我们首先先通过一个老生常谈的例子,学生成绩表(下面简化了些)来形象了解下行转列
(
[UserName] NVARCHAR(20), --学生姓名
[Subject] NVARCHAR(30), --科目
[Score] FLOAT, --成绩
)
INSERT INTO [StudentScores] SELECT 'Nick', '语文', 80
INSERT INTO [StudentScores] SELECT 'Nick', '数学', 90
INSERT INTO [StudentScores] SELECT 'Nick', '英语', 70
INSERT INTO [StudentScores] SELECT 'Nick', '生物', 85
INSERT INTO [StudentScores] SELECT 'Kent', '语文', 80
INSERT INTO [StudentScores] SELECT 'Kent', '数学', 90
INSERT INTO [StudentScores] SELECT 'Kent', '英语', 70
INSERT INTO [StudentScores] SELECT 'Kent', '生物', 85
如果我想知道每位学生的每科成绩,而且每个学生的全部成绩排成一行,这样方便我查看、统计,导出数据
UserName,
MAX(CASE Subject WHEN '语文' THEN Score ELSE 0 END) AS '语文',
MAX(CASE Subject WHEN '数学' THEN Score ELSE 0 END) AS '数学',
MAX(CASE Subject WHEN '英语' THEN Score ELSE 0 END) AS '英语',
MAX(CASE Subject WHEN '生物' THEN Score ELSE 0 END) AS '生物'
FROM dbo.[StudentScores]
GROUP BY UserName
查询结果如图所示,这样我们就能很清楚的了解每位学生所有的成绩了
接下来我们来看看第二个小列子。有一个游戏玩家充值表(仅仅为了说明,举的一个小例子),
代码
(
[ID] INT IDENTITY(1,1),
[UserName] NVARCHAR(20), --游戏玩家
[CreateTime] DATETIME, --充值时间
[PayType] NVARCHAR(20), --充值类型
[Money] DECIMAL, --充值金额
[IsSuccess] BIT, --是否成功 1表示成功, 0表示失败
CONSTRAINT [PK_Inpours_ID] PRIMARY KEY(ID)
)
INSERT INTO Inpours SELECT '张三', '2010-05-01', '支付宝', 50, 1
INSERT INTO Inpours SELECT '张三', '2010-06-14', '支付宝', 50, 1
INSERT INTO Inpours SELECT '张三', '2010-06-14', '手机短信', 100, 1
INSERT INTO Inpours SELECT '李四', '2010-06-14', '手机短信', 100, 1
INSERT INTO Inpours SELECT '李四', '2010-07-14', '支付宝', 100, 1
INSERT INTO Inpours SELECT '王五', '2010-07-14', '工商银行卡', 100, 1
INSERT INTO Inpours SELECT '赵六', '2010-07-14', '建设银行卡', 100, 1
CASE PayType WHEN '支付宝' THEN SUM(Money) ELSE 0 END AS '支付宝',
CASE PayType WHEN '手机短信' THEN SUM(Money) ELSE 0 END AS '手机短信',
CASE PayType WHEN '工商银行卡' THEN SUM(Money) ELSE 0 END AS '工商银行卡',
CASE PayType WHEN '建设银行卡' THEN SUM(Money) ELSE 0 END AS '建设银行卡'
FROM Inpours
GROUP BY CreateTime, PayType
如图所示,我们这样只是得到了这样的输出结果,还需进一步处理,才能得到想要的结果
SELECT
CreateTime,
ISNULL(SUM([支付宝]), 0) AS [支付宝],
ISNULL(SUM([手机短信]), 0) AS [手机短信],
ISNULL(SUM([工商银行卡]), 0) AS [工商银行卡],
ISNULL(SUM([建设银行卡]), 0) AS [建设银行卡]
FROM
(
SELECT CONVERT(VARCHAR(10), CreateTime, 120) AS CreateTime,
CASE PayType WHEN '支付宝' THEN SUM(Money) ELSE 0 END AS '支付宝',
CASE PayType WHEN '手机短信' THEN SUM(Money) ELSE 0 END AS '手机短信',
CASE PayType WHEN '工商银行卡' THEN SUM(Money) ELSE 0 END AS '工商银行卡',
CASE PayType WHEN '建设银行卡' THEN SUM(Money) ELSE 0 END AS '建设银行卡'
FROM Inpours
GROUP BY CreateTime, PayType
) T
GROUP BY CreateTime
其实行转列,关键是要理清逻辑,而且对分组(Group by)概念比较清晰。上面两个列子基本上就是行转列的类型了。但是有个问题来了,上面是我为了说明弄的一个简单列子。实际中,可能支付方式特别多,而且逻辑也复杂很多,可能涉及汇率、手续费等等(曾经做个这样一个),如果支付方式特别多,我们的CASE WHEN 会弄出一大堆,确实比较恼火,而且新增一种支付方式,我们还得修改脚本如果把上面的脚本用动态SQL改写一下,我们就能轻松解决这个问题
DECLARE @tmpSql VARCHAR(8000);
SET @cmdText = 'SELECT CONVERT(VARCHAR(10), CreateTime, 120) AS CreateTime,' + CHAR(10);
SELECT @cmdText = @cmdText + ' CASE PayType WHEN ''' + PayType + ''' THEN SUM(Money) ELSE 0 END AS ''' + PayType
+ ''',' + CHAR(10) FROM (SELECT DISTINCT PayType FROM Inpours ) T
SET @cmdText = LEFT(@cmdText, LEN(@cmdText) -2) --注意这里,如果没有加CHAR(10) 则用LEFT(@cmdText, LEN(@cmdText) -1)
SET @cmdText = @cmdText + ' FROM Inpours GROUP BY CreateTime, PayType ';
SET @tmpSql ='SELECT CreateTime,' + CHAR(10);
SELECT @tmpSql = @tmpSql + ' ISNULL(SUM(' + PayType + '), 0) AS ''' + PayType + ''',' + CHAR(10)
FROM (SELECT DISTINCT PayType FROM Inpours ) T
SET @tmpSql = LEFT(@tmpSql, LEN(@tmpSql) -2) + ' FROM (' + CHAR(10);
SET @cmdText = @tmpSql + @cmdText + ') T GROUP BY CreateTime ';
PRINT @cmdText
EXECUTE (@cmdText);
下面是通过PIVOT来进行行转列的用法,大家可以对比一下,确实要简单、更具可读性(呵呵,习惯的前提下)
CreateTime, [支付宝] , [手机短信],
[工商银行卡] , [建设银行卡]
FROM
(
SELECT CONVERT(VARCHAR(10), CreateTime, 120) AS CreateTime,PayType, Money
FROM Inpours
) P
PIVOT (
SUM(Money)
FOR PayType IN
([支付宝], [手机短信], [工商银行卡], [建设银行卡])
) AS T
ORDER BY CreateTime
有时可能会出现这样的错误:
消息 325,级别 15,状态 1,第 9 行
'PIVOT' 附近有语法错误。您可能需要将当前数据库的兼容级别设置为更高的值,以启用此功能。有关存储过程 sp_dbcmptlevel 的信息,请参见帮助。
这个是因为:对升级到 SQL Server 2005 或更高版本的数据库使用 PIVOT 和 UNPIVOT 时,必须将数据库的兼容级别设置为 90 或更高。有关如何设置数据库兼容级别的信息,请参阅
下面我们来看看列转行,主要是通过UNION ALL ,MAX来实现。假如有下面这么一个表
(
ProgrectName NVARCHAR(20), --工程名称
OverseaSupply INT, --海外供应商供给数量
NativeSupply INT, --国内供应商供给数量
SouthSupply INT, --南方供应商供给数量
NorthSupply INT --北方供应商供给数量
)
INSERT INTO ProgrectDetail
SELECT 'A', 100, 200, 50, 50
UNION ALL
SELECT 'B', 200, 300, 150, 150
UNION ALL
SELECT 'C', 159, 400, 20, 320
UNION ALL
SELECT 'D', 250, 30, 15, 15
我们可以通过下面的脚本来实现,查询结果如下图所示
MAX(OverseaSupply) AS 'SupplyNum'
FROM ProgrectDetail
GROUP BY ProgrectName
UNION ALL
SELECT ProgrectName, 'NativeSupply' AS Supplier,
MAX(NativeSupply) AS 'SupplyNum'
FROM ProgrectDetail
GROUP BY ProgrectName
UNION ALL
SELECT ProgrectName, 'SouthSupply' AS Supplier,
MAX(SouthSupply) AS 'SupplyNum'
FROM ProgrectDetail
GROUP BY ProgrectName
UNION ALL
SELECT ProgrectName, 'NorthSupply' AS Supplier,
MAX(NorthSupply) AS 'SupplyNum'
FROM ProgrectDetail
GROUP BY ProgrectName
用UNPIVOT 实现如下:
FROM
(
SELECT ProgrectName, OverseaSupply, NativeSupply,
SouthSupply, NorthSupply
FROM ProgrectDetail
)T
UNPIVOT
(
SupplyNum FOR Supplier IN
(OverseaSupply, NativeSupply, SouthSupply, NorthSupply )
) P