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Oracle分析函数

时间:2020-11-07 17:03:30      阅读:24      评论:0      收藏:0      [点我收藏+]

标签:epo   ber   ova   rank   排名   语法   ntile   order by   依次   

一、分析函数语法
function_name(<argument>,<argument>...) over(<partition_Clause><order by_Clause><windowing_Clause>);
function_name():函数名称
argument:参数
over( ):开窗函数
partition_Clause:分区子句,数据记录集分组,group by...
order by_Clause:排序子句,数据记录集排序,order by...
windowing_Clause:开窗子句,定义分析函数在操作行的集合,三种开窗方式:rows、range、Specifying
注:使用开窗子句时一定要有排序子句!!!
本篇未涉及开窗子句,开窗子句在另外的文章中单独说明

0、listagg () within group (),将多行合并成一行
select listagg(t.ename, ‘,‘) within group (order by t.ename) as names from emp t group by t.deptno

1、count() over()  :统计分区中各组的行数,partition by 可选,order by 可选
select ename,esex,eage,count(*) over() from emp; --总计数
select ename,esex,eage,count(*) over(order by eage) from emp; --递加计数
select ename,esex,eage,count(*) over(partition by esex) from emp; --分组计数
select ename,esex,eage,count(*) over(partition by esex order by eage) from emp;--分组递加计数

2、sum() over()  :统计分区中记录的总和,partition by 可选,order by 可选
select ename,esex,eage,sum(salary) over() from emp; --总累计求和
select ename,esex,eage,sum(salary) over(order by eage) from emp; --递加累计求和
select ename,esex,eage,sum(salary) over(partition by esex) from emp; --分组累计求和
select ename,esex,eage,sum(salary) over(partition by esex order by eage) from emp; --分组递加累计求和

3、avg() over()  :统计分区中记录的平均值,partition by 可选,order by 可选
select ename,esex,eage,avg(salary) over() from emp; --总平均值
select ename,esex,eage,avg(salary) over(order by eage) from emp; --递加求平均值
select ename,esex,eage,avg(salary) over(partition by esex) from emp; --分组求平均值
select ename,esex,eage,avg(salary) over(partition by esex order by eage) from emp; --分组递加求平均值

4. min() over() :统计分区中记录的最小值,partition by 可选,order by 可选
max() over() :统计分区中记录的最大值,partition by 可选,order by 可选
select ename,esex,eage,salary,min(salary) over() from emp; --求总最小值
select ename,esex,eage,salary,min(salary) over(order by eage) from emp; --递加求最小值
select ename,esex,eage,salary,min(salary) over(partition by esex) from emp; --分组求最小值
select ename,esex,eage,salary,min(salary) over(partition by esex order by eage) from emp; --分组递加求最小值

5、rank() over()  :跳跃排序,partition by 可选,order by 必选
select ename,eage,rank() over(partition by job order by eage) from emp;
select ename,eage,rank() over(order by eage) from emp;

6、dense_rank() :连续排序,partition by 可选,order by 必选

    select ename,eage,dense_rank() over(partition by job order by eage) from emp;
    select ename,eage,dense_rank() over(order by eage) from emp;

7、row_number() over() :排序,无重复值,partition by 可选,order by 必选--表示根据col1分组,在分组内部根据col2排序
select ename,eage,row_number() over(partition by job order by eage) from emp;
select ename,eage,row_number() over(order by eage) from emp;

8、ntile(n) over() :partition by 可选,order by 必选

    n表示将分区内记录平均分成n份,多出的按照顺序依次分给前面的组

    select ename,salary,ntile(3) over(order by salary desc) from emp;
    select ename,salary,ntile(3) over(partition by job order by salary desc) from emp;

9、first_value() over() :取出分区中第一条记录的字段值,partition by 可选,order by 可选

     last_value() over() :取出分区中最后一条记录的字段值,partition by 可选,order by 可选

    select ename,first_value(salary) over() from emp;
    select ename,first_value(salary) over(order by salary desc) from emp;
    select ename,first_value(salary) over(partition by job) from emp;                                                           
    select ename,first_value(salary) over(partition by job order by salary desc) from emp;

    select ename,last_value(ename) over() from emp;
    select ename,last_value(ename) over(order by salary desc) from emp;
    select ename,last_value(ename) over(partition by job) from emp;
    select ename,last_value(ename) over(partition by job order by salary desc) from emp;

10、first :从DENSE_RANK返回的集合中取出排在最前面的一个值的行

      last :从DENSE_RANK返回的集合中取出排在最后面的一个值的行

    select job,max(salary) keep(dense_rank first order by salary desc),
    max(salary) keep(dense_rank last order by salary desc) from emp
    group by job;

11、lag() over() :取出前n行数据,partition by 可选,order by 必选

      lead() over() :取出后n行数据,partition by 可选,order by 必选

    select ename,eage,lag(eage,1,0) over(order by salary),
    lead(eage,1,0) over(order by salary) from emp;
     
    select ename,eage,lag(eage,1) over(partition by esex order by salary),
    lead(eage,1) over(partition by esex order by salary) from emp;

12、ratio_to_report(a) over(partition by b) :求按照b分组后a的值在所属分组中总值的占比,a的值必须为数值或数值型字段

      partition by 可选,order by 不可选

    select ename,job,salary,ratio_to_report(1) over() from emp; --给每一行赋值1,求当前行在总值的占比,总是0.1
    select ename,job,salary,ratio_to_report(salary) over() from emp; --当前行的值在所有数据中的占比
    select ename,job,salary,ratio_to_report(1) over(partition by job) from emp; --给每一行赋值1,求当前行在分组后的组内总值的占比
    select ename,job,salary,ratio_to_report(salary) over(partition by job) from emp; --当前行的值在分组后组内总值占比

13、percent_rank() over()  :partition by 可选,order by 必选

     所在组排名序号-1除以该组所有的行数-1,排名跳跃排序

    select ename,job,salary,percent_rank() over(order by salary) from emp;
    select ename,job,salary,percent_rank() over(partition by job order by salary) from emp;

14、cume_dist() over() :partition by 可选,order by必选

所在组排名序号除以该组所有的行数,注意对于重复行,计算时取重复行中的最后一行的位置

    select ename,job,salary,cume_dist() over(order by salary) from emp;
    select ename,job,salary,cume_dist() over(partition by job order by salary) from emp;

15、precentile_cont( x ) within group(order by ...) over()    :over()中partition by可选,order by 不可选

x为输入的百分比,是0-1之间的一个小数,返回该百分比位置的数据,若没有则返回以下计算值(r):

a=1+( x *(N-1) )  x为输入的百分比,N为分区内的记录的行数

b=ceil ( a )  向上取整

c = floor( a ) 向下取整

r=a * 百分比位置上一条数据 + b * 百分比位置下一条数据

    select ename,job,salary,percentile_cont(0.5) within group(order by salary) over() from emp;
    select ename,job,salary,percentile_cont(0.5) within group(order by salary) over(partition by job) from emp;

16、precentile_disc( x ) within group(order by ...) over()   :over()中partition by可选,order by 不可选

x为输入的百分比,是0-1之间的一个小数,返回百分比位置对应位置上的数据值,若没有对应数据值,就取大于该分布值的下一个值

    select ename,job,salary,percentile_disc(0.5) within group(order by salary) over()from emp;
    select ename,job,salary,percentile_disc(0.5) within group(order by salary) over(partition by job) from emp;

17、stddev() over():计算样本标准差,只有一行数据时返回0,partition by 可选,order by 可选

      stddev_samp() over():计算样本标准差,只有一行数据时返回null,partition by 可选,order by 可选

      stddev_pop() over():计算总体标准差,partition by 可选,order by 可选

    select stddev(stu_age) over() from student; --计算所有记录的样本标准差
    select stddev(stu_age) over(order by stu_age) from student; --计算递加的样本标准差
    select stddev(stu_age) over(partition by stu_major) from student; --计算分组的样本标准差
    select stddev(stu_age) over(partition by stu_major order by stu_age) from student; --计算分组递加的样本标准差
     
     
    select stddev_samp(stu_age) over() from student; --计算所有记录的样本标准差
    select stddev_samp(stu_age) over(order by stu_age) from student; --计算递加的样本标准差
    select stddev_samp(stu_age) over(partition by stu_major) from student; --计算分组的样本标准差
    select stddev_samp(stu_age) over(partition by stu_major order by stu_age) from student; --计算分组递加的样本标准差
     
     
    select stddev_pop(stu_age) over() from student; --计算所有记录的总体标准差
    select stddev_pop(stu_age) over(order by stu_age) from student; --计算递加的总体标准差
    select stddev_pop(stu_age) over(partition by stu_major) from student; --计算分组的总体标准差
    select stddev_pop(stu_age) over(partition by stu_major order by stu_age) from student;--计算分组递加的总体标准差

18、variance() over():计算样本方差,只有一行数据时返回0,partition by 可选,order by 可选

       var_samp() over():计算样本方差,只有一行数据时返回null,partition by 可选,order by 可选

       var_pop() over():计算总体方差,partition by 可选,order by 可选

    select variance(stu_age) over() from student; --计算所有记录的样本方差
    select variance(stu_age) over(order by stu_age) from student; --计算递加的样本方差
    select variance(stu_age) over(partition by stu_major) from student; --计算分组的样本方差
    select variance(stu_age) over(partition by stu_major order by stu_age) from student; --计算分组递加的样本方差
     
     
    select var_samp(stu_age) over() from student; --计算所有记录的样本方差
    select var_samp(stu_age) over(order by stu_age) from student; --计算递加的样本方差
    select var_samp(stu_age) over(partition by stu_major) from student; --计算分组的样本方差
    select var_samp(stu_age) over(partition by stu_major order by stu_age) from student; --计算分组递加的样本方差
     
     
    select var_pop(stu_age) over() from student; --记录所有就的总体方差
    select var_pop(stu_age) over(order by stu_age) from student; --计算递加的总体方差
    select var_pop(stu_age) over(partition by stu_major) from student; --计算分组的总体方差
    select var_pop(stu_age) over(partition by stu_major order by stu_age) from student;--计算分组递加的样本方差

stddev()=sqrt( variance() )     sqrt()--求开方

stddev_samp()=sqrt( var_samp() )

stddec_pop=sqrt( var_pop() )


19、covar_samp over():返回一对表达式的样本协方差,partition by 可选,order by 可选

       covar_pop over(): 返回一堆表达式的总体协方差,partition by 可选,order by 可选

    select covar_samp(stu_age,line) over() from student; --计算所有记录的样本协方差
    select covar_samp(stu_age,line) over(order by stu_age) from student; --计算递加的样本协方差
    select covar_samp(stu_age,line) over(partition by stu_major) from student; --计算分组的样本协方差
    select covar_samp(stu_age,line) over(partition by stu_major order by stu_age) from student; --计算分组递加的样本协方差
     
     
    select covar_pop(stu_age,line) over() from student; --计算所有记录的总体协方差
    select covar_pop(stu_age,line) over(order by stu_age) from student; --计算递加的总体协方差
    select covar_pop(stu_age,line) over(partition by stu_major) from student; --计算分组的总体协方差
    select covar_pop(stu_age,line) over(partition by stu_major order by stu_age) from student; --计算分组递加的总体协方差

20、corr() over() :返回一对表达式的相关系数,partition by 可选,order by 可选

    select corr(stu_age,line) over() from student; --计算所有记录的相关系数
    select corr(stu_age,line) over(order by stu_age) from student; --计算递加的相关系数
    select corr(stu_age,line) over(partition by stu_major) from student; --计算分组的相关系数
    select corr(stu_age,line) over(partition by stu_major order by stu_age) from student; --计算分组递加的相关系数

21、REGR_ (Linear Regression) Functions:这些线性回归函数适合最小二乘法回归线,有9个不同的回归函数可使用

Oracle分析函数

标签:epo   ber   ova   rank   排名   语法   ntile   order by   依次   

原文地址:https://www.cnblogs.com/yifanSJ/p/13939635.html

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