Design
Search Engine Indexing System
Design the backend indexing pipeline that powers full-text search over a massive, constantly growing document corpus.
This is a Low-Level Design (LLD) problem. New to LLD vs HLD? Start here.
01 - Why interviewers ask this
It's the from-scratch "build Elasticsearch" question — interviewers check if you know the inverted-index data structure that makes full-text search fast at all.
02 - Where this system exists in the real world
You interact with this design every day.
Elasticsearch / Solr-style search infrastructure
Site search for large content platforms
Log search and observability platforms
03 - What you'll master
Solve this once. Know it forever.
Build and query an inverted index
Shard an index for parallel indexing/search
Rank results with TF-IDF/BM25-style scoring
04 - What you'll design
6 functional · 3 non-functional requirements.
Ingest and tokenize documents from a large, growing corpus
5 more requirements inside
Sign in to unlock the full brief and start designing
05 - Companies that ask this
You may face this exact question in your next interview.
Ready?
Open the canvas.
Design it yourself.
See all requirements, use staged hints, run your code, and compare with community discussions - all on the same canvas.