SQL语言学习（group by,having）

GROUP BY 的基本用法

GROUP BY 子句用于将结果集按照一个或多个列进行分组，通常与聚合函数（如 COUNT, SUM, AVG 等）一起使用。

实例：

按照部分分组统计员工数量：

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select department,count(*) as employee_count
from employees
group by department;

按产品和年份分组统计销售额：

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select product_id,YEAR(order_date) as order_year,SUM(amount) as total_sales
from orders
group by product_id,YEAR(order_date);

HAVING 的基本用法

HAVING 子句用于对 GROUP BY 分组后的结果进行过滤，类似于 WHERE 子句，但 WHERE 在分组前过滤，而 HAVING 在分组后过滤。

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//筛选员工数超过5人的部门
select department,count(*) as employee_count
from employees
group by department
having count(*)>5

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//筛选出销售总额超过10000的产品和年份组成
select product_id,year(order_date) as order_year,sum(amount) astotal_sales
from orders
group by product_id,year(order_date)
having sum(amount)>10000;

关键区别总结：

常见使用模式

1. 基本分组统计

|--------------------------------------------|
| SELECT category, AVG(price) as avg_price |
| FROM products |
| GROUP BY category; |

2. 分组后过滤

|-----------------------------------------------|
| SELECT customer_id, COUNT(*) as order_count |
| FROM orders |
| GROUP BY customer_id |
| HAVING COUNT(*) >= 3; |

3. 多列分组

|---------------------------------------------------|
| SELECT department, job_title, COUNT(*) as count |
| FROM employees |
| GROUP BY department, job_title |
| HAVING COUNT(*) > 2; |

4. 结合 WHERE 和 HAVING

|----------------------------------------------------------|
| -- 先过滤2023年的订单，再按客户分组，最后筛选总金额大于5000的客户 |
| SELECT customer_id, SUM(amount) as total_spent |
| FROM orders |
| WHERE order_date BETWEEN '2023-01-01' AND '2023-12-31' |
| GROUP BY customer_id |
| HAVING SUM(amount) > 5000; |

注意事项

SELECT 中的非聚合列：在 GROUP BY 查询中，SELECT 子句中的非聚合列必须出现在 GROUP BY 子句中。
性能考虑：GROUP BY 操作可能会消耗较多资源，特别是在大数据集上。
HAVING 中的聚合函数：HAVING 子句中可以使用聚合函数，这是它与 WHERE 的主要区别之一。
NULL 值处理：GROUP BY 会将所有 NULL 值视为相同的分组。

实际案例

案例1：销售分析

按地区和产品类别分组，计算销售总额，并筛选出销售额超过10000的组合

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select
    region,
    product_category,
    sum(sales_acount) as total_sales,
    count(*) as transaction_count
from sales
group by region,prodect_category
having sun(sales_amount) >10000
order by total_sales desc;

案例2：学生成绩分析

按班级和科目分组，计算平均分，并筛选出平均分低于60的科目

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select
    calss,
    subject,
    avg(score) as avg_score,
    count(*) as student_count
from exam_results
group by class,subject
having avg(score) < 60
order by class,avg_score;