SQL 工具包
直接从命令行操作关系型数据库。涵盖 SQLite、PostgreSQL 和 MySQL,包含模式设计、查询、迁移、索引和操作的模式。
使用场景
- 创建或修改数据库模式
- 编写复杂查询(连接、聚合、窗口函数、CTE)
- 构建迁移脚本
- 通过索引和 EXPLAIN 优化慢查询
- 备份和恢复数据库
- 使用 SQLite 快速进行数据探索(零配置)
SQLite(零配置)
SQLite 随 Python 附带,并在每个系统上都可用。可用于本地数据、原型设计和单文件数据库。
快速开始
# 创建/打开数据库 sqlite3 mydb.sqlite # 直接导入 CSV sqlite3 mydb.sqlite ".mode csv" ".import data.csv mytable" "SELECT COUNT(*) FROM mytable;" # 单行查询 sqlite3 mydb.sqlite "SELECT * FROM users WHERE created_at > '2026-01-01' LIMIT 10;" # 导出到 CSV sqlite3 -header -csv mydb.sqlite "SELECT * FROM orders;" > orders.csv # 带标题和列格式的交互模式 sqlite3 -header -column mydb.sqlite
模式操作
-- 创建表
CREATE TABLE users (
id INTEGER PRIMARY KEY AUTOINCREMENT,
email TEXT NOT NULL UNIQUE,
name TEXT NOT NULL,
created_at TEXT DEFAULT (datetime('now')),
updated_at TEXT DEFAULT (datetime('now'))
);
-- 创建带外键的表
CREATE TABLE orders (
id INTEGER PRIMARY KEY AUTOINCREMENT,
user_id INTEGER NOT NULL REFERENCES users(id) ON DELETE CASCADE,
total REAL NOT NULL CHECK(total >= 0),
status TEXT NOT NULL DEFAULT 'pending' CHECK(status IN ('pending','paid','shipped','cancelled')),
created_at TEXT DEFAULT (datetime('now'))
);
-- 添加列
ALTER TABLE users ADD COLUMN phone TEXT;
-- 创建索引
CREATE INDEX idx_orders_user_id ON orders(user_id);
CREATE UNIQUE INDEX idx_users_email ON users(email);
-- 查看模式
.schema users
.tables
PostgreSQL
连接
# 连接 psql -h localhost -U myuser -d mydb # 连接字符串 psql "postgresql://user:pass@localhost:5432/mydb?sslmode=require" # 运行单条查询 psql -h localhost -U myuser -d mydb -c "SELECT NOW();" # 运行 SQL 文件 psql -h localhost -U myuser -d mydb -f migration.sql # 列出数据库 psql -l
模式设计模式
-- 使用 UUID 作为分布式友好的主键
CREATE EXTENSION IF NOT EXISTS "uuid-ossp";
CREATE TABLE users (
id UUID PRIMARY KEY DEFAULT uuid_generate_v4(),
email TEXT NOT NULL,
name TEXT NOT NULL,
password_hash TEXT NOT NULL,
role TEXT NOT NULL DEFAULT 'user' CHECK(role IN ('user','admin','moderator')),
created_at TIMESTAMPTZ NOT NULL DEFAULT NOW(),
updated_at TIMESTAMPTZ NOT NULL DEFAULT NOW(),
CONSTRAINT users_email_unique UNIQUE(email)
);
-- 自动更新 updated_at
CREATE OR REPLACE FUNCTION update_modified_column()
RETURNS TRIGGER AS $$
BEGIN
NEW.updated_at = NOW();
RETURN NEW;
END;
$$ LANGUAGE plpgsql;
CREATE TRIGGER update_users_modtime
BEFORE UPDATE ON users
FOR EACH ROW EXECUTE FUNCTION update_modified_column();
-- 枚举类型 (PostgreSQL 特有)
CREATE TYPE order_status AS ENUM ('pending', 'paid', 'shipped', 'delivered', 'cancelled');
CREATE TABLE orders (
id UUID PRIMARY KEY DEFAULT uuid_generate_v4(),
user_id UUID NOT NULL REFERENCES users(id) ON DELETE CASCADE,
status order_status NOT NULL DEFAULT 'pending',
total NUMERIC(10,2) NOT NULL CHECK(total >= 0),
metadata JSONB DEFAULT '{}',
created_at TIMESTAMPTZ NOT NULL DEFAULT NOW()
);
-- 部分索引 (仅索引有效订单 — 更小、更快)
CREATE INDEX idx_orders_active ON orders(user_id, created_at)
WHERE status NOT IN ('delivered', 'cancelled');
-- 用于 JSONB 查询的 GIN 索引
CREATE INDEX idx_orders_metadata ON orders USING GIN(metadata);
JSONB 查询 (PostgreSQL)
-- 存储 JSON
INSERT INTO orders (user_id, total, metadata)
VALUES ('...', 99.99, '{"source": "web", "coupon": "SAVE10", "items": [{"sku": "A1", "qty": 2}]}');
-- 查询 JSON 字段
SELECT * FROM orders WHERE metadata->>'source' = 'web';
SELECT * FROM orders WHERE metadata->'items' @> '[{"sku": "A1"}]';
SELECT metadata->>'coupon' AS coupon, COUNT(*) FROM orders GROUP BY 1;
-- 更新 JSON 字段
UPDATE orders SET metadata = jsonb_set(metadata, '{source}', '"mobile"') WHERE id = '...';
MySQL
连接
mysql -h localhost -u root -p mydb mysql -h localhost -u root -p -e "SELECT NOW();" mydb
与PostgreSQL的主要区别
-- 自增 (不是 SERIAL)
CREATE TABLE users (
id BIGINT UNSIGNED AUTO_INCREMENT PRIMARY KEY,
email VARCHAR(255) NOT NULL UNIQUE,
name VARCHAR(255) NOT NULL,
created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4;
-- JSON 类型 (MySQL 5.7+)
CREATE TABLE orders (
id BIGINT UNSIGNED AUTO_INCREMENT PRIMARY KEY,
user_id BIGINT UNSIGNED NOT NULL,
metadata JSON,
FOREIGN KEY (user_id) REFERENCES users(id) ON DELETE CASCADE
);
-- 查询 JSON
SELECT * FROM orders WHERE JSON_EXTRACT(metadata, '$.source') = 'web';
-- 或者简写:
SELECT * FROM orders WHERE metadata->>'$.source' = 'web';
查询模式
连接
-- 内连接 (仅匹配的行) SELECT u.name, o.total, o.status FROM users u INNER JOIN orders o ON o.user_id = u.id WHERE o.created_at > '2026-01-01'; -- 左连接 (所有用户,即使没有订单) SELECT u.name, COUNT(o.id) AS order_count, COALESCE(SUM(o.total), 0) AS total_spent FROM users u LEFT JOIN orders o ON o.user_id = u.id GROUP BY u.id, u.name; -- 自连接 (查找具有相同电子邮件域的用户) SELECT a.name, b.name, SPLIT_PART(a.email, '@', 2) AS domain FROM users a JOIN users b ON SPLIT_PART(a.email, '@', 2) = SPLIT_PART(b.email, '@', 2) WHERE a.id < b.id;
聚合
-- 分组和 HAVING
SELECT status, COUNT(*) AS cnt, SUM(total) AS revenue
FROM orders
GROUP BY status
HAVING COUNT(*) > 10
ORDER BY revenue DESC;
-- 累计总和 (窗口函数)
SELECT date, revenue,
SUM(revenue) OVER (ORDER BY date) AS cumulative_revenue
FROM daily_sales;
-- 组内排名
SELECT user_id, total,
RANK() OVER (PARTITION BY user_id ORDER BY total DESC) AS rank
FROM orders;
-- 移动平均 (最近7条记录)
SELECT date, revenue,
AVG(revenue) OVER (ORDER BY date ROWS BETWEEN 6 PRECEDING AND CURRENT ROW) AS ma_7
FROM daily_sales;
公共表表达式 (CTE)
-- 可读的多步骤查询
WITH monthly_revenue AS (
SELECT DATE_TRUNC('month', created_at) AS month,
SUM(total) AS revenue
FROM orders
WHERE status = 'paid'
GROUP BY 1
),
growth AS (
SELECT month, revenue,
LAG(revenue) OVER (ORDER BY month) AS prev_revenue,
ROUND((revenue - LAG(revenue) OVER (ORDER BY month)) /
NULLIF(LAG(revenue) OVER (ORDER BY month), 0) * 100, 1) AS growth_pct
FROM monthly_revenue
)
SELECT * FROM growth ORDER BY month;
-- 递归 CTE (组织架构图 / 树遍历)
WITH RECURSIVE org_tree AS (
SELECT id, name, manager_id, 0 AS depth
FROM employees
WHERE manager_id IS NULL
UNION ALL
SELECT e.id, e.name, e.manager_id, t.depth + 1
FROM employees e
JOIN org_tree t ON e.manager_id = t.id
)
SELECT REPEAT(' ', depth) || name AS org_chart FROM org_tree ORDER BY depth, name;
数据库迁移
手动迁移脚本模式
#!/bin/bash
# migrate.sh - 运行带编号的 SQL 迁移文件
DB_URL="${1:?用法: migrate.sh <数据库URL>}"
MIGRATIONS_DIR="./migrations"
# 创建跟踪表
psql "$DB_URL" -c "CREATE TABLE IF NOT EXISTS schema_migrations (
version TEXT PRIMARY KEY,
applied_at TIMESTAMPTZ DEFAULT NOW()
);"
# 按顺序运行待处理的迁移
for file in $(ls "$MIGRATIONS_DIR"/*.sql | sort); do
version=$(basename "$file" .sql)
already=$(psql "$DB_URL" -tAc "SELECT 1 FROM schema_migrations WHERE version='$version';")
if [ "$already" = "1" ]; then
echo "跳过: $version (已应用)"
continue
fi
echo "应用: $version"
psql "$DB_URL" -f "$file" && \
psql "$DB_URL" -c "INSERT INTO schema_migrations (version) VALUES ('$version');" || {
echo "失败: $version"
exit 1
}
done
echo "所有迁移已应用。"
迁移文件约定
migrations/ 001_create_users.sql 002_create_orders.sql 003_add_users_phone.sql 004_add_orders_metadata_index.sql
每个文件:
-- 003_add_users_phone.sql -- 升级操作 ALTER TABLE users ADD COLUMN phone TEXT; -- 回滚操作: ALTER TABLE users DROP COLUMN phone;
查询优化
EXPLAIN (PostgreSQL)
-- 显示查询计划 EXPLAIN SELECT * FROM orders WHERE user_id = '...' AND status = 'paid'; -- 显示实际执行时间 EXPLAIN (ANALYZE, BUFFERS, FORMAT TEXT) SELECT * FROM orders WHERE user_id = '...' AND status = 'paid';
需要注意的地方:
- 顺序扫描在大表上 → 需要索引
- 嵌套循环处理大量行时 → 考虑哈希连接(可能需要更多work_mem)
- 过滤移除的行数过高 → 索引未覆盖过滤条件
- 实际行数与估计值相差甚远 → 运行ANALYZE 表名;以更新统计信息
索引策略
-- 单列索引(最常用) CREATE INDEX idx_orders_user_id ON orders(user_id); -- 复合索引(用于同时过滤多列的查询) CREATE INDEX idx_orders_user_status ON orders(user_id, status); -- 列顺序很重要:将等值过滤的列放在前面,范围过滤的列放在最后 -- 覆盖索引(包含数据列以避免回表查询) CREATE INDEX idx_orders_covering ON orders(user_id, status) INCLUDE (total, created_at); -- 部分索引(更小、更快——只索引查询所需的数据) CREATE INDEX idx_orders_pending ON orders(user_id) WHERE status = 'pending'; -- 检查未使用的索引 SELECT schemaname, tablename, indexname, idx_scan FROM pg_stat_user_indexes WHERE idx_scan = 0 AND indexname NOT LIKE '%pkey%' ORDER BY pg_relation_size(indexrelid) DESC;
SQLite 执行计划
EXPLAIN QUERY PLAN SELECT * FROM orders WHERE user_id = 5; -- 注意:SCAN(差) vs SEARCH USING INDEX(好)
备份与恢复
PostgreSQL
# 完整转储(自定义格式,压缩) pg_dump -Fc -h localhost -U myuser mydb > backup.dump # 恢复 pg_restore -h localhost -U myuser -d mydb --clean --if-exists backup.dump # SQL 转储(可移植,可读) pg_dump -h localhost -U myuser mydb > backup.sql # 转储特定表 pg_dump -h localhost -U myuser -t users -t orders mydb > partial.sql # 将表复制为 CSV psql -c "\copy (SELECT * FROM users) TO 'users.csv' CSV HEADER"
SQLite
# 备份(仅复制文件,但使用 .backup 以保持一致性) sqlite3 mydb.sqlite ".backup backup.sqlite" # 导出为 SQL sqlite3 mydb.sqlite .dump > backup.sql # 从 SQL 恢复 sqlite3 newdb.sqlite < backup.sql
MySQL
# 导出 mysqldump -h localhost -u root -p mydb > backup.sql # 恢复 mysql -h localhost -u root -p mydb < backup.sql
提示
- 在应用程序代码中始终使用参数化查询 —— 切勿将用户输入直接拼接到 SQL 语句中
- 在 PostgreSQL 中处理含时区的日期时使用TIMESTAMPTZ(而非TIMESTAMP)
- 在 SQLite 中设置PRAGMA journal_mode=WAL;以提升并发读取性能
- 部署任何在大表上运行的查询前,先使用EXPLAIN进行分析
- PostgreSQL:\d+ 表名可显示列、索引及表大小\di+列出所有索引及其大小
- 如需快速数据探索,可将任意 CSV 导入 SQLite:sqlite3 :memory: ".mode csv" ".import 文件.csv t" "SELECT ..."


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