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docs(search): document English stemming for the built-in full-text engine #2032

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lukekim merged 1 commit into from
Aug 1, 2026
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docs(search): document English stemming for the built-in full-text engine #2032

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8 changes: 8 additions & 0 deletions website/docs/features/search/full-text.md
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Expand Up @@ -26,6 +26,14 @@ Spice supports two full-text search engines:

When no engine is specified, Tantivy is used automatically.

### Text Analysis

The built-in Tantivy engine indexes text with Tantivy's `en_stem` tokenizer: terms are lowercased and reduced to their English (Snowball) stem, with token positions retained so phrase queries keep working. Query terms are analyzed the same way, so a search for `running` also matches documents containing `run` and `runs`.

Stemming is always on for the built-in engine and has no configuration parameter. It is English-only — text in other languages is still tokenized and lowercased, but not stemmed.

The local warm index used with `engine: elasticsearch` is a Tantivy index and analyzes text the same way. Searches [served directly by Elasticsearch](#warm-tier) — multi-column datasets, a warm index that could not be built, or an `on_zero_results: use_source` fallback — are analyzed by Elasticsearch's own analyzer for that index instead.

## Enabling Full-Text Search

To enable full-text search, configure your dataset columns within your dataset definition as follows:
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