documentdb-full-text-search
Full-text search best practices for Azure DocumentDB using the `createSearchIndexes` command and `$search` aggregation stage — BM25 keyword scoring, fuzzy search (`maxEdits`), phrase search with `slop`, custom analyzers (keyword + lowerCase + asciiFolding + edgeGram) for prefix / ID matching, `pathHierarchy` tokenizer for hierarchical IDs, multi-field search indexes, and hybrid (BM25 + vector) retrieval via Reciprocal Rank Fusion. Use when building search experiences, adding typo tolerance, matching phrases or prefixes on IDs / SKUs / part numbers, or combining lexical and semantic retrieval on the same collection.
Works with
---
name: documentdb-full-text-search
description: Full-text search best practices for Azure DocumentDB using the `createSearchIndexes` command and `$search` aggregation stage — BM25 keyword scoring, fuzzy search (`maxEdits`), phrase search with `slop`, custom analyzers (keyword + lowerCase + asciiFolding + edgeGram) for prefix / ID matching, `pathHierarchy` tokenizer for hierarchical IDs, multi-field search indexes, and hybrid (BM25 + vector) retrieval via Reciprocal Rank Fusion. Use when building search experiences, adding typo tolerance, matching phrases or prefixes on IDs / SKUs / part numbers, or combining lexical and semantic retrieval on the same collection.
license: MIT
---
# Full-Text Search — Azure DocumentDB (`$search` + `createSearchIndexes`)
Azure DocumentDB's full-text search is driven by search indexes built with the **`createSearchIndexes`** database command and queried through the **`$search`** aggregation stage. Scoring is **BM25**, exposed via `$meta: "searchScore"`. The community `$text` operator and `{ field: "text" }` index type are **not** the DocumentDB search path.
Key syntax points that differ from many blog posts and older docs:
- **Index command** is `createSearchIndexes` (not `createIndexes`) — each index has a `name` and a `definition.mappings.fields` block; `dynamic: false` is the safe default.
- **Custom analyzers** live inside `definition.analyzers` and are referenced per-field via `analyzer` / `searchAnalyzer`.
- **`$search` targets an index by name** via `index: "<name>"` — the engine does not auto-pick when multiple exist.
- **No `count` field** inside `$search` — use a downstream `{ $limit: N }` stage.
- **No `compound` operator yet** — query one field at a time and merge in the application (see `fts-multifield-index`).
## Rules
- [fts-create-search-index](fts-create-search-index.md) — Create a search index via `runCommand({ createSearchIndexes })`; use `definition.mappings` with `dynamic: false`.
- [fts-basic-search](fts-basic-search.md) — `$search` + `text` operator for BM25 keyword search; target `index`, project `searchScore`, cap with `$limit`.
- [fts-fuzzy-search](fts-fuzzy-search.md) — Add `fuzzy: { maxEdits: 1 }` to tolerate typos; keep `maxEdits` small.
- [fts-phrase-search](fts-phrase-search.md) — `phrase` operator with `slop` for ordered-proximity matching.
- [fts-custom-analyzers](fts-custom-analyzers.md) — Keyword tokenizer + `lowerCase` + `asciiFolding` + `edgeGram` for case-insensitive prefix matching on IDs, SKUs, part numbers. Index-time vs search-time analyzer pair.
- [fts-path-hierarchy](fts-path-hierarchy.md) — `pathHierarchy` tokenizer for hierarchical identifiers (`BN-747-ENG-2024.05`, dotted, slash paths).
- [fts-multifield-index](fts-multifield-index.md) — One search index mapping multiple fields; fan-out-and-merge in the app while `$search` `compound` is unavailable.
- [fts-hybrid-search](fts-hybrid-search.md) — Combine BM25 and vector search (RRF) on the same collection.More DevOps & Infrastructure skills
azure-ai
microsoft/azure-skills
Use for Azure AI: Search, Speech, OpenAI, Document Intelligence. Helps with search, vector/hybrid search, speech-to-text, text-to-speech, transcription, OCR. WHEN: AI Search, query search, vector search, hybrid search, semantic search, speech-to-text, text-to-speech, transcribe, OCR, convert text to speech.
appinsights-instrumentation
microsoft/azure-skills
Guidance for instrumenting webapps with Azure Application Insights. Provides telemetry patterns, SDK setup, and configuration references. WHEN: how to instrument app, App Insights SDK, telemetry patterns, what is App Insights, Application Insights guidance, instrumentation examples, APM best practices.
azure-storage
microsoft/azure-skills
Azure Storage Services including Blob Storage, File Shares, Queue Storage, Table Storage, and Data Lake. Answers questions about storage access tiers (hot, cool, cold, archive), when to use each tier, and tier comparison. Provides object storage, SMB file shares, async messaging, NoSQL key-value, and big data analytics. Includes lifecycle management. USE FOR: blob storage, file shares, queue storage, table storage, data lake, upload files, download blobs, storage accounts, access tiers, storage tiers, hot cool cold archive, storage tier comparison, when to use storage tiers, lifecycle management, Azure Storage concepts. DO NOT USE FOR: SQL databases, Cosmos DB (use azure-prepare), messaging with Event Hubs or Service Bus (use azure-messaging).
