hive：函数：排名函数：Rank（笔记）

Rank

1．函数说明

RANK() 排序（排名）相同时会重复，总数不会变

DENSE_RANK() 排序（排名）相同时会重复，总数会减少

ROW_NUMBER() 依次进行排名

2．数据准备

表6-7 数据准备

name	subject	score
孙悟空	语文	87
孙悟空	数学	95
孙悟空	英语	68
大海	语文	94
大海	数学	56
大海	英语	84
宋宋	语文	64
宋宋	数学	86
宋宋	英语	84
婷婷	语文	65
婷婷	数学	85
婷婷	英语	78

3．需求

计算每门学科成绩排名

4．创建本地score.txt，导入数据

 vi score.txt

5．创建hive表并导入数据

create table score(
name string,
subject string,
score int)
row format delimited fields terminated by "\t";

load data local inpath '/opt/module/datas/score.txt' into table score;

6．按需求查询数据

select name,
	subject,
	score,
	rank() over(partition by subject order by score desc) rank,
	dense_rank() over(partition by subject order by score desc) dense_rank,
	row_number() over(partition by subject order by score desc) row_number
from tmp.score;

 

 

扩展：求出每门学科前三名的学生？

select * from
(
	select
	name,
	subject,
	score,
	rank() over(partition by subject order by score desc ) rank,
	dense_rank() over(partition by subject order by score desc) dense_rank,
	row_number() over(partition by subject order by score desc) row_number
	from tmp.score
) s where row_number<=3

 

注意：partition后边有哪个字段只会影响最后的rank的排名，跟去重没关系，select后边字段可以指定多个，不一定跟partition后边的字段一致。

举例：

=================sql1：

select 
					create_time,creator_id,fullname,expectCity,positionName,keywords,row_number() over(partition by creator_id,fullname order by create_time desc) as rank
				from ( 
					select from_unixtime(ceil(c.create_time/1000),'yyyy-MM-dd') create_time,c.creator_id,e.fullname,
					c.expectCity,c.positionName,c.keywords,c.degree,c.minage,c.maxage,c.isNationalUnified,c.isFamous,c.companyName,c.expectIndustry,c.workCity,c.gender,c.minCurrentSalary,c.maxCurrentSalary,c.minWorkYear,c.maxWorkYear
					--,concat(expectCity,':',positionName,'(',keywords,' ',degree,' ',minage,'-',maxage,')') conditions 
					from tmp.t_conditions c
					--select c.creator_id,explode(split(regexp_replace(regexp_replace(expectCity,'\\[',''),'\\]',''),',')) city from tmp.t_conditions c
					left join ods.ods_aimsen_walre_anlle_base_employees e
					on c.creator_id=e.number
					where c.creator_id not in ('130000062','130000063','130000071','430000003')
					and c.tag in(2)
					and c.phone = ''
					and c.resumeId = ''
					and c.name = ''
					and from_unixtime(ceil(c.create_time/1000),'yyyy-MM-dd') > '2020-07-20'
					--and expectCity !='' and degree !=''  and (maxAge!='' or minAge!='') and (positionName !='' or keyWords!='')
					and creator_id=100400287
					group by create_time,c.creator_id,e.fullname,c.expectCity,c.positionName,c.keywords,c.degree,c.minage,c.maxage,c.isNationalUnified,c.isFamous,c.companyName,c.expectIndustry,c.workCity,c.gender,c.minCurrentSalary,c.maxCurrentSalary,c.minWorkYear,c.maxWorkYear--,concat(expectCity,':',positionName,'(',keywords,' ',degree,' ',minage,'-',maxage,')')
				) x


=================sql2：

select 
					create_time,creator_id,fullname,expectCity,positionName,keywords,row_number() over(partition by creator_id,fullname,expectCity order by create_time desc) as rank
				from ( 
					select from_unixtime(ceil(c.create_time/1000),'yyyy-MM-dd') create_time,c.creator_id,e.fullname,
					c.expectCity,c.positionName,c.keywords,c.degree,c.minage,c.maxage,c.isNationalUnified,c.isFamous,c.companyName,c.expectIndustry,c.workCity,c.gender,c.minCurrentSalary,c.maxCurrentSalary,c.minWorkYear,c.maxWorkYear
					--,concat(expectCity,':',positionName,'(',keywords,' ',degree,' ',minage,'-',maxage,')') conditions 
					from tmp.t_conditions c
					--select c.creator_id,explode(split(regexp_replace(regexp_replace(expectCity,'\\[',''),'\\]',''),',')) city from tmp.t_conditions c
					left join ods.ods_aimsen_walre_anlle_base_employees e
					on c.creator_id=e.number
					where c.creator_id not in ('130000062','130000063','130000071','430000003')
					and c.tag in(2)
					and c.phone = ''
					and c.resumeId = ''
					and c.name = ''
					and from_unixtime(ceil(c.create_time/1000),'yyyy-MM-dd') > '2020-07-20'
					--and expectCity !='' and degree !=''  and (maxAge!='' or minAge!='') and (positionName !='' or keyWords!='')
					and creator_id=100400287
					group by create_time,c.creator_id,e.fullname,c.expectCity,c.positionName,c.keywords,c.degree,c.minage,c.maxage,c.isNationalUnified,c.isFamous,c.companyName,c.expectIndustry,c.workCity,c.gender,c.minCurrentSalary,c.maxCurrentSalary,c.minWorkYear,c.maxWorkYear--,concat(expectCity,':',positionName,'(',keywords,' ',degree,' ',minage,'-',maxage,')')
				) x

sql1和sql2区别为：

sql2多个expectCity字段

create_time,creator_id,fullname,expectCity,positionName,keywords,row_number() over(partition by creator_id,fullname,expectCity order by create_time desc) as rank

sql1查询效果：

sql2查询效果：

​rank排名发生了变化，但最终查询出的结果条数并没有改变。