交叉表
交叉表(Cross Tabulations)是一种常用的分类汇总表格。使用交叉表查询,显示源于表中某个字段的汇总值,并将它们分组,其中一组列在数据表的左侧,另一组列在数据表的上部。行和列的交叉处可以对数据进行多种汇总计算,如:求和、平均值、记数、最大值、最小值等。使用交叉表查询数据非常直观明了,被广泛应用。交叉表查询也是数据库的一个特点。
例如:
select 表1.组名,
(select 表1.成员姓名 from 表2 b where 表1.成员1id=表2.成员id) as 成员1id,
(select 表1.成员姓名 from 表2 b where 表1.成员2id=表2.成员id) as 成员2id,
(select 表1.成员姓名 from 表2 b where 表1.成员3id=表2.成员id) as 成员3id
from 表1,表2
--这种就是交叉表查询
交叉报表是报表当中常见的类型,属于基本的报表,是行、列方向都有分组的报表。这里牵涉到另外一个概念即分组报表。这是所有报表当中最普通,最常见的报表类型,也是所有报表工具都支持的一种报表格式。从一般概念上来讲,分组报表就是只有纵向的分组。传统的分组报表制作方式是把报表划分为条带状,用户根据一个数据绑定向导指定分组,汇总字段,生成标准的分组报表。
这里我来演示下在POSTGRESQL里面如何实现交叉表的展示,下面话不多说了,来一起看看详细的介绍吧
原始表数据如下:
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t_girl=# select * from score;
name | subject | score
-------+---------+-------
Lucy | English | 100
Lucy | Physics | 90
Lucy | Math | 85
Lily | English | 95
Lily | Physics | 81
Lily | Math | 84
David | English | 100
David | Physics | 86
David | Math | 89
Simon | English | 90
Simon | Physics | 76
Simon | Math | 79
(12 rows )
Time : 2.066 ms
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想要实现以下的结果:
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name | English | Physics | Math
------+---------+---------+------
Simon | 90 | 76 | 79
Lucy | 100 | 90 | 85
Lily | 95 | 81 | 84
David | 100 | 86 | 89
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大致有以下几种方法:
1、用标准SQL展现出来
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t_girl=# select name ,
t_girl-# sum ( case when subject = 'English' then score else 0 end ) as "English" ,
t_girl-# sum ( case when subject = 'Physics' then score else 0 end ) as "Physics" ,
t_girl-# sum ( case when subject = 'Math' then score else 0 end ) as "Math"
t_girl-# from score
t_girl-# group by name order by name desc ;
name | English | Physics | Math
-------+---------+---------+------
Simon | 90 | 76 | 79
Lucy | 100 | 90 | 85
Lily | 95 | 81 | 84
David | 100 | 86 | 89
(4 rows )
Time : 1.123 ms
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2、用PostgreSQL 提供的第三方扩展 tablefunc 带来的函数实现
以下函数crosstab 里面的SQL必须有三个字段,name, 分类以及分类值来作为起始参数,必须以name,分类值作为输出参数。
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t_girl=# SELECT *
FROM crosstab( 'select name,subject,score from score order by name desc' ,$$ values ( 'English' ::text),( 'Physics' ::text),( 'Math' ::text)$$)
AS score( name text, English int , Physics int , Math int );
name | english | physics | math
-------+---------+---------+------
Simon | 90 | 76 | 79
Lucy | 100 | 90 | 85
Lily | 95 | 81 | 84
David | 100 | 86 | 89
(4 rows )
Time : 2.059 ms
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3、用PostgreSQL 自身的聚合函数实现
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t_girl = # select name,split_part(split_part(tmp,',',1),':',2) as "English",
t_girl - # split_part(split_part(tmp,',',2),':',2) as "Physics",
t_girl - # split_part(split_part(tmp,',',3),':',2) as "Math"
t_girl - # from
t_girl - # (
t_girl( # select name,string_agg(subject||':'||score,',') as tmp from score group by name order by name desc
t_girl( # ) as T;
name | English | Physics | Math
- - - - - - - + - - - - - - - - - + - - - - - - - - - + - - - - - -
Simon | 90 | 76 | 79
Lucy | 100 | 90 | 85
Lily | 95 | 81 | 84
David | 100 | 86 | 89
( 4 rows)
Time: 2.396 ms
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4、 存储函数实现
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create or replace function func_ytt_crosstab_py ()
returns setof ytt_crosstab
as
$ytt$
for row in plpy.cursor( "select name,string_agg(subject||':'||score,',') as tmp from score group by name order by name desc" ):
a = row[ 'tmp' ].split( ',' )
yield (row[ 'name' ],a[ 0 ].split( ':' )[ 1 ],a[ 1 ].split( ':' )[ 1 ],a[ 2 ].split( ':' )[ 1 ])
$ytt$ language plpythonu;
t_girl = # select name,english,physics,math from func_ytt_crosstab_py();
name | english | physics | math
- - - - - - - + - - - - - - - - - + - - - - - - - - - + - - - - - -
Simon | 90 | 76 | 79
Lucy | 100 | 90 | 85
Lily | 95 | 81 | 84
David | 100 | 86 | 89
( 4 rows)
Time: 2.687 ms
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5、 用PLPGSQL来实现
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t_girl = # create type ytt_crosstab as (name text, English text, Physics text, Math text);
CREATE TYPE
Time: 22.518 ms
create or replace function func_ytt_crosstab ()
returns setof ytt_crosstab
as
$ytt$
declare v_name text : = '';
v_english text : = '';
v_physics text : = '';
v_math text : = '';
v_tmp_result text : = '';
declare cs1 cursor for select name,string_agg(subject|| ':' ||score, ',' ) from score group by name order by name desc;
begin
open cs1;
loop
fetch cs1 into v_name,v_tmp_result;
exit when not found;
v_english = split_part(split_part(v_tmp_result, ',' , 1 ), ':' , 2 );
v_physics = split_part(split_part(v_tmp_result, ',' , 2 ), ':' , 2 );
v_math = split_part(split_part(v_tmp_result, ',' , 3 ), ':' , 2 );
return query select v_name,v_english,v_physics,v_math;
end loop;
end;
$ytt$ language plpgsql;
t_girl = # select name,English,Physics,Math from func_ytt_crosstab();
name | english | physics | math
- - - - - - - + - - - - - - - - - + - - - - - - - - - + - - - - - -
Simon | 90 | 76 | 79
Lucy | 100 | 90 | 85
Lily | 95 | 81 | 84
David | 100 | 86 | 89
( 4 rows)
Time: 2.127 ms
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总结
以上就是这篇文章的全部内容了,希望本文的内容对大家的学习或者工作具有一定的参考学习价值,如果有疑问大家可以留言交流,谢谢大家对服务器之家的支持。
原文链接:https://blog.csdn.net/a258831020/article/details/48446213