Hive实战之视频网站指标分析

一、需求

需求描述 统计视频网站的常规指标，各种TopN指标：

• 统计视频观看数Top10
• 统计视频类别热度Top10
• 统计视频观看数Top20所属类别
• 统计视频观看数Top50所关联视频的所属类别Rank
• 统计每个类别中的视频热度Top10
• 统计每个类别中视频流量Top10
• 统计上传视频最多的用户Top10以及他们上传的视频
• 统计每个类别视频观看数Top10

二、数据结构 2.1、视频表

2.2、用户表

2.3、测试数据 三、准备工作 3.1、创建表

创建表：chbvideo_ori，chbvideo_user_ori， 创建表：chbvideo_orc，chbvideo_user_orc

3.1.1、chbvideo_ori

create table chbvideo_ori(
    videoId string, 
    uploader string, 
    age int, 
    category array, 
    length int, 
    views int, 
    rate float, 
    ratings int, 
    comments int,
    relatedId array)
row format delimited 
fields terminated by "\t"
collection items terminated by "&"
stored as textfile;

3.1.2、chbvideo_user_ori

create table chbvideo_user_ori(
    uploader string,
    videos int,
    friends int)
row format delimited 
fields terminated by "\t" 
stored as textfile;

3.1.3、导入数据

load data inpath '/tmp/hivetest/chbVideoOut/video/2008/0222' overwrite into table chbvideo_ori;
load data local inpath '/uardata1/hivetest/chbVideo/user/2008/0903' into table chbvideo_user_ori;

3.1.4、导入到orc表中

create table chbvideo_orc(
    videoId string, 
    uploader string, 
    age int, 
    category array, 
    length int, 
    views int, 
    rate float, 
    ratings int, 
    comments int,
    relatedId array)
clustered by (uploader) into 8 buckets 
row format delimited fields terminated by "\t" 
collection items terminated by "&" 
stored as orc;


create table chbvideo_user_orc(
    uploader string,
    videos int,
    friends int)
row format delimited 
fields terminated by "\t" 
stored as orc;



# 导入到表中
chbvideo_orc：
insert into table chbvideo_orc select * from chbvideo_ori;

chbvideo_user_orc：
insert into table chbvideo_user_orc select * from chbvideo_user_ori;

四、业务分析 4.1、统计视频观看数Top10

思路：使用order by按照views字段做一个全局排序即可，同时我们设置只显示前10条。
select 
    videoId, 
    uploader, 
    age, 
    category, 
    length, 
    views, 
    rate, 
    ratings, 
    comments 
from chbvideo_orc 
order by views desc 
limit 10;

4.2、统计视频类别热度Top10

思路：

• 1、即统计每个类别有多少个视频，显示出包含视频最多的前10个类别。
• 2、我们需要按照类别group by聚合，然后count组内的videoId个数即可。
• 3、因为当前表结构为：一个视频对应一个或多个类别。所以如果要group by类别，需要先将类别进行列转行(展开)，然后再进行count即可。
• 4)、最后按照热度排序，显示前10条。

select 
    category_name as category, 
    count(t1.videoId) as hot 
from (
    select 
        videoId,
        category_name 
    from 
        chbvideo_orc lateral view explode(category) t_catetory as category_name) t1 
group by t1.category_name 
order by hot desc 
limit 10;

4.3、统计出视频观看数最高的20个视频的所属类别以及类别包含Top20视频的个数

思路：

• 1、 先找到观看数最高的20个视频所属条目的所有信息，降序排列
• 2、把这20条信息中的category分裂出来(列转行)
• 3、 最后查询视频分类名称和该分类下有多少个Top20的视频

select 
    category_name as category, 
    count(t2.videoId) as hot_with_views 
from (
    select 
        videoId, 
        category_name 
    from (
        select 
            * 
        from 
            chbvideo_orc 
        order by views desc 
        limit 20
    ) t1 lateral view explode(category) t_catetory as category_name) t2 
group by category_name 
order by hot_with_views desc;

4.4、统计视频观看数Top50所关联视频的所属类别Rank

思路

4.4.1、查询出观看数最多的前50个视频的所有信息(当然包含了每个视频对应的关联视频)，记为临时表t1

t1：观看数前50的视频

select 
    * 
from 
    chbvideo_orc 
order by views desc 
limit 50;

4.4.2、将找到的50条视频信息的相关视频relatedId列转行，记为临时表t2

t2：将相关视频的id进行列转行操作
select 
    explode(relatedId) as videoId 
from 
	t1;

4.4.3、将相关视频的id和chbvideo_orc表进行inner join操作

t5：得到两列数据，一列是category，一列是之前查询出来的相关视频id

 (select 
    distinct(t2.videoId), 
    t3.category 
from 
    t2
inner join 
    chbvideo_orc t3 on t2.videoId = t3.videoId) t4 lateral view explode(category) t_catetory as category_name;

4.4.4、按照视频类别进行分组，统计每组视频个数，然后排行

select 
    category_name as category, 
    count(t5.videoId) as hot 
from (
    select 
        videoId, 
        category_name 
    from (
        select 
            distinct(t2.videoId), 
            t3.category 
        from (
            select 
                explode(relatedId) as videoId 
            from (
                select 
                    * 
                from 
                    chbvideo_orc 
                order by views desc 
                limit 50
            ) t1
        ) t2 
        inner join 
            chbvideo_orc t3 on t2.videoId = t3.videoId) t4 lateral view explode(category) t_catetory as category_name) t5
group by category_name 
order by hot desc;

4.5、统计每个类别中的视频热度Top10，以Music为例 4.5.1、思路：

1. 要想统计Music类别中的视频热度Top10，需要先找到Music类别，那么就需要将category展开，所以可以创建一张表用于存放categoryId展开的数据。
2. 向category展开的表中插入数据。
3. 统计对应类别（Music）中的视频热度。

4.5.2、创建表类别表：

create table chbvideo_category(
    videoId string, 
    uploader string, 
    age int, 
    categoryId string, 
    length int, 
    views int, 
    rate float, 
    ratings int, 
    comments int, 
    relatedId array)
row format delimited 
fields terminated by "\t" 
collection items terminated by "&" 
stored as orc;

4.5.3、向类别表中插入数据：

insert into table chbvideo_category select videoId, uploader, age, categoryId, length, views, rate, ratings, comments, relatedId from chbvideo_orc lateral view explode(category) catetory as categoryId;

4.5.4、统计Music类别的Top10（也可以统计其他）

select 
    videoId, 
    views
from 
    chbvideo_category 
where 
    categoryId = "Music" 
order by views desc 
limit 10;

4.6、统计每个类别中视频流量Top10，以Music为例

思路：

• 1、创建视频类别展开表（categoryId列转行后的表）
• 2、按照ratings排序即可

select 
    videoId,
    views,
    ratings 
from 
    chbvideo_category 
where 
    categoryId = "Music" 
order by ratings desc 
limit 10;

4.7、统计上传视频最多的用户Top10以及他们上传的观看次数在前20的视频

思路：

4.7.1、先找到上传视频最多的10个用户的用户信息

select 
    * 
from 
    chbvideo_user_orc 
order by videos desc 
limit 10;

4.7.2、通过uploader字段与chbvideo_orc表进行join，得到的信息按照views观看次数进行排序即可。

select 
    t2.videoId, 
    t2.views,
    t2.ratings,
    t1.videos,
    t1.friends 
from (
    select 
        * 
    from 
        chbvideo_user_orc 
    order by videos desc 
    limit 10
) t1 
join 
    chbvideo_orc t2
on 
    t1.uploader = t2.uploader 
order by views desc 
limit 20;

4.8、统计每个类别视频观看数Top10

思路：

• 先得到categoryId展开的表数据
• 子查询按照categoryId进行分区，然后分区内排序，并生成递增数字，该递增数字这一列起名为rank列
• 通过子查询产生的临时表，查询rank值小于等于10的数据行即可。

select 
    t1.* 
from (
    select 
        videoId,
        categoryId,
        views,
        row_number() over(partition by categoryId order by views desc) rank from chbvideo_category) t1 
where 
    rank