简介:"Group By"根据字面上的意思理解,就是根据"By"后面指定的规则对数据进行分组(分组就是将一个数据集按照"By"指定的规则分成若干个子数据集)，然后再对子数据集进行数据处理。

1、下面通过一个实例来了解"Group By"的作用和功能,代码如下:

select * from course

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" 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这是一个课程明细表,现在有一个报表程序,需要每个老师的编号,以及每位老师所教的课程总数,下面是解决代码:

select tno,COUNT(cname) as courses from course group by tno

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" alt="" />

这就是个人的理解,上图是通过Group By分组之后的第一组,后面的数据集合包含教师ID为t001的所有行数数据,这个数据集合我们可以使用聚集函数来获取我们想要的信息,但是无法获取其中的详细的列信息！原因我们可以通过上图的结构可以看出!

ok,通过group by 完成需求!

上面的Select指定了两个列，tno包含教师的编号，courses 为计算字段(用Count()函数建立)，group by子句指示DBMS按tno排序并分组数据。这就会对每个tno而不是整个表计算courses一次(也就是说DBMS会对(按照tno排序并分组之后的单个数据子集)进行Count()运算，而不是真个数据集)。

2、下面是使用Group By子句需要知道的一些重要的规定

(1)Group By子句可以包含任意数目的列，因而可以对分组进行嵌套,进行更细致的分组。

(2)Group By子句中列出的每一列都必须是检索列(或者有效的表达式,注意不能是聚集函数)。如果在SELECT中使用了检索列(或者表达式),则在Group By子句中使用相同的表达式,不能使用别名。

(3)大多数SQL不允许Group By带有可变长度的数据类型(如文本,text类型)。

(4)除聚集计算语句外,SELECT语句中的每一列都必须在Group By中给出。

(5)如果分组列中包含具有Null值的行,则Null将作为一个分组返回,如果列中有多行Null，他们将作为一个分组返回。

(6)Group By必须出现在Where子句之后,Order By子句之前。

(7)如果在Group By子句中嵌套了分组,数据将在最后指定的分组上进行汇总。换句话说,在建立分组时，指定的所有列都一起计算(不能从个别的列中取回数据)。

3、Group By All+多个字段,Group By+多个字段

在SQL Server 中Group By All+多个字段和Group By+多个字段在效果是一样的,都是通过多个字段来分组!如下代码:

select * from course

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" 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这是一个课程明细表，现在有个报表程序需要展示每个老师教授的课程(相同的课程)一共教多少个班级,下面是解决代码:

select tno,cname,COUNT(cname) from course group by all tno,cname order by tno

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" alt="" />

这是个人的理解,上图是通过Group By分组之后的第一组,后面的数据集合包含(教师ID为t001并且课程名称为Oracle)的所有行数数据,这个数据集合我们可以使用聚集函数来获取我们想要的信息,但是无法获取其中的详细的列信息！原因我们可以通过上图的结构可以看出!

aaarticlea/png;base64,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" alt="" />

ok，解决需求,通过上面的结果图,我们可以看出,三个老师所教的课程基本都只教一个班，除了t003老师的sql SERVER 2005教了两个班，当然我们实际的业务中,并不会这样建表,我这边指示为了演示Group By+多个字段能完成的功能,才强行构建这个需求!