MySQL/第十八章、MySQL8.0的其它新特性.sql

#第十八章、MySQL8.0的其它新特性

CREATE DATABASE dbtest18;

USE dbtest18;

#一、窗口函数

#1.1、演示窗口函数的效果
CREATE TABLE sales(
id INT PRIMARY KEY AUTO_INCREMENT,
city VARCHAR(15),
county VARCHAR(15),
sales_value DECIMAL
);

INSERT INTO sales(city,county,sales_value)
VALUES
('北京','海淀',10.00),
('北京','朝阳',20.00),
('上海','黄埔',30.00),
('上海','长宁',10.00);

SELECT * FROM sales;

#需求：现在计算这个网站在每个城市的销售总额、在全国的销售总额、每个区的销售额
#占所在城市销售额中的比率，以及占总销售额中的比率。

#方式一：
CREATE TEMPORARY TABLE a       -- 创建临时表
SELECT SUM(sales_value) AS sales_value -- 计算总计金额
FROM sales;

SELECT * FROM a;

CREATE TEMPORARY TABLE b    -- 创建临时表
SELECT city,SUM(sales_value) AS sales_value  -- 计算城市销售合计
FROM sales
GROUP BY city;

SELECT * FROM b;

SELECT s.city AS 城市,s.county AS 区,s.sales_value AS 区销售额,
			b.sales_value AS 市销售额,s.sales_value/b.sales_value AS 市比率,
			a.sales_value AS 总销售额,s.sales_value/a.sales_value AS 总比率
FROM sales s
JOIN b ON (s.city=b.city) -- 连接市统计结果临时表
JOIN a                   -- 连接总计金额临时表
ORDER BY s.city,s.county;

#方式二：
SELECT city AS 城市,county AS 区,sales_value AS 区销售额,
SUM(sales_value) OVER(PARTITION BY city) AS 市销售额,  -- 计算市销售额
sales_value/SUM(sales_value) OVER(PARTITION BY city) AS 市比率,
SUM(sales_value) OVER() AS 总销售额,   -- 计算总销售额
sales_value/SUM(sales_value) OVER() AS 总比率
FROM sales
ORDER BY city,county;

#2、介绍窗口函数
CREATE TABLE employees
AS
SELECT * FROM atguigudb.employees;

SELECT * FROM employees;

#准备工作
CREATE TABLE goods(
id INT PRIMARY KEY AUTO_INCREMENT,
category_id INT,
category VARCHAR(15),
NAME VARCHAR(30),
price DECIMAL(10,2),
stock INT,
upper_time DATETIME
);

INSERT INTO goods(category_id,category,NAME,price,stock,upper_time)
VALUES
(1, '女装/女士精品', 'T恤', 39.90, 1000, '2020-11-10 00:00:00'),
(1, '女装/女士精品', '连衣裙', 79.90, 2500, '2020-11-10 00:00:00'),
(2, '户外运动', '骑行装备', 399.90, 3500, '2020-11-10 00:00:00'),
(1, '女装/女士精品', '牛仔裤', 89.90, 3500, '2020-11-10 00:00:00'),
(2, '户外运动', '山地自行车', 1399.90, 2500, '2020-11-10 00:00:00'),
(1, '女装/女士精品', '呢绒外套', 399.90, 1200, '2020-11-10 00:00:00'),
(2, '户外运动', '自行车', 399.90, 1000, '2020-11-10 00:00:00'),
(2, '户外运动', '登山杖', 59.90, 1500, '2020-11-10 00:00:00'),
(1, '女装/女士精品', '卫衣', 89.90, 1500, '2020-11-10 00:00:00'),
(2, '户外运动', '运动外套', 799.90, 500, '2020-11-10 00:00:00'),
(1, '女装/女士精品', '百褶裙', 29.90, 500, '2020-11-10 00:00:00'),
(2, '户外运动', '滑板', 499.90, 1200, '2020-11-10 00:00:00');

SELECT * FROM goods;

#1、序号函数
#1.1、ROW_NUMBER()函数
#举例1：查询 goods 数据表中每个商品分类下价格降序排列的各个商品信息。
SELECT ROW_NUMBER() OVER(PARTITION BY category_id ORDER BY price DESC) AS row_num,
id, category_id, category, NAME, price, stock
FROM goods;

#举例2：查询 goods 数据表中每个商品分类下价格最高的3种商品信息。
SELECT *
FROM (SELECT ROW_NUMBER() OVER(PARTITION BY category_id ORDER BY price DESC) 		AS row_num,
		id, category_id, category, NAME, price, stock
		FROM goods) t
WHERE row_num <= 3;

#1.2、RANK()函数
#举例1：使用RANK()函数获取 goods 数据表中各类别的价格从高到低排序的各商品信息。
SELECT RANK() OVER(PARTITION BY category_id ORDER BY price DESC) AS row_num,
id, category_id, category, NAME, price, stock
FROM goods;

#举例2：使用RANK()函数获取 goods 数据表中类别为“女装/女士精品”的价格最高的4款商品信息。

SELECT *
FROM(
	SELECT RANK() OVER(PARTITION BY category_id ORDER BY price DESC) AS row_num,
	id, category_id, category, NAME, price, stock
	FROM goods) t
WHERE category_id = 1 AND row_num <= 4;

#1.3、DENSE_RANK()函数
#举例1：使用DENSE_RANK()函数获取 goods 数据表中各类别的价格从高到低排序的各商品信息。

SELECT DENSE_RANK() OVER(PARTITION BY category_id ORDER BY price DESC) AS row_num,
id, category_id, category, NAME, price, stock
FROM goods;

#举例2：使用DENSE_RANK()函数获取 goods 数据表中类别为“女装/女士精品”的价格最高的4款商品信息。

SELECT *
FROM(
	SELECT DENSE_RANK() OVER(PARTITION BY category_id ORDER BY price DESC) AS 	row_num,
	id, category_id, category, NAME, price, stock
	FROM goods) t
WHERE category_id = 1 AND row_num <= 3;

#2、分布函数

#2.1、PERCENT_RANK()函数
#举例：计算 goods 数据表中名称为“女装/女士精品”的类别下的商品的PERCENT_RANK值。
#写法一：
SELECT RANK() OVER w AS r,
PERCENT_RANK() OVER w AS pr,
id, category_id, category, NAME, price, stock
FROM goods
WHERE category_id = 1 WINDOW w AS (PARTITION BY category_id ORDER BY price DESC);

#写法二：
SELECT RANK() OVER (PARTITION BY category_id ORDER BY price DESC) AS r,
PERCENT_RANK() OVER (PARTITION BY category_id ORDER BY price DESC) AS pr,
id, category_id, category, NAME, price, stock
FROM goods
WHERE category_id = 1;

#2.2、CUME_DIST()函数
#举例：查询goods数据表中小于或等于当前价格的比例。
SELECT CUME_DIST() OVER(PARTITION BY category_id ORDER BY price ASC) AS cd,
id, category, NAME, price
FROM goods;

#3、前后函数
#3.1、LAG(expr,n)函数
#举例：查询goods数据表中前一个商品价格与当前商品价格的差值。

SELECT id, category, NAME, price, pre_price, price - pre_price AS diff_price
FROM (
	SELECT  id, category, NAME, price,LAG(price,1) OVER w AS pre_price
	FROM goods
	WINDOW w AS (PARTITION BY category_id ORDER BY price)) t;
	
#其中，子查询如下：
SELECT  id, category, NAME, price,LAG(price,1) OVER (PARTITION BY category_id ORDER BY price) AS pre_price
FROM goods;

#3.2、LEAD(expr,n)函数
#举例：查询goods数据表中后一个商品价格与当前商品价格的差值。
SELECT id, category, NAME, behind_price, price,behind_price - price AS diff_price
FROM(
	SELECT id, category, NAME, price,LEAD(price, 1) OVER w AS behind_price
	FROM goods WINDOW w AS (PARTITION BY category_id ORDER BY price)) t;

#其中，子查询为：
SELECT id, category, NAME, price,LEAD(price, 1) OVER (PARTITION BY category_id ORDER BY price) AS behind_price
FROM goods;

#4、首尾函数
#4.1、FIRST_VALUE(expr)函数
#举例：按照价格排序，查询第1个商品的价格信息。

SELECT id, category, NAME, price, stock,FIRST_VALUE(price) OVER w AS first_price
FROM goods WINDOW w AS (PARTITION BY category_id ORDER BY price);

#4.2、LAST_VALUE(expr)函数
SELECT id, category, NAME, price, stock,LAST_VALUE(price) OVER w AS last_price
FROM goods WINDOW w AS (PARTITION BY category_id ORDER BY price);

#5、其他函数
#5.1、NTH_VALUE(expr,n)函数
#举例：查询goods数据表中排名第2和第3的价格信息。

SELECT id, category,NAME,price,
	NTH_VALUE(price,2) OVER w AS second_price,
	NTH_VALUE(price,3) OVER w AS third_price
FROM goods WINDOW w AS (PARTITION BY category_id ORDER BY price);

#5.2、NTILE(n)函数
#举例：将goods表中的商品按照价格分为3组。

SELECT NTILE(3) OVER w AS nt,id, category, NAME, price
FROM goods WINDOW w AS (PARTITION BY category_id ORDER BY price);

#二、新特性2：公用表表达式

#2.1、普通公用表表达式
#举例：查询员工所在的部门的详细信息。
#准备工作
CREATE TABLE departments
AS
SELECT * FROM atguigudb.departments;

#子查询实现
SELECT * FROM departments
WHERE department_id IN (
												SELECT DISTINCT department_id
												FROM employees
												);

#CTE实现
WITH cte_emp
AS (SELECT DISTINCT department_id FROM employees)

SELECT * 
FROM departments d JOIN cte_emp e
ON d.department_id = e.department_id;

#2.2、递归公用表表达式
#举例：找出公司employees表中所有的下下属。
WITH RECURSIVE cte 
AS 
(
SELECT employee_id,last_name,manager_id,1 AS n FROM employees WHERE employee_id = 100 -- 种子查询，找到第一代领导
UNION ALL
SELECT a.employee_id,a.last_name,a.manager_id,n+1 FROM employees AS a JOIN cte
ON (a.manager_id = cte.employee_id) -- 递归查询，找出以递归公用表表达式的人为领导的人
)
SELECT employee_id,last_name FROM cte WHERE n >= 3;