老生常談:SQL中的行轉(zhuǎn)列,列轉(zhuǎn)行操作
我們首先先通過一個老生常談的例子,學(xué)生成績表(下面簡化了些)來形象了解下行轉(zhuǎn)列
- CREATE TABLE [StudentScores]
- (
- [UserName] NVARCHAR(20), --學(xué)生姓名
- [Subject] NVARCHAR(30), --科目
- [Score] FLOAT, --成績
- )
- INSERT INTO [StudentScores] SELECT 'Nick', '語文', 80
- INSERT INTO [StudentScores] SELECT 'Nick', '數(shù)學(xué)', 90
- INSERT INTO [StudentScores] SELECT 'Nick', '英語', 70
- INSERT INTO [StudentScores] SELECT 'Nick', '生物', 85
- INSERT INTO [StudentScores] SELECT 'Kent', '語文', 80
- INSERT INTO [StudentScores] SELECT 'Kent', '數(shù)學(xué)', 90
- INSERT INTO [StudentScores] SELECT 'Kent', '英語', 70
- INSERT INTO [StudentScores] SELECT 'Kent', '生物', 85
如果我想知道每位學(xué)生的每科成績,而且每個學(xué)生的全部成績排成一行,這樣方便我查看、統(tǒng)計,導(dǎo)出數(shù)據(jù)
- SELECT
- UserName,
- MAX(CASE Subject WHEN '語文' THEN Score ELSE 0 END) AS '語文',
- MAX(CASE Subject WHEN '數(shù)學(xué)' THEN Score ELSE 0 END) AS '數(shù)學(xué)',
- MAX(CASE Subject WHEN '英語' THEN Score ELSE 0 END) AS '英語',
- MAX(CASE Subject WHEN '生物' THEN Score ELSE 0 END) AS '生物'
- FROM dbo.[StudentScores]
- GROUP BY UserName
查詢結(jié)果如圖所示,這樣我們就能很清楚的了解每位學(xué)生所有的成績了
接下來我們來看看第二個小列子。有一個游戲玩家充值表(僅僅為了說明,舉的一個小例子),
- CREATE TABLE [Inpours]
- (
- [ID] INT IDENTITY(1,1),
- [UserName] NVARCHAR(20), --游戲玩家
- [CreateTime] DATETIME, --充值時間
- [PayType] NVARCHAR(20), --充值類型
- [Money] DECIMAL, --充值金額
- [IsSuccess] BIT, --是否成功 1表示成功, 0表示失敗
- CONSTRAINT [PK_Inpours_ID] PRIMARY KEY(ID)
- )
- INSERT INTO Inpours SELECT '張三', '2010-05-01', '支付寶', 50, 1
- INSERT INTO Inpours SELECT '張三', '2010-06-14', '支付寶', 50, 1
- INSERT INTO Inpours SELECT '張三', '2010-06-14', '手機(jī)短信', 100, 1
- INSERT INTO Inpours SELECT '李四', '2010-06-14', '手機(jī)短信', 100, 1
- INSERT INTO Inpours SELECT '李四', '2010-07-14', '支付寶', 100, 1
- INSERT INTO Inpours SELECT '王五', '2010-07-14', '工商銀行卡', 100, 1
- INSERT INTO Inpours SELECT '趙六', '2010-07-14', '建設(shè)銀行卡', 100, 1
下面來了一個統(tǒng)計數(shù)據(jù)的需求,要求按日期、支付方式來統(tǒng)計充值金額信息。這也是一個典型的行轉(zhuǎn)列的例子。我們可以通過下面的腳本來達(dá)到目的
- SELECT CONVERT(VARCHAR(10), CreateTime, 120) AS CreateTime,
- CASE PayType WHEN '支付寶' THEN SUM(Money) ELSE 0 END AS '支付寶',
- CASE PayType WHEN '手機(jī)短信' THEN SUM(Money) ELSE 0 END AS '手機(jī)短信',
- CASE PayType WHEN '工商銀行卡' THEN SUM(Money) ELSE 0 END AS '工商銀行卡',
- CASE PayType WHEN '建設(shè)銀行卡' THEN SUM(Money) ELSE 0 END AS '建設(shè)銀行卡'
- FROM Inpours
- GROUP BY CreateTime, PayType
如圖所示,我們這樣只是得到了這樣的輸出結(jié)果,還需進(jìn)一步處理,才能得到想要的結(jié)果
- SELECT
- CreateTime,
- ISNULL(SUM([支付寶]), 0) AS [支付寶],
- ISNULL(SUM([手機(jī)短信]), 0) AS [手機(jī)短信],
- ISNULL(SUM([工商銀行卡]), 0) AS [工商銀行卡],
- ISNULL(SUM([建設(shè)銀行卡]), 0) AS [建設(shè)銀行卡]
- FROM
- (
- SELECT CONVERT(VARCHAR(10), CreateTime, 120) AS CreateTime,
- CASE PayType WHEN '支付寶' THEN SUM(Money) ELSE 0 END AS '支付寶',
- CASE PayType WHEN '手機(jī)短信' THEN SUM(Money) ELSE 0 END AS '手機(jī)短信',
- CASE PayType WHEN '工商銀行卡' THEN SUM(Money) ELSE 0 END AS '工商銀行卡',
- CASE PayType WHEN '建設(shè)銀行卡' THEN SUM(Money) ELSE 0 END AS '建設(shè)銀行卡'
- FROM Inpours
- GROUP BY CreateTime, PayType
- ) T
- GROUP BY CreateTime
其實(shí)行轉(zhuǎn)列,關(guān)鍵是要理清邏輯,而且對分組(Group by)概念比較清晰。上面兩個列子基本上就是行轉(zhuǎn)列的類型了。但是有個問題來了,上面是我為了說明弄的一個簡單列子。實(shí)際中,可能支付方式特別多,而且邏輯也復(fù)雜很多,可能涉及匯率、手續(xù)費(fèi)等等(曾經(jīng)做個這樣一個),如果支付方式特別多,我們的CASE WHEN 會弄出一大堆,確實(shí)比較惱火,而且新增一種支付方式,我們還得修改腳本如果把上面的腳本用動態(tài)SQL改寫一下,我們就能輕松解決這個問題
- 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) --注意這里,如果沒有加CHAR(10) 則用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);
下面是通過PIVOT來進(jìn)行行轉(zhuǎn)列的用法,大家可以對比一下,確實(shí)要簡單、更具可讀性(呵呵,習(xí)慣的前提下)
- SELECT
- CreateTime, [支付寶] , [手機(jī)短信],
- [工商銀行卡] , [建設(shè)銀行卡]
- FROM
- (
- SELECT CONVERT(VARCHAR(10), CreateTime, 120) AS CreateTime,PayType, Money
- FROM Inpours
- ) P
- PIVOT (
- SUM(Money)
- FOR PayType IN
- ([支付寶], [手機(jī)短信], [工商銀行卡], [建設(shè)銀行卡])
- ) AS T
- ORDER BY CreateTime
有時可能會出現(xiàn)這樣的錯誤:
消息 325,級別 15,狀態(tài) 1,第 9 行
'PIVOT' 附近有語法錯誤。您可能需要將當(dāng)前數(shù)據(jù)庫的兼容級別設(shè)置為更高的值,以啟用此功能。有關(guān)存儲過程 sp_dbcmptlevel 的信息,請參見幫助。
這個是因為:對升級到 SQL Server 2005 或更高版本的數(shù)據(jù)庫使用 PIVOT 和 UNPIVOT 時,必須將數(shù)據(jù)庫的兼容級別設(shè)置為 90 或更高。有關(guān)如何設(shè)置數(shù)據(jù)庫兼容級別的信息,請參閱
下面我們來看看列轉(zhuǎn)行,主要是通過UNION ALL ,MAX來實(shí)現(xiàn)。假如有下面這么一個表
- CREATE TABLE ProgrectDetail
- (
- ProgrectName NVARCHAR(20), --工程名稱
- OverseaSupply INT, --海外供應(yīng)商供給數(shù)量
- NativeSupply INT, --國內(nèi)供應(yīng)商供給數(shù)量
- SouthSupply INT, --南方供應(yīng)商供給數(shù)量
- NorthSupply INT --北方供應(yīng)商供給數(shù)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
我們可以通過下面的腳本來實(shí)現(xiàn),查詢結(jié)果如下圖所示
- 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 實(shí)現(xiàn)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
原文標(biāo)題:重溫SQL——行轉(zhuǎn)列,列轉(zhuǎn)行
鏈接:http://www.cnblogs.com/kerrycode/archive/2010/07/28/1786547.html