How to design a search engine architecture
· Category: System Design
Short answer
A search engine architecture has four components: a crawler that collects documents, an indexer that builds an inverted index, a ranking system (using TF-IDF or BM25), and a query server that processes user searches. For related content delivery, see how CDNs speed up content delivery.
Components
1. Crawler
Fetches web pages, follows links, and stores raw content. Uses a URL frontier queue and politeness policies to avoid overwhelming servers.
2. Indexer
Builds an inverted index mapping terms to document IDs. Processes raw content through tokenization, stemming, and stop-word removal. Stores the index in distributed shards.
3. Ranking
Scores documents by relevance using algorithms like TF-IDF, BM25, or machine learning models (Learning to Rank). PageRank adds authority signals based on link structure.
4. Query Server
Receives user queries, tokenizes them, looks up the inverted index, applies ranking, and returns top results with snippets.
Scaling considerations
- Shard the index across multiple nodes
- Use caching for popular queries
- Replicate for fault tolerance and lower latency
Tips
- Pre-compute ranking signals during indexing for faster query-time scoring
- For caching popular results, see how caching improves system performance