CUME_DIST - 云原生大数据计算服务 MaxCompute

计算累计分布。

使用限制

窗口函数的使用限制如下：

窗口函数只能出现在select语句中。
窗口函数中不能嵌套使用窗口函数和聚合函数。
窗口函数不能和同级别的聚合函数一起使用。

命令格式

double cume_dist() over([partition_clause] [orderby_clause])

命令说明

求累计分布，相当于求分区中大于等于当前行的数据在分区中的占比。大小关系由orderby_clause判定。

参数说明

partition_clause及orderby_clause：详情请参见windowing_definition。

返回值说明

返回DOUBLE类型。具体的返回值等于row_number_of_last_peer / partition_row_count，其中：row_number_of_last_peer指当前行所属GROUP的最后一行数据的ROW_NUMBER窗口函数返回值，partition_row_count为该行数据所属分区的数据行数。

示例数据

为便于理解各函数的使用方法，本文为您提供源数据，基于源数据提供函数相关示例。创建表emp，并添加数据，命令示例如下：

create table if not exists emp
   (empno bigint,
    ename string,
    job string,
    mgr bigint,
    hiredate datetime,
    sal bigint,
    comm bigint,
    deptno bigint);
tunnel upload emp.txt emp;

emp.txt中的数据如下：

7369,SMITH,CLERK,7902,1980-12-17 00:00:00,800,,20
7499,ALLEN,SALESMAN,7698,1981-02-20 00:00:00,1600,300,30
7521,WARD,SALESMAN,7698,1981-02-22 00:00:00,1250,500,30
7566,JONES,MANAGER,7839,1981-04-02 00:00:00,2975,,20
7654,MARTIN,SALESMAN,7698,1981-09-28 00:00:00,1250,1400,30
7698,BLAKE,MANAGER,7839,1981-05-01 00:00:00,2850,,30
7782,CLARK,MANAGER,7839,1981-06-09 00:00:00,2450,,10
7788,SCOTT,ANALYST,7566,1987-04-19 00:00:00,3000,,20
7839,KING,PRESIDENT,,1981-11-17 00:00:00,5000,,10
7844,TURNER,SALESMAN,7698,1981-09-08 00:00:00,1500,0,30
7876,ADAMS,CLERK,7788,1987-05-23 00:00:00,1100,,20
7900,JAMES,CLERK,7698,1981-12-03 00:00:00,950,,30
7902,FORD,ANALYST,7566,1981-12-03 00:00:00,3000,,20
7934,MILLER,CLERK,7782,1982-01-23 00:00:00,1300,,10
7948,JACCKA,CLERK,7782,1981-04-12 00:00:00,5000,,10
7956,WELAN,CLERK,7649,1982-07-20 00:00:00,2450,,10
7956,TEBAGE,CLERK,7748,1982-12-30 00:00:00,1300,,10

示例

将所有职工根据部门（deptno）分组（作为开窗列），计算薪水（sal）在同一组内的前百分之几。命令示例如下：

select deptno, ename, sal, concat(round(cume_dist() over (partition by deptno order by sal desc)*100,2),'%') as cume_dist from emp;

返回结果如下：

+------------+------------+------------+------------+
| deptno     | ename      | sal        | cume_dist  |
+------------+------------+------------+------------+
| 10         | JACCKA     | 5000       | 33.33%     |
| 10         | KING       | 5000       | 33.33%     |
| 10         | CLARK      | 2450       | 66.67%     |
| 10         | WELAN      | 2450       | 66.67%     |
| 10         | TEBAGE     | 1300       | 100.0%     |
| 10         | MILLER     | 1300       | 100.0%     |
| 20         | SCOTT      | 3000       | 40.0%      |
| 20         | FORD       | 3000       | 40.0%      |
| 20         | JONES      | 2975       | 60.0%      |
| 20         | ADAMS      | 1100       | 80.0%      |
| 20         | SMITH      | 800        | 100.0%     |
| 30         | BLAKE      | 2850       | 16.67%     |
| 30         | ALLEN      | 1600       | 33.33%     |
| 30         | TURNER     | 1500       | 50.0%      |
| 30         | MARTIN     | 1250       | 83.33%     |
| 30         | WARD       | 1250       | 83.33%     |
| 30         | JAMES      | 950        | 100.0%     |
+------------+------------+------------+------------+

云原生大数据计算服务 MaxCompute：CUME_DIST