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postgresql-optimization

postgresql-optimization

github.com/github数据与数据库40.5k16.6k 次安装1 天前更新
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关于 postgresql-optimization

面向 PostgreSQL 开发的优化指导技能,适用于希望分析查询性能并运用数据库特性的开发者。内容涵盖查询模式、索引、监控维护及安全检查,并给出可执行的 SQL 示例。

主要功能

  1. 01分析查询与执行计划
  2. 02选择复合、部分及表达式索引
  3. 03使用 JSONB、数组和窗口函数
  4. 04监控连接、查询及数据库容量
  5. 05检查安全、维护和性能

适用场景

  1. 01排查慢查询和低效扫描
  2. 02为常用筛选条件设计索引
  3. 03优化 JSONB 查询及分页
  4. 04规划数据库监控与维护

安装

复制下面的命令,在终端中运行。

$npx skills add https://github.com/github/awesome-copilot --skill postgresql-optimization

安装后在 Claude Code 中输入/postgresql-optimization确认已加载。

详细介绍

PostgreSQL 开发助手

针对 ${selection}(如果未选择则针对整个项目)提供专业 PostgreSQL 指导。重点关注 PostgreSQL 特有功能、优化模式以及高级能力。

� PostgreSQL 特有功能

JSONB 操作
-- Advanced JSONB queries
CREATE TABLE events (
    id SERIAL PRIMARY KEY,
    data JSONB NOT NULL,
    created_at TIMESTAMPTZ DEFAULT NOW()
);

-- GIN index for JSONB performance
CREATE INDEX idx_events_data_gin ON events USING gin(data);

-- JSONB containment and path queries
SELECT * FROM events 
WHERE data @> '{"type": "login"}'
  AND data #>> '{user,role}' = 'admin';

-- JSONB aggregation
SELECT jsonb_agg(data) FROM events WHERE data ? 'user_id';
数组操作
-- PostgreSQL arrays
CREATE TABLE posts (
    id SERIAL PRIMARY KEY,
    tags TEXT[],
    categories INTEGER[]
);

-- Array queries and operations
SELECT * FROM posts WHERE 'postgresql' = ANY(tags);
SELECT * FROM posts WHERE tags && ARRAY['database', 'sql'];
SELECT * FROM posts WHERE array_length(tags, 1) > 3;

-- Array aggregation
SELECT array_agg(DISTINCT category) FROM posts, unnest(categories) as category;
窗口函数与数据分析
-- Advanced window functions
SELECT 
    product_id,
    sale_date,
    amount,
    -- Running totals
    SUM(amount) OVER (PARTITION BY product_id ORDER BY sale_date) as running_total,
    -- Moving averages
    AVG(amount) OVER (PARTITION BY product_id ORDER BY sale_date ROWS BETWEEN 2 PRECEDING AND CURRENT ROW) as moving_avg,
    -- Rankings
    DENSE_RANK() OVER (PARTITION BY EXTRACT(month FROM sale_date) ORDER BY amount DESC) as monthly_rank,
    -- Lag/Lead for comparisons
    LAG(amount, 1) OVER (PARTITION BY product_id ORDER BY sale_date) as prev_amount
FROM sales;
全文搜索
-- PostgreSQL full-text search
CREATE TABLE documents (
    id SERIAL PRIMARY KEY,
    title TEXT,
    content TEXT,
    search_vector tsvector
);

-- Update search vector
UPDATE documents 
SET search_vector = to_tsvector('english', title || ' ' || content);

-- GIN index for search performance
CREATE INDEX idx_documents_search ON documents USING gin(search_vector);

-- Search queries
SELECT * FROM documents 
WHERE search_vector @@ plainto_tsquery('english', 'postgresql database');

-- Ranking results
SELECT *, ts_rank(search_vector, plainto_tsquery('postgresql')) as rank
FROM documents 
WHERE search_vector @@ plainto_tsquery('postgresql')
ORDER BY rank DESC;

� PostgreSQL 性能调优

查询优化
-- EXPLAIN ANALYZE for performance analysis
EXPLAIN (ANALYZE, BUFFERS, FORMAT TEXT) 
SELECT u.name, COUNT(o.id) as order_count
FROM users u
LEFT JOIN orders o ON u.id = o.user_id
WHERE u.created_at > '2024-01-01'::date
GROUP BY u.id, u.name;

-- Identify slow queries from pg_stat_statements
SELECT query, calls, total_time, mean_time, rows,
       100.0 * shared_blks_hit / nullif(shared_blks_hit + shared_blks_read, 0) AS hit_percent
FROM pg_stat_statements 
ORDER BY total_time DESC 
LIMIT 10;
索引策略
-- Composite indexes for multi-column queries
CREATE INDEX idx_orders_user_date ON orders(user_id, order_date);

-- Partial indexes for filtered queries
CREATE INDEX idx_active_users ON users(created_at) WHERE status = 'active';

-- Expression indexes for computed values
CREATE INDEX idx_users_lower_email ON users(lower(email));

-- Covering indexes to avoid table lookups
CREATE INDEX idx_orders_covering ON orders(user_id, status) INCLUDE (total, created_at);
连接与内存管理
-- Check connection usage
SELECT count(*) as connections, state 
FROM pg_stat_activity 
GROUP BY state;

-- Monitor memory usage
SELECT name, setting, unit 
FROM pg_settings 
WHERE name IN ('shared_buffers', 'work_mem', 'maintenance_work_mem');

�️ PostgreSQL 高级数据类型

自定义类型与域
-- Create custom types
CREATE TYPE address_type AS (
    street TEXT,
    city TEXT,
    postal_code TEXT,
    country TEXT
);

CREATE TYPE order_status AS ENUM ('pending', 'processing', 'shipped', 'delivered', 'cancelled');

-- Use domains for data validation
CREATE DOMAIN email_address AS TEXT 
CHECK (VALUE ~* '^[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Za-z]{2,}$');

-- Table using custom types
CREATE TABLE customers (
    id SERIAL PRIMARY KEY,
    email email_address NOT NULL,
    address address_type,
    status order_status DEFAULT 'pending'
);
范围类型
-- PostgreSQL range types
CREATE TABLE reservations (
    id SERIAL PRIMARY KEY,
    room_id INTEGER,
    reservation_period tstzrange,
    price_range numrange
);

-- Range queries
SELECT * FROM reservations 
WHERE reservation_period && tstzrange('2024-07-20', '2024-07-25');

-- Exclude overlapping ranges
ALTER TABLE reservations 
ADD CONSTRAINT no_overlap 
EXCLUDE USING gist (room_id WITH =, reservation_period WITH &&);
几何类型
-- PostgreSQL geometric types
CREATE TABLE locations (
    id SERIAL PRIMARY KEY,
    name TEXT,
    coordinates POINT,
    coverage CIRCLE,
    service_area POLYGON
);

-- Geometric queries
SELECT name FROM locations 
WHERE coordinates <-> point(40.7128, -74.0060) < 10; -- Within 10 units

-- GiST index for geometric data
CREATE INDEX idx_locations_coords ON locations USING gist(coordinates);

📊 PostgreSQL 扩展与工具

实用扩展
-- Enable commonly used extensions
CREATE EXTENSION IF NOT EXISTS "uuid-ossp";    -- UUID generation
CREATE EXTENSION IF NOT EXISTS "pgcrypto";     -- Cryptographic functions
CREATE EXTENSION IF NOT EXISTS "unaccent";     -- Remove accents from text
CREATE EXTENSION IF NOT EXISTS "pg_trgm";      -- Trigram matching
CREATE EXTENSION IF NOT EXISTS "btree_gin";    -- GIN indexes for btree types

-- Using extensions
SELECT uuid_generate_v4();                     -- Generate UUIDs
SELECT crypt('password', gen_salt('bf'));      -- Hash passwords
SELECT similarity('postgresql', 'postgersql'); -- Fuzzy matching
监控与维护
-- Database size and growth
SELECT pg_size_pretty(pg_database_size(current_database())) as db_size;

-- Table and index sizes
SELECT schemaname, tablename,
       pg_size_pretty(pg_total_relation_size(schemaname||'.'||tablename)) as size
FROM pg_tables 
ORDER BY pg_total_relation_size(schemaname||'.'||tablename) DESC;

-- Index usage statistics
SELECT schemaname, tablename, indexname, idx_scan, idx_tup_read, idx_tup_fetch
FROM pg_stat_user_indexes 
WHERE idx_scan = 0;  -- Unused indexes
PostgreSQL 特有优化技巧
  • 使用 EXPLAIN (ANALYZE, BUFFERS) 进行详细的查询分析
  • 配置 postgresql.conf 以适配你的工作负载(OLTP 与 OLAP)
  • 使用连接池(pgbouncer)应对高并发应用
  • 定期执行 VACUUM 和 ANALYZE 以获得最佳性能
  • 对大表进行分区,使用 PostgreSQL 10+ 的声明式分区
  • 使用 pg_stat_statements 监控查询性能

📊 监控与维护

查询性能监控
-- Identify slow queries
SELECT query, calls, total_time, mean_time, rows
FROM pg_stat_statements 
ORDER BY total_time DESC 
LIMIT 10;

-- Check index usage
SELECT schemaname, tablename, indexname, idx_scan, idx_tup_read, idx_tup_fetch
FROM pg_stat_user_indexes 
WHERE idx_scan = 0;
数据库维护
  • VACUUM 和 ANALYZE:定期维护以保持性能
  • 索引维护:监控并重建碎片化的索引
  • 统计信息更新:保持查询规划器统计信息最新
  • 日志分析:定期审查 PostgreSQL 日志

🛠️ 常见查询模式

分页
-- ❌ BAD: OFFSET for large datasets
SELECT * FROM products ORDER BY id OFFSET 10000 LIMIT 20;

-- ✅ GOOD: Cursor-based pagination
SELECT * FROM products 
WHERE id > $last_id 
ORDER BY id 
LIMIT 20;
聚合
-- ❌ BAD: Inefficient grouping
SELECT user_id, COUNT(*) 
FROM orders 
WHERE order_date >= '2024-01-01' 
GROUP BY user_id;

-- ✅ GOOD: Optimized with partial index
CREATE INDEX idx_orders_recent ON orders(user_id) 
WHERE order_date >= '2024-01-01';

SELECT user_id, COUNT(*) 
FROM orders 
WHERE order_date >= '2024-01-01' 
GROUP BY user_id;
JSON 查询
-- ❌ BAD: Inefficient JSON querying
SELECT * FROM users WHERE data::text LIKE '%admin%';

-- ✅ GOOD: JSONB operators and GIN index
CREATE INDEX idx_users_data_gin ON users USING gin(data);

SELECT * FROM users WHERE data @> '{"role": "admin"}';

📋 优化检查清单

查询分析
  • 对高开销查询运行 EXPLAIN ANALYZE
  • 检查大表上的顺序扫描
  • 验证连接算法是否合适
  • 审查 WHERE 子句的选择性
  • 分析排序和聚合操作
索引策略
  • 为频繁查询的列创建索引
  • 对多列搜索使用复合索引
  • 考虑为过滤查询使用部分索引
  • 移除未使用或重复的索引
  • 监控索引膨胀和碎片化
安全审查
  • 仅使用参数化查询
  • 实施适当的访问控制
  • 在需要时启用行级安全
  • 审计敏感数据访问
  • 使用安全的连接方式
性能监控
  • 设置查询性能监控
  • 配置适当的日志设置
  • 监控连接池使用情况
  • 跟踪数据库增长和维护需求
  • 为性能下降设置告警

🎯 优化输出格式

查询分析结果
## Query Performance Analysis

**Original Query**:
[Original SQL with performance issues]

**Issues Identified**:
- Sequential scan on large table (Cost: 15000.00)
- Missing index on frequently queried column
- Inefficient join order

**Optimized Query**:
[Improved SQL with explanations]

**Recommended Indexes**:
```sql
CREATE INDEX idx_table_column ON table(column);

性能影响:预计执行时间缩短 80%


## 🚀 Advanced PostgreSQL Features

### Window Functions
```sql
-- Running totals and rankings
SELECT 
    product_id,
    order_date,
    amount,
    SUM(amount) OVER (PARTITION BY product_id ORDER BY order_date) as running_total,
    ROW_NUMBER() OVER (PARTITION BY product_id ORDER BY amount DESC) as rank
FROM sales;
公共表表达式(CTE)
-- Recursive queries for hierarchical data
WITH RECURSIVE category_tree AS (
    SELECT id, name, parent_id, 1 as level
    FROM categories 
    WHERE parent_id IS NULL
    
    UNION ALL
    
    SELECT c.id, c.name, c.parent_id, ct.level + 1
    FROM categories c
    JOIN category_tree ct ON c.parent_id = ct.id
)
SELECT * FROM category_tree ORDER BY level, name;

专注于提供具体、可执行的 PostgreSQL 优化建议,在利用 PostgreSQL 高级功能的同时提升查询性能、安全性和可维护性。

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