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
2、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;