Sql 需要根据行中的日期将表数据选择到不同的列中

我不确定我在这里需要什么，看起来我可以使用枢轴，但我不认为这有那么复杂，如果可以的话，我想避免使用枢轴，因为我根本没有使用过它

我有这样的数据：

ID      score   notes               CreateDate
1661    9.2     8.0 on Sept 2010    7/22/2010
1661    7.6                         11/4/2010
1661    7.9                         6/10/2011
1661    8.3                         9/28/2011
1661    7.9                         1/20/2012

ID      score1  notes1              date1       score2  notes2  date2       score3  notes3  date3       score4  notes4  date4
1661    9.2     8.0 on Sept 2010    7/22/2010   7.6     blah    11/4/2010   7.9     blah2   6/10/2011   8.3     blah3   9/28/2011

我想将所有数据组织到一行，最早的日期在第一行，然后使用下一个最早的日期，然后是下一个最早的日期…直到我使用4或5个日期。所以最终的结果是这样的：

ID      score   notes               CreateDate
1661    9.2     8.0 on Sept 2010    7/22/2010
1661    7.6                         11/4/2010
1661    7.9                         6/10/2011
1661    8.3                         9/28/2011
1661    7.9                         1/20/2012

ID      score1  notes1              date1       score2  notes2  date2       score3  notes3  date3       score4  notes4  date4
1661    9.2     8.0 on Sept 2010    7/22/2010   7.6     blah    11/4/2010   7.9     blah2   6/10/2011   8.3     blah3   9/28/2011

---

在这种情况下，PIVOT会很棘手，因为如果您只想显示Score1、Score2、Score3等，那么每个测试PIVOT都有多个列。幸运的是，您可以使用CASE语句创建一个简单但冗长的解决方案：

select
  ID,

  max(case when RowNum = 1 then Score else null end) as Score1,
  max(case when RowNum = 1 then Notes else null end) as Notes1,
  max(case when RowNum = 1 then CreateDate else null end) as Date1,

  max(case when RowNum = 2 then Score else null end) as Score2,
  max(case when RowNum = 2 then Notes else null end) as Notes2,
  max(case when RowNum = 2 then CreateDate else null end) as Date2,

  max(case when RowNum = 3 then Score else null end) as Score3,
  max(case when RowNum = 3 then Notes else null end) as Notes3,
  max(case when RowNum = 3 then CreateDate else null end) as Date3,

  max(case when RowNum = 4 then Score else null end) as Score4,
  max(case when RowNum = 4 then Notes else null end) as Notes4,
  max(case when RowNum = 4 then CreateDate else null end) as Date4,

  max(case when RowNum = 5 then Score else null end) as Score5,
  max(case when RowNum = 5 then Notes else null end) as Notes5,
  max(case when RowNum = 5 then CreateDate else null end) as Date5

from

(
select 
   *, row_number() over (partition by ID order by CreateDate) as RowNum
from 
   mytable
) tt

group by
  ID

---

这是硬编码，涵盖5项测试。少一点就可以了，但不会显示第六个。显然，您可以创建更多的CASE语句来处理更多的测试。

正因为我喜欢PIVOT，我将向您展示如何使用PIVOT函数来实现这一点。为了获得PIVOT函数的结果，您首先需要取消PIVOT的多列score、notes和createdate。unpivot进程将多列转换为多行

由于您使用的是SQL Server 2008，因此可以使用交叉应用来取消对数据的归档，因此查询的第一部分类似于：

;with cte as
(
  select id, score, notes, createdate,
    row_number() over(partition by id order by createdate) seq
  from yourtable
) 
select id, col, value
from 
(
  select t.id, 
    col = col + cast(seq as varchar(10)),
    value
  from cte t
  cross apply
  (
    values
      ('score', cast(score as varchar(10))),
      ('notes', notes),
      ('date', convert(varchar(10), createdate, 120))
  ) c (col, value)
) d;

看。执行此操作将以以下格式获取数据：

|   ID |    COL |            VALUE |
| 1661 | score1 |             9.20 |
| 1661 | notes1 | 8.0 on Sept 2010 |
| 1661 |  date1 |       2010-07-22 |
| 1661 | score2 |             7.60 |
| 1661 | notes2 |           (null) |
| 1661 |  date2 |       2010-11-04 |
| 1661 | score3 |             7.90 |

现在，您可以应用PIVOT函数：

;with cte as
(
  select id, score, notes, createdate,
    row_number() over(partition by id order by createdate) seq
  from yourtable
) 
select id, col, value
from 
(
  select t.id, 
    col = col + cast(seq as varchar(10)),
    value
  from cte t
  cross apply
  (
    values
      ('score', cast(score as varchar(10))),
      ('notes', notes),
      ('date', convert(varchar(10), createdate, 120))
  ) c (col, value)
) d
pivot
(
  max(value)
  for col in (score1, notes1, date1, score2, notes2, date2,
              score3, notes3, date3, score4, notes4, date4,
              score5, notes5, date5)
) piv;

看

然后，如果每个id的值数目未知，则可以实现动态SQL以获得结果：

DECLARE @cols AS NVARCHAR(MAX),
    @query  AS NVARCHAR(MAX)

select @cols = STUFF((SELECT ',' + QUOTENAME(col + cast(seq as varchar(10))) 
                    from 
                    (
                      select row_number() over(partition by id order by createdate) seq
                      from yourtable
                    ) d
                    cross apply 
                    (
                      select 'score', 1 union all
                      select 'notes', 2 union all
                      select 'date', 3
                    ) c (col, so)
                    group by seq, col, so
                    order by seq, so
            FOR XML PATH(''), TYPE
            ).value('.', 'NVARCHAR(MAX)') 
        ,1,1,'')

set @query = 'SELECT id, ' + @cols + ' 
            from 
            (
              select t.id, 
                col = col + cast(seq as varchar(10)),
                value
              from
              (
                select id, score, notes, createdate,
                  row_number() over(partition by id order by createdate) seq
                from yourtable
              ) t
              cross apply
              (
                values
                  (''score'', cast(score as varchar(10))),
                  (''notes'', notes),
                  (''date'', convert(varchar(10), createdate, 120))
              ) c (col, value)
            ) x
            pivot 
            (
                max(value)
                for col in (' + @cols + ')
            ) p '

execute sp_executesql @query;

|   ID | SCORE1 |           NOTES1 |      DATE1 | SCORE2 | NOTES2 |      DATE2 | SCORE3 | NOTES3 |      DATE3 | SCORE4 | NOTES4 |      DATE4 | SCORE5 | NOTES5 |      DATE5 |
| 1661 |   9.20 | 8.0 on Sept 2010 | 2010-07-22 |   7.60 | (null) | 2010-11-04 |   7.90 | (null) | 2011-06-10 |   8.30 | (null) | 2011-09-28 |   7.90 | (null) | 2012-01-20 |

看。两个版本都给出了结果：

DECLARE @cols AS NVARCHAR(MAX),
    @query  AS NVARCHAR(MAX)

select @cols = STUFF((SELECT ',' + QUOTENAME(col + cast(seq as varchar(10))) 
                    from 
                    (
                      select row_number() over(partition by id order by createdate) seq
                      from yourtable
                    ) d
                    cross apply 
                    (
                      select 'score', 1 union all
                      select 'notes', 2 union all
                      select 'date', 3
                    ) c (col, so)
                    group by seq, col, so
                    order by seq, so
            FOR XML PATH(''), TYPE
            ).value('.', 'NVARCHAR(MAX)') 
        ,1,1,'')

set @query = 'SELECT id, ' + @cols + ' 
            from 
            (
              select t.id, 
                col = col + cast(seq as varchar(10)),
                value
              from
              (
                select id, score, notes, createdate,
                  row_number() over(partition by id order by createdate) seq
                from yourtable
              ) t
              cross apply
              (
                values
                  (''score'', cast(score as varchar(10))),
                  (''notes'', notes),
                  (''date'', convert(varchar(10), createdate, 120))
              ) c (col, value)
            ) x
            pivot 
            (
                max(value)
                for col in (' + @cols + ')
            ) p '

execute sp_executesql @query;

|   ID | SCORE1 |           NOTES1 |      DATE1 | SCORE2 | NOTES2 |      DATE2 | SCORE3 | NOTES3 |      DATE3 | SCORE4 | NOTES4 |      DATE4 | SCORE5 | NOTES5 |      DATE5 |
| 1661 |   9.20 | 8.0 on Sept 2010 | 2010-07-22 |   7.60 | (null) | 2010-11-04 |   7.90 | (null) | 2011-06-10 |   8.30 | (null) | 2011-09-28 |   7.90 | (null) | 2012-01-20 |

---

实际上，PIVOT在这里没有任何帮助，因为您不能在多个列上进行PIVOT。案例版本是两者中更灵活的一种。它可以缩短一点，否则null是多余的，因为这是默认行为。PIVOT是否可以按照OP的要求创建一行结果？@MartinSmith很好地说明了PIVOT不处理多个列。从技术上讲，可以从UNPIVOT开始，但是是的，它会变得混乱。@ExactaBox-它会变得非常混乱，因为数据类型是数字、日期和字符串。即使所有相同的数据类型都是UNPIVOT。。。PIVOT的效率比CASE要低。我说过如果可以的话我想避免PIVOT，但我并不反对使用它。也许我今天累了，不想再学习了。我会试试这个案例的解决方案，看看它能给我带来什么。如果您有一个pivot解决方案，我将看一看，因为这可能比实际情况更优雅。谢谢你。@ExactaBox我能说什么。