search engine to discover, organize, deliver the relevant results in response to the user’s query.