Hive实战

1．使用hive实现WordCount

(1) 创建数据库

create database wordcount;

(2) 创建外部表

create external table word_data
(
line string
) 
row format delimited fields 
terminated by ',' 
location '/home/hadoop/worddata';

(3) 映射数据表

load data inpath '/home/hadoop/worddata' into table word_data;

(4) 这里假设我们的数据存放在hadoop下，路径为：/home/hadoop/worddata，里面主要是一些单词文件，内容大概为：

hello man
what are you doing now
my running
hello
kevin
hi man

执行了上述hql就会创建一张表src_wordcount，内容是这些文件的每行数据，每行数据存在字段line中，select * from word_data;就可以看到这些数据。

(5) 根据MapReduce的规则，我们需要进行拆分，把每行数据拆分成单词，这里需要用到一个hive的内置表生成函数（UDTF）：explode(array)，参数是array，其实就是行变多列：

create table words(word string);
insert into table words select explode(split(line, " ")) as word from word_data;

(6) 查看words表内容

hello
man
what
are
you
doing
now
my
running
hello
kevin
hi
man

split是拆分函数，跟java的split功能一样，这里是按照空格拆分，所以执行完hql语句，words表里面就全部保存的单个单词

(7) group by统计单词

 select 
　　word, 
   count(*) 
 from wordcount.words 
 group by word;

结果：

are     1
doing   1
hello   2
hi      1
kevin   1
man     2
my      1
now     1
running 1
what    1
you     1

2．使用hive求TOP N

    rank() over()
    dense_rank() over()
    row_number() over()

3．使用Hive进行行列转换

问题

hive如何将
a       b       1
a       b       2
a       b       3
c       d       4
c       d       5
c       d       6
变为：
a       b       1,2,3
c       d       4,5,6

数据

test.txt

a       b       1
a       b       2
a       b       3
c       d       4
c       d       5
c       d       6

答案

(1).建表

drop table tmp_jiangzl_test;
create table tmp_jiangzl_test
(
　　col1 string,
　　col2 string,
　　col3 string
)
row format delimited fields terminated by '\t'
stored as textfile;

-- 加载数据
load data local inpath '/home/jiangzl/shell/test.txt' into table tmp_jiangzl_test;

(2).处理

select col1,col2,concat_ws(',',collect_set(col3))
from tmp_jiangzl_test
group by col1,col2;

二、列转行

问题

hive如何将
a       b       1,2,3
c       d       4,5,6
变为：
a       b       1
a       b       2
a       b       3
c       d       4
c       d       5
c       d       6

答案

(1). 建表

drop table tmp_jiangzl_test;
create table tmp_jiangzl_test
(
col1 string,
col2 string,
col3 string
)
row format delimited fields terminated by '\t'
stored as textfile;

(2). 处理：

select col1, col2, col5
from tmp_jiangzl_test a
lateral  view explode(split(col3,',')) b AS col5;

4．使用Hive进留存率统计

游戏公司等会很关注用户留存率问题,这里给出一个模板

SET mapreduce.job.queuename=xxx;
SET mapreduce.job.name=xxx;
SET mapreduce.job.reduces=19;

select '日期', '注册用户数', '次日留存率', '2日留存率', '3日留存率',  dim_date

                ,total_cnt

                ,concat_ws('% | ', cast(round(dif_1cnt*100/total_cnt, 2) as string), cast(dif_1cnt as string))

                ,concat_ws('% | ', cast(round(dif_2cnt*100/total_cnt, 2) as string), cast(dif_2cnt as string))

                ,concat_ws('% | ', cast(round(dif_3cnt*100/total_cnt, 2) as string), cast(dif_3cnt as string))

                ,concat_ws('% | ', cast(round(dif_4cnt*100/total_cnt, 2) as string), cast(dif_4cnt as string))

            from

            (

                select p1.state dim_date

                    ,p1.device_os

                    ,count(distinct p1.user_id) total_cnt

                    ,count(distinct if(datediff(p3.state,p1.state) = 1, p1.user_id, null)) dif_1cnt

                    ,count(distinct if(datediff(p3.state,p1.state) = 2, p1.user_id, null)) dif_2cnt

                    ,count(distinct if(datediff(p3.state,p1.state) = 3, p1.user_id, null)) dif_3cnt

                    ,count(distinct if(datediff(p3.state,p1.state) = 4, p1.user_id, null)) dif_4cnt

                from

                    (

                        select

                            from_unixtime(unix_timestamp(cast(partition_date as string), 'yyyyMMdd'), 'yyyy-MM-dd') state,

                            user_id

                        from user_active_day

                        where partition_date between date1 and date2

                        and user_is_new = 1

                        group by 1,2

                    )p1 --日新增用户名单(register_date,user_id)

                    left outer join

                    (

                        select

                            from_unixtime(unix_timestamp(cast(partition_date as string), 'yyyyMMdd'), 'yyyy-MM-dd') state,

                            user_id

                        from active_users

                        where partition_date between date1 and date2

                        group by 1,2

                    )p3 --期间活跃用户(active_date,user_id)

                    on (p3.user_id = p1.user_id)

                group by 1,2

            ) p4;