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六、Hue数据可视化实例
图标进入“我的文档”页面。
创建一个名为“销售订单”的新项目。
进入Impala查询编辑页面，创建一个新的Impala文档。-- 按产品分类查询销售量和销售额
select t2.product_category pro_category,
sum(order_quantity) sum_quantity,
sum(order_amount) sum_amount
from sales_order_fact t1, product_dim t2
where t1.product_sk = t2.product_sk
group by pro_category
order by pro_category;
-- 按产品查询销售量和销售额
select t2.product_name pro_name,
sum(order_quantity) sum_quantity,
sum(order_amount) sum_amount
from sales_order_fact t1, product_dim t2
where t1.product_sk = t2.product_sk
group by pro_name
order by pro_name; 点击“执行”按钮，结果显示按产品分类的销售统计，如下图所示。接着点击“下一页”按钮，结果会显示按产品的销售统计。
产品统计结果如下图所示。
-- 按州查询销售量和销售额
select t3.state state,
count(distinct t2.customer_sk) sum_customer_num,
sum(order_amount) sum_order_amount
from sales_order_fact t1
inner join customer_dim t2 on t1.customer_sk = t2.customer_sk
inner join customer_zip_code_dim t3 on t1.customer_zip_code_sk = t3.zip_code_sk
group by state
order by state;
-- 按城市查询销售量和销售额
select t3.city city,
count(distinct t2.customer_sk) sum_customer_num,
sum(order_amount) sum_order_amount
from sales_order_fact t1
inner join customer_dim t2 on t1.customer_sk = t2.customer_sk
inner join customer_zip_code_dim t3 on t1.customer_zip_code_sk = t3.zip_code_sk
group by city
order by city; 城市统计饼图如下图所示。从图中可以看到，mechanicsburg市的销售占整个销售额的一半。
（8）再建立一个“按年月统计”的查询，这次使用动态表单功能，运行时输入年份。SQL语句如下。
-- 按年月查询销售量和销售额
select t4.year*100 + t4.month ym,
sum(order_quantity) sum_quantity,
sum(order_amount) sum_amount
from sales_order_fact t1
inner join order_date_dim t4 on t1.order_date_sk = t4.date_sk
where (t4.year*100 + t4.month) between $ym1 and $ym2
group by ym
order by ym; 注意$ym1和$ym2是动态参数，执行此查询，会出现输入框要求输入参数，如下图所示。
[librdbms]
[[databases]]
[[[mysql]]]
# Name to show in the UI.
nice_name="MySQL DB"
name=hive
engine=mysql
host=172.16.1.102
port=3306
user=root
password=mypassword 这里配置的是一个MySQL数据库，如下图所示。
此时再次在Hue里点击“Query Editors” -> “DB 查询”，则会出现MySQL中hive库表，此库存放的是Hive元数据。此时就可以输入SQL进行查询了，如下图所示。
基于hadoop生态圈的数据仓库实践 —— OLAP与数据可视化（六）
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原文地址：http://blog.csdn.net/wzy0623/article/details/52386016
