CROSS APPLY & OUTER APPLY

CROSS APPLY & OUTER APPLY

CREATE TABLE [dbo].[Account](
	[UserId] [int] IDENTITY(1,1) NOT NULL,
	[Name] [nvarchar](50) NULL,
	[Age] [int] NULL,
	[Gender] [int] NULL,
	[BirthDate] [datetime] NULL,
 CONSTRAINT [PK_Account] PRIMARY KEY CLUSTERED 
(
	[UserId] ASC
)WITH (PAD_INDEX = OFF, STATISTICS_NORECOMPUTE = OFF, IGNORE_DUP_KEY = OFF, ALLOW_ROW_LOCKS = ON, ALLOW_PAGE_LOCKS = ON, OPTIMIZE_FOR_SEQUENTIAL_KEY = OFF) ON [PRIMARY]
) ON [PRIMARY]
GO
INSERT INTO [dbo].[Account]([UserId], [Name], [Age], [Gender], [BirthDate]) VALUES (1, N'User01', 21, 1, '2000-11-02 15:12:30.000');
INSERT INTO [dbo].[Account]([UserId], [Name], [Age], [Gender], [BirthDate]) VALUES (2, N'User02', 19, 0, '2002-02-02 15:12:30.000');
INSERT INTO [dbo].[Account]([UserId], [Name], [Age], [Gender], [BirthDate]) VALUES (3, N'User03', 20, 1, '2001-03-02 15:12:30.000');
GO

CREATE TABLE [dbo].[Message](
	[Id] [int] IDENTITY(1,1) NOT NULL,
	[UserId] [int] NULL,
	[Message] [nvarchar](200) NULL,
	[IsRead] [bit] NULL,
	[CreateTime] [datetime] NULL,
 CONSTRAINT [PK_Message] PRIMARY KEY CLUSTERED 
(
	[Id] ASC
)WITH (PAD_INDEX = OFF, STATISTICS_NORECOMPUTE = OFF, IGNORE_DUP_KEY = OFF, ALLOW_ROW_LOCKS = ON, ALLOW_PAGE_LOCKS = ON, OPTIMIZE_FOR_SEQUENTIAL_KEY = OFF) ON [PRIMARY]
) ON [PRIMARY]
GO
INSERT INTO [dbo].[Message]([Id], [UserId], [Message], [IsRead], [CreateTime]) VALUES (1, 1, N'Hello!', '0', '2021-11-28 15:16:14.000');
INSERT INTO [dbo].[Message]([Id], [UserId], [Message], [IsRead], [CreateTime]) VALUES (2, 1, N'First Message', '0', '2021-11-28 15:17:07.000');
INSERT INTO [dbo].[Message]([Id], [UserId], [Message], [IsRead], [CreateTime]) VALUES (3, 1, N'Second Message', '0', '2021-11-28 15:17:32.000');
INSERT INTO [dbo].[Message]([Id], [UserId], [Message], [IsRead], [CreateTime]) VALUES (4, 3, N'Hello!', '0', '2021-11-27 15:17:51.000');
GO

INNER JOIN

内连结,左右两表中交叉存在的交集记录.不会出现NULL

SELECT msg.Id,ac.Name,msg.Message,msg.IsRead,msg.CreateTime FROM dbo.Message AS msg INNER JOIN dbo.Account AS ac ON ac.UserId =msg.UserId

Id	Name	Message	IsRead	CreateTime
1	User01	Hello!	0	2021-11-28 15:16
2	User01	First Message	0	2021-11-28 15:17
3	User01	Second Message	0	2021-11-28 15:17
4	User03	Hello!	0	2021-11-27 15:17

LEFT JOIN

左侧为主表,进行匹配.如果右侧没有,则显示NULL

SELECT msg.Id,ac.Name,msg.Message,msg.IsRead,msg.CreateTime FROM dbo.Message AS msg LEFT JOIN dbo.Account AS ac ON ac.UserId =msg.UserId

Id	Name	Message	IsRead	CreateTime
1	User01	Hello!	0	2021-11-28 15:16
2	User01	First Message	0	2021-11-28 15:17
3	User01	Second Message	0	2021-11-28 15:17
4	User03	Hello!	0	2021-11-27 15:17

OUTER JOIN

RIGHT OUTER JOIN:
右侧表为主表,进行匹配.如果左侧没有,则显示NULL.
查询结果为右表的并集.

LEFT OUTER JOIN:
左侧表为主表,查询结果为左表的并集.

SELECT msg.Id,ac.Name,msg.Message,msg.IsRead,msg.CreateTime FROM dbo.Message AS msg RIGHT OUTER JOIN dbo.Account AS ac ON ac.UserId =msg.UserId

Id	Name	Message	IsRead	CreateTime
1	User01	Hello!	0	2021-11-28 15:16
2	User01	First Message	0	2021-11-28 15:17
3	User01	Second Message	0	2021-11-28 15:17
NULL	User02	NULL	NULL	NULL
4	User03	Hello!	0	2021-11-27 15:17

CROSS APPLY

如果不考虑外部表中的聚合函数.整体实现效果与INNER JOIN差不多.

通过连结查询,优先进行left外部表计算,然后在保持left外部表所有数据行的基础上,对right表进行查询匹配.

CROSS APPLY 可以根据当前左表的当前记录去查询右表;

INNER JOIN 是根据左表的当前记录匹配右表整个结果集;

执行查询/运算的顺序上,比INNER JOIN更严格.

查询结果与INNER JOIN一致,为左右两表的交集.

SELECT msg.Id,ac.Name,msg.Message,msg.IsRead,msg.CreateTime FROM dbo.Account AS ac CROSS APPLY (SELECT TOP (2) * FROM dbo.Message  WHERE ac.UserId=UserId ORDER BY CreateTime DESC) msg

Id	Name	Message	IsRead	CreateTime
3	User01	Second Message	0	2021-11-28 15:17
2	User01	First Message	0	2021-11-28 15:17
4	User03	Hello!	0	2021-11-27 15:17

OUTER APPLY

外联结,如果不考虑外部表中的聚合函数,与OUTER JOIN差不过.

与OUTER JOIN的区别在于,OUTER APPLY的左右表执行/运算顺序.

OUTER APPLY 可以根据当前左表的当前记录去查询右表;

INNER JOIN 是根据左表的当前记录匹配右表整个结果集;

查询结果与OUTER JOIN一致,为左/右表的并集.

SELECT msg.Id,ac.Name,msg.Message,msg.IsRead,msg.CreateTime FROM dbo.Account AS ac OUTER APPLY (SELECT TOP (2) * FROM dbo.Message  WHERE ac.UserId=UserId ORDER BY CreateTime DESC) msg

Id	Name	Message	IsRead	CreateTime
3	User01	Second Message	0	2021-11-28 15:17
2	User01	First Message	0	2021-11-28 15:17
NULL	User02	NULL	NULL	NULL
4	User03	Hello!	0	2021-11-27 15:17

OUTER APPLY

运算测试1

测试案例

WITH m AS (
    SELECT
	'数字' TypeGroup,
	'1,2,3,4,5,6,7,8,9' info UNION ALL
SELECT
	'字母' TypeGroup,
	'a,b,c,d,e,f,g,h,i' info
)
SELECT * FROM m;

TypeGroup	info
数字	1,2,3,4,5,6,7,8,9
字母	a,b,c,d,e,f,g,h,i

WITH m AS (
    SELECT
	'数字' TypeGroup,
	'1,2,3,4,5,6,7,8,9' info UNION ALL
SELECT
	'字母' TypeGroup,
	'a,b,c,d,e,f,g,h,i' info
)
-- SELECT * FROM m;
SELECT A.TypeGroup,B.info
FROM(  
    select TypeGroup, CONVERT(xml,'<root><v>' + REPLACE(info, ',', '</v><v>') + '</v></root>')  as info
    from m
) A
OUTER APPLY(
    SELECT info = N.c.value('.', 'varchar(8000)')
    FROM A.info.nodes('/root/v') N(c)
) B

TypeGroup	info
数字	1
数字	2
数字	3
数字	4
数字	5
数字	6
数字	7
数字	8
数字	9
字母	a
字母	b
字母	c
字母	d
字母	e
字母	f
字母	g
字母	h
字母	i

测试运算2

WITH Z AS (
SELECT '奇数' [Type],'1' [Value] UNION ALL
SELECT '奇数' [Type],'3' [Value] UNION ALL
SELECT '奇数' [Type],'5' [Value] UNION ALL
SELECT '奇数' [Type],'7' [Value] UNION ALL
SELECT '偶数' [Type],'2' [Value] UNION ALL
SELECT '偶数' [Type],'4' [Value] UNION ALL
SELECT '偶数' [Type],'6' [Value] UNION ALL
SELECT '偶数' [Type],'8' [Value]
)
SELECT * FROM 
(SELECT DISTINCT [Z].[Type] FROM Z) A 
OUTER APPLY (
SELECT [VALUES]=CAST((SELECT [Z].[Value] FROM Z WHERE Z.[Type]=A.[Type] FOR XML AUTO) AS NVARCHAR(MAX))
) B

Type	VALUES
偶数
奇数