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SQL 查询优化助手

by @goldath

Use this skill when you need to write, review, optimize, or debug SQL queries. Covers query construction, performance tuning, index strategy, window function...

TERMINAL
clawhub install sql-assistant

📖 About This Skill


name: sql-assistant description: > Use this skill when you need to write, review, optimize, or debug SQL queries. Covers query construction, performance tuning, index strategy, window functions, CTEs, and common anti-patterns for PostgreSQL, MySQL, and SQLite.

SQL 查询优化助手

核心工作流

Step 1 — 理解需求

收集上下文:

  • 数据库类型(PostgreSQL / MySQL / SQLite / SQL Server)
  • 表结构(DDL 或列描述)
  • 业务目标(查什么、过滤条件、聚合逻辑)
  • 数据量级(小表 <10万 / 中表 <1000万 / 大表 >1000万)
  • 性能问题描述(慢查询?错误结果?)
  • Step 2 — 查询构建

    #### 基础查询框架

    SELECT
      col1,
      col2,
      agg_func(col3) AS alias
    FROM table_name t
    JOIN other_table o ON t.id = o.fk_id
    WHERE condition
    GROUP BY col1, col2
    HAVING agg_condition
    ORDER BY alias DESC
    LIMIT 100;
    

    #### CTE 模式(复杂逻辑拆分)

    WITH base_data AS (
      SELECT user_id, COUNT(*) AS order_count
      FROM orders
      WHERE created_at >= '2026-01-01'
      GROUP BY user_id
    ),
    ranked AS (
      SELECT *, RANK() OVER (ORDER BY order_count DESC) AS rk
      FROM base_data
    )
    SELECT * FROM ranked WHERE rk <= 10;
    

    Step 3 — 性能优化策略

    #### 索引策略

    -- 单列索引
    CREATE INDEX idx_orders_user ON orders(user_id);

    -- 复合索引(遵循最左前缀原则) CREATE INDEX idx_orders_user_date ON orders(user_id, created_at);

    -- 覆盖索引(避免回表) CREATE INDEX idx_orders_cover ON orders(user_id, created_at, status, amount);

    #### EXPLAIN 分析

    EXPLAIN (ANALYZE, BUFFERS, FORMAT JSON)
    SELECT * FROM orders WHERE user_id = 42;
    

    关注指标:

  • Seq Scan → 考虑加索引
  • rows 估算偏差大 → 需要 ANALYZE
  • cost 高 → 优化 JOIN 顺序或添加索引
  • Buffers: shared hit/read → 缓存命中率
  • Step 4 — 常见优化模式

    #### 分页优化(大表 OFFSET 慢)

    -- ❌ 慢:OFFSET 需扫描丢弃前N行
    SELECT * FROM orders ORDER BY id LIMIT 20 OFFSET 100000;

    -- ✅ 快:游标分页 SELECT * FROM orders WHERE id > :last_seen_id ORDER BY id LIMIT 20;

    #### IN 子查询优化

    -- ❌ 可能慢
    SELECT * FROM users WHERE id IN (SELECT user_id FROM premium_members);

    -- ✅ 用 EXISTS 或 JOIN SELECT u.* FROM users u JOIN premium_members pm ON u.id = pm.user_id;

    #### 避免函数破坏索引

    -- ❌ 函数包装列,索引失效
    WHERE YEAR(created_at) = 2026

    -- ✅ 范围条件,索引有效 WHERE created_at >= '2026-01-01' AND created_at < '2027-01-01'

    Step 5 — 窗口函数常用模式

    -- 分组内排名
    ROW_NUMBER() OVER (PARTITION BY user_id ORDER BY created_at DESC)

    -- 累计求和 SUM(amount) OVER (PARTITION BY user_id ORDER BY created_at)

    -- 环比计算 LAG(revenue, 1) OVER (ORDER BY month) AS prev_month_revenue

    -- 移动平均 AVG(score) OVER (ORDER BY date ROWS BETWEEN 6 PRECEDING AND CURRENT ROW)

    Step 6 — 查询审查清单

  • [ ] SELECT 只取需要的列(避免 SELECT *)
  • [ ] WHERE 条件列有索引
  • [ ] JOIN 条件有索引
  • [ ] 大表分页用游标而非 OFFSET
  • [ ] 聚合前先 WHERE 过滤(减少聚合数据量)
  • [ ] 复杂逻辑用 CTE 而非嵌套子查询
  • [ ] 无 N+1 查询问题
  • 反模式速查

    | 反模式 | 修复方式 | |--------|----------| | SELECT * | 显式列出需要的列 | | OFFSET 大分页 | 改用游标/keyset 分页 | | WHERE 列用函数 | 改用范围条件 | | 隐式类型转换 | 确保参数类型匹配 | | 无 LIMIT 的全表扫描 | 加 LIMIT 或索引过滤 | | OR 替代 UNION | 改用 UNION ALL |