将多列数据合二为一的 SQL 数据透视表，逗号分隔

如何解决将多列数据合二为一的 SQL 数据透视表，逗号分隔

SQL 查询表：

Date        Production LineName  Buyer Style
2021-04-30  100          A       Lev    1a
2021-04-30  200          B       Kont   2d
2021-04-30  300          C       ABB    4l
2021-04-30  400          A       Lev    1a
2021-04-29  600          A       BDA    3z

输出需要像：

LineName  2021-04-29  2021-04-30
A         600,BDA,3Z  500,Lev,1a
B         NULL        200,Kont,2d
C         NULL        300,ABB,4l

我开始编码并停留在

DECLARE @query VARCHAR(4000),@Dates VARCHAR(4000)

SET @Dates = STUFF((
            SELECT DISTINCT '],[' + Cast([Date] As Varchar)
            FROM Table_17M
            ORDER BY '],[' + Cast([Date] As Varchar)
            FOR XML PATH('')
            ),1,2,'') + ']'

SET @query = ';With PivotData
As
(
    Select 
        LineName,-- grouping element
        [Date],-- spreading element
        PlanProduction-- aggregating element
    From Table_17M
)
Select *
From PivotData
Pivot (Sum(PlanProduction) For [Date] In (' + @Dates + ')) As P;'

EXEC (@query);

任何想法请分享。这将非常有帮助。谢谢。

解决方法

如果您使用的是 SQLServer 2017 或更高版本，则使用 string_agg() 而不是 suff()。实施起来更容易，速度也更快。

select @cols=  string_agg(quotename([date]),',') from (select distinct [date] from Table_17M)t

DB-小提琴

 create table Table_17M(Date Date,Production int,LineName varchar(50),Buyer varchar(50),Style varchar(50));
 insert into Table_17M values('2021-04-30',100,'A','Lev','1a');
 insert into Table_17M values('2021-04-30',200,'B','Kont','2d');
 insert into Table_17M values('2021-04-30',300,'C','ABB','4l');
 insert into Table_17M values('2021-04-30',400,'1a');
 insert into Table_17M values('2021-04-29',600,'BDA','3z');

查询：

 DECLARE @cols AS NVARCHAR(MAX),@query  AS NVARCHAR(MAX)
     
 SET @cols = STUFF((SELECT distinct ',' + quotename([date])
             FROM Table_17M
             FOR XML PATH(''),TYPE
             ).value('.','NVARCHAR(MAX)'),1,'')
                
            
        
 set @query = 'select LineName,' + @cols + ' from 
             (
             
             select LineName,[date],concat(sum(production),'',max(buyer),string_agg(Style,'')) other_columns
             from Table_17M
             group by LineName,[date]
             ) x
             pivot 
             (
               max(other_columns)
               for [date] in (' + @cols + ')
 
             ) p 
             group by LineName,' + @cols 
 
 execute( @query)

输出：

LineName	2021-04-29	2021-04-30
A	600,BDA,3z	500,Lev,1a,1a
B	null	200,Kont,2d
C	null	300,ABB,4l

dbhere