Kylin入门案例

冷不防 2022-10-31 10:48 218阅读 0赞

### 目录 ###

*   *  测试数据表结构介绍
     *  导入测试数据
     *  Kylin方法步骤
     *  按照日期统计订单总额/总数量
     *   *  Kylin入门案例\_一张表
     *  按照订单渠道名称统计订单总额/总数量
     *   *  Kylin入门案例\_多张表
     *  按照日期、区域、产品维度统计订单总额/总数量
     *   *  Kylin入门案例\_一张事实表多张维度表

## 测试数据表结构介绍 ##

1、（事实表）dw\_sales

<table> 
 <thead> 
  <tr> 
   <th>列名</th> 
   <th>列类型</th> 
   <th>说明</th> 
  </tr> 
 </thead> 
 <tbody> 
  <tr> 
   <td>id</td> 
   <td>string</td> 
   <td>订单id</td> 
  </tr> 
  <tr> 
   <td>date1</td> 
   <td>string</td> 
   <td>订单日期</td> 
  </tr> 
  <tr> 
   <td>channelid</td> 
   <td>string</td> 
   <td>订单渠道（商场、京东、天猫）</td> 
  </tr> 
  <tr> 
   <td>productid</td> 
   <td>string</td> 
   <td>产品id</td> 
  </tr> 
  <tr> 
   <td>regionid</td> 
   <td>string</td> 
   <td>区域名称</td> 
  </tr> 
  <tr> 
   <td>amount</td> 
   <td>int</td> 
   <td>商品下单数量</td> 
  </tr> 
  <tr> 
   <td>price</td> 
   <td>double</td> 
   <td>商品金额</td> 
  </tr> 
 </tbody> 
</table>

2、（维度表\_渠道方式）dim\_channel

<table> 
 <thead> 
  <tr> 
   <th>列名</th> 
   <th>列类型</th> 
   <th>说明</th> 
  </tr> 
 </thead> 
 <tbody> 
  <tr> 
   <td>channelid</td> 
   <td>string</td> 
   <td>渠道id</td> 
  </tr> 
  <tr> 
   <td>channelname</td> 
   <td>string</td> 
   <td>渠道名称</td> 
  </tr> 
 </tbody> 
</table>

3、（维度表\_产品名称）dim\_product

<table> 
 <thead> 
  <tr> 
   <th>列名</th> 
   <th>列类型</th> 
   <th>说明</th> 
  </tr> 
 </thead> 
 <tbody> 
  <tr> 
   <td>productid</td> 
   <td>string</td> 
   <td>产品id</td> 
  </tr> 
  <tr> 
   <td>productname</td> 
   <td>string</td> 
   <td>产品名称</td> 
  </tr> 
 </tbody> 
</table>

4、（维度表\_区域）dim\_region

<table> 
 <thead> 
  <tr> 
   <th>列名</th> 
   <th>列类型</th> 
   <th>说明</th> 
  </tr> 
 </thead> 
 <tbody> 
  <tr> 
   <td>regionid</td> 
   <td>string</td> 
   <td>产品id</td> 
  </tr> 
  <tr> 
   <td>regionname</td> 
   <td>string</td> 
   <td>产品名称</td> 
  </tr> 
 </tbody> 
</table>

## 导入测试数据 ##

为了方便后续学习Kylin的使用，需要准备一些测试表、测试数据。  
dim\_channel\_data.txt

01,商场
    02,京东
    03,天猫

dim\_product\_data.txt

01,meta20
    02,p30
    03,ihpone Xs
    04,小米 9

dim\_region\_data.txt

010,北京
    021,上海

dw\_sales\_data.txt

0001,2019-02-01,01,01,010,1,3400.00
    0002,2019-02-01,02,02,021,2,6800.00
    0003,2019-02-01,01,01,010,1,3400.00
    0004,2019-02-01,01,02,021,1,3400.00
    0005,2019-02-01,02,01,010,1,3400.00
    0006,2019-02-01,01,01,021,2,6800.00
    0007,2019-02-01,03,02,010,1,3400.00
    0008,2019-02-01,01,01,021,1,3400.00
    0009,2019-02-01,01,03,010,1,3400.00
    0010,2019-02-01,02,01,021,3,10200.00
    0011,2019-02-01,01,04,010,1,3400.00
    0012,2019-02-01,03,01,021,1,3400.00
    0013,2019-02-01,01,04,010,1,3400.00
    0014,2019-02-02,01,01,010,1,3400.00
    0015,2019-02-02,02,02,021,2,6800.00
    0016,2019-02-02,01,01,010,1,3400.00
    0017,2019-02-02,01,02,021,1,3400.00
    0018,2019-02-02,02,01,010,1,3400.00
    0019,2019-02-02,01,01,021,2,6800.00
    0020,2019-02-02,03,02,010,1,3400.00
    0021,2019-02-02,01,01,021,1,3400.00
    0022,2019-02-02,01,03,010,1,3400.00
    0023,2019-02-02,02,01,021,3,10200.00
    0024,2019-02-02,01,04,010,1,3400.00
    0025,2019-02-02,03,01,021,1,3400.00
    0026,2019-02-02,01,04,010,1,3400.00
    0027,2019-02-02,01,04,010,1,3400.00

建表导入语句

-- 1、销售表：dw_sales
    -- id   唯一标识
    -- date1 日期
    -- channelId 渠道 ID
    -- productId 产品 ID
    -- regionId 区域 ID
    -- amount 数量
    -- price 金额
    create table dw_sales(id string,date1 string,channelId string, productId string, regionId string,amount int,price double)ROW FORMAT DELIMITED FIELDS TERMINATED BY ',' stored as textfile;
    
    -- 2、渠道表：dim_channel
    -- channelId 渠道ID
    -- channelName 渠道名称
    create table dim_channel(channelId string, channelName string )ROW FORMAT DELIMITED FIELDS TERMINATED BY ',' stored as textfile;
    
    -- 3、产品表：dim_product
    create table dim_product(productId string, productName string )ROW FORMAT DELIMITED FIELDS TERMINATED BY ',' stored as textfile;
    
    --4、区域表：dim_region
    create table dim_region(regionId string,regionName string)ROW FORMAT DELIMITED FIELDS TERMINATED BY ',' stored as textfile;
    
    -- 导入数据
    LOAD DATA LOCAL INPATH '/export/data/dw_sales_data.txt' OVERWRITE  INTO TABLE dw_sales;
    LOAD DATA LOCAL INPATH '/export/data/dim_channel_data.txt' OVERWRITE  INTO TABLE dim_channel;
    LOAD DATA LOCAL INPATH '/export/data/dim_product_data.txt' OVERWRITE  INTO TABLE dim_product;
    LOAD DATA LOCAL INPATH '/export/data/dim_region_data.txt' OVERWRITE  INTO TABLE dim_region;

## Kylin方法步骤 ##

要使用Kylin进行OLAP分析，需要按照以下方式来进行。

1、创建项目（Project）
    2、创建数据源（DataSource）
    - 指定有哪些数据需要进行数据分析
    3、创建模型（Model）
    - 指定具体要对哪个事实表、那些维度进行数据分析
    4、创建立方体（Cube）
    - 指定对哪个数据模型执行数据预处理，生成不同维度的数据
    5、执行构建、等待构建完成
    6、再执行SQL查询，获取结果
    - 从Cube中查询数据

## 按照日期统计订单总额/总数量 ##

select date1, sum(price) as total_money, sum(amount) as total_amount 
    from dw_sales group by date1;

### Kylin入门案例\_一张表 ###

创建项目（Project）  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ2NTQ4ODU1_size_16_color_FFFFFF_t_70]  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ2NTQ4ODU1_size_16_color_FFFFFF_t_70 1]  
**创建数据源（DataSource）**  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ2NTQ4ODU1_size_16_color_FFFFFF_t_70 2]  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ2NTQ4ODU1_size_16_color_FFFFFF_t_70 3]  
**创建模型（Model）**  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ2NTQ4ODU1_size_16_color_FFFFFF_t_70 4]  
指定模型名称  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ2NTQ4ODU1_size_16_color_FFFFFF_t_70 5]  
指定事实表  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ2NTQ4ODU1_size_16_color_FFFFFF_t_70 6]  
指定维度字段  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ2NTQ4ODU1_size_16_color_FFFFFF_t_70 7]  
指定待分析的指标  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ2NTQ4ODU1_size_16_color_FFFFFF_t_70 8]  
指定分区和过滤条件  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ2NTQ4ODU1_size_16_color_FFFFFF_t_70 9]  
**创建立方体（Cube）**  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ2NTQ4ODU1_size_16_color_FFFFFF_t_70 10]  
1、选择数据模型  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ2NTQ4ODU1_size_16_color_FFFFFF_t_70 11]

2、指定维度  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ2NTQ4ODU1_size_16_color_FFFFFF_t_70 12]

3、指定度量  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ2NTQ4ODU1_size_16_color_FFFFFF_t_70 13]  
4、指定刷新设置  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ2NTQ4ODU1_size_16_color_FFFFFF_t_70 14]  
5、指定执行引擎  
不选也可以，默认hive上的  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ2NTQ4ODU1_size_16_color_FFFFFF_t_70 15]  
**执行构建**  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ2NTQ4ODU1_size_16_color_FFFFFF_t_70 16]  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ2NTQ4ODU1_size_16_color_FFFFFF_t_70 17]  
数据存储在hbase  
![在这里插入图片描述][20210223171844184.png]  
**执行SQL语句分析**  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ2NTQ4ODU1_size_16_color_FFFFFF_t_70 18]

select
      date1,
      sum(price) as total_money,
      sum(amount) as total_amount
    from
      dw_sales
    group by date1;

在hive上执行花费40s  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ2NTQ4ODU1_size_16_color_FFFFFF_t_70 19]

## 按照订单渠道名称统计订单总额/总数量 ##

select
    	t2.channelid,
    	t2.channelname,
    	sum(t1.price) as total_money,
    	sum(t1.amount) as total_amount
    from 
    	dw_sales t1
    inner join dim_channel t2
    on t1.channelid = t2.channelid
    group by t2.channelid, t2.channelname

### Kylin入门案例\_多张表 ###

1、创建Model  
指定关联表、关联条件  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ2NTQ4ODU1_size_16_color_FFFFFF_t_70 20]  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ2NTQ4ODU1_size_16_color_FFFFFF_t_70 21]  
指定维度字段  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ2NTQ4ODU1_size_16_color_FFFFFF_t_70 22]  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ2NTQ4ODU1_size_16_color_FFFFFF_t_70 23]  
指定待分析的指标  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ2NTQ4ODU1_size_16_color_FFFFFF_t_70 24]  
2、创建Cube  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ2NTQ4ODU1_size_16_color_FFFFFF_t_70 25]  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ2NTQ4ODU1_size_16_color_FFFFFF_t_70 26]  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ2NTQ4ODU1_size_16_color_FFFFFF_t_70 27]

3、执行构建、等待构建完成  
4、执行SQL查询，获取结果  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ2NTQ4ODU1_size_16_color_FFFFFF_t_70 28]

## 按照日期、区域、产品维度统计订单总额/总数量 ##

select
    	t1.date1, 
    	t2.regionid, 
    	t2.regionname, 
    	t3.productid, 
    	t3.productname,
    	sum(t1.price) as total_money,
    	sum(t1.amount) as total_amount
    from
    	dw_sales t1
    inner join dim_region t2
    on t1.regionid = t2.regionid
    inner join dim_product t3
    on t1.productid = t3.productid
    group by 
    	t1.date1, 
    	t2.regionid, 
    	t2.regionname, 
    	t3.productid, 
    	t3.productname
    order by 
    	t1.date1,
    	t2.regionname,
    	t3.productname

### Kylin入门案例\_一张事实表多张维度表 ###

1、创建Model

*  指定关联表、关联条件  
    ![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ2NTQ4ODU1_size_16_color_FFFFFF_t_70 29][]  
    ![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ2NTQ4ODU1_size_16_color_FFFFFF_t_70 30]  
    ![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ2NTQ4ODU1_size_16_color_FFFFFF_t_70 31]  
    2、创建Cube  
    ![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ2NTQ4ODU1_size_16_color_FFFFFF_t_70 32]  
    ![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ2NTQ4ODU1_size_16_color_FFFFFF_t_70 33]  
    ![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ2NTQ4ODU1_size_16_color_FFFFFF_t_70 34]

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