Search System Design: Inverted Indexes, Tokenization, and Ranking
The life of a query through a search stack: keystroke, query parser, tokenizer, index lookup, scorer, and ranked results. We build an inverted index in the video and watch a two-word query merge its posting lists, so the difference between an AND and an OR of terms is visible in the lists themselves. Then the part people skip: tokenization on the write side — what happens to case, punctuation, and stems — and how ranking degrades when documents are indexed with rules the query parser doesn't share.
Topics covered:
- The inverted index: posting lists and term dictionaries
- Tokenization and stemming at index time
- Query parsing and boolean operators
- TF-IDF and scoring by relevance
- Indexing pipeline: what a doc touches before it is searchable
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