How does tokenization, stemming, and lowercasing affect the index?
Ingestion splits text into tokens, normalizes them to lowercase, and stems them to root forms (e.g., 'testing' → 'test'). This deduplicates terms across documents—'tests' and 'testing' both map to 'test'—reducing index size and improving recall so searches find more relevant results.
Answered in
The Inverted IndexA sorted dictionary mapping terms to document IDs. Transform search from O(corpus size) to O(1) lookup, enabling full-text search at scale.
Read the full analysisOther questions this article answers
More system design questions
- Why doesn't Google just run Dijkstra faster?
- What is a shortcut edge and when is it precomputed?
- How much space do shortcut edges take compared to the original graph?
- Can Contraction Hierarchies handle dynamic graphs like traffic or road closure?
- Why contract low-degree nodes first instead of high-degree ones?
- What is a CRDT and why does it matter for real-time collaboration?
- How do CRDTs handle concurrent edits without a central server referee?
- Why did Figma move from operational transforms to CRDTs?
Every answer on Crashtech is written by the editor of the article it comes from — never auto-summarised. Browse all answers or the System Design beat.