SQL on zcys univ II Hugo ver

Chapter 3-5 SQL 进阶查询语法大全

Wed, 01 Oct 2025 00:00:00 +0800

一、基础查询 (Basic Queries)

1. SELECT & FROM

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SELECT * FROM employees;
SELECT name, salary FROM employees;

2. WHERE 条件筛选

SELECT * FROM employees WHERE salary > 5000;
SELECT * FROM employees WHERE department = 'IT' AND salary > 6000;
SELECT * FROM employees WHERE name LIKE 'A%';  -- 名字以A开头
SELECT * FROM employees WHERE age BETWEEN 25 AND 35;
SELECT * FROM employees WHERE department IN ('IT', 'HR', 'Finance');

3. ORDER BY 排序

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SELECT * FROM employees ORDER BY salary DESC;
SELECT * FROM employees ORDER BY department ASC, salary DESC;

4. DISTINCT 去重

`1`	`SELECT DISTINCT department FROM employees;`

二、聚合函数与分组 (Aggregation & Grouping)

5. 聚合函数

SELECT 
    COUNT(*) as total_employees,
    AVG(salary) as avg_salary,
    MAX(salary) as max_salary,
    MIN(salary) as min_salary,
    SUM(salary) as total_salary
FROM employees;

6. GROUP BY 分组

SELECT 
    department,
    COUNT(*) as emp_count,
    AVG(salary) as avg_salary
FROM employees
GROUP BY department;

7. HAVING 分组后筛选

SELECT 
    department,
    COUNT(*) as emp_count
FROM employees
GROUP BY department
HAVING COUNT(*) > 5;

三、多表连接 (Joins)

8. INNER JOIN

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SELECT e.name, d.department_name
FROM employees e
INNER JOIN departments d ON e.department_id = d.id;

9. LEFT/RIGHT JOIN

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SELECT e.name, d.department_name
FROM employees e
LEFT JOIN departments d ON e.department_id = d.id;

10. FULL OUTER JOIN

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SELECT e.name, d.department_name
FROM employees e
FULL OUTER JOIN departments d ON e.department_id = d.id;

11. 多表连接

SELECT e.name, d.department_name, p.project_name
FROM employees e
JOIN departments d ON e.department_id = d.id
JOIN projects p ON e.id = p.leader_id;

四、子查询 (Subqueries)

12. 标量子查询

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SELECT name, salary,
    (SELECT AVG(salary) FROM employees) as company_avg
FROM employees;

13. IN 子查询

SELECT name
FROM employees
WHERE department_id IN (
    SELECT id FROM departments WHERE budget > 100000
);

14. EXISTS 子查询

SELECT name
FROM employees e
WHERE EXISTS (
    SELECT 1 FROM projects p 
    WHERE p.leader_id = e.id
);

15. 关联子查询

SELECT name, salary, department
FROM employees e1
WHERE salary > (
    SELECT AVG(salary) 
    FROM employees e2 
    WHERE e2.department = e1.department
);

五、高级查询技术 (Advanced Techniques)

16. CTE (公用表表达式)

WITH department_stats AS (
    SELECT 
        department,
        AVG(salary) as avg_salary
    FROM employees
    GROUP BY department
)
SELECT * FROM department_stats WHERE avg_salary > 6000;

17. 递归 CTE

WITH RECURSIVE org_chart AS (
    -- 基础情况
    SELECT employee_id, name, manager_id, 1 as level
    FROM employees
    WHERE manager_id IS NULL
    
    UNION ALL
    
    -- 递归情况
    SELECT e.employee_id, e.name, e.manager_id, oc.level + 1
    FROM employees e
    JOIN org_chart oc ON e.manager_id = oc.employee_id
)
SELECT * FROM org_chart;

18. 窗口函数

SELECT 
    name,
    department,
    salary,
    RANK() OVER (PARTITION BY department ORDER BY salary DESC) as dept_rank,
    AVG(salary) OVER (PARTITION BY department) as dept_avg_salary,
    LAG(salary) OVER (ORDER BY salary) as prev_salary
FROM employees;

19. PIVOT 行列转换

-- SQL Server
SELECT *
FROM (
    SELECT department, salary
    FROM employees
) AS SourceTable
PIVOT (
    AVG(salary)
    FOR department IN ([IT], [HR], [Finance])
) AS PivotTable;

六、数据操作 (Data Manipulation)

20. INSERT

INSERT INTO employees (name, salary, department) 
VALUES ('John Doe', 5000, 'IT');

-- 插入查询结果
INSERT INTO high_paid_employees (name, salary)
SELECT name, salary FROM employees WHERE salary > 8000;

21. UPDATE

UPDATE employees 
SET salary = salary * 1.1 
WHERE department = 'IT';

-- 使用子查询更新
UPDATE employees 
SET salary = (
    SELECT AVG(salary) FROM employees
) 
WHERE salary IS NULL;

22. DELETE

DELETE FROM employees WHERE salary < 3000;

-- 使用子查询删除
DELETE FROM employees 
WHERE department_id IN (
    SELECT id FROM departments WHERE active = 0
);

23. MERGE/UPSERT

-- PostgreSQL
INSERT INTO employees (id, name, salary)
VALUES (1, 'John', 5000)
ON CONFLICT (id) 
DO UPDATE SET name = EXCLUDED.name, salary = EXCLUDED.salary;

七、事务控制 (Transaction Control)

24. 事务处理

BEGIN TRANSACTION;

UPDATE accounts SET balance = balance - 100 WHERE id = 1;
UPDATE accounts SET balance = balance + 100 WHERE id = 2;

-- 如果一切正常
COMMIT;

-- 如果出现错误
ROLLBACK;

八、性能优化相关

25. 索引使用

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CREATE INDEX idx_employee_department ON employees(department);
CREATE INDEX idx_employee_name_salary ON employees(name, salary);

26. 分页查询

-- MySQL
SELECT * FROM employees ORDER BY id LIMIT 10 OFFSET 20;

-- SQL Server
SELECT * FROM employees ORDER BY id OFFSET 20 ROWS FETCH NEXT 10 ROWS ONLY;

27. 查询性能分析

-- 查看执行计划
EXPLAIN SELECT * FROM employees WHERE salary > 5000;

-- SQL Server
SET STATISTICS TIME ON;
SELECT * FROM employees WHERE salary > 5000;

九、实用函数

28. 字符串函数

SELECT 
    UPPER(name) as upper_name,
    LOWER(name) as lower_name,
    LENGTH(name) as name_length,
    SUBSTRING(name, 1, 3) as name_prefix,
    CONCAT(first_name, ' ', last_name) as full_name
FROM employees;

29. 日期函数

SELECT 
    CURRENT_DATE as today,
    EXTRACT(YEAR FROM hire_date) as hire_year,
    DATE_ADD(hire_date, INTERVAL 1 YEAR) as anniversary,
    DATEDIFF(CURRENT_DATE, hire_date) as days_employed
FROM employees;

30. 条件表达式

SELECT 
    name,
    salary,
    CASE 
        WHEN salary < 3000 THEN 'Low'
        WHEN salary BETWEEN 3000 AND 7000 THEN 'Medium'
        ELSE 'High'
    END as salary_level,
    COALESCE(bonus, 0) as bonus_amount
FROM employees;

这份指南涵盖了 SQL 从基础到高级的大部分常用语法。建议在实际工作中根据需要查阅相关部分，并通过练习来熟练掌握。

Chapter3 SQL集合操作

Wed, 01 Oct 2025 00:00:00 +0800

NOT EXISTS 和 EXCEPT 是 SQL 中用于处理集合差集的高级操作，它们在不同场景下非常有用。

一、 NOT EXISTS 用法

1. 基本语法

SELECT columns
FROM table1 t1
WHERE NOT EXISTS (
    SELECT 1 
    FROM table2 t2 
    WHERE t1.related_column = t2.related_column
);

2. 实际例子

例1：找出没有项目的员工

SELECT e.employee_id, e.name
FROM employees e
WHERE NOT EXISTS (
    SELECT 1 
    FROM projects p 
    WHERE p.leader_id = e.employee_id
);

例2：找出没有订单的客户

SELECT c.customer_id, c.customer_name
FROM customers c
WHERE NOT EXISTS (
    SELECT 1 
    FROM orders o 
    WHERE o.customer_id = c.customer_id
);

例3：找出从未被订购的产品

SELECT p.product_id, p.product_name
FROM products p
WHERE NOT EXISTS (
    SELECT 1 
    FROM order_items oi 
    WHERE oi.product_id = p.product_id
);

3. 复杂例子：找出没有下属的管理者

SELECT e1.employee_id, e1.name
FROM employees e1
WHERE e1.is_manager = 1
  AND NOT EXISTS (
    SELECT 1 
    FROM employees e2 
    WHERE e2.manager_id = e1.employee_id
);

二、 EXCEPT 用法

1. 基本语法

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SELECT column1, column2 FROM table1
EXCEPT
SELECT column1, column2 FROM table2;

2. 实际例子

例1：找出只在A表不在B表的记录

-- 找出在employees表但不在former_employees表的员工
SELECT employee_id, name FROM employees
EXCEPT
SELECT employee_id, name FROM former_employees;

例2：找出有库存但从未被订购的产品

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SELECT product_id FROM inventory
EXCEPT
SELECT product_id FROM order_items;

例3：多列比较

-- 找出在2023年有销售但2024年没有的客户
SELECT customer_id, product_id FROM sales_2023
EXCEPT
SELECT customer_id, product_id FROM sales_2024;

三、 NOT EXISTS vs EXCEPT 对比

相同需求的不同实现

需求：找出没有项目的部门

使用 NOT EXISTS:

SELECT d.department_id, d.department_name
FROM departments d
WHERE NOT EXISTS (
    SELECT 1 
    FROM projects p 
    WHERE p.department_id = d.department_id
);

使用 EXCEPT:

SELECT department_id, department_name 
FROM departments
EXCEPT
SELECT d.department_id, d.department_name
FROM departments d
JOIN projects p ON d.department_id = p.department_id;

四、高级应用场景

1. 多层 NOT EXISTS（复杂逻辑）

找出所有产品都库存充足的产品类别

SELECT c.category_id, c.category_name
FROM categories c
WHERE NOT EXISTS (
    -- 找出该类别中库存不足的产品
    SELECT 1
    FROM products p
    WHERE p.category_id = c.category_id
      AND p.current_stock < p.minimum_stock
);

2. EXCEPT 用于数据验证

验证两个表的结构一致性

-- 找出在source_table中存在但在target_table中不存在的记录
SELECT id, name, value FROM source_table
EXCEPT
SELECT id, name, value FROM target_table;

3. 组合使用 NOT EXISTS 和 EXISTS

找出只订购过一次的客户

SELECT c.customer_id, c.customer_name
FROM customers c
WHERE EXISTS (
    -- 至少有一个订单
    SELECT 1 FROM orders o 
    WHERE o.customer_id = c.customer_id
)
AND NOT EXISTS (
    -- 没有第二个订单
    SELECT 1 FROM orders o1, orders o2
    WHERE o1.customer_id = c.customer_id
      AND o2.customer_id = c.customer_id
      AND o1.order_id <> o2.order_id
);

五、性能考虑和最佳实践

1. NOT EXISTS 通常性能更好

-- 推荐：使用NOT EXISTS
SELECT * FROM table1 t1
WHERE NOT EXISTS (SELECT 1 FROM table2 t2 WHERE t2.id = t1.id);

-- 不推荐：使用NOT IN（对NULL值处理有问题）
SELECT * FROM table1 
WHERE id NOT IN (SELECT id FROM table2 WHERE id IS NOT NULL);

2. EXCEPT 自动去重

-- EXCEPT 会自动去除重复记录
SELECT department FROM employees
EXCEPT
SELECT department FROM former_employees;

3. 处理NULL值

-- NOT EXISTS 能正确处理NULL值
SELECT * FROM products p
WHERE NOT EXISTS (
    SELECT 1 FROM discontinued_products dp 
    WHERE dp.product_id = p.product_id
);

六、实际业务场景

场景1：电商平台 - 找出从未被浏览的商品

SELECT product_id, product_name
FROM products
WHERE NOT EXISTS (
    SELECT 1 
    FROM user_browsing_history 
    WHERE product_id = products.product_id
);

场景2：学校系统 - 找出没有选课的学生

SELECT student_id, student_name
FROM students
EXCEPT
SELECT s.student_id, s.student_name
FROM students s
JOIN enrollments e ON s.student_id = e.student_id;

场景3：银行系统 - 找出有账户但从未交易的客户

SELECT c.customer_id, c.customer_name
FROM customers c
JOIN accounts a ON c.customer_id = a.customer_id
WHERE NOT EXISTS (
    SELECT 1 
    FROM transactions t 
    WHERE t.account_id = a.account_id
);

总结

NOT EXISTS: 更适合关联查询，性能通常较好，能正确处理NULL值
EXCEPT: 更适合比较两个结果集的差异，语法更直观，自动去重
选择依据:
- 需要关联条件时用 NOT EXISTS
- 直接比较两个查询结果时用 EXCEPT
- 考虑数据库优化器和具体数据量进行测试

两者都是处理"在A中但不在B中"这类需求的强大工具！

Chapter3 Intro-to-SQL

Tue, 30 Sep 2025 00:00:00 +0800

SQL

语法

SELECT

distinct 去重

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select `distinct/all` dept_name 
from instructor

四则运算和重命名

`1`	`select ID, name, salary/12 as monthly_salary`

FROM

natural join 自然连接

select name, course_id 
from instructor natural join teaches 
where instructor. dept_name = ‘Art’
// 等价于加上 where instructor.ID = teaches.ID and

WHERE

SQL allows the use of the logical connectives and, or, and not The operands of the logical connectives can be expressions involving the comparison operators <, <=, >, >=, =, and <>.（以及between A and B 用法）

Tuple comparison

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select name, course_id 
from instructor, teaches 
where (instructor.ID, dept_name) = (teaches.ID, 'Biology');

Tuple Variables

涉及到对instructor关系中属性salary的不同值的比较

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select distinct T.name 
from instructor as T, instructor as S
where T.salary > S.salary and S.dept_name = ‘Comp. Sci.’

执行顺序

FROM - 从表中获取数据

WHERE - 对原始行数据进行筛选

GROUP BY - 对筛选后的数据进行分组

HAVING - 对分组后的聚合结果进行筛选

SELECT - 选择要显示的列

在 WHERE 子句中不能直接使用 COUNT 等聚合函数，因为执行顺序的问题。

-- ✅ 正确：使用HAVING对分组结果进行筛选
SELECT department, COUNT(*) as emp_count
FROM employees
GROUP BY department
HAVING COUNT(*) > 5;  -- 这里COUNT()在每组内计算

CTE

WITH 
department_stats AS (
    SELECT 
        department,
        AVG(salary) as avg_salary,
        COUNT(*) as employee_count
    FROM employees
    GROUP BY department
),
high_avg_departments AS (
    -- 这个CTE引用了前一个CTE
    SELECT 
        department,
        avg_salary
    FROM department_stats
    WHERE avg_salary > 6000
)
-- 主查询
SELECT 
    e.name,
    e.salary,
    h.avg_salary as department_avg
FROM employees e
JOIN high_avg_departments h ON e.department = h.department
WHERE e.salary > h.avg_salary;

GROUP BY

Attributes in select clause outside of aggregate functions must appear in group by list（必须要有聚合运算）错误示例：

/* erroneous query */
select dept_name, ID, avg (salary) -- ID 不在聚合属性中
from instructor
group by dept_name

正确用法：（可以有多个聚合运算）

product	category	sales_amount
A	Electronics	100
B	Electronics	150
A	Electronics	200
C	Clothing	80
B	Electronics	120

SELECT 
    category,
    COUNT(*) as transaction_count,
    SUM(sales_amount) as total_sales
FROM sales
GROUP BY category;

category	transaction_count	total_sales
Electronics	4	570
Clothing	1	80

常用聚合函数

SELECT 
    department,
    COUNT(*) as employee_count,      -- 计数
    AVG(salary) as avg_salary,       -- 平均值
    SUM(salary) as total_salary,     -- 求和
    MAX(salary) as max_salary,       -- 最大值
    MIN(salary) as min_salary        -- 最小值
FROM employees
GROUP BY department;

ORDER BY

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SELECT * FROM employees ORDER BY salary DESC;
SELECT * FROM employees ORDER BY department ASC, salary DESC;

Chapter2 关系数据库基础

Wed, 10 Sep 2025 00:00:00 +0800

关系数据库结构

table、relation、attributes

key

A superkey (超键) is a set of one or more attributes that, taken collectively, can be used to identify uniquely a tuple in the relation.

K is a candidate key (候选键) if K is minimal super key. e.g.{ID} is a candidate key for instructor, assuming no two instructors can possibly have the same identifiers. A relation may have several candidate keys

Primary key (主键) is a candidate key chosen by the database designer as principal means to identify tuples within a relation

Def. Primary attributes (主属性!) taking the key as a attribute set, the attributes in the candidate keys, i.e. the element of the primary key is called the primary attributes non-primary attributes (非主属性)

Super key >= candidate key >= primary key

relational algebra (关系代数)

Six basic operators

(选择) select: $\sigma$ (投影) project: (笛卡尔积) Cartesian product: x (集合并) union: (集合差) set difference: – (重命名) rename:

复合关系运算

暂时值（Assignment）

SQL on zcys univ II Hugo ver

Chapter 3-5 SQL 进阶查询语法大全

一、 基础查询 (Basic Queries)

1. SELECT & FROM

2. WHERE 条件筛选

3. ORDER BY 排序

4. DISTINCT 去重

二、 聚合函数与分组 (Aggregation & Grouping)

5. 聚合函数

6. GROUP BY 分组

7. HAVING 分组后筛选

三、 多表连接 (Joins)

8. INNER JOIN

9. LEFT/RIGHT JOIN

10. FULL OUTER JOIN

11. 多表连接

四、 子查询 (Subqueries)

12. 标量子查询

13. IN 子查询

14. EXISTS 子查询

15. 关联子查询

五、 高级查询技术 (Advanced Techniques)

16. CTE (公用表表达式)

17. 递归 CTE

18. 窗口函数

19. PIVOT 行列转换

六、 数据操作 (Data Manipulation)

20. INSERT

21. UPDATE

22. DELETE

23. MERGE/UPSERT

七、 事务控制 (Transaction Control)

24. 事务处理

八、 性能优化相关

25. 索引使用

26. 分页查询

27. 查询性能分析

九、 实用函数

28. 字符串函数

29. 日期函数

30. 条件表达式

Chapter3 SQL集合操作

一、 NOT EXISTS 用法

1. 基本语法

2. 实际例子

例1：找出没有项目的员工

例2：找出没有订单的客户

例3：找出从未被订购的产品

3. 复杂例子：找出没有下属的管理者

二、 EXCEPT 用法

1. 基本语法

2. 实际例子

例1：找出只在A表不在B表的记录

例2：找出有库存但从未被订购的产品

例3：多列比较

三、 NOT EXISTS vs EXCEPT 对比

相同需求的不同实现

需求：找出没有项目的部门

四、 高级应用场景

1. 多层 NOT EXISTS（复杂逻辑）

找出所有产品都库存充足的产品类别

2. EXCEPT 用于数据验证

验证两个表的结构一致性

3. 组合使用 NOT EXISTS 和 EXISTS

找出只订购过一次的客户

五、 性能考虑和最佳实践

1. NOT EXISTS 通常性能更好

2. EXCEPT 自动去重

3. 处理NULL值

六、 实际业务场景

场景1：电商平台 - 找出从未被浏览的商品

场景2：学校系统 - 找出没有选课的学生

场景3：银行系统 - 找出有账户但从未交易的客户

总结

Chapter3 Intro-to-SQL

SQL

语法

SELECT

distinct 去重

四则运算和重命名

一、基础查询 (Basic Queries)

二、聚合函数与分组 (Aggregation & Grouping)

三、多表连接 (Joins)

四、子查询 (Subqueries)

五、高级查询技术 (Advanced Techniques)

六、数据操作 (Data Manipulation)

七、事务控制 (Transaction Control)

八、性能优化相关

九、实用函数

四、高级应用场景

五、性能考虑和最佳实践

六、实际业务场景