database-optimizer
优化数据库性能
缓慢的查询和糟糕的数据库性能会严重影响应用程序的响应能力。本技能提供关于查询优化、索引策略和可扩展架构的专家指导，帮助显著提升数据库性能。
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Tester
Utilisation de "database-optimizer". Optimize this slow query: SELECT * FROM orders o JOIN customers c ON o.customer_id = c.id WHERE c.status = 'active' AND o.created_at > '2024-01-01'
Résultat attendu:
Analysis:
1. **Problem**: SELECT * retrieves unnecessary columns; no index on created_at; status filter may not be selective
Recommendations:
- Add covering index: CREATE INDEX idx_orders_customer_date ON orders(customer_id, created_at) INCLUDE (status, total)
- Replace SELECT * with specific columns
- Consider partitioning by date if tables are large
- Add index on customers.status if frequently filtered
Utilisation de "database-optimizer". How do I implement caching for a frequently-accessed database query?
Résultat attendu:
Multi-tier caching approach:
1. **L1 (Application)**: In-memory cache (e.g., Go map, Python functools.lru_cache) for hot data
2. **L2 (Distributed)**: Redis with TTL-based expiration
3. **Cache Strategy**: Use cache-aside pattern - check cache first, load from DB on miss, store in cache
4. **Invalidation**: Set appropriate TTL (e.g., 5-15 minutes) or use event-driven invalidation
5. **Key Design**: Use composite keys like 'user:123:orders' for specific cache entries
Audit de sécurité
SûrPrompt-only skill with no executable code. Static analysis scanned 0 files (0 lines) and detected no suspicious patterns. This is a pure instructional prompt providing database optimization guidance. No scripts, network calls, filesystem access, environment access, or external commands are present. No prompt injection attempts detected.
Score de qualité
Ce que vous pouvez construire
应用开发者排查慢查询问题
开发者注意到其应用程序因数据库查询导致页面加载缓慢。该技能提供查询模式的逐步分析和优化建议。
DBA 设计索引策略
数据库管理员需要为高流量电子商务应用设计索引策略。该技能提供关于索引类型和列排序的全面指导。
架构师规划数据库扩展
软件架构师计划扩展单体应用以处理增加的负载。该技能提供关于分区、分片和缓存策略的指导。
Essayez ces prompts
Help me optimize this slow SQL query: [PASTE YOUR QUERY]. Analyze the query structure and suggest improvements for better performance.
Design an indexing strategy for our [DATABASE TYPE] database that handles [DESCRIBE YOUR WORKLOAD - e.g., high read, frequent updates]. Our main query patterns include [LIST QUERY PATTERNS].
We are experiencing N+1 query problems in our [ORM NAME] application when loading [DESCRIBE ENTITIES]. The current code does [DESCRIBE CURRENT PATTERN]. How can we optimize this?
Our database is experiencing [DESCRIBE PROBLEM - e.g., high write volume, slow queries under load]. Current setup: [DESCRIBE CURRENT ARCHITECTURE]. What scaling and optimization strategies would you recommend?
Bonnes pratiques
- 优化前先测量 - 使用 EXPLAIN ANALYZE 了解实际查询性能，而不是猜测
- 根据实际查询模式而非理论知识设计索引 - 分析应用最频繁的查询
- 实施全面的监控，包括慢查询日志和性能基线，以便早期发现性能回退
Éviter
- 为了"以防万一"而索引每一列 - 这会增加写入开销和存储，却没有相应的收益
- 忽略 ORM 中的 N+1 查询 - 始终使用急切加载、批量查询或 DataLoader 模式
- 在未分析具体工作负载模式和数据分布的情况下应用通用优化建议