What is an Index File?
An index file is a physical file (or segment) on disk that stores parts of the search index—like the term dictionary, postings lists, stored fields, doc values, and metadata. Engines use multiple files/segments to enable fast writes and efficient reads.
How It Works (quick)
- Segmentation: New data is written to segments; background merges combine them for efficiency.
- Core contents:
- Terms/lexicon with pointers to postings.
- Postings lists (doc IDs, term frequencies, positions, offsets).
- Stored fields (title, snippet) and doc values (price, rating) for retrieval/sorting.
- Vector blocks for ANN if semantic search is enabled.
- Metadata & checks: Footers, checksums, and version info guard integrity.
Why It Matters in E-commerce
- Performance: Well-structured files mean faster search, facets, and sorting.
- Freshness: Segment strategy affects update speed and query latency.
- Scale: Efficient storage keeps costs down for large catalogs.
Best Practices
- Tune merge policy: Balance write speed vs query performance; avoid too many tiny segments.
- Compression: Use modern codecs; store only needed fields.
- Field choices: Keep SKU/MPN exact in keyword fields; numeric types for price/stock.
- Monitoring: Track segment count, merge backlog, I/O, and cache hit rates.
- Backups: Snapshot index files; practice restore drills.
Challenges
- File bloat from unused fields; hot updates causing merge churn; inconsistent mappings across locales.
Examples
- Move long descriptions to stored fields, keep doc values only for sortable/filterable attributes.
- Add a vector column for title embeddings to enable semantic recall.
Summary
Index files are how your logical index lives on disk. With sane segment/merge policies, compression, and field hygiene, they deliver fast, reliable storefront search.
