我根据以下内容编写了一个动态数据透视表查询.这是一个 SQL FIDDLE 供参考.

I have written a Dynamic Pivot Table Query based on the following. Here is a SQL FIDDLE for reference.

CREATE TABLE TestTable1 ([idnumber] INT, [DataTypeId] INT)
GO
INSERT INTO TestTable1 
VALUES (1, 108), (1, 108), (1, 108), (2, 108), 
       (2, 108), (3, 108), (1, 109),(1, 109),
       (1, 110),(2, 110),(1, 111),(4, 108),(4, 108),
       (4, 110),(4, 111)
GO

这是我写的动态 SQL

Here is the Dynamic SQL that I wrote

DECLARE  @SQL  NVARCHAR(MAX), 
@Cols NVARCHAR(MAX),
@ColsP NVARCHAR(MAX)


SELECT @Cols = STUFF((select  ',  
ISNULL([' + CAST([DataTypeId] as varchar(10)) + '], 0) AS ''' + CAST([DataTypeId] as varchar(10)) + ''''
FROM 
(
SELECT [DataTypeId] FROM [TestTable1] 
GROUP BY [DataTypeId] 
HAVING [DataTypeId] <> '' 
) AS d
ORDER BY [DataTypeId] FOR XML PATH(''),type).value('.','varchar(max)'),1,2,'')

-- /////////////THIS IS WHAT I WANT REMOVED ////////////////////

SELECT @ColsP = STUFF((select  ',  
[' + CAST([DataTypeId] as varchar(10)) + ']'
FROM 
(
SELECT [DataTypeId] FROM [TestTable1] 
GROUP BY [DataTypeId] 
HAVING [DataTypeId] <> '' 
) AS d
ORDER BY [DataTypeId] FOR XML PATH(''),type).value('.','varchar(max)'),1,2,'')

-- /////////////////////////////////////////////////////////////

SET @SQL = 'SELECT idnumber,' + @Cols + ' 
FROM 
(SELECT  idnumber, COUNT([DataTypeId]) AS Total, [DataTypeId] FROM [TestTable1] 
GROUP BY  idnumber, [DataTypeId] 
HAVING [DataTypeId] <> ''''
) p
PIVOT
(
SUM(Total) FOR [DataTypeId] IN (' + @ColsP + ')
) AS pvt 
ORDER BY pvt.idnumber'


-- print @SQL 
EXECUTE( @SQL)

我得到了我想要的结果:

I get the result that I want:

| IDNUMBER | 108 | 109 | 110 | 111 |
|----------|-----|-----|-----|-----|
|        1 |   3 |   2 |   1 |   1 |
|        2 |   2 |   0 |   1 |   0 |
|        3 |   1 |   0 |   0 |   0 |
|        4 |   2 |   0 |   1 |   1 |

但我相信它可以做得更好.我想删除填充变量的位置 @ColsP - SELECT @ColsP = STUFF((select...")

But I am sure it can be done better. I would like to remove where I populate the variable @ColsP - SELECT @ColsP = STUFF((select...")

应该有一种方法可以让我通过 TestTable1 只需一个循环即可创建此动态代码.如您所见，我循环了两次.一次读取要为 select 语句创建的列，一次读取 PIVOT 表.

There should be a way where I can create this dynamic code with just one loop through TestTable1. As you can see, I loop through it twice. Once to read what columns to create for the select statement, and once for the PIVOT table.

下面是动态 SQL 生成的代码:

Here is the code that is generated by the Dynamic SQL:

SELECT idnumber, 
  ISNULL([108], 0) AS '108',  
  ISNULL([109], 0) AS '109',  
  ISNULL([110], 0) AS '110',  
  ISNULL([111], 0) AS '111' 
FROM 
(
   SELECT  idnumber, COUNT([DataTypeId]) AS Total, [DataTypeId] 
   FROM [TestTable2] 
   GROUP BY  idnumber, [DataTypeId] 
   HAVING [DataTypeId] <> ''
) p
PIVOT
(
  SUM(Total) FOR [DataTypeId] IN ([108], [109], [110], [111])
) AS pvt 
ORDER BY pvt.idnumber

推荐答案

您可以大大缩短您的代码.首先，您可以只使用 count 来聚合 PIVOT 中的数据.不需要内部计数来聚合数据或 HAVING 子句.最后，您只需要创建一次列列表.您可以轻松地将代码改进为:

You can shorten your code considerably. First, you can just use count to aggregate the data in the PIVOT. There is no need for the inner count to aggregate the data or the HAVING clause. Finally, you only need to create the list of columns once. You could easily improve the code to:

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

select @cols = STUFF((SELECT ',' + QUOTENAME(DataTypeId) 
                    from TestTable1
                    group by DataTypeId
                    order by DataTypeId
            FOR XML PATH(''), TYPE
            ).value('.', 'NVARCHAR(MAX)') 
        ,1,1,'')

set @query 
      = N'SELECT idnumber, ' + @cols + N' 
          from 
          (
            select idnumber, DataTypeId
            from TestTable1
          ) x
          pivot 
          (
            count(DataTypeId)
            for DataTypeId in (' + @cols + N')
          ) p '

exec sp_executesql @query;

请参阅 SQL Fiddle with Demo.这给出了相同的结果:

See SQL Fiddle with Demo. This gives the same result:

| IDNUMBER | 108 | 109 | 110 | 111 |
|----------|-----|-----|-----|-----|
|        1 |   3 |   2 |   1 |   1 |
|        2 |   2 |   0 |   1 |   0 |
|        3 |   1 |   0 |   0 |   0 |
|        4 |   2 |   0 |   1 |   1 |