开窗函数 First_Value 和 Last_Value
在Sql server 2012里面，开窗函数丰富了许多，其中带出了2个新的函数 First_Value 和 Last Value .现在来介绍一下这2个函数的应用场景.
首先分析一下First_Value()，用法是根据Partition By对数据进行分区，如果忽略Partition By ，那么默认整块数据一个区域，然后根据Order By 进行排序，取出第一个值。
;WITH CTE AS( SELECT 1 AS ID ,'2016-06-01' AS DT,'A' AS UName,135 AS TotalAmount UNION ALL SELECT 2 AS ID ,'2016-06-05' AS DT,'A' AS UName,148 AS TotalAmount UNION ALL SELECT 3 AS ID ,'2016-06-02' AS DT,'B' AS UName,120 AS TotalAmount UNION ALL SELECT 4 AS ID ,'2016-06-06' AS DT,'B' AS UName,153 AS TotalAmount UNION ALL SELECT 5 AS ID ,'2016-06-10' AS DT,'B' AS UName,198 AS TotalAmount ) SELECT * , FIRST_VALUE(CTE.TotalAmount) OVER (PARTITION BY CTE.UName ORDER BY CTE.ID) AS FirstDeal, FIRST_VALUE(CTE.DT) OVER (PARTITION BY CTE.UName ORDER BY CTE.ID) AS FirstDate FROM CTE
ID DT UName TotalAmount FirstDeal FirstDate
----------- ---------- ----- ----------- ----------- ----------
1 2016-06-01 A 135 135 2016-06-01
2 2016-06-05 A 148 135 2016-06-01
3 2016-06-02 B 120 120 2016-06-02
4 2016-06-06 B 153 120 2016-06-02
5 2016-06-10 B 198 120 2016-06-02
在这个场景里面，我求出了根据用户名称(UName)来进行分区，根据ID进行一个排序，求出每个用户第一次购买商品的时间以及交易的金额。如果不使用First_Value 我们也可以换另外一种写法
;WITH CTE AS( SELECT 1 AS ID ,'2016-06-01' AS DT,'A' AS UName,135 AS TotalAmount UNION ALL SELECT 2 AS ID ,'2016-06-05' AS DT,'A' AS UName,148 AS TotalAmount UNION ALL SELECT 3 AS ID ,'2016-06-02' AS DT,'B' AS UName,120 AS TotalAmount UNION ALL SELECT 4 AS ID ,'2016-06-06' AS DT,'B' AS UName,153 AS TotalAmount UNION ALL SELECT 5 AS ID ,'2016-06-10' AS DT,'B' AS UName,198 AS TotalAmount ) SELECT * FROM CTE a CROSS APPLY(SELECT TOP 1 a.TotalAmount AS FirstDeal,DT AS FirstDate FROM CTE WHERE a.UName = CTE.UName ORDER BY CTE.ID) AS b --或者改写成这种形式 ;WITH CTE AS( SELECT 1 AS ID ,'2016-06-01' AS DT,'A' AS UName,135 AS TotalAmount UNION ALL SELECT 2 AS ID ,'2016-06-05' AS DT,'A' AS UName,148 AS TotalAmount UNION ALL SELECT 3 AS ID ,'2016-06-02' AS DT,'B' AS UName,120 AS TotalAmount UNION ALL SELECT 4 AS ID ,'2016-06-06' AS DT,'B' AS UName,153 AS TotalAmount UNION ALL SELECT 5 AS ID ,'2016-06-10' AS DT,'B' AS UName,198 AS TotalAmount ) SELECT a.*,b.TotalAmount AS FirstDeal,b.DT AS FirstDate FROM CTE a LEFT JOIN CTE b ON a.UName = b.UName AND NOT EXISTS(SELECT * FROM CTE WHERE b.UName = UName AND DT < b.DT)
在这三种写法里面，查询的结果是一致的，燃鹅从查询分析器分析的分析来看，查询性能，使用First_Value 的效率最高，not exists 的效率其次,使用Cross Apply 效率最低。
但是这只是从查询这么少量的测试数据反馈出来的结果，如果具体的场景需要应用，最好是结合实际情况看实际的查询计划来得出最适当的查询效果。
然后说下 Last_Value() 的用法,虽然说First_Value 和 Last_Value 一看就想两兄弟。但是！用起来真不是这样的一回事啊！
如果根据First_Value 的解释，那么Last_Value 就是根据Partition进行分区，根据Order By 进行排序返回最后的一个值。想我是这样想的，但是操作起来就不是这么一回事了。
;WITH CTE AS( SELECT 1 AS ID ,'2016-06-01' AS DT,'A' AS UName,135 AS TotalAmount UNION ALL SELECT 2 AS ID ,'2016-06-05' AS DT,'A' AS UName,148 AS TotalAmount UNION ALL SELECT 3 AS ID ,'2016-06-02' AS DT,'B' AS UName,120 AS TotalAmount UNION ALL SELECT 4 AS ID ,'2016-06-06' AS DT,'B' AS UName,153 AS TotalAmount UNION ALL SELECT 5 AS ID ,'2016-06-10' AS DT,'B' AS UName,198 AS TotalAmount ) SELECT * , LAST_VALUE(CTE.TotalAmount) OVER ( PARTITION BY CTE.UName ORDER BY CTE.DT) AS LR FROM CTE ID DT UName TotalAmount LR ----------- ---------- ----- ----------- ----------- 1 2016-06-01 A 135 135 2 2016-06-05 A 148 148 3 2016-06-02 B 120 120 4 2016-06-06 B 153 153 5 2016-06-10 B 198 198
咦！？说好的根据 UName 进行分组，然后再DT进行排序区最后一个价格呢？？完全不是这样子啊！！
对，这才是Last_Value的用法，实际上。在我测试的版本里面 (2012,2014)， 除了根据 Partition By 进行分区，还对Order by 不一样的值产生不一样的取值。
所以，如果你想看到这个效果，我们不妨把测试样例数据修改一下，把其中2个DT改成一样的，如下面效果
;WITH CTE AS( SELECT 1 AS ID ,'2016-06-05' AS DT,'A' AS UName,135 AS TotalAmount UNION ALL SELECT 2 AS ID ,'2016-06-05' AS DT,'A' AS UName,148 AS TotalAmount UNION ALL SELECT 3 AS ID ,'2016-06-02' AS DT,'B' AS UName,120 AS TotalAmount UNION ALL SELECT 4 AS ID ,'2016-06-02' AS DT,'B' AS UName,153 AS TotalAmount UNION ALL SELECT 5 AS ID ,'2016-06-10' AS DT,'B' AS UName,198 AS TotalAmount ) SELECT * , LAST_VALUE(CTE.TotalAmount) OVER ( PARTITION BY CTE.UName ORDER BY CTE.DT) AS LR FROM CTE ID DT UName TotalAmount LR ----------- ---------- ----- ----------- ----------- 1 2016-06-01 A 135 135 2 2016-06-05 A 148 148 3 2016-06-02 B 120 120 4 2016-06-06 B 153 153 5 2016-06-10 B 198 198
so 现在就看到取值是不一样的，燃鹅，确还是有一个问题，到底哪个才是Last_Value 呢？？查询计划说了算~(这个我还真没验证过，请各位大神指导一下)
所以啊，不要看名字就觉得First_Value 和 Last_Value 是亲兄弟啊！！是隔壁老王的啊！！
好，本次分享到这里~
