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SQL总结(三)其他查询

时间:2014-06-03 09:59:00      阅读:306      评论:0      收藏:0      [点我收藏+]

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SQL总结(三)其他查询

 其他常用的SQL,在这里集合。

1、SELECT INTO

从一个表中选取数据,然后把数据插入另一个表中。常用于创建表的备份或者用于对记录进行存档。

语法:

SELECT column_name(s)
INTO new_table_name [IN externaldatabase] 
FROM old_tablename

IN 子句可用于向另一个数据库中拷贝表。

1)备份表信息

SELECT ID,Name 
INTO Students_Backup
FROM Students

2)复制到备份库

SELECT *
INTO Students IN Backup.mdb
FROM Students

2、IDENTITY 

作用:创建唯一的,递增的列

注意:一张表中只能有一列为IDENTITY

1)创建学生信息表时,指定其ID为自增列,从1开始,每次递增1

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IF OBJECT_ID (NStudents, NU) IS NOT NULL
    DROP TABLE Students;
GO
--学生信息表
CREATE TABLE Students(
ID int primary key IDENTITY(1,1) not null,
Name nvarchar(50),
Age int,
Sex bit,
City nvarchar(50),
MajorID int
)
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2)如果指定了自增列,又需要插入指定ID的值,需要停止INDENTIY,执行后再开启。

SET IDENTITY_Insert Students ON 
insert Students(ID,Name,Age,City) values(10,Jim,18,NewYank) 
SET IDENTITY_Insert Students OFF 

3)与SELECT INTO 合用,插入行号

这个常常用于临时表分页时使用。

注意:如果查询的列中有自增列,需要将其删除,或者屏蔽,因为一张表中只有一个IDENTITY字段。

SELECT IDENTITY(int,1,1) AS RowNumber,Name,Age,Sex,City
INTO Students_Backup
FROM Students

SCOPE_IDENTITY() 

还有一个常用的函数,与此一起使用 SCOPE_IDENTITY()

常常在有IDENTITY列的插入时,需要返回当前的行的IDENTITY的列值。

如: 

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IF OBJECT_ID (NStudents, NU) IS NOT NULL
    DROP TABLE Students;
GO
--学生信息表
CREATE TABLE Students(
    ID int IDENTITY(1,1) PRIMARY KEY not null,
    Name nvarchar(50),
    Age int,
    Sex bit,
    City nvarchar(50),
    MajorID int
)

INSERT INTO Students(Name,Age,Sex,City,MajorID) VALUES(Jim,18,0,ShangHai,12)
SELECT SCOPE_IDENTITY()
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这个例子,每次返回插入记录的ID的值。如果有其他关联表用到此ID,这时就不用再从数据库查一遍了。 

3、OBJECT_ID 

返回架构范围内对象的数据库对象标识号。

1)查询表是否存在

SELECT OBJECT_ID(NStudents,NU)

与以下语句等价:

SELECT id FROM sysobjects WHERE name=NStudents and type=NU

 

2)常常用于创建表、视图时,做判定。保证脚本的重复执行

创建学生信息表时,需要判定该表是否存在,如果存在则删除

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IF OBJECT_ID (NStudents, NU) IS NOT NULL
    DROP TABLE Students;
GO
--学生信息表
CREATE TABLE Students(
ID int primary key IDENTITY(1,1) not null,
Name nvarchar(50),
Age int,
Sex bit,
City nvarchar(50),
MajorID int
)
bubuko.com,布布扣

 

 4、跨库执行

 

如果系统需要多个数据库,当执行跨库脚本,无需再次进行连接,可以执行如下脚本

 

实例:当前在master库,查询TestDB库的Students表信息:

 

USE master

SELECT * FROM TestDB..Students

 

 

常用函数

1、LEN函数

计算字段值的长度

SELECT LEN(Name) AS NameLength FROM Students

2、FORMAT函数

FORMAT 函数用于对字段的显示进行格式化。

语法:

SELECT FORMAT(column_name,format) FROM table_name

1)时间格式化

SELECT FORMAT(GETDATE(),yyyy-MM-dd) 

结果:2014-05-13

3、CAST函数

1、实例:将价格转为整型

SELECT CAST(Price AS smallint) AS CPrice FROM Orders

结果:10

2、将字段解析为XML

SELECT CAST(Scheme AS xml) AS CPrice FROM Orders

结果:

<xml>
  <ProductID>101</ProductID>
  <ProductName>Card</ProductName>
</xml>

 4、CONVERT

语法:

 CONVERT(data_type,expression[,style])

说明:
此样式一般在时间类型(datetime,smalldatetime)与字符串类型(nchar,nvarchar,char,varchar)
相互转换的时候才用到.

tyle数字在转换时间时的含义如下:
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------------------------------------------------------------------------------------------------------------
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Style(2位表示年份)         |  Style(4位表示年份)   |   输入输出格式                                    
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------------------------------------------------------------------------------------------------------------
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0                               | 100                           |   mon dd yyyy hh:miAM(或PM)              
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------------------------------------------------------------------------------------------------------------
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1                               |  101   美国                |   mm/dd/yy                                       
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------------------------------------------------------------------------------------------------------------
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2                               |  102    ANSI               |   yy-mm-dd                                        
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------------------------------------------------------------------------------------------------------------
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3                               |  103    英法                |   dd/mm/yy                                       
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------------------------------------------------------------------------------------------------------------
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4                               |  104    德国                |   dd.mm.yy                                        
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------------------------------------------------------------------------------------------------------------
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5                               |  105    意大利             |   dd-mm-yy                                        
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------------------------------------------------------------------------------------------------------------
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6                               |  106                            |   dd mon yy                                        
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------------------------------------------------------------------------------------------------------------
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7                               |  107                            |   mon dd,yy                                        
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------------------------------------------------------------------------------------------------------------
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8                               |  108                            |   hh:mm:ss                                         
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------------------------------------------------------------------------------------------------------------
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9                               |  109                            |   mon dd yyyy hh:mi:ss:mmmmAM(或PM)
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------------------------------------------------------------------------------------------------------------
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10                             |  110    美国                 |   mm-dd-yy                                         
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------------------------------------------------------------------------------------------------------------
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11                             |  111    日本                 |   yy/mm/dd                                        
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------------------------------------------------------------------------------------------------------------
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12                             |  112    ISO                  |   yymmdd                                           
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------------------------------------------------------------------------------------------------------------
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13                             |  113     欧洲默认值     |   dd mon yyyy hh:mi:ss:mmm(24小时制)  
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------------------------------------------------------------------------------------------------------------
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14                             |  114                            |   hh:mi:ss:mmm(24小时制)                    
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------------------------------------------------------------------------------------------------------------
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20                             |  120     ODBC 规范     |    yyyy-mm-dd hh:mi:ss(24小时制)         
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------------------------------------------------------------------------------------------------------------
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21                             |   121                           |    yyyy-mm-dd hh:mi:ss:mmm(24小时制) 
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------------------------------------------------------------------------------------------------------------

1)实例:时间转换为指定形式

SELECT CONVERT(NVARCHAR(20),GETDATE(),120) 

结果:2014-05-13 23:49:34

2)实例转为XML格式

SELECT CONVERT(xml,Scheme) FROM Orders

结果:

<xml>
  <ProductID>101</ProductID>
  <ProductName>Card</ProductName>
</xml>

   

全部脚本

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SELECT UCASE(Name) FROM Students
SELECT UCASE(LastName) as LastName,FirstName FROM Persons





SELECT GETDATE() --2014-05-13 23:15:36.130

SELECT FORMAT(GETDATE(),yyyy-MM-dd)  --2014-05-13

IF OBJECT_ID(Orders,U) IS NOT NULL
DROP TABLE Orders
CREATE TABLE Orders
(
    ID bigint primary key not null,
    ProductID int,
    ProductName nvarchar(50),
    Price float,
    Scheme text,
    Created datetime default(getdate())
)

INSERT INTO Orders(ID,ProductID,ProductName,Price,Scheme) 
VALUES(201405130001,101,Card,10.899,<xml><ProductID>101</ProductID><ProductName>Card</ProductName></xml>)


SELECT LEN(ProductName) AS NameLength FROM Orders    --4

SELECT FORMAT(Created,yyyy-MM-dd) AS FormatDate FROM Orders 

--2014-05-13

SELECT ROUND(Price,2) FROM Orders   --10.9

SELECT CAST(Price AS smallint) AS CPrice FROM Orders     
--10

SELECT CAST(Scheme AS xml) AS CPrice FROM Orders

--CONVERT
SELECT CONVERT(NVARCHAR(20),GETDATE(),120) --2014-05-13 23:49:34
SELECT CONVERT(xml,Scheme) FROM Orders
/* 结果:
<xml>
  <ProductID>101</ProductID>
  <ProductName>Card</ProductName>
</xml>
*/
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SQL总结(三)其他查询,布布扣,bubuko.com

SQL总结(三)其他查询

标签:c   style   class   blog   code   java   

原文地址:http://www.cnblogs.com/yank/p/3722565.html

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