电商数据仓库

天才的白鸟2024-07-05 14:47

1.数据仓库的数据来源为业务数据库（mysql）

2.通过sqoop将mysql中的业务数据导入到大数据平台（hive）

3.通过hive进行数据计算和数据分析 形成数据报表

4.再通过sqoop将数据报表导出到mysql

5.使用FineReport制作数据报表

1.数据仓库的数据来源为业务数据库（mysql）

-- 测试sqoop是否能够连接mysql

sqoop list-databases --connect jdbc:mysql://bigdata004:3306/ --username root --password root123
初始化脚本

init_mysql.sql 在navicat中新建查询 ，运行

sql 复制代码 
-- 设置sql_mode
set sql_mode = 'NO_ENGINE_SUBSTITUTION,STRICT_TRANS_TABLES';

-- 创建数据库mall
create database mall;

-- 切换数据库
use mall;

-- 创建用户信息表
CREATE TABLE t_user_info(
	user_id        varchar(100) not null,
	user_name      varchar(100) not null,
	sex            varchar(10)  not null,
	age            int not null,
	country_code   varchar(100) not null,
	province_code  varchar(100) not null,
	city_code      varchar(100) not null
)DEFAULT CHARSET='utf8';

-- 创建订单表
CREATE TABLE t_sale_order(
	sale_id        varchar(100) not null,
	user_id        varchar(100) not null,
	goods_id       varchar(100) not null,
	price          int not null,
	sale_count     int not null,
	total_price    int not null,
	create_time    varchar(100) not null
)DEFAULT CHARSET='utf8';

-- 创建商品信息表
CREATE TABLE dim_goods_info(
	goods_id   varchar(100) not null,
	goods_name varchar(100) not null
)DEFAULT CHARSET='utf8';

-- 创建国家信息表
CREATE TABLE dim_country_info(
	country_code   varchar(100) not null,
	country_name   varchar(100) not null
)DEFAULT CHARSET='utf8';

-- 创建省份信息表
CREATE TABLE dim_province_info(
	province_code   varchar(100) not null,
	province_name   varchar(100) not null,
	country_code    varchar(100) not null
)DEFAULT CHARSET='utf8';

-- 创建城市信息表
CREATE TABLE dim_city_info(
	city_code     varchar(100) not null,
	city_name     varchar(100) not null,
	province_code varchar(100) not null
)DEFAULT CHARSET='utf8';

-- 创建用户浏览日志表
CREATE TABLE t_access_log(
	log_str varchar(500) not null
)DEFAULT CHARSET='utf8';


-- 创建商品类别表
CREATE TABLE dim_goods_type(
	goods_id   varchar(100) not null,
	type_id    varchar(100) not null,
	type_name  varchar(100) not null
)DEFAULT CHARSET='utf8';


-- 用户信息表插入数据
insert into t_user_info values('c001','王小名','男',22,'86','32','320100');
insert into t_user_info values('c002','李虎','男',40,'86','32','320200');
insert into t_user_info values('c003','韩静','女',26,'86','32','320600');
insert into t_user_info values('c004','董冬','男',35,'86','32','321100');
insert into t_user_info values('c005','张茗','男',21,'86','32','321200');
insert into t_user_info values('c006','张一凡','男',56,'86','32','321300');
insert into t_user_info values('c007','王花','女',20,'86','32','320100');
insert into t_user_info values('c008','刘梦','女',31,'86','32','320600');
insert into t_user_info values('u001','peter','男',30,'1','12','2233');
insert into t_user_info values('u002','rose','女',22,'1','08','2345');
insert into t_user_info values('u003','jack','男',26,'1','02','3663');
insert into t_user_info values('u004','marel','男',31,'1','11','4567');
commit;

-- 订单表插入数据
insert into t_sale_order values('s001','c002','g005',1099,1,1099,'2022-11-08 09:23:54');
insert into t_sale_order values('s002','c002','g001',3000,2,6000,'2022-11-08 10:12:36');
insert into t_sale_order values('s003','c004','g006',2899,1,2899,'2022-11-08 09:23:54');
insert into t_sale_order values('s004','u001','g001',3000,1,3000,'2022-11-08 08:01:21');
insert into t_sale_order values('s005','u002','g002',100,3,300,'2022-11-08 13:40:00');
insert into t_sale_order values('s006','c006','g009',299,1,299,'2022-11-08 08:11:20');
insert into t_sale_order values('s007','u003','g005',1099,1,1099,'2022-11-08 15:01:33');
insert into t_sale_order values('s008','c006','g004',3000,1,3000,'2022-11-08 17:08:01');
insert into t_sale_order values('s009','c005','g008',10,8,80,'2022-11-08 12:08:23');
insert into t_sale_order values('s010','c006','g002',100,1,100,'2022-11-08 22:23:14');
insert into t_sale_order values('s011','c006','g007',99,10,999,'2022-11-08 23:07:42');
insert into t_sale_order values('s012','c007','g007',99,1,99,'2022-11-08 06:51:03');
commit;

-- 商品信息表插入数据
insert into dim_goods_info values('g001','OPPO K9x 5G全网通手机');
insert into dim_goods_info values('g002','儿童历史地理大百科全书 绘本礼盒典藏全40册');
insert into dim_goods_info values('g003','欧珀莱 AUPRES 时光锁小紫钻抗皱紧实眼霜');
insert into dim_goods_info values('g004','苏泊尔(SUPOR)净水器家用超滤软水机');
insert into dim_goods_info values('g005','小米粽 平板电脑');
insert into dim_goods_info values('g006','GoPro HERO11 Black运动相机');
insert into dim_goods_info values('g007','云南实建褚橙冰糖橙');
insert into dim_goods_info values('g008','四色蓝泡泡洁厕');
insert into dim_goods_info values('g009','奥康男鞋');
commit;

-- 国家信息表插入数据
insert into dim_country_info values('1','美国');
insert into dim_country_info values('65','新加坡');
insert into dim_country_info values('81','日本');
insert into dim_country_info values('61','澳大利亚');
insert into dim_country_info values('54','阿根廷');
insert into dim_country_info values('55','巴西');
insert into dim_country_info values('45','丹麦');
insert into dim_country_info values('86','中国');
commit;

-- 省份信息表插入数据
insert into dim_province_info values('11','北京市','86');
insert into dim_province_info values('12','天津市','86');
insert into dim_province_info values('31','上海市','86');
insert into dim_province_info values('50','重庆市','86');
insert into dim_province_info values('13','河北省','86');
insert into dim_province_info values('41','河南省','86');
insert into dim_province_info values('53','云南省','86');
insert into dim_province_info values('21','辽宁省','86');
insert into dim_province_info values('23','湖南省','86');
insert into dim_province_info values('43','黑龙江省','86');
insert into dim_province_info values('34','安徽省','86');
insert into dim_province_info values('37','山东省','86');
insert into dim_province_info values('65','新疆维吾尔自治区','86');
insert into dim_province_info values('32','江苏省','86');
insert into dim_province_info values('33','浙江省','86');
insert into dim_province_info values('36','江西省','86');
commit;

-- 城市信息表插入数据
insert into dim_city_info values('320100','南京市','32');
insert into dim_city_info values('320200','无锡市','32');
insert into dim_city_info values('320300','徐州市','32');
insert into dim_city_info values('320400','常州市','32');
insert into dim_city_info values('320500','苏州市','32');
insert into dim_city_info values('320600','南通市','32');
insert into dim_city_info values('320700','连云港市','32');
insert into dim_city_info values('320800','淮安市','32');
insert into dim_city_info values('320900','盐城市','32');
insert into dim_city_info values('321000','扬州市','32');
insert into dim_city_info values('321100','镇江市','32');
insert into dim_city_info values('321200','泰州市','32');
insert into dim_city_info values('321300','宿迁市','32');
commit;

-- 用户浏览日志表插入数据
insert into t_access_log values('{"user_id": "c001","productId": "g002","productName": "儿童历史地理大百科全书 绘本礼盒典藏全40册","viewTimestamp": "2022-11-07 13:42:38"}');

insert into t_access_log values('{"user_id": "c006","productId": "g007","productName": "云南实建褚橙冰糖橙","viewTimestamp": "2022-11-09 01:02:18"}');

insert into t_access_log values('{"user_id": "c002","productId": "g001","productName": "OPPO K9x 5G全网通手机","viewTimestamp": "2022-11-07 11:02:28"}');

insert into t_access_log values('{"user_id": "c006","productId": "g001","productName": "OPPO K9x 5G全网通手机","viewTimestamp": "2022-11-09 13:01:05"}');

insert into t_access_log values('{"user_id": "c008","productId": "g005","productName": "小米粽 平板电脑","viewTimestamp": "2022-11-09 01:02:18"}');

insert into t_access_log values('{"user_id": "c006","productId": "g007","productName": "云南实建褚橙冰糖橙","viewTimestamp": "2022-11-09 01:02:18"}');

insert into t_access_log values('{"user_id": "u001","productId": "g001","productName": "OPPO K9x 5G全网通手机","viewTimestamp": "2022-11-08 08:45:00"}');

insert into t_access_log values('{"user_id": "u003","productId": "g005","productName": "小米粽 平板电脑","viewTimestamp": "2022-11-09 01:02:18"}');

insert into t_access_log values('{"user_id": "u001","productId": "g006","productName": "GoPro HERO11 Black运动相机","viewTimestamp": "2022-11-07 09:06:27"}');

insert into t_access_log values('{"user_id": "u001","productId": "g002","productName": "儿童历史地理大百科全书 绘本礼盒典藏全40册","viewTimestamp": "2022-11-09 08:02:29"}');

commit;


-- 商品类别表插入数据
insert into dim_goods_type values('g001','1','3C产品');
insert into dim_goods_type values('g002','2','书籍');
insert into dim_goods_type values('g003','3','日用品');
insert into dim_goods_type values('g004','4','家电');
insert into dim_goods_type values('g005','1','3C产品');
insert into dim_goods_type values('g006','1','3C产品');
insert into dim_goods_type values('g007','5','水果');
insert into dim_goods_type values('g008','3','日用品');
insert into dim_goods_type values('g009','6','鞋帽');
commit;

init_result.sql

sql 复制代码 
-- 设置sql_mode
set sql_mode = 'NO_ENGINE_SUBSTITUTION,STRICT_TRANS_TABLES';

-- 创建数据库result,并进行切换
create database result;

use result;

-- 创建城市订单总额表
CREATE TABLE t_city_sale_total(
	city_name         varchar(100) not null,
	city_total_price  int not null
)DEFAULT CHARSET='utf8';


-- 创建商品类别浏览量表
CREATE TABLE t_goods_type_view_count(
	goods_type        varchar(100) not null,
	view_count        int not null
)DEFAULT CHARSET='utf8';

数据库搭建完成

2.通过sqoop将mysql中的业务数据导入到大数据平台（hive）

在hive中建立映射的数据库

init_hive.sql 在beeline中运行

表的格式和mysql中的一一对应

sql 复制代码 
--创建数据库mall_bigdata
create database if not exists mall_bigdata;

--切换数据库至mall_bigdata
use mall_bigdata;

--创建用户信息表
create table if not exists mall_bigdata.ods_user_info
(
	 user_id       STRING    comment "用户id"
	,user_name     STRING    comment "用户姓名"
	,sex           STRING    comment "性别"
	,age           INT       comment "年龄"
	,country_code  STRING    comment "国家码"
    ,province_code STRING    comment "省份码"
	,city_code     STRING    comment "城市码"
)
comment "用户信息表"
row format delimited fields terminated by ","
stored as textfile;

--创建订单表
create table if not exists mall_bigdata.ods_sale_order
(
	 sale_id       STRING    comment "订单id"
	,user_id       STRING    comment "用户id"
	,goods_id      STRING    comment "商品id"
	,price         INT       comment "单价"
	,sale_count    INT       comment "购买数量"
    ,total_price   INT       comment "购买总金额"
	,create_time   STRING    comment "订单生成时间"
)
comment "销售订单表"
row format delimited fields terminated by ","
stored as textfile;

--创建商品信息表
create table if not exists mall_bigdata.dim_goods_info
(
	 goods_id       STRING    comment "商品id"
	,goods_name     STRING    comment "商品名称"
)
comment "商品信息表"
row format delimited fields terminated by ","
stored as textfile;


--创建国家信息表
create table if not exists mall_bigdata.dim_country_info
(
	 country_code       STRING    comment "国家码"
	,country_name       STRING    comment "国家名称"
)
comment "国家信息表"
row format delimited fields terminated by ","
stored as textfile;


--创建省份信息表
create table if not exists mall_bigdata.dim_province_info
(
	 province_code       STRING    comment "省份码"
	,province_name       STRING    comment "省份名称"
	,country_code        STRING    comment "国家码"
)
comment "省份信息表"
row format delimited fields terminated by ","
stored as textfile;


--创建城市信息表
create table if not exists mall_bigdata.dim_city_info
(
	 city_code       STRING    comment "城市码"
	,city_name       STRING    comment "城市名称"
	,province_code   STRING    comment "省份码"
)
comment "城市信息表"
row format delimited fields terminated by ","
stored as textfile;

--创建用户浏览日志表
create table if not exists mall_bigdata.ods_access_log
(
	 log_str       STRING    comment "浏览日志"
)
comment "用户浏览日志表"
row format delimited fields terminated by "|"
stored as textfile;


--创建商品类别表
create table if not exists mall_bigdata.dim_goods_type
(
	 goods_id      STRING    comment "商品id"
	,type_id       STRING    comment "商品类别id"
	,type_name     STRING    comment "商品类别名称"
)
comment "商品类别表"
row format delimited fields terminated by ","
stored as textfile;
导入数据

表的映射关系

|-------------------|-------------------|
| hive | mysql |
| ods_user_info | t_user_info |
| ods_sale_order | t_sale_order |
| dim_goods_info | dim_goods_info |
| dim_country_info | dim_country_info |
| dim_province_info | dim_province_info |
| dim_city_info | dim_city_info |
| ods_access_log | t_access_log |
| dim_goods_type | dim_goods_type |

sqoop import \

虚拟机 端口号 mysql中的数据库名

--connect jdbc:mysql://bigdata004:3306/mall \

--username root \

--password root123 \

mysql中的表名

--table t_user_info \

--num-mappers 1 \

--hive-import \

--fields-terminated-by "," \

--hive-overwrite \

hive中的表名

--hive-table mall_bigdata.ods_user_info

sql 复制代码 
sqoop import \

--connect jdbc:mysql://bigdata004:3306/mall \

--username root \

--password root123 \

--table t_user_info \

--num-mappers 1 \

--hive-import \

--fields-terminated-by "," \

--hive-overwrite \

--hive-table mall_bigdata.ods_user_info

直接在虚拟机运行，每次改变两个表，将所有数据导入到hive中

3.通过hive进行数据计算和数据分析 形成数据报表

用户信息表

sql 复制代码 
 user_id       STRING    comment "用户id"
	,user_name     STRING    comment "用户姓名"
	,sex           STRING    comment "性别"
	,age           INT       comment "年龄"
	,country_code  STRING    comment "国家码"
    ,province_code STRING    comment "省份码"
	,city_code     STRING    comment "城市码"
补全用户信息表中的关于用户的所在国家名称,所在省份名称,所在城市名称
sql 复制代码 
--切换数据库
use mall_bigdata;


--补全用户信息表中的关于用户的所在国家名称,所在省份名称,所在城市名称
create table if not exists mall_bigdata.tmp_dwd_user_info
as
	select
		user_id,
		user_name,
		sex,
		age,
		country_name,
		province_name,
		city_name
		
		
	from
	
	 (select
		user_id,
		user_name,
		sex,
		age,
		country_code,
		province_code,
		city_code
	from mall_bigdata.ods_user_info) t1
	left join
	(
		select 
			country_code,
			country_name
		from dim_country_info
	) t2
	on t1.country_code = t2.country_code
	left join
	(
		select
			province_code,
			province_name,
			country_code
		from dim_province_info
	) t3i
	on t1.province_code=t3.province_code and t1.country_code= t3.country_code
	left join
	(
		select
		 city_code,
		 city_name,
		 province_code
	    from dim_city_info
	) t4
	on t1.city_code=t4.city_code and t1.province_code=t4.province_code;
补全订单表中的用户名称和商品名称

过滤中国用户的订单记录

sql 复制代码 
--补全订单表中的用户名称和商品名称
--过滤中国用户的订单记录

--切换数据库
use mall_bigdata;

create table if not exists mall_bigdata.dwd_sale_order_detail
as 
	select 
		sale_id,
		t1.user_id,
		user_name,
		sex,
		age,
		country_name,
		province_name,
		city_name,
		t1.goods_id,
		goods_name,
		price,sale_count,
		total_price,
		create_time
	from
	 (
	 select
	 sale_id,
	 user_id,
	 goods_id,
	 price,
	 sale_count,
	 total_price,
	 create_time
	 from  ods_sale_order
	 ) t1
	 left join
	 (
		select 
		user_id,
		user_name,
		sex,
		age,
		country_name,
		province_name,
		city_name
		from tmp_dwd_user_info
	 ) t2
	 on t1.user_id=t2.user_id
	 left join
	 (
		select
			goods_id,
			goods_name
		
		from dim_goods_info
	 ) t3
	 on t1.goods_id = t3.goods_id
	 where country_name='中国';
计算不同城市的销售总额
sql 复制代码 
--切换数据库
use mall_bigdata;

--计算不同城市的销售总额

create table if not exists mall_bigdata.dws_sale_order_city_total
as
	select
		city_name,
		sum(total_price) as total_price
	from dwd_sale_order_detail
	group by city_name;
提取用户浏览日志表中的商品信息 补全商品的类型

再根据商品类型的不同 计算用户对于不同商品类型的浏览次数

sql 复制代码 
--切换数据库
use mall_bigdata;

--提取用户浏览日志表中的商品信息 补全商品的类型
--再根据商品类型的不同 计算用户对于不同商品类型的浏览次数

create table if not exists mall_bigdata.dws_view_goods_type_count
as
	select
		type_name,
		count(type_name) as view_goods_type_count
	from
	(
	 select
		get_json_object(log_str,'$.productId') as product_id
	 from mall_bigdata.ods_access_log
	) t1
	inner join
	(
	 select
	 goods_id,
	 typr_name
	 from dim_goods_type
	) t2
	on t1.product_id = t2.goods_id
	group by type_name;
相关推荐
字节数据平台10 小时前
基于OLAP湖仓一体架构，火山引擎ByteHouse助力企业降本提效
数据仓库·火山引擎
isNotNullX11 小时前
数据仓库还是数据集市？这俩怎么选？
大数据·数据仓库·分布式·etl
hamish-wu14 小时前
Dolphinscheduler配置dataX离线采集任务写入hive实践（二）
数据仓库·hive·hadoop
朽木自雕，格物致知！19 小时前
hive分区表
数据仓库·hive·hadoop
isNotNullX19 小时前
数据网格能替代数据仓库吗？
大数据·数据库·数据仓库·etl·数据同步·数据网格
hamish-wu20 小时前
dolphin 配置data 从文件导入hive 实践（一）
数据仓库·hive·hadoop
Yz987620 小时前
Hive的远程模式
大数据·linux·数据仓库·hive·hadoop·分布式·big data
isNotNullX1 天前
数据集市是什么？有什么优势？
大数据·数据库·数据仓库·etl
duration～1 天前
ServletContext介绍
数据仓库·hive·hadoop
宝哥大数据2 天前
酒店行业数据仓库
数据仓库
热门推荐
01聊聊 Python 中的同步原语，为什么有了 GIL 还需要同步原语02【HarmonyOS】HUAWEI DevEco Studio 下载地址汇总03Windows10安装PCL1.14.0及点云配准04C++——超强级病毒代码05全面解析：构建基于深度学习的安全帽检测系统（UI界面+YOLO代码+数据集）06组基轨迹建模 GBTM的介绍与实现（Stata 或 R）07硬件预取之空间预取08Ubuntu 20.04使用Livox mid 360 测试 FAST_LIO09Coze扣子平台完整体验和实践（附国内和国际版对比）10【SCS-CN】SCS-CN模型中CN值的确定