Add semantic_text index_options examples for BBQ quantization #3854
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Addresses elastic#3804 by adding comprehensive examples showing how to use index_options with semantic_text fields for dense vector quantization strategies. Changes: - Added new section "Optimizing vector storage with index_options" to semantic-search-semantic-text.md - Included 5 complete examples: bbq_hnsw, bbq_flat, bbq_disk (DiskBBQ), int8_hnsw, and custom HNSW tuning - Added cross-references from dense-vector.md and knn.md to semantic_text examples - All examples tested and verified on Elasticsearch 9.2 The examples demonstrate memory optimization strategies including: - bbq_hnsw: Up to 32x memory reduction (default for 384+ dimensions) - bbq_flat: BBQ without HNSW for simpler use cases - bbq_disk: Disk-based storage with minimal memory requirements (ES 9.2+) - int8_hnsw: 8-bit quantization for 4x memory reduction - Custom HNSW parameters: m and ef_construction tuning 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
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Summary
Addresses #3804 by adding comprehensive examples showing how to use
index_optionswithsemantic_textfields for dense vector quantization strategies.Changes
index_options" to semantic-search-semantic-text.mdbbq_hnsw,bbq_flat,bbq_disk(DiskBBQ),int8_hnsw, and custom HNSW tuningExamples Included
The examples demonstrate memory optimization strategies:
mandef_constructionparameter tuningTesting
All 5 examples were tested against an Elasticsearch 9.2 cluster using the
.multilingual-e5-small-elasticsearchinference endpoint. Each mapping successfully created indices with the specified quantization strategies.Test plan
index_options.dense_vectorsyntax