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nestjs-search

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Mis à jour24 juin 2026 à 09:24

Integrate Elasticsearch and implement search index Sync patterns in NestJS. Use when integrating Elasticsearch or implementing search index sync in NestJS.

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FilippoDeSilva

FilippoDeSilva/skills

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Développeurs de logicielsProfessions informatiques et mathématiques·SOC 15-1252

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SKILL.md

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name	nestjs-search
description	Integrate Elasticsearch and implement search index Sync patterns in NestJS. Use when integrating Elasticsearch or implementing search index sync in NestJS.
license	MIT
version	1.0.0
author	[Filippo De Silva](https://github.com/FilippoDeSilva)
tags	["nestjs","search","elasticsearch","full-text","cqrs","synchronization"]
metadata	{"triggers":{"files":["*/.service.ts","/search/"],"keywords":["Elasticsearch","CQRS","Synchronization"]}}

Search Engine & Full-Text

Priority: P1 (OPERATIONAL)

Pattern: CQRS (Command Query Responsibility Segregation).
Write: To Primary Database (Postgres/MySQL). Source of Truth.
Read (Complex): To Search Engine (Elasticsearch, OpenSearch, MeiliSearch). Optimized for filtering, fuzzy search, and aggregation.

Synchronization ( Hard Part)

Dual Write (Anti-Pattern): await db.save(); await es.index();.
Why: Partial failures leave data inconsistent. Slows down HTTP response.
Event-Driven (Recommended):

Service writes to DB.
Service emits EntityUpdated.
Event Handler (Async) pushes to Queue (BullMQ).
Worker indexes document to Search Engine with retries.

CDC (Golden Standard): Change Data Capture (Debezium). Connects directly to DB transaction log. No app conceptual overhead, but higher ops complexity.

Organization

Module: Encapsulate client in SearchModule.
Abstraction: Create generic SearchService<T> helpers.
indexDocument(id, body)
search(query, filters)
Mapping: Use class-transformer to map Entities to "Search Documents". Keep docs flatter than relational entities.

Testing

E2E: not mock search engine in critical E2E flows.
Docker: Spin up elasticsearch:8 container in test harness to verify indexing works.

Anti-Patterns

No dual writes to DB + ES: Use event-driven or CDC pattern; dual writes risk partial failure inconsistency.
No Elasticsearch for structured queries: Use DB indexes for filtering; ES for full-text and complex search.
No ES mocks in E2E search tests: Spin up elasticsearch:8 container to verify indexing behavior accurately.

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Search Engine & Full-Text

Priority: P1 (OPERATIONAL)

Pattern: CQRS (Command Query Responsibility Segregation).

Write: To Primary Database (Postgres/MySQL). Source of Truth.

Read (Complex): To Search Engine (Elasticsearch, OpenSearch, MeiliSearch). Optimized for filtering, fuzzy search, and aggregation.

Synchronization ( Hard Part)

Dual Write (Anti-Pattern): await db.save(); await es.index();.

Why: Partial failures leave data inconsistent. Slows down HTTP response.

Event-Driven (Recommended):

Service writes to DB.

Service emits EntityUpdated.

Event Handler (Async) pushes to Queue (BullMQ).

Worker indexes document to Search Engine with retries.

CDC (Golden Standard): Change Data Capture (Debezium). Connects directly to DB transaction log. No app conceptual overhead, but higher ops complexity.

Organization

Module: Encapsulate client in SearchModule.

Abstraction: Create generic SearchService<T> helpers.

indexDocument(id, body)

search(query, filters)

Mapping: Use class-transformer to map Entities to "Search Documents". Keep docs flatter than relational entities.

Testing

E2E: not mock search engine in critical E2E flows.

Docker: Spin up elasticsearch:8 container in test harness to verify indexing works.

Anti-Patterns

No dual writes to DB + ES: Use event-driven or CDC pattern; dual writes risk partial failure inconsistency.

No Elasticsearch for structured queries: Use DB indexes for filtering; ES for full-text and complex search.

No ES mocks in E2E search tests: Spin up elasticsearch:8 container to verify indexing behavior accurately.