ORACLE日常统计分析函数
以下文章来源于cc_0101
正文
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！！！ 并且排序字段能确定唯一性数据!如果根据排序字段得到的数据不具有唯一性,开窗时会随机取数。
本篇未涉及开窗子句，开窗子句在另外的文章中单独说明
二、分析函数汇总
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
select ename,esex,eage,salary,max(salary) over() from emp; --求总最大值
select ename,esex,eage,salary,max(salary) over(order by eage) from emp; --递加求最大值
select ename,esex,eage,salary,max(salary) over(partition by esex) from emp; --分组求最大值
select ename,esex,eage,salary,max(salary) over(partition by esex order by eage) from emp; --分组递加求最大值
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
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;
-- 按照job分组,按照salary降序。取出占占5%的salary数据
select ename,job,salary,percentile_cont(0.5) within group(order by salary desc) 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;
15.16、precentile函数详解样例数据：
– 准备数据：
create table EMP
(
EMPNO NUMBER(4) not null,
ENAME VARCHAR2(10),
JOB VARCHAR2(9),
MGR NUMBER(4),
HIREDATE DATE,
SAL NUMBER(7,2),
COMM NUMBER(7,2),
DEPTNO NUMBER(2)
);
insert into emp (EMPNO, ENAME, JOB, MGR, HIREDATE, SAL, COMM, DEPTNO)
values (7369, 'SMITH', 'CLERK', 7902, to_date('17-12-1980', 'dd-mm-yyyy'), 800.00, null, 20);
insert into emp (EMPNO, ENAME, JOB, MGR, HIREDATE, SAL, COMM, DEPTNO)
values (7499, 'ALLEN', 'SALESMAN', 7698, to_date('20-02-1981', 'dd-mm-yyyy'), 1600.00, 300.00, 30);
insert into emp (EMPNO, ENAME, JOB, MGR, HIREDATE, SAL, COMM, DEPTNO)
values (7521, 'WARD', 'SALESMAN', 7698, to_date('22-02-1981', 'dd-mm-yyyy'), 1250.00, 500.00, 30);
insert into emp (EMPNO, ENAME, JOB, MGR, HIREDATE, SAL, COMM, DEPTNO)
values (7566, 'JONES', 'MANAGER', 7839, to_date('02-04-1981', 'dd-mm-yyyy'), 2975.00, null, 20);
insert into emp (EMPNO, ENAME, JOB, MGR, HIREDATE, SAL, COMM, DEPTNO)
values (7654, 'MARTIN', 'SALESMAN', 7698, to_date('28-09-1981', 'dd-mm-yyyy'), 1250.00, 1400.00, 30);
insert into emp (EMPNO, ENAME, JOB, MGR, HIREDATE, SAL, COMM, DEPTNO)
values (7698, 'BLAKE', 'MANAGER', 7839, to_date('01-05-1981', 'dd-mm-yyyy'), 2850.00, null, 30);
insert into emp (EMPNO, ENAME, JOB, MGR, HIREDATE, SAL, COMM, DEPTNO)
values (7782, 'CLARK', 'MANAGER', 7839, to_date('09-06-1981', 'dd-mm-yyyy'), 2450.00, null, 10);
insert into emp (EMPNO, ENAME, JOB, MGR, HIREDATE, SAL, COMM, DEPTNO)
values (7788, 'SCOTT', 'ANALYST', 7566, to_date('19-04-1987', 'dd-mm-yyyy'), 3000.00, null, 20);
insert into emp (EMPNO, ENAME, JOB, MGR, HIREDATE, SAL, COMM, DEPTNO)
values (7839, 'KING', 'PRESIDENT', null, to_date('17-11-1981', 'dd-mm-yyyy'), 5000.00, null, 10);
insert into emp (EMPNO, ENAME, JOB, MGR, HIREDATE, SAL, COMM, DEPTNO)
values (7844, 'TURNER', 'SALESMAN', 7698, to_date('08-09-1981', 'dd-mm-yyyy'), 1500.00, 0.00, 30);
insert into emp (EMPNO, ENAME, JOB, MGR, HIREDATE, SAL, COMM, DEPTNO)
values (7876, 'ADAMS', 'CLERK', 7788, to_date('23-05-1987', 'dd-mm-yyyy'), 1100.00, null, 20);
insert into emp (EMPNO, ENAME, JOB, MGR, HIREDATE, SAL, COMM, DEPTNO)
values (7900, 'JAMES', 'CLERK', 7698, to_date('03-12-1981', 'dd-mm-yyyy'), 950.00, null, 30);
insert into emp (EMPNO, ENAME, JOB, MGR, HIREDATE, SAL, COMM, DEPTNO)
values (7902, 'FORD', 'ANALYST', 7566, to_date('03-12-1981', 'dd-mm-yyyy'), 3000.00, null, 20);
insert into emp (EMPNO, ENAME, JOB, MGR, HIREDATE, SAL, COMM, DEPTNO)
values (7934, 'MILLER', 'CLERK', 7782, to_date('23-01-1982', 'dd-mm-yyyy'), 1300.00, null, 10);
commit;
– 使用样例说明： 需求是“按薪水的倒序，取薪水的排名，及一定百分比的薪水值”
select e.ename,e.sal,e.deptno,
percent_rank() over(partition by deptno order by sal desc) p_rank, --以deptno分组，以sal倒序，取出百分比排名
PERCENTILE_CONT(0) within group(order by sal desc)
over(partition by deptno) max_sal , --以deptno分组，以sal倒序，取出占0%的薪水
PERCENTILE_CONT(0.25) within group(order by sal desc)
over(partition by deptno) max_sal_25, --以deptno分组，以sal倒序，取出25%的薪水
PERCENTILE_CONT(0.5) within group(order by sal desc)
over(partition by deptno) max_sal_50, --以deptno分组，以sal倒序，取出50%的薪水
PERCENTILE_CONT(0.75) within group(order by sal desc) --以deptno分组，以sal倒序，取出70%的薪水
over(partition by deptno) max_sal_75
from emp e;
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