projection-patterns
從 event stream 建立 CQRS read model 與 projection
中文翻譯
--- name: projection-patterns description: 從 event stream 建立 read model 與 projection。在實作 CQRS 的讀取端、建立 materialized view，或優化 event sourcing 系統的查詢效能時使用。 --- # Projection Patterns 為 event sourcing 系統建立 projection 與 read model 的完整指南。 ## When to Use This Skill - 建立 CQRS read model - 從事件建立 materialized view - 優化查詢效能 - 實作即時 dashboard - 從事件建立搜尋索引 - 跨 stream 彙整資料 ## Core Concepts ### 1. Projection Architecture ``` ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │ Event Store │────►│ Projector │────►│ Read Model │ │ │ │ │ │ (Database) │ │ ┌─────────┐ │ │ ┌─────────┐ │ │ ┌─────────┐ │ │ │ Events │ │ │ │ Handler │ │ │ │ Tables │ │ │ └─────────┘ │ │ │ Logic │ │ │ │ Views │ │ │ │ │ └─────────┘ │ │ │ Cache │ │ └─────────────┘ └─────────────┘ └─────────────┘ ``` ### 2. Projection Types | Type | Description | Use Case | | -------------- | --------------------------- | ---------------------- | | **Live** | 從訂閱即時處理 | 查詢目前狀態 | | **Catchup** | 處理歷史事件 | 重建 read model | | **Persistent** | 儲存 checkpoint | 重啟後繼續 | | **Inline** | 跟寫入在同一個交易 | 強一致性 | ## Templates and detailed worked examples 完整的範本庫與詳細的範例放在 `references/details.md`。需要具體範本時，再去讀那個檔案。 ## Best Practices ### Do's - **讓 projection 具冪等性** - 重播時是安全的 - **使用交易** - 用於多表更新 - **儲存 checkpoint** - 失敗後可以繼續 - **監控延遲** - 對 projection 的延遲設警報 - **規劃重建** - 設計時就考慮能重新建構 ### Don'ts - **不要讓 projection 互相耦合** - 每一個都是獨立的 - **不要跳過錯誤處理** - 失敗時要記錄並發出警報 - **不要忽略順序** - 事件必須依序處理 - **不要過度正規化** - 依查詢模式反正規化
英文原文
--- name: projection-patterns description: 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. --- # 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 | Type | Description | Use Case | | -------------- | --------------------------- | ---------------------- | | **Live** | Real-time from subscription | Current state queries | | **Catchup** | Process historical events | Rebuilding read models | | **Persistent** | Stores checkpoint | Resume after restart | | **Inline** | Same transaction as write | Strong 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