为了获得结果,您需要对数据应用 UNPIVOT 和 PIVOT 函数。 UNPIVOT 将获取列(ID、网站)并将它们转换为行,一旦完成,您就可以将数据 PIVOT 回列。
UNPIVOT 代码将类似于以下内容:
select name,
col+'_'+cast(col_num as varchar(10)) col,
value
from
(
select name,
cast(id as varchar(11)) id,
website,
row_number() over(partition by name order by id) col_num
from yt
) src
unpivot
(
value
for col in (id, website)
) unpiv;
见SQL Fiddle with Demo。这给出了一个结果:
| NAME | COL | VALUE |
-------------------------------------
| Aaron | id_1 | 2305 |
| Aaron | website_1 | CoolSave1 |
| Aaron | id_2 | 8464 |
| Aaron | website_2 | DiscoWorld1 |
如您所见,我在 unpivot 之前对数据应用了 row_number(),行号用于生成新的列名。 UNPIVOT 中的列也必须是相同的数据类型,我将cast 应用于子查询中的id 列,以便在数据透视之前将数据转换为varchar。
然后在 PIVOT 中使用 col 值。取消透视数据后,应用 PIVOT 函数:
select *
from
(
select name,
col+'_'+cast(col_num as varchar(10)) col,
value
from
(
select name,
cast(id as varchar(11)) id,
website,
row_number() over(partition by name order by id) col_num
from yt
) src
unpivot
(
value
for col in (id, website)
) unpiv
) d
pivot
(
max(value)
for col in (id_1, website_1, id_2, website_2, id_3, website_3)
) piv;
见SQL Fiddle with Demo。
如果您的值数量有限或已知,则上述版本非常有用。但如果行数未知,则需要使用动态 SQL 生成结果:
DECLARE @cols AS NVARCHAR(MAX),
@query AS NVARCHAR(MAX)
select @cols = STUFF((SELECT ',' + QUOTENAME( col+'_'+cast(col_num as varchar(10)))
from
(
select row_number() over(partition by name order by id) col_num
from yt
) t
cross apply
(
select 'id' col union all
select 'website'
) c
group by col, col_num
order by col_num, col
FOR XML PATH(''), TYPE
).value('.', 'NVARCHAR(MAX)')
,1,1,'')
set @query = 'SELECT name,' + @cols + '
from
(
select name,
col+''_''+cast(col_num as varchar(10)) col,
value
from
(
select name,
cast(id as varchar(11)) id,
website,
row_number() over(partition by name order by id) col_num
from yt
) src
unpivot
(
value
for col in (id, website)
) unpiv
) x
pivot
(
max(value)
for col in (' + @cols + ')
) p '
execute(@query);
见SQL Fiddle with Demo。两个版本都给出了结果:
| NAME | ID_1 | WEBSITE_1 | ID_2 | WEBSITE_2 | ID_3 | WEBSITE_3 |
------------------------------------------------------------------------
| Aaron | 2305 | CoolSave1 | 8464 | DiscoWorld1 | (null) | (null) |
| Adriana | 2956 | NewCin1 | 4563 | NewCin3 | 5991 | NewCin2 |