基于Hadoop生态圈的数据仓库实践 —— 进阶技术（十）

用户1148526

发布于 2019-05-25 19:40:17

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发布于 2019-05-25 19:40:17

十、杂项维度 本节讨论杂项维度。简单地说，杂项维度就是一种包含的数据具有很少可能值的维度。例如销售订单，它可能有很多离散数据（yes-no这种类型的值），如

verification_ind（如果订单已经被审核，值为yes）
credit_check_flag（表示此订单的客户信用状态是否已经检查）
new_customer_ind（如果这是新客户的首个订单，值为yes）
web_order_flag（表示此订单是否是在线下的订单）

这类数据常被用于增强销售分析，其特点是属性可能很多但每种属性的可能值很少，适合用称为杂项维度的特殊维度类型存储。 1. 新增销售订单属性杂项维度 给现有的数据仓库新增一个销售订单杂项维度，需要新增一个名为sales_order_attribute_dim的维度表。下图显示了增加杂项维度表后的数据仓库模式（这里只显示了和销售订单属性相关的表）。

新的维度表包括四个yes-no列：verification_ind、credit_check_flag、new_customer_ind和web_order_flag。每个列可以有两个可能值中的一个（Y 或 N），因此sales_order_attribute_dim表最多有16（2^4）行。可以预装载这个维度，并且只需装载一次。注意，如果知道某种组合是不可能出现的，就不需要装载这种组合。执行下面的脚本修改数据库模式。这个脚本做了四项工作：建立sales_order_attribute_dim表，向表中预装载全部16种可能的数据，给销售订单事实表添加杂项维度代理键，给源数据库里的sales_order表增加对应的四个属性列。

USE dw;  
  
-- 建立杂项维度表  
CREATE TABLE sales_order_attribute_dim (  
    sales_order_attribute_sk INT COMMENT 'sales order attribute surrogate key',  
    verification_ind CHAR(1) COMMENT 'verification index, Y or N',  
    credit_check_flag CHAR(1) COMMENT 'credit check flag, Y or N',  
    new_customer_ind CHAR(1) COMMENT 'new customer index, Y or N',  
    web_order_flag CHAR(1) COMMENT 'web order flag, Y or N',  
    version int COMMENT 'version',  
    effective_date DATE COMMENT 'effective date',  
    expiry_date DATE COMMENT 'expiry date'
)
clustered by (sales_order_attribute_sk) into 8 buckets    
stored as orc tblproperties ('transactional'='true');  
  
-- 生成杂项维度数据  
INSERT INTO sales_order_attribute_dim VALUES (1, 'Y', 'N', 'N', 'N', 1,'1900-00-00', '2200-01-01');
INSERT INTO sales_order_attribute_dim VALUES (2, 'Y', 'Y', 'N', 'N', 1,'1900-00-00', '2200-01-01');  
INSERT INTO sales_order_attribute_dim VALUES (3, 'Y', 'Y', 'Y', 'N', 1,'1900-00-00', '2200-01-01');  
INSERT INTO sales_order_attribute_dim VALUES (4, 'Y', 'Y', 'Y', 'Y', 1,'1900-00-00', '2200-01-01');  
INSERT INTO sales_order_attribute_dim VALUES (5, 'Y', 'N', 'Y', 'N', 1,'1900-00-00', '2200-01-01');  
INSERT INTO sales_order_attribute_dim VALUES (6, 'Y', 'N', 'Y', 'Y', 1,'1900-00-00', '2200-01-01');  
INSERT INTO sales_order_attribute_dim VALUES (7, 'Y', 'N', 'N', 'Y', 1,'1900-00-00', '2200-01-01');  
INSERT INTO sales_order_attribute_dim VALUES (8, 'Y', 'Y', 'N', 'Y', 1,'1900-00-00', '2200-01-01');  
INSERT INTO sales_order_attribute_dim VALUES (9, 'N', 'N', 'N', 'N', 1,'1900-00-00', '2200-01-01');  
INSERT INTO sales_order_attribute_dim VALUES (10, 'N', 'Y', 'N', 'N', 1,'1900-00-00', '2200-01-01');  
INSERT INTO sales_order_attribute_dim VALUES (11, 'N', 'Y', 'Y', 'N', 1,'1900-00-00', '2200-01-01');  
INSERT INTO sales_order_attribute_dim VALUES (12, 'N', 'Y', 'Y', 'Y', 1,'1900-00-00', '2200-01-01');  
INSERT INTO sales_order_attribute_dim VALUES (13, 'N', 'N', 'Y', 'N', 1,'1900-00-00', '2200-01-01');  
INSERT INTO sales_order_attribute_dim VALUES (14, 'N', 'N', 'Y', 'Y', 1,'1900-00-00', '2200-01-01');  
INSERT INTO sales_order_attribute_dim VALUES (15, 'N', 'N', 'N', 'Y', 1,'1900-00-00', '2200-01-01');  
INSERT INTO sales_order_attribute_dim VALUES (16, 'N', 'Y', 'N', 'Y', 1,'1900-00-00', '2200-01-01');  

-- 建立杂项维度外键  
alter table sales_order_fact rename to sales_order_fact_old;
create table sales_order_fact(                                                
   order_number int COMMENT 'order number',                                     
   customer_sk int COMMENT 'customer surrogate key',                               
   product_sk int COMMENT 'product surrogate key', 
   sales_order_attribute_sk int COMMENT 'sales order attribute surrogate key',
   order_date_sk int COMMENT 'order date surrogate key',                           
   allocate_date_sk int COMMENT 'allocate date surrogate key',                     
   allocate_quantity int COMMENT 'allocate quantity',                              
   packing_date_sk int COMMENT 'packing date surrogate key',                       
   packing_quantity int COMMENT 'packing quantity',                                
   ship_date_sk int COMMENT 'ship date surrogate key',                             
   ship_quantity int COMMENT 'ship quantity',                                      
   receive_date_sk int COMMENT 'receive date surrogate key',                       
   receive_quantity int COMMENT 'receive quantity',                                
   request_delivery_date_sk int COMMENT 'request delivery date surrogate key',     
   order_amount decimal(10,2) COMMENT 'order amount',                              
   order_quantity int COMMENT 'order quantity')  
clustered by (order_number) into 8 buckets    
stored as orc tblproperties ('transactional'='true');
insert into table sales_order_fact
select order_number,
       customer_sk,
       product_sk,
       null,
       order_date_sk,
       allocate_date_sk,
       allocate_quantity,
       packing_date_sk,
       packing_quantity,
       ship_date_sk,
       ship_quantity,
       receive_date_sk,
       receive_quantity,
       request_delivery_date_sk,
       order_amount,
       order_quantity
  from sales_order_fact_old;
drop table sales_order_fact_old;

-- 给源库的销售订单表增加对应的属性  
USE source;   
ALTER TABLE sales_order  
  ADD verification_ind CHAR (1) AFTER product_code  
, ADD credit_check_flag CHAR (1) AFTER verification_ind  
, ADD new_customer_ind CHAR (1) AFTER credit_check_flag  
, ADD web_order_flag CHAR (1) AFTER new_customer_ind ;  

-- 给销售订单过渡表增加对应的属性 
USE rds;    
ALTER TABLE sales_order ADD COLUMNS 
(
verification_ind CHAR(1) COMMENT 'verification index, Y or N',  
credit_check_flag CHAR(1) COMMENT 'credit check flag, Y or N',  
new_customer_ind CHAR(1) COMMENT 'new customer index, Y or N',  
web_order_flag CHAR(1) COMMENT 'web order flag, Y or N'
) ;

2. 重建Sqoop作业

last_value=`sqoop job --show myjob_incremental_import --meta-connect jdbc:hsqldb:hsql://cdh2:16000/sqoop | grep incremental.last.value | awk '{print $3}'`  
sqoop job --delete myjob_incremental_import --meta-connect jdbc:hsqldb:hsql://cdh2:16000/sqoop    
sqoop job \
--meta-connect jdbc:hsqldb:hsql://cdh2:16000/sqoop \
--create myjob_incremental_import \
-- \
import \
--connect "jdbc:mysql://cdh1:3306/source?useSSL=false&user=root&password=mypassword" \
--table sales_order \
--columns "order_number, customer_number, product_code, status_date, entry_date, order_amount, quantity, request_delivery_date, order_status, verification_ind, credit_check_flag, new_customer_ind, web_order_flag" \
--hive-import \
--hive-table rds.sales_order \
--incremental append \
--check-column id \
--last-value $last_value

3. 修改定期装载脚本 由于有了一个新的维度，必须修改定期装载脚本。下面显示了修改后的regular_etl.sql脚本文件内容。

-- 设置变量以支持事务    
set hive.support.concurrency=true;    
set hive.exec.dynamic.partition.mode=nonstrict;    
set hive.txn.manager=org.apache.hadoop.hive.ql.lockmgr.DbTxnManager;    
set hive.compactor.initiator.on=true;    
set hive.compactor.worker.threads=1;    
    
USE dw;    
      
-- 设置SCD的生效时间和过期时间    
SET hivevar:cur_date = CURRENT_DATE();
SET hivevar:pre_date = DATE_ADD(${hivevar:cur_date},-1);    
SET hivevar:max_date = CAST('2200-01-01' AS DATE);    
      
-- 设置CDC的上限时间    
INSERT OVERWRITE TABLE rds.cdc_time SELECT last_load, ${hivevar:cur_date} FROM rds.cdc_time;    
    
-- 装载customer维度    
-- 设置已删除记录和地址相关列上SCD2的过期，用<=>运算符处理NULL值。    
UPDATE customer_dim     
   SET expiry_date = ${hivevar:pre_date}      
 WHERE customer_dim.customer_sk IN      
(SELECT a.customer_sk     
   FROM (SELECT customer_sk,    
                customer_number,    
                customer_street_address,    
                customer_zip_code,    
                customer_city,    
                customer_state,    
                shipping_address,    
                shipping_zip_code,    
                shipping_city,    
                shipping_state    
           FROM customer_dim WHERE expiry_date = ${hivevar:max_date}) a LEFT JOIN     
                rds.customer b ON a.customer_number = b.customer_number     
          WHERE b.customer_number IS NULL OR     
          (  !(a.customer_street_address <=> b.customer_street_address)    
          OR !(a.customer_zip_code <=> b.customer_zip_code)    
          OR !(a.customer_city <=> b.customer_city)    
          OR !(a.customer_state <=> b.customer_state)    
          OR !(a.shipping_address <=> b.shipping_address)    
          OR !(a.shipping_zip_code <=> b.shipping_zip_code)    
          OR !(a.shipping_city <=> b.shipping_city)    
          OR !(a.shipping_state <=> b.shipping_state)    
          ));     
    
-- 处理customer_street_addresses列上SCD2的新增行      
INSERT INTO customer_dim    
SELECT    
    ROW_NUMBER() OVER (ORDER BY t1.customer_number) + t2.sk_max,    
    t1.customer_number,    
    t1.customer_name,    
    t1.customer_street_address,    
    t1.customer_zip_code,    
    t1.customer_city,    
    t1.customer_state,    
    t1.shipping_address,    
    t1.shipping_zip_code,    
    t1.shipping_city,    
    t1.shipping_state,    
    t1.version,    
    t1.effective_date,    
    t1.expiry_date    
FROM      
(      
SELECT      
    t2.customer_number customer_number,    
    t2.customer_name customer_name,    
    t2.customer_street_address customer_street_address,    
    t2.customer_zip_code customer_zip_code,    
    t2.customer_city customer_city,    
    t2.customer_state customer_state,    
    t2.shipping_address shipping_address,    
    t2.shipping_zip_code shipping_zip_code,    
    t2.shipping_city shipping_city,    
    t2.shipping_state shipping_state,    
    t1.version + 1 version,    
    ${hivevar:pre_date} effective_date,      
    ${hivevar:max_date} expiry_date      
 FROM customer_dim t1     
INNER JOIN rds.customer t2      
   ON t1.customer_number = t2.customer_number       
  AND t1.expiry_date = ${hivevar:pre_date}      
 LEFT JOIN customer_dim t3     
   ON t1.customer_number = t3.customer_number     
  AND t3.expiry_date = ${hivevar:max_date}      
WHERE (!(t1.customer_street_address <=> t2.customer_street_address)    
   OR  !(t1.customer_zip_code <=> t2.customer_zip_code)    
   OR  !(t1.customer_city <=> t2.customer_city)    
   OR  !(t1.customer_state <=> t2.customer_state)    
   OR  !(t1.shipping_address <=> t2.shipping_address)    
   OR  !(t1.shipping_zip_code <=> t2.shipping_zip_code)    
   OR  !(t1.shipping_city <=> t2.shipping_city)    
   OR  !(t1.shipping_state <=> t2.shipping_state)    
   )    
  AND t3.customer_sk IS NULL) t1      
CROSS JOIN      
(SELECT COALESCE(MAX(customer_sk),0) sk_max FROM customer_dim) t2;    
    
-- 处理customer_name列上的SCD1    
-- 因为hive的update的set子句还不支持子查询，所以这里使用了一个临时表存储需要更新的记录，用先delete再insert代替update    
-- 因为SCD1本身就不保存历史数据，所以这里更新维度表里的所有customer_name改变的记录，而不是仅仅更新当前版本的记录    
DROP TABLE IF EXISTS tmp;    
CREATE TABLE tmp AS    
SELECT    
    a.customer_sk,    
    a.customer_number,    
    b.customer_name,    
    a.customer_street_address,    
    a.customer_zip_code,    
    a.customer_city,    
    a.customer_state,    
    a.shipping_address,    
    a.shipping_zip_code,    
    a.shipping_city,    
    a.shipping_state,    
    a.version,    
    a.effective_date,    
    a.expiry_date    
  FROM customer_dim a, rds.customer b      
 WHERE a.customer_number = b.customer_number AND !(a.customer_name <=> b.customer_name);      
DELETE FROM customer_dim WHERE customer_dim.customer_sk IN (SELECT customer_sk FROM tmp);      
INSERT INTO customer_dim SELECT * FROM tmp;    
    
-- 处理新增的customer记录     
INSERT INTO customer_dim    
SELECT    
    ROW_NUMBER() OVER (ORDER BY t1.customer_number) + t2.sk_max,    
    t1.customer_number,    
    t1.customer_name,    
    t1.customer_street_address,    
    t1.customer_zip_code,    
    t1.customer_city,    
    t1.customer_state,    
    t1.shipping_address,    
    t1.shipping_zip_code,    
    t1.shipping_city,    
    t1.shipping_state,    
    1,    
    ${hivevar:pre_date},    
    ${hivevar:max_date}    
FROM      
(      
SELECT t1.* FROM rds.customer t1 LEFT JOIN customer_dim t2 ON t1.customer_number = t2.customer_number      
 WHERE t2.customer_sk IS NULL) t1      
CROSS JOIN      
(SELECT COALESCE(MAX(customer_sk),0) sk_max FROM customer_dim) t2;    
    
-- 重载PA客户维度    
TRUNCATE TABLE pa_customer_dim;      
INSERT INTO pa_customer_dim      
SELECT      
  customer_sk      
, customer_number      
, customer_name      
, customer_street_address      
, customer_zip_code      
, customer_city      
, customer_state      
, shipping_address      
, shipping_zip_code      
, shipping_city      
, shipping_state      
, version      
, effective_date      
, expiry_date      
FROM customer_dim      
WHERE customer_state = 'PA' ;     
    
-- 装载product维度    
-- 设置已删除记录和product_name、product_category列上SCD2的过期    
UPDATE product_dim    
   SET expiry_date = ${hivevar:pre_date}      
 WHERE product_dim.product_sk IN      
(SELECT a.product_sk     
   FROM (SELECT product_sk,product_code,product_name,product_category     
           FROM product_dim WHERE expiry_date = ${hivevar:max_date}) a LEFT JOIN     
                rds.product b ON a.product_code = b.product_code     
          WHERE b.product_code IS NULL OR (a.product_name <> b.product_name OR a.product_category <> b.product_category));    
    
-- 处理product_name、product_category列上SCD2的新增行      
INSERT INTO product_dim    
SELECT    
    ROW_NUMBER() OVER (ORDER BY t1.product_code) + t2.sk_max,    
    t1.product_code,    
    t1.product_name,    
    t1.product_category,    
    t1.version,    
    t1.effective_date,    
    t1.expiry_date    
FROM      
(      
SELECT      
    t2.product_code product_code,    
    t2.product_name product_name,    
    t2.product_category product_category,        
    t1.version + 1 version,    
    ${hivevar:pre_date} effective_date,      
    ${hivevar:max_date} expiry_date      
 FROM product_dim t1     
INNER JOIN rds.product t2      
   ON t1.product_code = t2.product_code      
  AND t1.expiry_date = ${hivevar:pre_date}      
 LEFT JOIN product_dim t3     
   ON t1.product_code = t3.product_code     
  AND t3.expiry_date = ${hivevar:max_date}      
WHERE (t1.product_name <> t2.product_name OR t1.product_category <> t2.product_category) AND t3.product_sk IS NULL) t1      
CROSS JOIN      
(SELECT COALESCE(MAX(product_sk),0) sk_max FROM product_dim) t2;    
    
-- 处理新增的product记录    
INSERT INTO product_dim    
SELECT    
    ROW_NUMBER() OVER (ORDER BY t1.product_code) + t2.sk_max,    
    t1.product_code,    
    t1.product_name,    
    t1.product_category,    
    1,    
    ${hivevar:pre_date},    
    ${hivevar:max_date}    
FROM      
(      
SELECT t1.* FROM rds.product t1 LEFT JOIN product_dim t2 ON t1.product_code = t2.product_code      
 WHERE t2.product_sk IS NULL) t1      
CROSS JOIN      
(SELECT COALESCE(MAX(product_sk),0) sk_max FROM product_dim) t2;    
    
-- 装载销售订单事实表 
-- 前一天新增的销售订单   
INSERT INTO sales_order_fact    
SELECT    
    a.order_number,    
    customer_sk,    
    product_sk, 
    g.sales_order_attribute_sk,
    e.order_date_sk,
    null,
    null,
    null,
    null,
    null,
    null,
    null,
    null,
    f.request_delivery_date_sk,
    order_amount,    
    quantity    
  FROM    
    rds.sales_order a,     
    customer_dim c,    
    product_dim d,    
    order_date_dim e,  
    request_delivery_date_dim f, 
    sales_order_attribute_dim g,
    rds.cdc_time h
 WHERE 
    a.order_status = 'N'
AND a.customer_number = c.customer_number    
AND a.status_date >= c.effective_date    
AND a.status_date < c.expiry_date    
AND a.product_code = d.product_code    
AND a.status_date >= d.effective_date    
AND a.status_date < d.expiry_date    
AND to_date(a.status_date) = e.order_date   
AND to_date(a.request_delivery_date) = f.request_delivery_date
AND a.verification_ind = g.verification_ind  
AND a.credit_check_flag = g.credit_check_flag  
AND a.new_customer_ind = g.new_customer_ind  
AND a.web_order_flag = g.web_order_flag 
AND a.entry_date >= h.last_load AND a.entry_date < h.current_load ;    

-- 处理分配库房、打包、配送和收货四个状态
DROP TABLE IF EXISTS tmp;
CREATE TABLE tmp AS
select t0.order_number order_number,
       t0.customer_sk customer_sk,
       t0.product_sk product_sk,
       t0.sales_order_attribute_sk,
       t0.order_date_sk order_date_sk,
       t2.allocate_date_sk allocate_date_sk,
       t1.quantity allocate_quantity,
       t0.packing_date_sk packing_date_sk,
       t0.packing_quantity packing_quantity,
       t0.ship_date_sk ship_date_sk,
       t0.ship_quantity ship_quantity,
       t0.receive_date_sk receive_date_sk,
       t0.receive_quantity receive_quantity,
       t0.request_delivery_date_sk request_delivery_date_sk,
       t0.order_amount order_amount,
       t0.order_quantity order_quantity
  from sales_order_fact t0,
       rds.sales_order t1,
       allocate_date_dim t2,
       rds.cdc_time t4
 where t0.order_number = t1.order_number and t1.order_status = 'A' 
   and to_date(t1.status_date) = t2.allocate_date
   and t1.entry_date >= t4.last_load and t1.entry_date < t4.current_load;

DELETE FROM sales_order_fact WHERE sales_order_fact.order_number IN (SELECT order_number FROM tmp); 
INSERT INTO sales_order_fact SELECT * FROM tmp;

DROP TABLE IF EXISTS tmp;
CREATE TABLE tmp AS
select t0.order_number order_number,
       t0.customer_sk customer_sk,
       t0.product_sk product_sk,
       t0.sales_order_attribute_sk,
       t0.order_date_sk order_date_sk,
       t0.allocate_date_sk allocate_date_sk,
       t0.allocate_quantity allocate_quantity,
       t2.packing_date_sk packing_date_sk,
       t1.quantity packing_quantity,
       t0.ship_date_sk ship_date_sk,
       t0.ship_quantity ship_quantity,
       t0.receive_date_sk receive_date_sk,
       t0.receive_quantity receive_quantity,
       t0.request_delivery_date_sk request_delivery_date_sk,
       t0.order_amount order_amount,
       t0.order_quantity order_quantity
  from sales_order_fact t0,
       rds.sales_order t1,
       packing_date_dim t2,
       rds.cdc_time t4
 where t0.order_number = t1.order_number and t1.order_status = 'P' 
   and to_date(t1.status_date) = t2.packing_date
   and t1.entry_date >= t4.last_load and t1.entry_date < t4.current_load; 
   
DELETE FROM sales_order_fact WHERE sales_order_fact.order_number IN (SELECT order_number FROM tmp); 
INSERT INTO sales_order_fact SELECT * FROM tmp;

DROP TABLE IF EXISTS tmp;
CREATE TABLE tmp AS
select t0.order_number order_number,
       t0.customer_sk customer_sk,
       t0.product_sk product_sk,
       t0.sales_order_attribute_sk,
       t0.order_date_sk order_date_sk,
       t0.allocate_date_sk allocate_date_sk,
       t0.allocate_quantity allocate_quantity,
       t0.packing_date_sk packing_date_sk,
       t0.packing_quantity packing_quantity,
       t2.ship_date_sk ship_date_sk,
       t1.quantity ship_quantity,
       t0.receive_date_sk receive_date_sk,
       t0.receive_quantity receive_quantity,
       t0.request_delivery_date_sk request_delivery_date_sk,
       t0.order_amount order_amount,
       t0.order_quantity order_quantity
  from sales_order_fact t0,
       rds.sales_order t1,
       ship_date_dim t2,
       rds.cdc_time t4
 where t0.order_number = t1.order_number and t1.order_status = 'S' 
   and to_date(t1.status_date) = t2.ship_date
   and t1.entry_date >= t4.last_load and t1.entry_date < t4.current_load;
   
DELETE FROM sales_order_fact WHERE sales_order_fact.order_number IN (SELECT order_number FROM tmp); 
INSERT INTO sales_order_fact SELECT * FROM tmp;

DROP TABLE IF EXISTS tmp;
CREATE TABLE tmp AS
select t0.order_number order_number,
       t0.customer_sk customer_sk,
       t0.product_sk product_sk,
       t0.sales_order_attribute_sk,
       t0.order_date_sk order_date_sk,
       t0.allocate_date_sk allocate_date_sk,
       t0.allocate_quantity allocate_quantity,
       t0.packing_date_sk packing_date_sk,
       t0.packing_quantity packing_quantity,
       t0.ship_date_sk ship_date_sk,
       t0.ship_quantity ship_quantity,
       t2.receive_date_sk receive_date_sk,
       t1.quantity receive_quantity,
       t0.request_delivery_date_sk request_delivery_date_sk,
       t0.order_amount order_amount,
       t0.order_quantity order_quantity
  from sales_order_fact t0,
       rds.sales_order t1,
       receive_date_dim t2,
       rds.cdc_time t4
 where t0.order_number = t1.order_number and t1.order_status = 'R' 
   and to_date(t1.status_date) = t2.receive_date
   and t1.entry_date >= t4.last_load and t1.entry_date < t4.current_load;
   
DELETE FROM sales_order_fact WHERE sales_order_fact.order_number IN (SELECT order_number FROM tmp); 
INSERT INTO sales_order_fact SELECT * FROM tmp;

-- 更新时间戳表的last_load字段    
INSERT OVERWRITE TABLE rds.cdc_time SELECT current_load, current_load FROM rds.cdc_time;

4. 测试修改后的定期装载 （1）使用下面的脚本添加八个销售订单。

USE source;  
DROP TABLE IF EXISTS temp_sales_order_data;    
CREATE TABLE temp_sales_order_data AS SELECT * FROM sales_order WHERE 1=0; 

SET @start_date := unix_timestamp('2016-07-31');    
SET @end_date := unix_timestamp('2016-08-01');    

SET @order_date := from_unixtime(@start_date + rand() * (@end_date - @start_date));    
SET @amount := floor(1000 + rand() * 9000);   
SET @quantity := floor(10 + rand() * 90);      
INSERT INTO temp_sales_order_data VALUES (1, 133, 1, 1, 'Y', 'Y', 'N', 'Y', @order_date, 'N', '2016-08-05', @order_date, @amount, @quantity);  

SET @order_date := from_unixtime(@start_date + rand() * (@end_date - @start_date));    
SET @amount := floor(1000 + rand() * 9000);   
SET @quantity := floor(10 + rand() * 90);      
INSERT INTO temp_sales_order_data VALUES (2, 134, 2, 2, 'N', 'N', 'N', 'N', @order_date, 'N', '2016-08-05', @order_date, @amount, @quantity);  

SET @order_date := from_unixtime(@start_date + rand() * (@end_date - @start_date));    
SET @amount := floor(1000 + rand() * 9000);   
SET @quantity := floor(10 + rand() * 90);      
INSERT INTO temp_sales_order_data VALUES (3, 135, 3, 3, 'Y', 'Y', 'N', 'N', @order_date, 'N', '2016-08-05', @order_date, @amount, @quantity);  

SET @order_date := from_unixtime(@start_date + rand() * (@end_date - @start_date));    
SET @amount := floor(1000 + rand() * 9000);   
SET @quantity := floor(10 + rand() * 90);      
INSERT INTO temp_sales_order_data VALUES (4, 136, 4, 4, 'Y', 'N', 'N', 'N', @order_date, 'N', '2016-08-05', @order_date, @amount, @quantity); 

SET @order_date := from_unixtime(@start_date + rand() * (@end_date - @start_date));    
SET @amount := floor(1000 + rand() * 9000);   
SET @quantity := floor(10 + rand() * 90);      
INSERT INTO temp_sales_order_data VALUES (5, 137, 11, 1, 'N', 'Y', 'Y', 'Y', @order_date, 'N', '2016-08-05', @order_date, @amount, @quantity); 

SET @order_date := from_unixtime(@start_date + rand() * (@end_date - @start_date));    
SET @amount := floor(1000 + rand() * 9000);   
SET @quantity := floor(10 + rand() * 90);      
INSERT INTO temp_sales_order_data VALUES (6, 138, 12, 2, 'N', 'Y', 'Y', 'N', @order_date, 'N', '2016-08-05', @order_date, @amount, @quantity); 

SET @order_date := from_unixtime(@start_date + rand() * (@end_date - @start_date));    
SET @amount := floor(1000 + rand() * 9000);   
SET @quantity := floor(10 + rand() * 90);      
INSERT INTO temp_sales_order_data VALUES (7, 139, 13, 3, 'Y', 'Y', 'Y', 'N', @order_date, 'N', '2016-08-05', @order_date, @amount, @quantity); 

SET @order_date := from_unixtime(@start_date + rand() * (@end_date - @start_date));    
SET @amount := floor(1000 + rand() * 9000);   
SET @quantity := floor(10 + rand() * 90);      
INSERT INTO temp_sales_order_data VALUES (8, 140, 14, 4, 'Y', 'N', 'Y', 'N', @order_date, 'N', '2016-08-05', @order_date, @amount, @quantity); 

INSERT INTO sales_order          
select null,    
       @rn:=@rn+1,    
       customer_number,    
       product_code,
       verification_ind,
       credit_check_flag,
       new_customer_ind,
       web_order_flag,  
       status_date,    
       order_status,    
       request_delivery_date,    
       entry_date,    
       order_amount,    
       quantity    
  from temp_sales_order_data t1 ,(select @rn:=132) t2
 order by t1.status_date;  
  
COMMIT;

（2）执行定期装载

./regular_etl.sh

（3）验证结果可以使用下面的分析性查询确认装载正确。该查询分析出检查了信用状态的新用户有所占的比例。

USE dw;  
SELECT CONCAT(ROUND(checked / (checked + not_checked) * 100),' % ')  
  FROM (SELECT sum(case when credit_check_flag='Y' then 1 else 0 end) checked,
               sum(case when credit_check_flag='N' then 1 else 0 end) not_checked
          FROM sales_order_fact a, sales_order_attribute_dim b  
         WHERE new_customer_ind = 'Y'              
           AND a.sales_order_attribute_sk = b.sales_order_attribute_sk) t;

查询结果下图所示。