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
-- 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
-- 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
--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
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
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
--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
--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
--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
--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;
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