摘要:本文主要向大家介绍了【云计算】Hive分析函数解析,通过具体的内容向大家展现,希望对大家学习云计算有所帮助。
本文主要向大家介绍了【云计算】Hive分析函数解析,通过具体的内容向大家展现,希望对大家学习云计算有所帮助。
1、窗口函数(开窗函数),关键字:over
(0)基础知识
2 preceding ====== 前两行
2 following ====== 后两行
current row ====== 当前行
unbounded preceding?====== 无上限
unbounded following ====== 无下限
(1)表user_par的结构和数据如下图
(2)以行定义窗口界限
(2-1)按id排序,并计算当前行和以下两行的年龄之和
select id, name, age, sum(age)over(order by id rows between current row and 2 following) from user_par;
(2-2)按id排序,并计算当前行和以上两行的年龄之和
select id, name, age, sum(age)over(order by id rows between current row and 2 following) from user_par;
(3)以值定义窗口界限,必须和排序一起使用,否则没有意义
(3-1)按age排序,并计算当前的年龄比它大10岁的所有年龄之和
select id, name, age, sum(age)over(order by age range between current row and 10 following) from user_par;
(3-2)不加order by时计算的是所有年龄的总和,值定义窗口界限没有意义
select id, name, age, sum(age)over(range between current row and 10 following) from user_par;
2、排名函数
(0)表user_nopar的结构和数据如下图
(1)并列跳跃排名:按省份分区,并按年龄大小排序
select id, name, province, age, rank()over(partition by province order by age asc) from user_nopar;
(2)并列不跳跃:按省份分区,并按年龄大小排序
select id, name, province, age, dense_rank()over(partition by province order by age asc) from user_nopar;
(3)顺序排名:按省份分区,并按年龄大小排序
select id, name, province, age, row_number()over(partition by province order by age asc) from user_nopar;
3、最大值函数
select id, name, province, age, first_value(age)over(partition by province order by age desc) from user_nopar;
select id, name, province, age, last_value(age)over(partition by province order by age asc range between unbounded preceding and unbounded following) from user_nopar;
4、最小值函数
select id, name, province, age, first_value(age)over(partition by province order by age asc) from user_nopar;
select id, name, province, age, last_value(age)over(partition by province order by age desc range between unbounded preceding and unbounded following) from user_nopar;
5、三六九等函数
select id, name, age, ntile(3)over(order by age) from user_nopar;
6、上提和下沉函数
(1)按province分区,并将age字段向上提一行
select id, name, province, age, lead(age)over(partition by province order by age asc) from user_nopar;
(2)按province分区,并将age字段向上提两行
select id, name, province, age, lead(age,2)over(partition by province order by age asc) from user_nopar;
(3)按province分区,并将age字段向下沉两行
select id, name, province, age, lag(age,2)over(partition by province order by age asc) from user_nopar;
7、指定值占总数的百分比
(1)年龄按降序排列,统计年龄大于等于当前值的人占所有人的百分比
select id, name, age, cume_dist()over(order by age desc) from user_nopar;
(2)按省份分区,并按年龄升序排列,统计每个分区内年龄小于等于当前值的人占所有人的百分比
select id, name, province, age, cume_dist()over(partition by province order by age asc) from user_nopar;
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