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Elasticsearch cheat sheet & developer notes

Elasticsearch cheat sheet and 2 curated developer notes — core concepts, patterns, and interview prep. Maintained by the DevRecall team.

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01 · Elasticsearch

Documents, Mapping & Indexing

Documents, Mapping & Indexing. The Core Model. A distributed search/analytics engine built on Lucene. An index is roughly a "table" (a collection of similar documents); a document is roughly a "row" — a JSON object. Inte…

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02 · Elasticsearch

Querying, Filtering & Aggregations

Querying, Filtering & Aggregations. Basic Full-Text Search. POST /articles/_search { "query": { "match": { "title": "elasticsearch" } } }. bool Query — Combining Conditions. POST /articles/_search { "query": { "bool": { …

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Concepts to know for Elasticsearch

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Observability: Logs, Metrics and TracesWhat logs, metrics and traces each answer, why label cardinality breaks metrics, how a trace ID crosses services, and how SLOs turn signals into alerts.Intermediate·15 minRAG: Retrieval-Augmented GenerationHow RAG fetches permitted, fresh text and puts it in the prompt so an LLM answers with citations, and why chunking and retrieval decide the quality.Intermediate·14 minEmbeddings and Vector SearchHow text becomes a vector whose distance tracks meaning, why exact search does not scale, and how HNSW and IVF indexes trade recall for speed and memory.Intermediate·14 min

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