Hive的ETL实战

需求：

对web点击流日志基础数据表进行etl（按照仓库模型设计）
按各时间维度统计来源域名top10

已有数据表 “t_orgin_weblog” ：

+------------------+------------+----------+--+

| col_name | data_type | comment |

+------------------+------------+----------+--+

| valid | string | |

| remote_addr | string | |

| remote_user | string | |

| time_local | string | |

| request | string | |

| status | string | |

| body_bytes_sent | string | |

| http_referer | string | |

| http_user_agent | string | |

+------------------+------------+----------+--+

数据示例：

| true|1.162.203.134| - | 18/Sep/2013:13:47:35| /images/my.jpg | 200| 19939 | "http://www.angularjs.cn/A0d9" | "Mozilla/5.0 (Windows |

| true|1.202.186.37 | - | 18/Sep/2013:15:39:11| /wp-content/uploads/2013/08/windjs.png| 200| 34613 | "http://cnodejs.org/topic/521a30d4bee8d3cb1272ac0f" | "Mozilla/5.0 (Macintosh;|

实现步骤：

1、对原始数据进行抽取转换

--将来访url分离出host path query query id

drop table if exists t_etl_referurl;

create table t_etl_referurl as

SELECT a.*,b.*

FROM t_orgin_weblog a LATERAL VIEW parse_url_tuple(regexp_replace(http_referer, "\"", ""), 'HOST', 'PATH','QUERY', 'QUERY:id') b as host, path, query, query_id

3、从前述步骤进一步分离出日期时间形成ETL明细表“t_etl_detail” day tm

drop table if exists t_etl_detail;

create table t_etl_detail as

select b.*,substring(time_local,0,11) as daystr,

substring(time_local,13) as tmstr,

substring(time_local,4,3) as month,

substring(time_local,0,2) as day,

substring(time_local,13,2) as hour

from t_etl_referurl b;

3、对etl数据进行分区(包含所有数据的结构化信息)

drop table t_etl_detail_prt;

create table t_etl_detail_prt(

valid string,

remote_addr string,

remote_user string,

time_local string,

request string,

status string,

body_bytes_sent string,

http_referer string,

http_user_agent string,

host string,

path string,

query string,

query_id string,

daystr string,

tmstr string,

month string,

day string,

hour string)

partitioned by (mm string,dd string);

导入数据

insert into table t_etl_detail_prt partition(mm='Sep',dd='18')

select * from t_etl_detail where daystr='18/Sep/2013';

insert into table t_etl_detail_prt partition(mm='Sep',dd='19')

select * from t_etl_detail where daystr='19/Sep/2013';

分个时间维度统计各referer_host的访问次数并排序

create table t_refer_host_visit_top_tmp as

select referer_host,count(*) as counts,mm,dd,hh from t_display_referer_counts group by hh,dd,mm,referer_host order by hh asc,dd asc,mm asc,counts desc;

4、来源访问次数topn各时间维度URL

取各时间维度的referer_host访问次数topn

select * from (select referer_host,counts,concat(hh,dd),row_number() over (partition by concat(hh,dd) order by concat(hh,dd) asc) as od from t_refer_host_visit_top_tmp) t where od<=3;