基于SQL Server中如何比较两个表的各组数据 图解说明

开始

前一阵子,在项目中碰到这样一个sql查询需求,有两个相同结构的表(table_left & table_right),如下:

图1.

检查表table_left的各组(groupid),是否在表table_right中存在有一组(groupid)数据(data)与它的数据(data)完全相等.

如图1. 可以看出表table_left和table_right存在两组数据完整相等:

图2.

分析

从上面的两个表,可以知道它们存放的是一组一组的数据;那么,接下来我借助数学集合的列举法和运算进行分析。

先通过集合的列举法描述两个表的各组数据:

图3.

这里只有两种情况,相等和不相等。对于不相等,可再分为部分相等、包含、和完全不相等。使用集合描述,可使用交集,子集,并集。如下面图4.,我列举出这几种常见的情况:

图4.

实现

在数据库中,要找出表table_left和表table_right存在相同数据的组,方法很多,这里我列出两种常用的方法。

(下面的sql脚本,是以图4.的数据为基础参考)

方法1:

通过”select … from …order by … xml for path(”) “把各组的data列数据连串起来(如,图4.把table_left的组#11的列data连串起来成”data1-data2-data3″),其他分组(包含表table_right)以此方法实现data列数据连串起来;然后通过比较两表的连串后字段是否存在相等,若是相等就说明这比较多两组数据相等,由此可以判断出表table_left的哪组数据在表table_right存在与它数据完全相等的组。

针对方法1,需要对原表增加一个字段datapath,用于存储data列数据连串的结果,如:

复制代码 代码如下:

alter table table_left add datapath nvarchar(200)

alter table table_right add datapath nvarchar(200)

分组连串data列数据并update至刚新增的列datapath,如:

复制代码 代码如下:

update a

    set datapath=b.datapath

    from table_left a

        cross apply(select (select ‘-‘+x.data from table_left x where x.groupid=a.groupid order by x.data for xml path(”)) as datapath)b

update a

    set datapath=b.datapath

    from table_right a

        cross apply(select (select ‘-‘+x.data from table_right x where x.groupid=a.groupid order by x.data for xml path(”)) as datapath)b

接下来就是查询了,如:

复制代码 代码如下:

select distinct a.groupid

    from table_left a

    where exists(select 1 from table_right x where x.datapath=a.datapath)

完整代码:

复制代码 代码如下:

view code

use tempdb

go

if object_id(‘table_left’) is not null drop table table_left

if object_id(‘table_right’) is not null drop table table_right

go

create table table_left(groupid nvarchar(5),data nvarchar(10))

create table table_right(groupid nvarchar(5),data nvarchar(10))

go

alter table table_left add datapath nvarchar(200)

alter table table_right add datapath nvarchar(200)

go

create nonclustered index ix_left on table_left(datapath)

create nonclustered index ix_right on table_right(datapath)

go

set nocount on

go

insert into table_right(groupid,data)

select ‘#1′,’data1’ union all

select ‘#1′,’data2’ union all

select ‘#1′,’data3’ union all

select ‘#2′,’data55’ union all

select ‘#2′,’data55’ union all

select ‘#3′,’data91’ union all

select ‘#3′,’data92’ union all

select ‘#4′,’data65’ union all

select ‘#4′,’data66’ union all

select ‘#4′,’data67’ union all

select ‘#4′,’data68’ union all

select ‘#4′,’data69’ union all

select ‘#5′,’data77’ union all

select ‘#5′,’data79’

insert into table_left(groupid,data)

select ‘#11′,’data1’ union all

select ‘#11′,’data2’ union all

select ‘#11′,’data3’ union all

select ‘#22′,’data55’ union all

select ‘#22′,’data57’ union all

select ‘#33′,’data99’ union all

select ‘#33′,’data99’ union all

select ‘#44′,’data66’ union all

select ‘#44′,’data68’ union all

select ‘#55′,’data77’ union all

select ‘#55′,’data78’ union all

select ‘#55′,’data79’

go

update a

    set datapath=b.datapath

    from table_left a

        cross apply(select (select ‘-‘+x.data from table_left x where x.groupid=a.groupid order by x.data for xml path(”)) as datapath)b

update a

    set datapath=b.datapath

    from table_right a

        cross apply(select (select ‘-‘+x.data from table_right x where x.groupid=a.groupid order by x.data for xml path(”)) as datapath)b



select distinct a.groupid

    from table_left a

    where exists(select 1 from table_right x where x.datapath=a.datapath)

方法2:

通过sql sever提供的集运算符”except”,判断两组非重复的数据。如果两组针对对方都不存在非重复的数据,就说明这两组数据完全相等。如,表table_left中的组#11和表 table_right中的组#1,对列data进行”except”集运算,无任是(#11 à #1)进行except集运算,还是(#1 à #11 )进行except集合运算,都返回空结果,这就说明组#1 和#11的data数据完全相等,如:

复制代码 代码如下:

select data from table_left where groupid=’#11′ except select data from table_right where groupid=’#1′

select data from table_right where groupid=’#1′ except select data from table_left where groupid=’#11′

同样道理,我们把表table_left中的组#11和表 table_right中的组#2,对列data进行”except”集运算,如:

复制代码 代码如下:

select data from table_left where groupid=’#11′ except select data from table_right where groupid=’#2′

select data from table_right where groupid=’#2′ except select data from table_left where groupid=’#11′

只要(#11 à #2 )或 (#2 à #11 )的”except”集运算结果有记录,就说明两组的数据不相等。

两张表的所有组都进行比较,我们需要通过以下sql脚本实现,如:

复制代码 代码如下:

select distinct a.groupid

    from table_left a

        inner join table_right b on b.data=a.data

    where not exists(select x.data from table_left x where x.groupid=a.groupid except select y.data from table_right y where y.groupid=b.groupid )

        and not exists(select x.data from table_right x where x.groupid=b.groupid except select y.data from table_left y where y.groupid=a.groupid )

 完整代码:

复制代码 代码如下:

view code

use tempdb

go

if object_id(‘table_left’) is not null drop table table_left

if object_id(‘table_right’) is not null drop table table_right

go

create table table_left(groupid nvarchar(5),data nvarchar(10))

create table table_right(groupid nvarchar(5),data nvarchar(10))

go

create nonclustered index ix_left on table_left(data)

create nonclustered index ix_right on table_right(data)

go

set nocount on

go

insert into table_right(groupid,data)

select ‘#1′,’data1’ union all

select ‘#1′,’data2’ union all

select ‘#1′,’data3’ union all

select ‘#2′,’data55’ union all

select ‘#2′,’data55’ union all

select ‘#3′,’data91’ union all

select ‘#3′,’data92’ union all

select ‘#4′,’data65’ union all

select ‘#4′,’data66’ union all

select ‘#4′,’data67’ union all

select ‘#4′,’data68’ union all

select ‘#4′,’data69’ union all

select ‘#5′,’data77’ union all

select ‘#5′,’data79’

insert into table_left(groupid,data)

select ‘#11′,’data1’ union all

select ‘#11′,’data2’ union all

select ‘#11′,’data3’ union all

select ‘#22′,’data55’ union all

select ‘#22′,’data57’ union all

select ‘#33′,’data99’ union all

select ‘#33′,’data99’ union all

select ‘#44′,’data66’ union all

select ‘#44′,’data68’ union all

select ‘#55′,’data77’ union all

select ‘#55′,’data78’ union all

select ‘#55′,’data79’

go

–select

select distinct a.groupid

    from table_left a

        inner join table_right b on b.data=a.data

    where not exists(select x.data from table_left x where x.groupid=a.groupid except select y.data from table_right y where y.groupid=b.groupid )

        and not exists(select x.data from table_right x where x.groupid=b.groupid except select y.data from table_left y where y.groupid=a.groupid )

方法1 vs. 方法2 :

方法1和方法2都能找出表table_left在table_right存在数据完全相等的组#11。但性能角度上,方法2比方法1略胜一筹,可以看它们执行过程的统计信息:

方法1:

图5.

方法2:

图6.

如果,数据量大情况下,那么方法2比方法1更具有明显的优点。因为方法1,多两个更新datapath的部分,数据量随着增加,这里位置的更新就耗很多的资源;如果datapath列数据大小超过900字节,会导致无法在datapath创建索引,影响后面的select查询性能。

扩展

这里说扩展,主要是针对上面的方法2来说。在当列data的数据大小超过900字节,或者含有多个数据列要进行比较,看是否存在两组(groupid)的各对应列数据一一相等。

图7.

这样的情况,可对字段datasub1 & datasub2 创建一个哈希索引,如:

复制代码 代码如下:

alter table table_left add datachecksum as checksum(datasub1,datasub2)

alter table table_right add datachecksum as checksum(datasub1,datasub2)

go

create nonclustered index ix_table_left_cs on table_right(datachecksum)

create nonclustered index table_right_cs on table_right(datachecksum)

后面的select查询语句,在inner join 部分稍改动下即可,如:

复制代码 代码如下:

select distinct a.groupid

    from table_left a

        inner join table_right b on b.datachecksum=a.datachecksum

            and b.datasub1=a.datasub1

            and b.datasub2=a.datasub2

    where not exists(select x.datasub1,x.datasub2 from table_left x where x.groupid=a.groupid except select y.datasub1,y.datasub2 from table_right y where y.groupid=b.groupid )

        and not exists(select x.datasub1,x.datasub2 from table_right x where x.groupid=b.groupid except select y.datasub1,y.datasub2 from table_left y where y.groupid=a.groupid )

 完整代码:

复制代码 代码如下:

view code

use tempdb

go

if object_id(‘table_left’) is not null drop table table_left

if object_id(‘table_right’) is not null drop table table_right

go

create table table_left(groupid nvarchar(5),datasub1 nvarchar(10),datasub2 nvarchar(10))

create table table_right(groupid nvarchar(5),datasub1 nvarchar(10),datasub2 nvarchar(10))

go

alter table table_left add datachecksum as checksum(datasub1,datasub2)

alter table table_right add datachecksum as checksum(datasub1,datasub2)

go

create nonclustered index ix_table_left_cs on table_left(datachecksum)

create nonclustered index table_right_cs on table_right(datachecksum)

go

set nocount on

go

insert into table_right(groupid,datasub1,datasub2)

select ‘#1′,’data1′,’data7’ union all

select ‘#1′,’data2′,’data8’ union all

select ‘#1′,’data3′,’data9’ union all

select ‘#2′,’data55′,’data4’ union all

select ‘#2′,’data55′,’data5’

insert into table_left(groupid,datasub1,datasub2)

select ‘#11′,’data1′,’data7’ union all

select ‘#11′,’data2′,’data8’ union all

select ‘#11′,’data3′,’data9’ union all

select ‘#22′,’data55′,’data0’ union all

select ‘#22′,’data57′,’data2’ union all

select ‘#33′,’data99′,’data4’ union all

select ‘#33′,’data99′,’data6’

go

–select

select distinct a.groupid

    from table_left a

        inner join table_right b on b.datachecksum=a.datachecksum

            and b.datasub1=a.datasub1

            and b.datasub2=a.datasub2

    where not exists(select x.datasub1,x.datasub2 from table_left x where x.groupid=a.groupid except select y.datasub1,y.datasub2 from table_right y where y.groupid=b.groupid )

        and not exists(select x.datasub1,x.datasub2 from table_right x where x.groupid=b.groupid except select y.datasub1,y.datasub2 from table_left y where y.groupid=a.groupid )

小结

对于这个问题,可能还有其他的或更优的解决方法.而且在实际的生产环境中,可能碰到的情况会有所不同,无论如何,需要多分析,多动手多实验,找到最优的解决方法。

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