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Hive 0.11.0以后增加了分析函数row_number()、rank()、dense_rank()，说明：

row_number() over ([partition col1] [order by col2])

rank() over ([partition col1] [order by col2])

dense_rank() over ([partition col1] [order by col2])

三个函数都是根据col1字段分组，然后对col2字段进行排序，对排序后的每行生成一个行号，这个行号从1开始递增col1、col2都可以是多个字段，用','分隔

三个函数的区别是：

row_number() 是没有重复值的排序(即使记录相等也是不重复的)，可以利用它来实现分页； dense_rank() 是连续排序，排名相等会在名次中不会留下空位，两个第二名仍然跟着第三名；rank()是跳跃排序，排名相等会在名次中留下空位，如两个第二名下来就是第四名。

实例：

1. hive> create table t(name string, sub string, score int) row format delimited fields terminated by ‘\t‘;

数据在a.txt文件中

1. a chinese 98

2. a english 90

3. d chinese 88

4. c english 82

5. c math 98

6. b math 89

7. b chinese 79

8. z english 90

9. z math 89

10. z chinese 80

11. e math 99

12. e english 87

13. d english 90

1、row_number

1. hive (test)> select *, row_number() over (partition by sub order by score) as od from t;

2、rank

1. hive (test)> select *, rank() over (partition by sub order by score) as od from t;

3、dense_ran

1. hive (test)> select *, dense_rank() over (partition by sub order by score desc) od from t;

业务实例：

统计每个学科的前三名

hive> select * from (select *, row_number() over (partition by sub order by score desc) as od from t ) tt where od<=3;

语文成绩是80分的排名是多少

hive> select od from (select *, row_number() over (partition by sub order by score desc) as od from t ) t where sub=‘chinese‘ and score=80;

分页查询

hive> select * from (select *, row_number() over () as rn from t) t1 where rn between 1 and 5;

select *, row_number() over () as rn from t;