intermediateCreativity & Design

Projection Patterns

Build read models and projections from event streams. Use when implementing CQRS read sides, building materialized views, or optimizing query performance in event-sourced systems.

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Overview

Projection Patterns

Comprehensive guide to building projections and read models for event-sourced systems.

When to Use This Skill

  • Building CQRS read models
  • Creating materialized views from events
  • Optimizing query performance
  • Implementing real-time dashboards
  • Building search indexes from events
  • Aggregating data across streams

Core Concepts

1. Projection Architecture

┌─────────────┐     ┌─────────────┐     ┌─────────────┐
│ Event Store │────►│ Projector   │────►│ Read Model  │
│             │     │             │     │ (Database)  │
│ ┌─────────┐ │     │ ┌─────────┐ │     │ ┌─────────┐ │
│ │ Events  │ │     │ │ Handler │ │     │ │ Tables  │ │
│ └─────────┘ │     │ │ Logic   │ │     │ │ Views   │ │
│             │     │ └─────────┘ │     │ │ Cache   │ │
└─────────────┘     └─────────────┘     └─────────────┘

2. Projection Types

TypeDescriptionUse Case
LiveReal-time from subscriptionCurrent state queries
CatchupProcess historical eventsRebuilding read models
PersistentStores checkpointResume after restart
InlineSame transaction as writeStrong consistency

Templates and detailed worked examples

Full template library and detailed worked examples live in references/details.md. Read that file when you need the concrete templates.

Best Practices

Do's

  • Make projections idempotent - Safe to replay
  • Use transactions - For multi-table updates
  • Store checkpoints - Resume after failures
  • Monitor lag - Alert on projection delays
  • Plan for rebuilds - Design for reconstruction

Don'ts

  • Don't couple projections - Each is independent
  • Don't skip error handling - Log and alert on failures
  • Don't ignore ordering - Events must be processed in order
  • Don't over-normalize - Denormalize for query patterns

Best for

  • Building CQRS read models
  • Creating materialized views from events
  • Optimizing query performance
  • Implementing real-time dashboards
  • Building search indexes from events
  • Aggregating data across streams

Tips and best practices

  • Review the source instructions and adapt inputs before running the workflow.

What This Skill Can Do

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