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1. TVP, 表变量,临时表,CTE 的区别
TVP和临时表都是可以索引的,总是存在tempdb中,会增加系统数据库开销,而表变量和CTE只有在内存溢出时才会被写入tempdb中。对于数据量大,并且反复使用,反复进行查询关联的,建议使用临时表或TVP,数据量小,使用表变量或CTE比较合适
2. sql_variant 万能类型
可以存放所有数据类型,相当于C#中的object数据类型
3. datetime, datetime2, datetimeoffset
datetime 时间有效期较小,在1753-1-1 之前就不能使用了,精度为毫秒级别,而datetime2 数据范围相当于C#中的datetime ,精度达到了秒后面小数点后7位,datetimeoffset则是考虑是时区的日期类型
4. MERGE的用法
语法很简单就不说了,主要是处理两张表某些字段对比后的操作,需注意 when not matched (by target) 与 when not matched by source的区别,前者是是针对对比后目标表不存在的记录,可以选择insert操作,而后者则是针对对比后目标表多出来的记录,可以选择delete或update操作
5. rowversion 类型
代替以前的timestamp,时间戳,8字节二进制值,常用来进行解决并发操作的问题
6. Sysdatetime()
返回datetime2类型,精度比datetime高
7. with cube , with rollup , grouping sets 运算符
都可与group by 后连用,with cube 表示汇总所有级别的组合,with rollup 则是按级别汇总,从下面的代码可以详细看出区别。注意,汇总行,null可以看成所有值
而grouping sets运算符,则仅返回每个分组顶级汇总行,在查询汇总行中 可使用grouping(字段名) = 1来判断,该运算符可和rollup, cube连用,表示按照grouping by sets和按照rollup/cube处理的结果集union all
示例代码如下:
复制代码 代码如下:
With cube, With rollup
--示例代码
declare @t table(goodsname VARCHAR(max) ,sku1name VARCHAR(max) , sku2name VARCHAR(max), qty INT)
insert @t select '凡客TX','红色','S',1
insert @t select '凡客TX','黑色','S',2
insert @t select '凡客TX','白色','L',3
insert @t select '京东村山','白色','L',4
insert @t select '京东村山','红色','S',5
insert @t select '京东村山','黑色','L',6
insert @t select '亚马逊拖鞋','白色','L',7
insert @t select '亚马逊拖鞋','红色','S',8
SELECT * FROM @t
select goodsname,sku1name,sku2name,sum(qty) sumqty
from @t
group by goodsname,sku1name,sku2name with rollup
ORDER BY goodsname,sku1name,sku2name
select goodsname,sku1name,sku2name,sum(qty) sumqty
from @t
group by goodsname,sku1name,sku2name with cube
ORDER BY goodsname,sku1name,sku2name
-----------------------
declare @t table(goodsname VARCHAR(max) ,sku1name VARCHAR(max) , sku2name VARCHAR(max), qty INT)
insert @t select '凡客TX','红色','S',1
insert @t select '凡客TX','黑色','S',2
insert @t select '凡客TX','白色','L',3
insert @t select '京东村山','白色','L',4
insert @t select '京东村山','红色','S',5
insert @t select '京东村山','黑色','L',6
insert @t select '亚马逊拖鞋','白色','L',7
insert @t select '亚马逊拖鞋','红色','S',8
--GROUPING SETS 运算符
SELECT goodsname,sku1name,sku2name, SUM(qty) FROM @t GROUP BY GROUPING SETS(goodsname,sku1name,sku2name)
SELECT goodsname, sku1name, sku2name ,SUM(qty) FROM @t
GROUP BY GROUPING SETS(goodsname), ROLLUP(sku1name,sku2name)
ORDER BY goodsname,sku1name,sku2name
SELECT goodsname, sku1name, sku2name ,SUM(qty) FROM @t
GROUP BY ROLLUP(goodsname,sku1name,sku2name)
ORDER BY goodsname,sku1name,sku2name
SELECT CASE WHEN GROUPING(goodsname) = 1 THEN '[ALL]' ELSE goodsname END goodsname,
CASE WHEN GROUPING(sku1name) = 1 THEN '[ALL]' ELSE sku1name END sku1name,
CASE WHEN GROUPING(sku2name) = 1 THEN '[ALL]' ELSE sku2name END sku2name ,SUM(qty) FROM @t
GROUP BY GROUPING SETS(goodsname), ROLLUP(sku1name,sku2name)
ORDER BY goodsname,sku1name,sku2name
8. 一些快捷的语法 例如 Declare @id int = 0
虽然有时很快捷,但DBA不建议这样使用,Declare @id = select top 1 id from 表名,建议声明和查表赋值分开
9. 公用表达式 CTE
特点:可嵌套使用,代替联接表中的子查询,结构层次更加清晰,也可用来递归查询,另外通过巧妙的常量列控制递归层次
示例代码如下:
复制代码 代码如下:
--公用表达式CTE Common table expression
--用CTE实现递归算法
CREATE TABLE EMPLOYEETREE(
EMPLOYEE INT PRIMARY KEY,
employeename nvarchar(50),
reportsto int
)
insert into EMPLOYEETREE values(1,'Richard',null)
insert into EMPLOYEETREE values(2,'Stephen',1)
insert into EMPLOYEETREE values(3,'Clemens',2)
insert into EMPLOYEETREE values(4,'Malek',2)
insert into EMPLOYEETREE values(5,'Goksin',4)
insert into EMPLOYEETREE values(6,'Kimberly',1)
insert into EMPLOYEETREE values(7,'Ramesh',5)
----------------------
--确定哪些员工向Stephen报告的递归查询
with employeeTemp as
(
select EMPLOYEE, employeename, reportsto from EMPLOYEETREE where EMPLOYEE = 2
union all
select a.EMPLOYEE, a.employeename, a.reportsto from EMPLOYEETREE as a
inner join employeeTemp as b on a.reportsto = b.EMPLOYEE
)
select * from employeeTemp where EMPLOYEE <> 2 --option(maxrecursion 2)
--不报错设置级联关联递归
with employeeTemp as
(
select EMPLOYEE, employeename, reportsto,0 as sublevel from EMPLOYEETREE where EMPLOYEE = 2
union all
select a.EMPLOYEE, a.employeename, a.reportsto,sublevel+1 from EMPLOYEETREE as a
inner join employeeTemp as b on a.reportsto = b.EMPLOYEE
)
select * from employeeTemp where EMPLOYEE <> 2 and sublevel <=2 --option(maxrecursion 2)
10. pivot 与 unpivot
前者用在行转列,注意:必须用聚合函数与PIVOT一起使用,计算聚会时将不考虑出现在值列中的任何空值;一般情况下,可以用列上的子查询来替换pivot语句,但是这样做效率不高
后者用在列转行,注意:如果某些列中有null值,将会被过滤掉,不产生新行;语法上For前指定的新列,对应原表指定列名中的值,For后指定的新列对应原表指定列名中的标题的值
两者都有的共性:语法上最后必须要有别名;IN里面指定的列类型必须是一致的。
示例代码如下:
复制代码 代码如下:
pivot与unpivot
--关于PIVOT的操作
CREATE TABLE #test
(
NAME VARCHAR(max),
SCORE INT
)
INSERT INTO #test VALUES ('张三','97')
INSERT INTO #test VALUES ('李四','28')
INSERT INTO #test VALUES ('王五','33')
INSERT INTO #test VALUES ('神人','78')
--NAME SCORE
--张三 97
--李四 28
--王五 33
--神人 78
--行转列
SELECT --'成绩单' AS SCORENAME ,
[张三], [李四], [王五]
FROM #test
PIVOT (AVG(SCORE) FOR NAME IN ([张三], [李四], [王五])) b
-----------------------------------------
CREATE TABLE VendorEmployee(
VendorId INT,
Emp1Order INT,
Emp2Order INT,
Emp3Order INT,
Emp4Order INT,
Emp5Order INT,
)
GO
INSERT INTO VendorEmployee VALUES(1,4,3,5,4,4)
INSERT INTO VendorEmployee VALUES(2,4,1,5,5,5)
INSERT INTO VendorEmployee VALUES(3,4,3,5,4,4)
INSERT INTO VendorEmployee VALUES(4,4,2,5,4,4)
INSERT INTO VendorEmployee VALUES(5,5,1,5,5,5)
SELECT * FROM VendorEmployee
----------------
--列转行
SELECT * FROM (
SELECT VendorId,[Emp1Order],[Emp2Order],[Emp3Order],[Emp4Order],[Emp5Order] FROM VendorEmployee) AS unpiv
UNPIVOT (orders FOR elyid IN ([Emp1Order],[Emp2Order],[Emp3Order],[Emp4Order],[Emp5Order])) AS child
ORDER BY elyid
SELECT * FROM VendorEmployee
UNPIVOT (orders FOR elyid IN ([Emp1Order],[Emp2Order],[Emp3Order],[Emp4Order],[Emp5Order])) AS child
ORDER BY elyid
SELECT * FROM VendorEmployee UNPIVOT ( ORDERS FOR [操作员名字] IN ([Emp1Order],[Emp2Order],[Emp3Order],[Emp4Order],[Emp5Order]))
TVP和临时表都是可以索引的,总是存在tempdb中,会增加系统数据库开销,而表变量和CTE只有在内存溢出时才会被写入tempdb中。对于数据量大,并且反复使用,反复进行查询关联的,建议使用临时表或TVP,数据量小,使用表变量或CTE比较合适
2. sql_variant 万能类型
可以存放所有数据类型,相当于C#中的object数据类型
3. datetime, datetime2, datetimeoffset
datetime 时间有效期较小,在1753-1-1 之前就不能使用了,精度为毫秒级别,而datetime2 数据范围相当于C#中的datetime ,精度达到了秒后面小数点后7位,datetimeoffset则是考虑是时区的日期类型
4. MERGE的用法
语法很简单就不说了,主要是处理两张表某些字段对比后的操作,需注意 when not matched (by target) 与 when not matched by source的区别,前者是是针对对比后目标表不存在的记录,可以选择insert操作,而后者则是针对对比后目标表多出来的记录,可以选择delete或update操作
5. rowversion 类型
代替以前的timestamp,时间戳,8字节二进制值,常用来进行解决并发操作的问题
6. Sysdatetime()
返回datetime2类型,精度比datetime高
7. with cube , with rollup , grouping sets 运算符
都可与group by 后连用,with cube 表示汇总所有级别的组合,with rollup 则是按级别汇总,从下面的代码可以详细看出区别。注意,汇总行,null可以看成所有值
而grouping sets运算符,则仅返回每个分组顶级汇总行,在查询汇总行中 可使用grouping(字段名) = 1来判断,该运算符可和rollup, cube连用,表示按照grouping by sets和按照rollup/cube处理的结果集union all
示例代码如下:
复制代码 代码如下:
With cube, With rollup
--示例代码
declare @t table(goodsname VARCHAR(max) ,sku1name VARCHAR(max) , sku2name VARCHAR(max), qty INT)
insert @t select '凡客TX','红色','S',1
insert @t select '凡客TX','黑色','S',2
insert @t select '凡客TX','白色','L',3
insert @t select '京东村山','白色','L',4
insert @t select '京东村山','红色','S',5
insert @t select '京东村山','黑色','L',6
insert @t select '亚马逊拖鞋','白色','L',7
insert @t select '亚马逊拖鞋','红色','S',8
SELECT * FROM @t
select goodsname,sku1name,sku2name,sum(qty) sumqty
from @t
group by goodsname,sku1name,sku2name with rollup
ORDER BY goodsname,sku1name,sku2name
select goodsname,sku1name,sku2name,sum(qty) sumqty
from @t
group by goodsname,sku1name,sku2name with cube
ORDER BY goodsname,sku1name,sku2name
-----------------------
declare @t table(goodsname VARCHAR(max) ,sku1name VARCHAR(max) , sku2name VARCHAR(max), qty INT)
insert @t select '凡客TX','红色','S',1
insert @t select '凡客TX','黑色','S',2
insert @t select '凡客TX','白色','L',3
insert @t select '京东村山','白色','L',4
insert @t select '京东村山','红色','S',5
insert @t select '京东村山','黑色','L',6
insert @t select '亚马逊拖鞋','白色','L',7
insert @t select '亚马逊拖鞋','红色','S',8
--GROUPING SETS 运算符
SELECT goodsname,sku1name,sku2name, SUM(qty) FROM @t GROUP BY GROUPING SETS(goodsname,sku1name,sku2name)
SELECT goodsname, sku1name, sku2name ,SUM(qty) FROM @t
GROUP BY GROUPING SETS(goodsname), ROLLUP(sku1name,sku2name)
ORDER BY goodsname,sku1name,sku2name
SELECT goodsname, sku1name, sku2name ,SUM(qty) FROM @t
GROUP BY ROLLUP(goodsname,sku1name,sku2name)
ORDER BY goodsname,sku1name,sku2name
SELECT CASE WHEN GROUPING(goodsname) = 1 THEN '[ALL]' ELSE goodsname END goodsname,
CASE WHEN GROUPING(sku1name) = 1 THEN '[ALL]' ELSE sku1name END sku1name,
CASE WHEN GROUPING(sku2name) = 1 THEN '[ALL]' ELSE sku2name END sku2name ,SUM(qty) FROM @t
GROUP BY GROUPING SETS(goodsname), ROLLUP(sku1name,sku2name)
ORDER BY goodsname,sku1name,sku2name
8. 一些快捷的语法 例如 Declare @id int = 0
虽然有时很快捷,但DBA不建议这样使用,Declare @id = select top 1 id from 表名,建议声明和查表赋值分开
9. 公用表达式 CTE
特点:可嵌套使用,代替联接表中的子查询,结构层次更加清晰,也可用来递归查询,另外通过巧妙的常量列控制递归层次
示例代码如下:
复制代码 代码如下:
--公用表达式CTE Common table expression
--用CTE实现递归算法
CREATE TABLE EMPLOYEETREE(
EMPLOYEE INT PRIMARY KEY,
employeename nvarchar(50),
reportsto int
)
insert into EMPLOYEETREE values(1,'Richard',null)
insert into EMPLOYEETREE values(2,'Stephen',1)
insert into EMPLOYEETREE values(3,'Clemens',2)
insert into EMPLOYEETREE values(4,'Malek',2)
insert into EMPLOYEETREE values(5,'Goksin',4)
insert into EMPLOYEETREE values(6,'Kimberly',1)
insert into EMPLOYEETREE values(7,'Ramesh',5)
----------------------
--确定哪些员工向Stephen报告的递归查询
with employeeTemp as
(
select EMPLOYEE, employeename, reportsto from EMPLOYEETREE where EMPLOYEE = 2
union all
select a.EMPLOYEE, a.employeename, a.reportsto from EMPLOYEETREE as a
inner join employeeTemp as b on a.reportsto = b.EMPLOYEE
)
select * from employeeTemp where EMPLOYEE <> 2 --option(maxrecursion 2)
--不报错设置级联关联递归
with employeeTemp as
(
select EMPLOYEE, employeename, reportsto,0 as sublevel from EMPLOYEETREE where EMPLOYEE = 2
union all
select a.EMPLOYEE, a.employeename, a.reportsto,sublevel+1 from EMPLOYEETREE as a
inner join employeeTemp as b on a.reportsto = b.EMPLOYEE
)
select * from employeeTemp where EMPLOYEE <> 2 and sublevel <=2 --option(maxrecursion 2)
10. pivot 与 unpivot
前者用在行转列,注意:必须用聚合函数与PIVOT一起使用,计算聚会时将不考虑出现在值列中的任何空值;一般情况下,可以用列上的子查询来替换pivot语句,但是这样做效率不高
后者用在列转行,注意:如果某些列中有null值,将会被过滤掉,不产生新行;语法上For前指定的新列,对应原表指定列名中的值,For后指定的新列对应原表指定列名中的标题的值
两者都有的共性:语法上最后必须要有别名;IN里面指定的列类型必须是一致的。
示例代码如下:
复制代码 代码如下:
pivot与unpivot
--关于PIVOT的操作
CREATE TABLE #test
(
NAME VARCHAR(max),
SCORE INT
)
INSERT INTO #test VALUES ('张三','97')
INSERT INTO #test VALUES ('李四','28')
INSERT INTO #test VALUES ('王五','33')
INSERT INTO #test VALUES ('神人','78')
--NAME SCORE
--张三 97
--李四 28
--王五 33
--神人 78
--行转列
SELECT --'成绩单' AS SCORENAME ,
[张三], [李四], [王五]
FROM #test
PIVOT (AVG(SCORE) FOR NAME IN ([张三], [李四], [王五])) b
-----------------------------------------
CREATE TABLE VendorEmployee(
VendorId INT,
Emp1Order INT,
Emp2Order INT,
Emp3Order INT,
Emp4Order INT,
Emp5Order INT,
)
GO
INSERT INTO VendorEmployee VALUES(1,4,3,5,4,4)
INSERT INTO VendorEmployee VALUES(2,4,1,5,5,5)
INSERT INTO VendorEmployee VALUES(3,4,3,5,4,4)
INSERT INTO VendorEmployee VALUES(4,4,2,5,4,4)
INSERT INTO VendorEmployee VALUES(5,5,1,5,5,5)
SELECT * FROM VendorEmployee
----------------
--列转行
SELECT * FROM (
SELECT VendorId,[Emp1Order],[Emp2Order],[Emp3Order],[Emp4Order],[Emp5Order] FROM VendorEmployee) AS unpiv
UNPIVOT (orders FOR elyid IN ([Emp1Order],[Emp2Order],[Emp3Order],[Emp4Order],[Emp5Order])) AS child
ORDER BY elyid
SELECT * FROM VendorEmployee
UNPIVOT (orders FOR elyid IN ([Emp1Order],[Emp2Order],[Emp3Order],[Emp4Order],[Emp5Order])) AS child
ORDER BY elyid
SELECT * FROM VendorEmployee UNPIVOT ( ORDERS FOR [操作员名字] IN ([Emp1Order],[Emp2Order],[Emp3Order],[Emp4Order],[Emp5Order]))
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