爲了得到這個結果,您將必須UNPIVOT和母雞的PIVOT數據。 UNPIVOT將取fwildcardId
,refNumber
,wildcardName
,wildcardValue
和comments
列中的值,並將它們變成行。一旦數據成行,那麼您可以應用PIVOT函數來獲得最終結果。
要取消轉換數據,可以使用UNPIVOT函數,也可以使用CROSS APPLY和VALUES子句。
UNPIVOT:
select recordid,
col+cast(rn as varchar(10)) col,
unpiv_value
from
(
select recordid,
cast(fwildcardid as varchar(10)) fwildcardid,
cast(refnumber as varchar(10)) refnumber,
cast(wildcardname as varchar(10)) name,
cast(wildcardvalue as varchar(10)) value,
cast(comments as varchar(10)) comments,
row_number() over(partition by recordid
order by fwildcardid) rn
from tempp
) d
unpivot
(
unpiv_value
for col in (fwildcardid, refnumber, name, value, comments)
) c
見SQL Fiddle with Demo。
CROSS APPLY和值:
select recordid,
col+cast(rn as varchar(10)) col,
value
from
(
select recordid,
cast(fwildcardid as varchar(10)) fwildcardid,
cast(refnumber as varchar(10)) refnumber,
wildcardname,
wildcardvalue,
comments,
row_number() over(partition by recordid
order by fwildcardid) rn
from tempp
) d
cross apply
(
values
('fwildcardid', fwildcardid),
('refnumber', refnumber),
('name', wildcardname),
('value', wildcardvalue),
('comments', comments)
) c (col, value)
見SQL Fiddle with Demo。
這些轉換結果的格式:
| RECORDID | COL | VALUE |
------------------------------------
| 404450 | fwildcardid1 | 154833 |
| 404450 | refnumber1 | 1 |
| 404450 | name1 | aa |
| 404450 | value1 | oi |
| 404450 | comments1 | p |
| 404450 | fwildcardid2 | 154834 |
當你unpivot的數據轉換成同一列,它必須是相同的數據類型。您會注意到我對列應用了cast
,因此數據類型相同。
一旦數據行格式,您可以將其轉換回柱與PIVOT:
select *
from
(
select recordid,
col+cast(rn as varchar(10)) col,
unpiv_value
from
(
select recordid,
cast(fwildcardid as varchar(10)) fwildcardid,
cast(refnumber as varchar(10)) refnumber,
cast(wildcardname as varchar(10)) name,
cast(wildcardvalue as varchar(10)) value,
cast(comments as varchar(10)) comments,
row_number() over(partition by recordid
order by fwildcardid) rn
from tempp
) d
unpivot
(
unpiv_value
for col in (fwildcardid, refnumber, name, value, comments)
) c
) src
pivot
(
max(unpiv_value)
for col in (fwildcardid1, refnumber1, name1, value1, comments1,
fwildcardid2, refnumber2, name2, value2, comments2)
) piv;
見SQL Fiddle with Demo。
如果您有已知數量的列,上述版本的工作效果很好,但如果您將有未知數量的值將被轉換爲列,那麼您將需要使用動態sql來獲得結果:
DECLARE @cols AS NVARCHAR(MAX),
@query AS NVARCHAR(MAX)
select @cols = STUFF((SELECT ',' + QUOTENAME(c.col+cast(rn as varchar(10)))
from
(
select row_number() over(partition by recordid
order by fwildcardid) rn
from tempp
) t
cross apply
(
select 'fwildcardid' col, 1 sortorder union all
select 'refNumber', 2 union all
select 'name', 3 union all
select 'value', 4 union all
select 'comments', 5
) c
group by col, rn, sortorder
order by rn, sortorder
FOR XML PATH(''), TYPE
).value('.', 'NVARCHAR(MAX)')
,1,1,'')
set @query = 'SELECT recordid,' + @cols + ' from
(
select recordid,
col+cast(rn as varchar(10)) col,
unpiv_value
from
(
select recordid,
cast(fwildcardid as varchar(10)) fwildcardid,
cast(refnumber as varchar(10)) refnumber,
cast(wildcardname as varchar(10)) name,
cast(wildcardvalue as varchar(10)) value,
cast(comments as varchar(10)) comments,
row_number() over(partition by recordid
order by fwildcardid) rn
from tempp
) d
unpivot
(
unpiv_value
for col in (fwildcardid, refnumber, name, value, comments)
) c
) src
pivot
(
max(unpiv_value)
for col in (' + @cols + ')
) p '
execute(@query);
見SQL Fiddle with Demo。這兩個給出結果:
| RECORDID | FWILDCARDID1 | REFNUMBER1 | NAME1 | VALUE1 | COMMENTS1 | FWILDCARDID2 | REFNUMBER2 | NAME2 | VALUE2 | COMMENTS2 |
-------------------------------------------------------------------------------------------------------------------------------
| 404450 | 154833 | 1 | aa | oi | p | 154834 | 2 | aaa | p | p |
| 406115 | 154867 | 1 | 98 | ff | ff | (null) | (null) | (null) | (null) | (null) |
| 406199 | 154869 | 1 | kki | aaaa | ssss | (null) | (null) | (null) | (null) | (null) |
| 406212 | 154880 | 1 | bbbbb | card | comm | (null) | (null) | (null) | (null) | (null) |
有上重複任何限制嗎? – Luv 2013-04-23 06:28:38
是最大值是10 – 2013-04-23 06:31:18
可能的重複[將多行合併到一行並根據行數添加列](http://stackoverflow.com/questions/15355100/combining-multiple-rows-into-one-行和附加的列依賴於) – 2013-04-23 06:51:56