一.HIVE的基础知识

• Hive复合数据类型:map
  – 创建map:map、str_to_map
  – 取key、value:map_keys、map_values
  – 使用:map与lateral view
• Hive的窗口和分析函数入门
  – row_number、rank、dense_rank等对一窗口内给定列进行:取行号、排名
• 企业应用信息安全
  – Hive、Impala转换函数translate进行简单数据保护
• HiveServer2 JDBC接口实例应用、中文支持Bug纠错

一. 数据准备之数据库设计

原始三个表后面的表是衍生出来的

数据表设计.png

三, 数据表详细设计

• f_orders 的数据内容

    11  2014-05-01 06:01:12.334+01  10703007267488  item8:2|item1:1
    22  2014-05-01 07:28:12.342+01  10101043505096  item6:3|item3:2
    33  2014-05-01 07:50:12.33+01   10103043509747  item7:7
    11  2014-05-01 09:27:12.33+01   10103043501575  item5:5|item1:1|item4:1|item9:1
    22  2014-05-01 09:03:12.324+01  10104043514061  item1:3
    33  2014-05-02 19:10:12.343+01  11003002067594  item4:2|item1:1
    11  2014-05-02 09:07:12.344+01  10101043497459  item9:1
    35  2014-05-03 11:07:12.339+01  10203019269975  item5:1|item1:1
    789 2014-05-03 12:59:12.743+01  10401003346256  item7:3|item8:2|item9:1
    77  2014-05-03 18:04:12.355+01  10203019262235  item5:2|item1:1
    99  2014-05-04 00:36:39.713+01  10103044681799  item9:3|item1:1
    33  2014-05-04 19:10:12.343+01  12345678901234  item5:1|item1:1
    11  2014-05-05 09:07:12.344+01  12345678901235  item6:1|item1:1
    35  2014-05-05 11:07:12.339+01  12345678901236  item5:2|item1:1
    22  2014-05-05 12:59:12.743+01  12345678901237  item9:3|item1:1
    77  2014-05-05 18:04:12.355+01  12345678901238  item8:3|item1:1
    99  2014-05-05 20:36:39.713+01  12345678901239  item9:3|item1:1
  

• 创建f_orders的数据表

   CREATE EXTERNAL TABLE f_orders (
       user_id   STRING
     , ts        STRING
     , order_id  STRING
     , items     map<STRING,BIGINT>
   )
   ROW FORMAT DELIMITED
   FIELDS TERMINATED BY '\t'
   COLLECTION ITEMS TERMINATED BY '|'
   MAP KEYS TERMINATED BY ':'
  

• 将数组拆开查询

  select user_id, order_id, item, amount from f_orders LATERAL VIEW explode(items) t AS item, amount
  

• d_items的数据内容设计

    item1   100.2   catalogA|catalogD|catalogX
    item2   200.3   catalogA
    item3   300.4   catalogA|catalogX
    item4   400.5   catalogB
    item5   500.6   catalogB|catalogX
    item6   600.7   catalogB
    item7   700.8   catalogC
    item8   800.9   catalogC|catalogD
    item9   899.99  catalogC|catalogA
  

• d_item的数据表创建

    CREATE EXTERNAL TABLE d_items (
      item_sku  STRING,
      price     DOUBLE,
      catalogs  array<STRING>
    )
    ROW FORMAT DELIMITED
    FIELDS TERMINATED BY '\t'
    COLLECTION ITEMS TERMINATED BY '|'
  

• d_item的查询语句

    CREATE TABLE usr_cat AS
    select user_id, catalog, row_number() OVER (PARTITION BY user_id ORDER BY weight DESC) as row_num
    FROM usr_cat_weight order by user_id,row_num;
    FROM (  
    select orders.user_id, catalogs.catalog, sum(orders.amount) as weight
    from (
      select user_id, item, amount from f_orders LATERAL VIEW explode(items) t AS item, amount
    ) orders
    join (
      select item_sku, catalog from d_items LATERAL VIEW explode(catalogs) t AS catalog
    ) catalogs
    on (orders.item = catalogs.item_sku)
    group by orders.user_id, catalogs.catalog
    order by user_id, weight
    ) x
    ORDER BY user_id, row_num;
  

• d_user 表的数据

    11;m;1981-01-01;user11@gmail.com;2014-04-21
    22;w;1982-01-01;user22@abcn.net;2014-04-22
    33;m;1983-01-01;user33@fxlive.de;2014-04-23
    77;w;1977-01-01;user77@fxlive.fr;2014-05-01
    88;m;1988-01-01;user88@fxlive.eu;2014-05-02
    99;w;1999-01-01;user99@abcn.net;2014-05-03
  

• d_user的创建语句

    CREATE EXTERNAL TABLE d_users (
        user_id  STRING
      , gender   STRING
      , birthday STRING
      , email    STRING
      , regday   STRING
    )
    ROW FORMAT DELIMITED FIELDS TERMINATED BY '\073'
  

• 对隐秘字段信息进行加密

    select user_id, birthday, translate(birthday, '0123456789', '1234567890'), email, translate(email, 'userfxgmail1234567890', '1234567890userfxgmail') from d_users;
  
    CREATE TABLE user_segment AS
    select c.user_id, u.gender, u.age, c.catalogs
    from (
      select user_id, group_concat(catalog, '|') as catalogs from usr_cat where row_num < 3 group by user_id
    ) c
    left outer join (
      select user_id, gender, year(now()) - cast(substr(birthday, 1, 4) as int) as age from d_users
    ) u
    on (c.user_id = u.user_id)
    ;