Hive--笔试题05_1--求TopN

刺骨的言语ヽ痛彻心扉 2021-12-23 20:11 246阅读 0赞

现在有一个面试题

# 场景举例 #

北京市学生成绩分析

# 成绩的数据格式 #

exercise5\_1.txt 文件中的每一行就是一个学生的成绩信息。字段之间的分隔符是","

时间,学校,年纪,姓名,科目,成绩

#    样例数据 #

2013,北大,1,黄渤,语文,97
    2013,北大,1,徐峥,语文,52
    2013,北大,1,刘德华,语文,85
    2012,清华,0,马云,英语,61
    2015,北理工,3,李彦宏,物理,81
    2016,北科,4,马化腾,化学,92
    2014,北航,2,刘强东,数学,70
    2012,清华,0,刘诗诗,英语,59
    2014,北航,2,刘亦菲,数学,49
    2014,北航,2,刘嘉玲,数学,77

# 建表导数据 #

create database if not exists exercise;
    use exercise;
    drop table if exists exercise5_1;
    create table exercise5_1(year int, school string, grade int, name string, course string, score int) row format delimited fields terminated by ',';
    load data local inpath "/home/hadoop/exercise5_1.txt" into table exercise5_1;
    select * from exercise5_1;
    desc exercise5_1;

# 需求 #

### 1、分组TopN，选出今年每个学校、每个年级、分数前三的科目 ###

select t.* 
    from 
    (select school, grade, course, score,
    row_number() over (partition by school, grade, course order by score desc) rank_code 
    from exercise5_1 
    where year = "2017"
    ) t
    where t.rank_code <= 3;

详解如下：  
  row\_number函数：row\_number() 按指定的列进行分组生成行序列，从 1 开始，如果两行记录的分组列相同，则行序列 +1。  
  over 函数：是一个窗口函数。  
  over (order by score) 按照 score 排序进行累计，order by 是个默认的开窗函数。  
  over (partition by grade) 按照班级分区。  
  over (partition by grade order by score) 按照班级分区，并按着分数排序。  
  over (order by score range between 2 preceding and 2 following) 窗口范围为当前行的数据幅度减2加2后的范围内的数据求和。

### 2、今年，北航，每个班级，每科的分数，及分数上下浮动2分的总和 ###

select school, grade, course, score,
    sum(score) over (order by score range between 2 preceding and 2 following) sscore
    from exercise5_1 
    where year = "2017" and school="北航";

### 3、where与having：今年，清华1年级，总成绩大于200分的学生以及学生数 ###

select school, grade, name, sum(score) as total_score,
    count(1) over (partition by school, grade) nct
    from exercise5_1
    where year = "2017" and school="清华" and grade = 1
    group by school, grade, name
    having total_score > 200;

having 是分组（group by）后的筛选条件，分组后的数据组内再筛选，也就是说 HAVING 子句可以让我们筛选成组后的各组数据。  
where 则是在分组，聚合前先筛选记录。也就是说作用在 GROUP BY 子句和 HAVING 子句前。