基于Hadoop生态圈的数据仓库实践 —— 进阶技术（五）

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USE dw;   
  
CREATE TABLE month_end_sales_order_fact (  
    order_month_sk INT COMMENT ‘order month surrogate key‘, 
    product_sk INT COMMENT ‘product surrogate key‘, 
    month_order_amount DECIMAL(10,2) COMMENT ‘month order amount‘, 
    month_order_quantity INT COMMENT ‘month order quantity‘
)
CLUSTERED BY (order_month_sk) INTO 8 BUCKETS      
STORED AS ORC TBLPROPERTIES (‘transactional‘=‘true‘);

-- 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;  

SET hivevar:pre_month_date = add_months(current_date,-1);  

delete from month_end_sales_order_fact 
 where month_end_sales_order_fact.order_month_sk in
 (select month_sk 
    from month_dim 
   where month = month(${hivevar:pre_month_date}) 
     and year = year(${hivevar:pre_month_date}));
 
insert into month_end_sales_order_fact
select b.month_sk, a.product_sk, sum(order_amount), sum(order_quantity)
  from sales_order_fact a,
       month_dim b,
       order_date_dim d  -- 视图
 where a.order_date_sk = d.order_date_sk
   and b.month = d.month
   and b.year = d.year
   and b.month = month(${hivevar:pre_month_date}) 
   and b.year = year(${hivevar:pre_month_date})
 group by b.month_sk, a.product_sk ;

<?xml version="1.0" encoding="UTF-8"?>
<workflow-app xmlns="uri:oozie:workflow:0.1" name="regular_etl">
    <start to="fork-node"/>
    <fork name="fork-node">
        <path start="sqoop-customer" />
        <path start="sqoop-product" />
        <path start="sqoop-sales_order" />
    </fork>

    <action name="sqoop-customer">
        <sqoop xmlns="uri:oozie:sqoop-action:0.2">
            <job-tracker>${jobTracker}</job-tracker>
            <name-node>${nameNode}</name-node>
            <arg>import</arg>
            <arg>--connect</arg>
            <arg>jdbc:mysql://cdh1:3306/source?useSSL=false</arg>
            <arg>--username</arg>
            <arg>root</arg>
            <arg>--password</arg>
            <arg>mypassword</arg>
            <arg>--table</arg>
            <arg>customer</arg>
            <arg>--hive-import</arg>
            <arg>--hive-table</arg>
            <arg>rds.customer</arg>
            <arg>--hive-overwrite</arg>            
            <file>/tmp/hive-site.xml#hive-site.xml</file>
            <archive>/tmp/mysql-connector-java-5.1.38-bin.jar#mysql-connector-java-5.1.38-bin.jar</archive>
        </sqoop>
        <ok to="joining"/>
        <error to="fail"/>
    </action>
	<action name="sqoop-product">
        <sqoop xmlns="uri:oozie:sqoop-action:0.2">
            <job-tracker>${jobTracker}</job-tracker>
            <name-node>${nameNode}</name-node>
            <arg>import</arg>
            <arg>--connect</arg>
            <arg>jdbc:mysql://cdh1:3306/source?useSSL=false</arg>
            <arg>--username</arg>
            <arg>root</arg>
            <arg>--password</arg>
            <arg>mypassword</arg>
            <arg>--table</arg>
            <arg>product</arg>
            <arg>--hive-import</arg>
            <arg>--hive-table</arg>
            <arg>rds.product</arg>
            <arg>--hive-overwrite</arg>            
            <file>/tmp/hive-site.xml#hive-site.xml</file>
            <archive>/tmp/mysql-connector-java-5.1.38-bin.jar#mysql-connector-java-5.1.38-bin.jar</archive>
        </sqoop>
        <ok to="joining"/>
        <error to="fail"/>
    </action>
    <action name="sqoop-sales_order">
        <sqoop xmlns="uri:oozie:sqoop-action:0.2">
            <job-tracker>${jobTracker}</job-tracker>
            <name-node>${nameNode}</name-node>
            <command>job --exec myjob_incremental_import --meta-connect jdbc:hsqldb:hsql://cdh2:16000/sqoop</command>
            <file>/tmp/hive-site.xml#hive-site.xml</file>
            <archive>/tmp/mysql-connector-java-5.1.38-bin.jar#mysql-connector-java-5.1.38-bin.jar</archive>
        </sqoop>
        <ok to="joining"/>
        <error to="fail"/>
    </action>

    <join name="joining" to="hive-node"/>

    <action name="hive-node">
        <hive xmlns="uri:oozie:hive-action:0.2">
            <job-tracker>${jobTracker}</job-tracker>
            <name-node>${nameNode}</name-node> 
            <job-xml>/tmp/hive-site.xml</job-xml>
            <script>/tmp/regular_etl.sql</script>
        </hive>
        <ok to="decision-node"/>
        <error to="fail"/>
    </action>

    <decision name="decision-node">
       <switch>
         <case to="month-sum">
             ${date eq 20}
         </case>
         <default to="end"/>
       </switch>
    </decision>

    <action name="month-sum">
        <hive xmlns="uri:oozie:hive-action:0.2">
            <job-tracker>${jobTracker}</job-tracker>
            <name-node>${nameNode}</name-node>
            <job-xml>/tmp/hive-site.xml</job-xml>
            <script>/tmp/month_sum.sql</script>
        </hive>
        <ok to="end"/>
        <error to="fail"/>
    </action>

    <kill name="fail">
        <message>Sqoop failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message>
    </kill>
    <end name="end"/>
</workflow-app>

<coordinator-app name="regular_etl-coord" frequency="${coord:days(1)}" start="${start}" end="${end}" timezone="${timezone}" xmlns="uri
:oozie:coordinator:0.1">
    <action>
        <workflow>
            <app-path>${workflowAppUri}</app-path>
            <configuration>
                <property>
                    <name>jobTracker</name>
                    <value>${jobTracker}</value>
                </property>
                <property>
                    <name>nameNode</name>
                    <value>${nameNode}</value>
                </property>
                <property>
                    <name>queueName</name>
                    <value>${queueName}</value>
                </property>
                <property>
                    <name>date</name>
                    <value>${date}</value>
                </property>
            </configuration>
        </workflow>
    </action>
</coordinator-app>

nameNode=hdfs://cdh2:8020
jobTracker=cdh2:8032
queueName=default
oozie.use.system.libpath=true
oozie.coord.application.path=${nameNode}/user/${user.name}
timezone=UTC
start=2016-07-20T01:30Z
end=2020-12-31T01:30Z
workflowAppUri=${nameNode}/user/${user.name}

hdfs dfs -put -f coordinator.xml /user/root/  
hdfs dfs -put -f /root/workflow.xml /user/root/  
hdfs dfs -put -f /etc/hive/conf.cloudera.hive/hive-site.xml /tmp/  
hdfs dfs -put -f /root/mysql-connector-java-5.1.38/mysql-connector-java-5.1.38-bin.jar /tmp/  
hdfs dfs -put -f /root/regular_etl.sql /tmp/
hdfs dfs -put -f /root/month_sum.sql /tmp/

oozie job -oozie http://cdh2:11000/oozie -config /root/job-coord.properties -run -D date=`date +"%d"`

select year,month from month_dim where month_sk=198;

-- MySQL
USE source;  
-- 修改销售订单事务表  
ALTER TABLE sales_order  
  CHANGE order_date status_date datetime  
, ADD order_status VARCHAR(1) AFTER status_date  
, CHANGE order_quantity quantity INT;  

-- 删除sales_order表的主键  
alter table sales_order change order_number order_number int not null;  
alter table sales_order drop primary key;  
 
-- 建立新的主键
alter table sales_order add id int unsigned not null auto_increment primary key comment ‘主键‘ first;
 
-- Hive
-- rds.sales_order并没有增加id列，原因有两个：
-- 1. 该列只作为增量检查列，不用存储
-- 2. 不用再重新导入所有数据
use rds;
alter table sales_order
change order_date status_date timestamp comment ‘status date‘;
alter table sales_order
change order_quantity quantity int comment ‘quantity‘;
alter table sales_order
add columns (order_status varchar(1) comment ‘order status‘);

USE dw;  
-- 事实表增加八列
alter table sales_order_fact rename to sales_order_fact_old;
create table sales_order_fact
(
  order_sk int comment ‘order surrogate key‘,
  customer_sk int comment ‘customer surrogate key‘, 
  product_sk int comment ‘product 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_sk) INTO 8 BUCKETS  
STORED AS ORC TBLPROPERTIES (‘transactional‘=‘true‘); 
insert into sales_order_fact 
select order_sk,
       customer_sk,
       product_sk,
       order_date_sk,
       null,
       null,
       null,
       null,
       null,
       null,
       null,
       null,
       request_delivery_date_sk,
       order_amount,
       order_quantity
  from sales_order_fact_old;
drop table sales_order_fact_old;
  
-- 建立四个日期维度视图  
CREATE VIEW allocate_date_dim (allocate_date_sk, allocate_date, month, month_name, quarter, year, promo_ind) 
AS 
SELECT date_sk,
       date,
       month,
       month_name,
       quarter,
       year,
       promo_ind
  FROM date_dim ;
  
CREATE VIEW packing_date_dim (packing_date_sk, packing_date, month, month_name, quarter, year, promo_ind) 
AS  
SELECT date_sk,
       date,
       month,
       month_name,
       quarter,
       year,
       promo_ind
  FROM date_dim ;
  
CREATE VIEW ship_date_dim (ship_date_sk, ship_date, month, month_name, quarter, year, promo_ind) 
AS  
SELECT date_sk,
       date,
       month,
       month_name,
       quarter,
       year,
       promo_ind
  FROM date_dim ;
  
CREATE VIEW receive_date_dim (receive_date_sk, receive_date, month, month_name, quarter, year, promo_ind) 
AS  
SELECT date_sk,
       date,
       month,
       month_name,
       quarter,
       year,
       promo_ind
  FROM date_dim ;

 

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" --hive-import --hive-table rds.sales_order --incremental append --check-column id --last-value $last_value

-- 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order维度，
-- 前一天新增的销售订单号   
INSERT INTO order_dim    
SELECT    
    ROW_NUMBER() OVER (ORDER BY t1.order_number) + t2.sk_max,    
    t1.order_number,    
    t1.version,    
    t1.effective_date,    
    t1.expiry_date    
  FROM    
(    
SELECT    
    order_number order_number,    
    1 version,    
    status_date effective_date,    
    ‘2200-01-01‘ expiry_date    
  FROM rds.sales_order, rds.cdc_time     
 WHERE order_status = ‘N‘ AND entry_date >= last_load AND entry_date < current_load ) t1    
CROSS JOIN      
(SELECT COALESCE(MAX(order_sk),0) sk_max FROM order_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    
    order_sk,    
    customer_sk,    
    product_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,    
    order_dim b,    
    customer_dim c,    
    product_dim d,    
    order_date_dim e,  
    request_delivery_date_dim f,  
    rds.cdc_time g    
 WHERE 
    a.order_status = ‘N‘
AND a.order_number = b.order_number    
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.entry_date >= g.last_load AND a.entry_date < g.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_sk order_sk,
       t0.customer_sk customer_sk,
       t0.product_sk product_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,
       order_dim t3,
       rds.cdc_time t4
 where t0.order_sk = t3.order_sk
   and t3.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_sk IN (SELECT order_sk FROM tmp); 
INSERT INTO sales_order_fact SELECT * FROM tmp;

DROP TABLE IF EXISTS tmp;
CREATE TABLE tmp AS
select t0.order_sk order_sk,
       t0.customer_sk customer_sk,
       t0.product_sk product_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,
       order_dim t3,
       rds.cdc_time t4
 where t0.order_sk = t3.order_sk
   and t3.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_sk IN (SELECT order_sk FROM tmp); 
INSERT INTO sales_order_fact SELECT * FROM tmp;

DROP TABLE IF EXISTS tmp;
CREATE TABLE tmp AS
select t0.order_sk order_sk,
       t0.customer_sk customer_sk,
       t0.product_sk product_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,
       order_dim t3,
       rds.cdc_time t4
 where t0.order_sk = t3.order_sk
   and t3.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_sk IN (SELECT order_sk FROM tmp); 
INSERT INTO sales_order_fact SELECT * FROM tmp;

DROP TABLE IF EXISTS tmp;
CREATE TABLE tmp AS
select t0.order_sk order_sk,
       t0.customer_sk customer_sk,
       t0.product_sk product_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,
       order_dim t3,
       rds.cdc_time t4
 where t0.order_sk = t3.order_sk
   and t3.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_sk IN (SELECT order_sk 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;

USE source;  
/***        
新增订单日期为2016年7月20日的2条订单。    
***/      
SET @start_date := unix_timestamp(‘2016-07-20‘);      
SET @end_date := unix_timestamp(‘2016-07-21‘);   
SET @request_delivery_date := ‘2016-07-25‘;     
DROP TABLE IF EXISTS temp_sales_order_data;      
CREATE TABLE temp_sales_order_data AS SELECT * FROM sales_order WHERE 1=0;       
      
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, 1, 1, 1, @order_date, ‘N‘, @request_delivery_date, @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, 2, 2, 2, @order_date, ‘N‘, @request_delivery_date, @order_date, @amount, @quantity);         

INSERT INTO sales_order      
select null,
       (@order_number:=@order_number + 1) + 128,
       customer_number,
       product_code,
       status_date,
       order_status,
       request_delivery_date,
       entry_date,
       order_amount,
       quantity
  from temp_sales_order_data t1,(select @order_number:=0) t2
 order by t1.status_date;        
    
COMMIT ;

use rds;
INSERT OVERWRITE TABLE rds.cdc_time SELECT ‘2016-07-20‘, ‘2016-07-21‘ FROM rds.cdc_time;

./regular_etl.sh

use dw;
select b.order_number,
       c.order_date,
       d.allocate_date,
       e.packing_date,
       f.ship_date,
       g.receive_date
  from sales_order_fact a
 inner join order_dim b on a.order_sk = b.order_sk
  left join order_date_dim c on a.order_date_sk = c.order_date_sk
  left join allocate_date_dim d on a.allocate_date_sk = d.allocate_date_sk
  left join packing_date_dim e on a.packing_date_sk = e.packing_date_sk
  left join ship_date_dim f on a.ship_date_sk = f.ship_date_sk
  left join receive_date_dim g on a.receive_date_sk = g.receive_date_sk
 where b.order_number IN (129 , 130);

USE source;  

SET @start_date := unix_timestamp(‘2016-07-21‘);      
SET @end_date := unix_timestamp(‘2016-07-22‘);   
SET @mid_date := unix_timestamp(‘2016-07-21 12:00:00‘);
SET @request_delivery_date := ‘2016-07-25‘;     
DROP TABLE IF EXISTS temp_sales_order_data;      
CREATE TABLE temp_sales_order_data AS SELECT * FROM sales_order WHERE 1=0;       
      
SET @order_date := from_unixtime(@start_date + rand() * (@mid_date - @start_date));   
select order_amount,quantity into @amount,@quantity from sales_order where order_number=129;
INSERT INTO temp_sales_order_data VALUES (1, 129, 1, 1, @order_date, ‘A‘, @request_delivery_date, @order_date, @amount, @quantity);      
      
SET @order_date := from_unixtime(@mid_date + rand() * (@end_date - @mid_date));      
INSERT INTO temp_sales_order_data VALUES (2, 129, 1, 1, @order_date, ‘P‘, @request_delivery_date, @order_date, @amount, @quantity);         

SET @order_date := from_unixtime(@start_date + rand() * (@end_date - @start_date));   
select order_amount,quantity into @amount,@quantity from sales_order where order_number=130;
INSERT INTO temp_sales_order_data VALUES (3, 130, 2, 2, @order_date, ‘A‘, @request_delivery_date, @order_date, @amount, @quantity);

INSERT INTO sales_order      
select null,
       order_number,
       customer_number,
       product_code,
       status_date,
       order_status,
       request_delivery_date,
       entry_date,
       order_amount,
       quantity
  from temp_sales_order_data
 order by entry_date;

COMMIT ;

use rds;
INSERT OVERWRITE TABLE rds.cdc_time SELECT ‘2016-07-21‘, ‘2016-07-22‘ FROM rds.cdc_time;

./regular_etl.sh

use dw;
select b.order_number,
       c.order_date,
       d.allocate_date,
       e.packing_date,
       f.ship_date,
       g.receive_date
  from sales_order_fact a
 inner join order_dim b on a.order_sk = b.order_sk
  left join order_date_dim c on a.order_date_sk = c.order_date_sk
  left join allocate_date_dim d on a.allocate_date_sk = d.allocate_date_sk
  left join packing_date_dim e on a.packing_date_sk = e.packing_date_sk
  left join ship_date_dim f on a.ship_date_sk = f.ship_date_sk
  left join receive_date_dim g on a.receive_date_sk = g.receive_date_sk
 where b.order_number IN (129 , 130);

USE source;  

SET @start_date := unix_timestamp(‘2016-07-22‘);      
SET @end_date := unix_timestamp(‘2016-07-23‘);   
SET @mid_date := unix_timestamp(‘2016-07-22 12:00:00‘);
SET @request_delivery_date := ‘2016-07-25‘;     
DROP TABLE IF EXISTS temp_sales_order_data;      
CREATE TABLE temp_sales_order_data AS SELECT * FROM sales_order WHERE 1=0;       
      
SET @order_date := from_unixtime(@start_date + rand() * (@mid_date - @start_date));   
select order_amount,quantity into @amount,@quantity from sales_order where order_number=129 limit 1;
INSERT INTO temp_sales_order_data VALUES (1, 129, 1, 1, @order_date, ‘S‘, @request_delivery_date, @order_date, @amount, @quantity);      
      
SET @order_date := from_unixtime(@mid_date + rand() * (@end_date - @mid_date));      
INSERT INTO temp_sales_order_data VALUES (2, 129, 1, 1, @order_date, ‘R‘, @request_delivery_date, @order_date, @amount, @quantity);         

SET @order_date := from_unixtime(@start_date + rand() * (@end_date - @start_date));   
select order_amount,quantity into @amount,@quantity from sales_order where order_number=130 limit 1;
INSERT INTO temp_sales_order_data VALUES (3, 130, 2, 2, @order_date, ‘P‘, @request_delivery_date, @order_date, @amount, @quantity);

INSERT INTO sales_order      
select null,
       order_number,
       customer_number,
       product_code,
       status_date,
       order_status,
       request_delivery_date,
       entry_date,
       order_amount,
       quantity
  from temp_sales_order_data
 order by entry_date;

COMMIT ;

use rds;
INSERT OVERWRITE TABLE rds.cdc_time SELECT ‘2016-07-22‘, ‘2016-07-23‘ FROM rds.cdc_time;

./regular_etl.sh

use dw;
select b.order_number,
       c.order_date,
       d.allocate_date,
       e.packing_date,
       f.ship_date,
       g.receive_date
  from sales_order_fact a
 inner join order_dim b on a.order_sk = b.order_sk
  left join order_date_dim c on a.order_date_sk = c.order_date_sk
  left join allocate_date_dim d on a.allocate_date_sk = d.allocate_date_sk
  left join packing_date_dim e on a.packing_date_sk = e.packing_date_sk
  left join ship_date_dim f on a.ship_date_sk = f.ship_date_sk
  left join receive_date_dim g on a.receive_date_sk = g.receive_date_sk
 where b.order_number IN (129 , 130);

基于Hadoop生态圈的数据仓库实践 —— 进阶技术（五）

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原文地址：http://blog.csdn.net/wzy0623/article/details/51992827