{"product_id":"elasticsearch-9-bbq-vector-search-and-ai-powered-semantic-retrieval-build-production-systems-with-better-binary-quantization-esql-joins-and-hybrid-9798261990079","title":"Elasticsearch 9: BBQ Vector Search and AI-Powered Semantic Retrieval: Build Production Systems with Better Binary Quantization, Esql Joins, and Hybrid","description":"\u003cp\u003e • Author(s): Eero Sullivan\u003cbr\u003e • Publisher: Independently Published\u003cbr\u003e • Publisher Imprint: Independently Published\u003cbr\u003e • BISAC: Data Science - Data Analytics\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003eDesign Elasticsearch 9 vector search and RAG systems that stay fast, accurate, and predictable in production.\u003c\/b\u003e\u003c\/p\u003e\u003cp\u003eElasticsearch 9 changes how vector search, quantization, and hybrid retrieval behave under real load, yet many teams still ship clusters that fall over when traffic or data grows. Guesswork around HNSW settings, BBQ, DiskBBQ, and filtered ANN often leads to fragile systems and painful outages.\u003c\/p\u003e\u003cp\u003eThis book walks you through the full lifecycle of Elasticsearch 9 search workloads, from upgrade planning and data modeling to dense vectors, BBQ and DiskBBQ, ESQL workflows, and production playbooks, so you can reason about behavior instead of tuning by accident.\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eUnderstand Elasticsearch 9 search architecture, shards, segments, and upgrade paths for vector heavy clusters\u003c\/li\u003e\n\u003cli\u003eModel documents and chunks for hybrid retrieval and RAG with clean metadata for filters multi tenant access and citations\u003c\/li\u003e\n\u003cli\u003eChoose and tune dense_vector mappings similarity functions and HNSW parameters for balanced recall and latency\u003c\/li\u003e\n\u003cli\u003eApply Better Binary Quantization and DiskBBQ to cut memory and storage while keeping quality with oversampling and rescoring\u003c\/li\u003e\n\u003cli\u003eDesign filtered vector search that actually works using ACORN concepts and patterns for ACL and time sliced data\u003c\/li\u003e\n\u003cli\u003eBuild maintainable hybrid search that combines lexical search vectors RRF fusion and rerankers without unreadable queries\u003c\/li\u003e\n\u003cli\u003eUse retrievers as the primary query interface and wire them into ESQL FORK and FUSE pipelines\u003c\/li\u003e\n\u003cli\u003eMap and query semantic_text fields and roll out semantic retrieval safely across models and indices\u003c\/li\u003e\n\u003cli\u003eIntegrate inference endpoints for embeddings and reranking with clear security observability and fallback paths\u003c\/li\u003e\n\u003cli\u003eAdopt ESQL LOOKUP JOIN for in cluster enrichment and cleaner joins between chunk and source indices\u003c\/li\u003e\n\u003cli\u003eRun relevance experiments, Rally style benchmarks, and capacity planning focused on recall latency and cost per query\u003c\/li\u003e\n\u003cli\u003eFollow concrete production playbooks and reference implementations for hybrid retrieval, RAG services, and ESQL based search stacks\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eYou also get practical add ons, including deployment checklists, reference pipelines using retrievers, rerankers, and ESQL LOOKUP JOIN, plus a benchmark harness with Rally style tests and a capacity sizing worksheet that you can adapt to your own environment.\u003c\/p\u003e\u003cp\u003eThroughout the chapters you work through realistic JSON mappings, curl examples, Docker and configuration snippets, and ESQL queries that you can lift into your own clusters with minimal adjustment.\u003c\/p\u003e\u003cp\u003e\u003cb\u003eGrab your copy today and build Elasticsearch 9 search systems you can trust in production.\u003c\/b\u003e\u003c\/p\u003e","brand":"Independently Published","offers":[{"title":"Paperback","offer_id":46860930089111,"sku":"9798261990079","price":2994.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0666\/3471\/1191\/files\/9798261990079.webp?v=1769959852","url":"https:\/\/atlanticbooks.com\/products\/elasticsearch-9-bbq-vector-search-and-ai-powered-semantic-retrieval-build-production-systems-with-better-binary-quantization-esql-joins-and-hybrid-9798261990079","provider":"Atlantic Books","version":"1.0","type":"link"}