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jsamuelsen11
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aggregation-patterns

Standardize and optimize MongoDB aggregation pipelines with $lookup, $facet, and $merge.

Updated Feb 7, 2026
Search Tags:#performance#aggregation#merge#pipeline#mongodb#lookup#facet
One-click install
npx skills add https://github.com/jsamuelsen11/claude-config --skill aggregation-patterns
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: aggregation-patterns
Source: https://github.com/jsamuelsen11/claude-config/tree/main/plugins/ccfg-mongodb/skills/aggregation-patterns
Command: npx skills add https://github.com/jsamuelsen11/claude-config --skill aggregation-patterns

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

MongoDB aggregation pipelines frequently become complex and hard to maintain, making it difficult to reason about performance, correctness, and maintainability.

Core Features & Use Cases

  • Provides a catalog of proven patterns for stage ordering, joins, facets, and materialized views to standardize pipeline design.
  • Offers guidance on when to use $lookup versus app-side joins, when to employ $facet for multi-analysis, and how to choose between $merge and $out for incremental versus full replacements.
  • Includes practical use cases for analytics, reporting, and data transformation workloads with concrete example scenarios.

Quick Start

Analyze a representative aggregation scenario and apply the recommended patterns to improve clarity and efficiency.

Frequently Asked Questions about aggregation-patterns

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
What is the best way to structure MongoDB aggregation pipelines for performance?▼

The best way to structure MongoDB aggregation pipelines is by applying proven patterns for stage ordering, joins, and facets to standardize pipeline design, ensuring clarity and efficiency in data transformation workloads.

How do I choose between $merge and $out in a MongoDB aggregation pipeline?▼

Choose $merge for incremental updates to existing collections and $out for full materialized view replacements, following explicit usage guidelines to optimize pipeline performance and maintainability.

When should I use $lookup versus app-side joins in MongoDB?▼

Use $lookup for server-side data aggregation across collections, but employ app-side joins when pipeline performance degrades or stage complexity increases, balancing database workload with application logic.

How do I optimize MongoDB aggregation pipelines using explain plans and indexes?▼

Optimize MongoDB aggregation pipelines by analyzing explain plans and applying index guidance to stage ordering and materialized views, resolving performance bottlenecks in complex data transformation workloads.

When do I need $facet for multi-analysis in MongoDB aggregations?▼

You need $facet for multi-analysis when a single MongoDB aggregation pipeline requires multiple independent grouping or filtering operations to generate comprehensive analytics and reporting outputs simultaneously.

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