Home >Database >Mysql Tutorial >oracle分析函数技术详解(配上开窗函数over())
一、Oracle分析函数入门 分析函数是什么? 分析函数是Oracle专门用于 解决复杂报表统计需求 的功能强大的函数, 它可以在数据中进行分组然后计算基于组的某种统计 ,并且每一组的每一行都可以返回一个统计。 分析函数和聚合函数的不同之处是什么? 普通的聚
分析函数是什么?
分析函数是Oracle专门用于解决复杂报表统计需求的功能强大的函数,它可以在数据中进行分组然后计算基于组的某种统计值,并且每一组的每一行都可以返回一个统计值。
分析函数和聚合函数的不同之处是什么?
普通的聚合函数用group by分组,每个分组返回一个统计值,而分析函数采用partition by分组,并且每组每行都可以返回一个统计值。
分析函数的形式
分析函数带有一个开窗函数over(),包含三个分析子句:分组(partition by), 排序(order by), 窗口(rows) ,他们的使用形式如下:over(partition by xxx order by yyy rows between zzz)。
注:窗口子句在这里我只说rows方式的窗口,range方式和滑动窗口也不提
分析函数例子(在scott用户下模拟)
示例目的:显示各部门员工的工资,并附带显示该部分的最高工资。
<span>--</span><span>显示各部门员工的工资,并附带显示该部分的最高工资。</span><span>SELECT</span> E.DEPTNO, E.EMPNO, E.ENAME, E.SAL, LAST_VALUE(E.SAL) <span>OVER</span>(PARTITION <span>BY</span> E.DEPTNO <span>ORDER</span> <span>BY</span> E.SAL ROWS <span>--</span><span>unbounded preceding and unbouned following针对当前所有记录的前一条、后一条记录,也就是表中的所有记录</span> <span>--</span><span>unbounded:不受控制的,无限的</span> <span>--</span><span>preceding:在...之前</span> <span>--</span><span>following:在...之后</span> <span>BETWEEN</span> UNBOUNDED PRECEDING <span>AND</span> UNBOUNDED FOLLOWING) MAX_SAL <span>FROM</span> EMP E;
运行结果:
示例目的:按照deptno分组,然后计算每组值的总和
<span>SELECT</span> EMPNO, ENAME, DEPTNO, SAL, <span>SUM</span>(SAL) <span>OVER</span>(PARTITION <span>BY</span> DEPTNO <span>ORDER</span> <span>BY</span> ENAME) max_sal <span>FROM</span> SCOTT.EMP;
运行结果:
示例目的:对各部门进行分组,并附带显示第一行至当前行的汇总
<span>SELECT</span> EMPNO, ENAME, DEPTNO, SAL, <span>--</span><span>注意ROWS BETWEEN unbounded preceding AND current row 是指第一行至当前行的汇总</span> <span>SUM</span>(SAL) <span>OVER</span>(PARTITION <span>BY</span> DEPTNO <span>ORDER</span> <span>BY</span> ENAME ROWS <span>BETWEEN</span> UNBOUNDED PRECEDING <span>AND</span> <span>CURRENT</span> ROW) max_sal <span>FROM</span> SCOTT.EMP;
运行结果:
示例目标:当前行至最后一行的汇总
<span>SELECT</span> EMPNO, ENAME, DEPTNO, SAL, <span>--</span><span>注意ROWS BETWEEN current row AND unbounded following 指当前行到最后一行的汇总</span> <span>SUM</span>(SAL) <span>OVER</span>(PARTITION <span>BY</span> DEPTNO <span>ORDER</span> <span>BY</span> ENAME ROWS <span>BETWEEN</span> <span>CURRENT</span> ROW <span>AND</span> UNBOUNDED FOLLOWING) max_sal <span>FROM</span> SCOTT.EMP;
运行结果:
示例目标:当前行的上一行(rownum-1)到当前行的汇总
<span>SELECT</span> EMPNO, ENAME, DEPTNO, SAL, <span>--</span><span>注意ROWS BETWEEN 1 preceding AND current row 是指当前行的上一行(rownum-1)到当前行的汇总 </span> <span>SUM</span>(SAL) <span>OVER</span>(PARTITION <span>BY</span> DEPTNO <span>ORDER</span> <span>BY</span> ENAME ROWS <span>BETWEEN</span> <span>1</span> PRECEDING <span>AND</span> <span>CURRENT</span> ROW) max_sal <span>FROM</span> SCOTT.EMP;
运行结果:
示例目标: 当前行的上一行(rownum-1)到当前行的下辆行(rownum+2)的汇总
<span>SELECT</span> EMPNO, ENAME, DEPTNO, SAL, <span>--</span><span>注意ROWS BETWEEN 1 preceding AND 1 following 是指当前行的上一行(rownum-1)到当前行的下辆行(rownum+2)的汇总</span> <span>SUM</span>(SAL) <span>OVER</span>(PARTITION <span>BY</span> DEPTNO <span>ORDER</span> <span>BY</span> ENAME ROWS <span>BETWEEN</span> <span>1</span> PRECEDING <span>AND</span> <span>2</span> FOLLOWING) max_sal <span>FROM</span> SCOTT.EMP;
运行结果:
1.1、两个order by的执行时机
分析函数(以及与其配合的开窗函数over())是在整个sql查询结束后(sql语句中的order by的执行比较特殊)再进行的操作, 也就是说sql语句中的order by也会影响分析函数的执行结果:
a) 两者一致:如果sql语句中的order by满足与分析函数配合的开窗函数over()分析时要求的排序,即sql语句中的order by子句里的内容和开窗函数over()中的order by子句里的内容一样,
那么sql语句中的排序将先执行,分析函数在分析时就不必再排序;
b) 两者不一致:如果sql语句中的order by不满足与分析函数配合的开窗函数over()分析时要求的排序,即sql语句中的order by子句里的内容和开窗函数over()中的order
by子句里的内容不一样,
那么sql语句中的排序将最后在分析函数分析结束后执行排序。
1.2、开窗函数over()分析函数中的分组/排序/窗口
开窗函数over()分析函数包含三个分析子句:分组子句(partition by), 排序子句(order by), 窗口子句(rows)
窗口就是分析函数分析时要处理的数据范围,就拿sum来说,它是sum窗口中的记录而不是整个分组中的记录,因此我们在想得到某个栏位的累计值时,我们需要把窗口指定到该分组中的第一行数据到当前行, 如果你指定该窗口从该分组中的第一行到最后一行,那么该组中的每一个sum值都会一样,即整个组的总和。
窗口子句在这里我只说rows方式的窗口,range方式和滑动窗口也不提。
窗口子句中我们经常用到指定第一行,当前行,最后一行这样的三个属性:
第一行是 unbounded preceding,
当前行是 current row,
最后一行是 unbounded following,
注释:
当开窗函数over()出现分组(partition by)子句时,
unbounded preceding即第一行是指表中一个分组里的第一行, unbounded following即最后一行是指表中一个分组里的最后一行;
当开窗函数over()省略了分组(partition
by)子句时,
unbounded preceding即第一行是指表中的第一行, unbounded following即最后一行是指表中的最后一行。
窗口子句不能单独出现,必须有order by子句时才能出现,
例如:
<span>last_value(sal) <span>over</span>(partition <span>by</span> deptno <span>order</span> <span>by</span> sal rows <span>between</span> unbounded preceding <span>and</span> unbounded following)</span>
以上示例指定窗口为整个分组。而出现order by子句的时候,不一定要有窗口子句,但效果会很不一样,此时的窗口默认是当前组的第一行到当前行!
如果省略分组,则把全部记录当成一个组。
a) 如果存在order by则默认窗口是unbounded preceding and current row --当前组的第一行到当前行
b) 如果这时省略order by则窗口默认为unbounded preceding and unbounded following
--整个组
而无论是否省略分组子句,如下结论都是成立的:
1、窗口子句不能单独出现,必须有order by子句时才能出现。
2、当省略窗口子句时:
a) 如果存在order by则默认的窗口是unbounded preceding and current row --当前组的第一行到当前行,即在当前组中,第一行到当前行
b) 如果同时省略order by则默认的窗口是unbounded preceding and unbounded following
--整个组
所以,
lag(sal) over(order by sal) 解释
over(order by salary)表示意义如下:
首先,我们要知道由于省略分组子句,所以当前组的范围为整个表的数据行,
然后,在当前组(此时为整个表的数据行)这个范围里执行排序(即order by salary),
最后,我们知道分析函数lag(sal)在当前组(此时为整个表的数据行)这个范围里的窗口范围为当前组的第一行到当前行,即分析函数lag(sal)在这个窗口范围执行。
参见:
1.3、帮助理解over()的实例
例1:关注点:sql无排序,over()排序子句省略
<span>SELECT</span> DEPTNO, EMPNO, ENAME, SAL, LAST_VALUE(SAL) <span>OVER</span>(PARTITION <span>BY</span> DEPTNO) <span>FROM</span> EMP;
运行结果:
例2:关注点:sql无排序,over()排序子句有,窗口省略
<span>SELECT</span> DEPTNO, EMPNO, ENAME, SAL, LAST_VALUE(SAL) <span>OVER</span>(PARTITION <span>BY</span> DEPTNO <span>ORDER</span> <span>BY</span> SAL <span>DESC</span>) <span>FROM</span> EMP;
运行结果:
例3:关注点:sql无排序,over()排序子句有,窗口也有,窗口特意强调全组数据
<span>SELECT</span> DEPTNO, EMPNO, ENAME, SAL, LAST_VALUE(SAL) <span>OVER</span>(PARTITION <span>BY</span> DEPTNO <span>ORDER</span> <span>BY</span> SAL ROWS <span>BETWEEN</span> UNBOUNDED PRECEDING <span>AND</span> UNBOUNDED FOLLOWING) MAX_SAL <span>FROM</span> EMP;
运行结果:
例4:关注点:sql有排序(正序),over()排序子句无,先做sql排序再进行分析函数运算
<span>SELECT</span> DEPTNO, MGR, ENAME, SAL, HIREDATE, LAST_VALUE(SAL) <span>OVER</span>(PARTITION <span>BY</span> DEPTNO) LAST_VALUE <span>FROM</span> EMP <span>WHERE</span> DEPTNO <span>=</span> <span>30</span> <span>ORDER</span> <span>BY</span> DEPTNO, MGR;
运行结果:
例5:关注点:sql有排序(倒序),over()排序子句无,先做sql排序再进行分析函数运算
<span>SELECT</span> DEPTNO, MGR, ENAME, SAL, HIREDATE, LAST_VALUE(SAL) <span>OVER</span>(PARTITION <span>BY</span> DEPTNO) LAST_VALUE <span>FROM</span> EMP <span>WHERE</span> DEPTNO <span>=</span> <span>30</span> <span>ORDER</span> <span>BY</span> DEPTNO, MGR <span>DESC</span>;
运行结果:
例6:关注点:sql有排序(倒序),over()排序子句有,窗口子句无,此时的运算是:sql先选数据但是不排序,而后排序子句先排序并进行分析函数处理(窗口默认为第一行到当前行),最后再进行sql排序
<span>SELECT</span> DEPTNO, MGR, ENAME, SAL, HIREDATE, <span>MIN</span>(SAL) <span>OVER</span>(PARTITION <span>BY</span> DEPTNO <span>ORDER</span> <span>BY</span> SAL <span>ASC</span>) LAST_VALUE <span>FROM</span> EMP <span>WHERE</span> DEPTNO <span>=</span> <span>30</span> <span>ORDER</span> <span>BY</span> DEPTNO, MGR <span>DESC</span>;
运行结果:
<span>SELECT</span> DEPTNO, MGR, ENAME, SAL, HIREDATE, <span>MIN</span>(SAL) <span>OVER</span>(PARTITION <span>BY</span> DEPTNO <span>ORDER</span> <span>BY</span> SAL <span>DESC</span>) LAST_VALUE <span>FROM</span> EMP <span>WHERE</span> DEPTNO <span>=</span> <span>30</span> <span>ORDER</span> <span>BY</span> DEPTNO, MGR <span>DESC</span>;
运行结果:
为了方便进行实践,特将演示表和数据罗列如下:
一、创建表
<span>create</span> <span>table</span> t( bill_month <span>varchar2</span>(<span>12</span>) , area_code <span>number</span>, net_type <span>varchar</span>(<span>2</span>), local_fare <span>number</span> );
二、插入数据
<span>insert</span> <span>into</span> t <span>values</span>(<span>'</span><span>200405</span><span>'</span>,<span>5761</span>,<span>'</span><span>G</span><span>'</span>, <span>7393344.04</span>); <span>insert</span> <span>into</span> t <span>values</span>(<span>'</span><span>200405</span><span>'</span>,<span>5761</span>,<span>'</span><span>J</span><span>'</span>, <span>5667089.85</span>); <span>insert</span> <span>into</span> t <span>values</span>(<span>'</span><span>200405</span><span>'</span>,<span>5762</span>,<span>'</span><span>G</span><span>'</span>, <span>6315075.96</span>); <span>insert</span> <span>into</span> t <span>values</span>(<span>'</span><span>200405</span><span>'</span>,<span>5762</span>,<span>'</span><span>J</span><span>'</span>, <span>6328716.15</span>); <span>insert</span> <span>into</span> t <span>values</span>(<span>'</span><span>200405</span><span>'</span>,<span>5763</span>,<span>'</span><span>G</span><span>'</span>, <span>8861742.59</span>); <span>insert</span> <span>into</span> t <span>values</span>(<span>'</span><span>200405</span><span>'</span>,<span>5763</span>,<span>'</span><span>J</span><span>'</span>, <span>7788036.32</span>); <span>insert</span> <span>into</span> t <span>values</span>(<span>'</span><span>200405</span><span>'</span>,<span>5764</span>,<span>'</span><span>G</span><span>'</span>, <span>6028670.45</span>); <span>insert</span> <span>into</span> t <span>values</span>(<span>'</span><span>200405</span><span>'</span>,<span>5764</span>,<span>'</span><span>J</span><span>'</span>, <span>6459121.49</span>); <span>insert</span> <span>into</span> t <span>values</span>(<span>'</span><span>200405</span><span>'</span>,<span>5765</span>,<span>'</span><span>G</span><span>'</span>, <span>13156065.77</span>); <span>insert</span> <span>into</span> t <span>values</span>(<span>'</span><span>200405</span><span>'</span>,<span>5765</span>,<span>'</span><span>J</span><span>'</span>, <span>11901671.70</span>); <span>insert</span> <span>into</span> t <span>values</span>(<span>'</span><span>200406</span><span>'</span>,<span>5761</span>,<span>'</span><span>G</span><span>'</span>, <span>7614587.96</span>); <span>insert</span> <span>into</span> t <span>values</span>(<span>'</span><span>200406</span><span>'</span>,<span>5761</span>,<span>'</span><span>J</span><span>'</span>, <span>5704343.05</span>); <span>insert</span> <span>into</span> t <span>values</span>(<span>'</span><span>200406</span><span>'</span>,<span>5762</span>,<span>'</span><span>G</span><span>'</span>, <span>6556992.60</span>); <span>insert</span> <span>into</span> t <span>values</span>(<span>'</span><span>200406</span><span>'</span>,<span>5762</span>,<span>'</span><span>J</span><span>'</span>, <span>6238068.05</span>); <span>insert</span> <span>into</span> t <span>values</span>(<span>'</span><span>200406</span><span>'</span>,<span>5763</span>,<span>'</span><span>G</span><span>'</span>, <span>9130055.46</span>); <span>insert</span> <span>into</span> t <span>values</span>(<span>'</span><span>200406</span><span>'</span>,<span>5763</span>,<span>'</span><span>J</span><span>'</span>, <span>7990460.25</span>); <span>insert</span> <span>into</span> t <span>values</span>(<span>'</span><span>200406</span><span>'</span>,<span>5764</span>,<span>'</span><span>G</span><span>'</span>, <span>6387706.01</span>); <span>insert</span> <span>into</span> t <span>values</span>(<span>'</span><span>200406</span><span>'</span>,<span>5764</span>,<span>'</span><span>J</span><span>'</span>, <span>6907481.66</span>); <span>insert</span> <span>into</span> t <span>values</span>(<span>'</span><span>200406</span><span>'</span>,<span>5765</span>,<span>'</span><span>G</span><span>'</span>, <span>13562968.81</span>); <span>insert</span> <span>into</span> t <span>values</span>(<span>'</span><span>200406</span><span>'</span>,<span>5765</span>,<span>'</span><span>J</span><span>'</span>, <span>12495492.50</span>); <span>insert</span> <span>into</span> t <span>values</span>(<span>'</span><span>200407</span><span>'</span>,<span>5761</span>,<span>'</span><span>G</span><span>'</span>, <span>7987050.65</span>); <span>insert</span> <span>into</span> t <span>values</span>(<span>'</span><span>200407</span><span>'</span>,<span>5761</span>,<span>'</span><span>J</span><span>'</span>, <span>5723215.28</span>); <span>insert</span> <span>into</span> t <span>values</span>(<span>'</span><span>200407</span><span>'</span>,<span>5762</span>,<span>'</span><span>G</span><span>'</span>, <span>6833096.68</span>); <span>insert</span> <span>into</span> t <span>values</span>(<span>'</span><span>200407</span><span>'</span>,<span>5762</span>,<span>'</span><span>J</span><span>'</span>, <span>6391201.44</span>); <span>insert</span> <span>into</span> t <span>values</span>(<span>'</span><span>200407</span><span>'</span>,<span>5763</span>,<span>'</span><span>G</span><span>'</span>, <span>9410815.91</span>); <span>insert</span> <span>into</span> t <span>values</span>(<span>'</span><span>200407</span><span>'</span>,<span>5763</span>,<span>'</span><span>J</span><span>'</span>, <span>8076677.41</span>); <span>insert</span> <span>into</span> t <span>values</span>(<span>'</span><span>200407</span><span>'</span>,<span>5764</span>,<span>'</span><span>G</span><span>'</span>, <span>6456433.23</span>); <span>insert</span> <span>into</span> t <span>values</span>(<span>'</span><span>200407</span><span>'</span>,<span>5764</span>,<span>'</span><span>J</span><span>'</span>, <span>6987660.53</span>); <span>insert</span> <span>into</span> t <span>values</span>(<span>'</span><span>200407</span><span>'</span>,<span>5765</span>,<span>'</span><span>G</span><span>'</span>, <span>14000101.20</span>); <span>insert</span> <span>into</span> t <span>values</span>(<span>'</span><span>200407</span><span>'</span>,<span>5765</span>,<span>'</span><span>J</span><span>'</span>, <span>12301780.20</span>); <span>insert</span> <span>into</span> t <span>values</span>(<span>'</span><span>200408</span><span>'</span>,<span>5761</span>,<span>'</span><span>G</span><span>'</span>, <span>8085170.84</span>); <span>insert</span> <span>into</span> t <span>values</span>(<span>'</span><span>200408</span><span>'</span>,<span>5761</span>,<span>'</span><span>J</span><span>'</span>, <span>6050611.37</span>); <span>insert</span> <span>into</span> t <span>values</span>(<span>'</span><span>200408</span><span>'</span>,<span>5762</span>,<span>'</span><span>G</span><span>'</span>, <span>6854584.22</span>); <span>insert</span> <span>into</span> t <span>values</span>(<span>'</span><span>200408</span><span>'</span>,<span>5762</span>,<span>'</span><span>J</span><span>'</span>, <span>6521884.50</span>); <span>insert</span> <span>into</span> t <span>values</span>(<span>'</span><span>200408</span><span>'</span>,<span>5763</span>,<span>'</span><span>G</span><span>'</span>, <span>9468707.65</span>); <span>insert</span> <span>into</span> t <span>values</span>(<span>'</span><span>200408</span><span>'</span>,<span>5763</span>,<span>'</span><span>J</span><span>'</span>, <span>8460049.43</span>); <span>insert</span> <span>into</span> t <span>values</span>(<span>'</span><span>200408</span><span>'</span>,<span>5764</span>,<span>'</span><span>G</span><span>'</span>, <span>6587559.23</span>); <span>insert</span> <span>into</span> t <span>values</span>(<span>'</span><span>200408</span><span>'</span>,<span>5764</span>,<span>'</span><span>J</span><span>'</span>, <span>7342135.86</span>); <span>insert</span> <span>into</span> t <span>values</span>(<span>'</span><span>200408</span><span>'</span>,<span>5765</span>,<span>'</span><span>G</span><span>'</span>, <span>14450586.63</span>); <span>insert</span> <span>into</span> t <span>values</span>(<span>'</span><span>200408</span><span>'</span>,<span>5765</span>,<span>'</span><span>J</span><span>'</span>, <span>12680052.38</span>); <span>commit</span>;
三、first_value()与last_value():求最值对应的其他属性
问题、取出每月通话费最高和最低的两个地区。
<span>SELECT</span> BILL_MONTH, AREA_CODE, <span>SUM</span>(LOCAL_FARE) LOCAL_FARE, FIRST_VALUE(AREA_CODE) <span>OVER</span>(PARTITION <span>BY</span> BILL_MONTH <span>ORDER</span> <span>BY</span> <span>SUM</span>(LOCAL_FARE) <span>DESC</span> ROWS <span>BETWEEN</span> UNBOUNDED PRECEDING <span>AND</span> UNBOUNDED FOLLOWING) FIRSTVAL, LAST_VALUE(AREA_CODE) <span>OVER</span>(PARTITION <span>BY</span> BILL_MONTH <span>ORDER</span> <span>BY</span> <span>SUM</span>(LOCAL_FARE) <span>DESC</span> ROWS <span>BETWEEN</span> UNBOUNDED PRECEDING <span>AND</span> UNBOUNDED FOLLOWING) LASTVAL <span>FROM</span> T <span>GROUP</span> <span>BY</span> BILL_MONTH, AREA_CODE <span>ORDER</span> <span>BY</span> BILL_MONTH
运行结果:
四、rank(),dense_rank()与row_number():求排序
rank,dense_rank,row_number函数为每条记录产生一个从1开始至n的自然数,n的值可能小于等于记录的总数。这3个函数的唯一区别在于当碰到相同数据时的排名策略。
①row_number:
row_number函数返回一个唯一的值,当碰到相同数据时,排名按照记录集中记录的顺序依次递增。
②dense_rank:
dense_rank函数返回一个唯一的值,当碰到相同数据时,此时所有相同数据的排名都是一样的。
③rank:
rank函数返回一个唯一的值,当碰到相同的数据时,此时所有相同数据的排名是一样的,同时会在最后一条相同记录和下一条不同记录的排名之间空出排名。
演示数据在Oracle自带的scott用户下:
1、rank()值相同时排名相同,其后排名跳跃不连续
<span>SELECT</span> <span>*</span> <span>FROM</span> (<span>SELECT</span> DEPTNO, RANK() <span>OVER</span>(PARTITION <span>BY</span> DEPTNO <span>ORDER</span> <span>BY</span> SAL <span>DESC</span>) RW, ENAME, SAL <span>FROM</span> SCOTT.EMP) <span>WHERE</span> RW <span> <span>4</span>;</span>
运行结果:
2、dense_rank()值相同时排名相同,其后排名连续不跳跃
<span>SELECT</span> <span>*</span> <span>FROM</span> (<span>SELECT</span> DEPTNO, DENSE_RANK() <span>OVER</span>(PARTITION <span>BY</span> DEPTNO <span>ORDER</span> <span>BY</span> SAL <span>DESC</span>) RW, ENAME, SAL <span>FROM</span> SCOTT.EMP) <span>WHERE</span> RW <span> <span>4</span>;</span>
运行结果:
3、row_number()值相同时排名不相等,其后排名连续不跳跃
<span>SELECT</span> <span>*</span> <span>FROM</span> (<span>SELECT</span> DEPTNO, ROW_NUMBER() <span>OVER</span>(PARTITION <span>BY</span> DEPTNO <span>ORDER</span> <span>BY</span> SAL <span>DESC</span>) RW, ENAME, SAL <span>FROM</span> SCOTT.EMP) <span>WHERE</span> RW <span> <span>4</span>;</span>
运行结果:
五、lag()与lead():求之前或之后的第N行
lag和lead函数可以在一次查询中取出同一字段的前n行的数据和后n行的值。这种操作可以使用对相同表的表连接来实现,不过使用lag和lead有更高的效率。
lag(arg1,arg2,arg3)
第一个参数是列名,
第二个参数是偏移的offset,
第三个参数是超出记录窗口时的默认值。
举例如下:
SQL> select * from kkk;
ID NAME
---------- --------------------
1 1name
2 2name
3 3name
4 4name
5 5name
SQL> select id,name,lag(name,1,0) over(order by id) from kkk;
ID NAME LAG(NAME,1,0)OVER(ORDERBYID)
---------- -------------------- ----------------------------
1 1name 0
2 2name 1name
3 3name 2name
4 4name 3name
5 5name 4name
SQL> select id,name,lead(name,1,0) over(order by id) from kkk;
ID NAME LEAD(NAME,1,0)OVER(ORDERBYID)
---------- -------------------- -----------------------------
1 1name 2name
2 2name 3name
3 3name 4name
4 4name 5name
5 5name 0
SQL> select id,name,lead(name,2,0) over(order by id) from kkk;
ID NAME LEAD(NAME,2,0)OVER(ORDERBYID)
---------- -------------------- -----------------------------
1 1name 3name
2 2name 4name
3 3name 5name
4 4name 0
5 5name 0
SQL> select id,name,lead(name,1,'linjiqin') over(order by id) from kkk;
ID NAME LEAD(NAME,1,'ALSDFJLASDJFSAF')
---------- -------------------- ------------------------------
1 1name 2name
2 2name 3name
3 3name 4name
4 4name 5name
5 5name linjiqin
---------------------------------------------------------------------------------------
六、rollup()与cube():排列组合分组
1)、group by rollup(a, b, c):
首先会对(a、b、c)进行group by,
然后再对(a、b)进行group by,
其后再对(a)进行group by,
最后对全表进行汇总操作。
2)、group by cube(a, b, c):
则首先会对(a、b、c)进行group by,
然后依次是(a、b),(a、c),(a),(b、c),(b),(c),
最后对全表进行汇总操作。
1、生成演示数据:
Connected to Oracle Database 10g Enterprise Edition Release 10.2.0.1.0
Connected as ds_trade
SQL> conn system/oracle as sysdba
Connected to Oracle Database 10g Enterprise Edition Release 10.2.0.3.0
Connected as SYS
SQL> create table scott.t as select * from dba_indexes;
Table created
SQL> connect scott/oracle
Connected to Oracle Database 10g Enterprise Edition Release 10.2.0.3.0
Connected as scott
SQL>
2、普通group by体验
sql> select owner, index_type, status, count(*) from t where owner like 'SY%' group by owner, index_type, status;
3、group by rollup(A,B,C)
GROUP BY ROLLUP(A, B, C):
首先会对(A、B、C)进行GROUP BY,
然后再对(A、B)进行GROUP BY,
其后再对(A)进行GROUP BY,
最后对全表进行汇总操作。
sql> select owner, index_type, status, count(*) from t where owner like 'SY%' group by ROLLUP(owner, index_type, status);
4、group by cube(A,B,C)
GROUP BY CUBE(A, B, C):
则首先会对(A、B、C)进行GROUP BY,
然后依次是(A、B),(A、C),(A),(B、C),(B),(C),
最后对全表进行汇总操作。
sql> select owner, index_type, status, count(*) from t where owner like 'SY%' group by cube(owner, index_type, status);
七、max(),min(),sun()与avg():求移动的最值总和与平均值
问题:计算出各个地区连续3个月的通话费用的平均数(移动平均值)
<span>SELECT</span> AREA_CODE, BILL_MONTH, LOCAL_FARE, <span>SUM</span>(LOCAL_FARE) <span>OVER</span>(PARTITION <span>BY</span> AREA_CODE <span>ORDER</span> <span>BY</span> TO_NUMBER(BILL_MONTH) RANGE <span>BETWEEN</span> <span>1</span> PRECEDING <span>AND</span> <span>1</span> FOLLOWING) "3month_sum", <span>AVG</span>(LOCAL_FARE) <span>OVER</span>(PARTITION <span>BY</span> AREA_CODE <span>ORDER</span> <span>BY</span> TO_NUMBER(BILL_MONTH) RANGE <span>BETWEEN</span> <span>1</span> PRECEDING <span>AND</span> <span>1</span> FOLLOWING) "3month_avg", <span>MAX</span>(LOCAL_FARE) <span>OVER</span>(PARTITION <span>BY</span> AREA_CODE <span>ORDER</span> <span>BY</span> TO_NUMBER(BILL_MONTH) RANGE <span>BETWEEN</span> <span>1</span> PRECEDING <span>AND</span> <span>1</span> FOLLOWING) "3month_max", <span>MIN</span>(LOCAL_FARE) <span>OVER</span>(PARTITION <span>BY</span> AREA_CODE <span>ORDER</span> <span>BY</span> TO_NUMBER(BILL_MONTH) RANGE <span>BETWEEN</span> <span>1</span> PRECEDING <span>AND</span> <span>1</span> FOLLOWING) "3month_min" <span>FROM</span> (<span>SELECT</span> T.AREA_CODE, T.BILL_MONTH, <span>SUM</span>(T.LOCAL_FARE) LOCAL_FARE <span>FROM</span> T <span>GROUP</span> <span>BY</span> T.AREA_CODE, T.BILL_MONTH)
运行结果:
问题:求各地区按月份累加的通话费
<span>SELECT</span> AREA_CODE, BILL_MONTH, LOCAL_FARE, <span>SUM</span>(LOCAL_FARE) <span>OVER</span>(PARTITION <span>BY</span> AREA_CODE <span>ORDER</span> <span>BY</span> BILL_MONTH <span>ASC</span>) "last_sum_value" <span>FROM</span> (<span>SELECT</span> T.AREA_CODE, T.BILL_MONTH, <span>SUM</span>(T.LOCAL_FARE) LOCAL_FARE <span>FROM</span> T <span>GROUP</span> <span>BY</span> T.AREA_CODE, T.BILL_MONTH) <span>ORDER</span> <span>BY</span> AREA_CODE, BILL_MONTH
运行结果:
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另见:《Oracle分析函数ROW_NUMBER()|RANK()|LAG()使用详解》