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
- CREATE TABLE [StudentScores]
- (
- [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
- SELECT
- 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),
- CREATE TABLE [Inpours]
- (
- [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
下面来了一个统计数据的需求,要求按日期、支付方式来统计充值金额信息。这也是一个典型的行转列的例子。我们可以通过下面的脚本来达到目的
- 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
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 @cmdText VARCHAR(8000);
- 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)
- SELECT
- 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
- CREATE TABLE ProgrectDetail
- (
- 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
- SELECT ProgrectName, 'OverseaSupply' AS Supplier,
- 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:
- SELECT ProgrectName,Supplier,SupplyNum
- FROM
- (
- SELECT ProgrectName, OverseaSupply, NativeSupply,
- SouthSupply, NorthSupply
- FROM ProgrectDetail
- )T
- UNPIVOT
- (
- SupplyNum FOR Supplier IN
- (OverseaSupply, NativeSupply, SouthSupply, NorthSupply )
- ) P
原文标题:重温SQL——行转列,列转行
链接:http://www.cnblogs.com/kerrycode/archive/2010/07/28/1786547.html