文章目錄
歡迎訪問筆者個人技術博客:http://rukihuang.xyz/
學習視頻來源於尚硅谷,視頻鏈接:尚硅谷大數據項目數據倉庫,電商數倉V1.2新版,Respect!
1 MySQL安裝
- 卸載安裝均需要在root用戶身份下
1.1 安裝包準備
- 查看mysql是否安裝,如果安裝,先卸載(需要在
root
角色下)
#查看
rpm -qa|grep mysql
#卸載
rpm -e --nodeps mysql-libs-5.1.73-7.el6.x86_64
- 解壓
mysql-libs.zip
文件到/opt/software
目錄
unzip mysql-libs.zip
1.2 安裝mysql服務器
- 安裝mysql服務端(在
/opt/software/mysql-libs
目錄下)- 如果安裝報錯(博主遇到了),參考這篇文章:https://blog.csdn.net/qq_42191775/article/details/103939104
rpm -ivh MySQL-server-5.6.24-1.el6.x86_64.rpm
- 查看產生的隨機密碼(之後改密碼需要用)
cat /root/.mysql_secret
- 查看mysql狀態
service mysql status
- 啓動mysql
service mysql start
1.3 安裝mysql客戶端
- 安裝mysql客戶端(在
/opt/software/mysql-libs
目錄下)
rpm -ivh MySQL-client-5.6.24-1.el6.x86_64.rpm
- 連接Mysql
mysql -uroot -p[步驟1.2.2得到的隨機密鑰]
- 修改密碼
set password=password('root')
- 退出
exit
1.4 mysql中主機配置(user表)
配置只要是root 用戶+密碼,在任何主機上都能登錄MySQL 數據庫。
- 進入mysql
mysql -uroot -proot
- 顯示數據庫
show databases;
- 使用mysql數據庫
use mysql;
- 顯示mysql中的所有表
show tables;
- 查詢user表
select User, Host, Password from user;
- 修改user 表,把Host 表內容修改爲%
update user set host='%' where host='localhost';
- 刪除root用戶其他host
delete from user where Host='hadoop102';
delete from user where Host='127.0.0.1';
delete from user where Host='::1';
- 刷新
flush privileges;
- 退出
quit
2 Sqoop的安裝
2.1 安裝sqoop
- 上傳安裝包
sqoop-1.4.6.bin__hadoop-2.0.4-alpha.tar.gz
到hadoop102 的/opt/software
路徑中 - 將安裝包解壓到
/opt/module
tar -zxf sqoop-1.4.6.bin__hadoop-2.0.4-alpha.tar.gz -C /opt/module/
- 修改文件夾的名字(
/opt/module
)
mv sqoop-1.4.6.bin__hadoop-2.0.4-alpha/ sqoop
2.2 修改配置文件
- 進入到
/opt/module/sqoop/conf
目錄,重命名配置文件
mv sqoop-env-template.sh sqoop-env.sh
- 修改配置文件
#增加如下內容
export HADOOP_COMMON_HOME=/opt/module/hadoop-2.7.2
export HADOOP_MAPRED_HOME=/opt/module/hadoop-2.7.2
export HIVE_HOME=/opt/module/hive
export ZOOKEEPER_HOME=/opt/module/zookeeper-3.4.10
export ZOOCFGDIR=/opt/module/zookeeper-3.4.10/conf
export HBASE_HOME=/opt/module/hbase
2.3 拷貝JDBC驅動
- 進入到
/opt/software/mysql-libs
路徑,解壓mysql-connector-java-5.1.27.tar.gz
到當前路徑
tar -zxvf mysql-connector-java-5.1.27.tar.gz
- 進入到
/opt/software/mysql-libs/mysql-connector-java-5.1.27
路徑,拷貝jdbc 驅動到sqoop的lib
目錄下。
cp mysql-connector-java-5.1.27-bin.jar /opt/module/sqoop/lib/
2.4 測試Sqoop是否能連接數據庫
bin/sqoop list-databases --connect jdbc:mysql://hadoop102:3306/ --username root --password root
3 業務數據的生成
- 在hadoop102 的
/opt/module/
目錄下創建db_log
文件夾
mkdir db_log
-
把
gmall-mock-db-2020-03-16-SNAPSHOT.jar
和application.properties
上傳到hadoop102的/opt/module/db_log
路徑上。 -
根據需求修改
application.properties
相關配置- 通過修改
mock.date=2020-03-11
,生成那天的數據 - 通過修改
mock.clear=0
,刪除原有的數據,生成新的隨機數據
- 通過修改
logging.pattern.console=%m%n
logging.level.root=info
spring.datasource.driver-class-name=com.mysql.jdbc.Driver
spring.datasource.url=jdbc:mysql://hadoop102:3306/gmall?characterEncoding=utf-8&useSSL=false&serverTimezone=GMT%2B8
spring.datasource.username=root
spring.datasource.password=root
logging.pattern.console=%m%n
mybatis-plus.global-config.db-config.field-strategy=not_null
#業務日期
mock.date=2020-03-11
#是否重置 1表示重置 0表示不重置
mock.clear=0
#是否生成新用戶
mock.user.count=50
#男性比例
mock.user.male-rate=20
#收藏取消比例
mock.favor.cancel-rate=10
#收藏數量
mock.favor.count=100
#購物車數量
mock.cart.count=10
#每個商品最多購物個數
mock.cart.sku-maxcount-per-cart=3
#用戶下單比例
mock.order.user-rate=80
#用戶從購物中購買商品比例
mock.order.sku-rate=70
#是否參加活動
mock.order.join-activity=1
#是否使用購物券
mock.order.use-coupon=1
#購物券領取人數
mock.coupon.user-count=10
#支付比例
mock.payment.rate=70
#支付方式 支付寶:微信 :銀聯
mock.payment.payment-type=30:60:10
#評價比例 好:中:差:自動
mock.comment.appraise-rate=30:10:10:50
#退款原因比例:質量問題 商品描述與實際描述不一致 缺貨 號碼不合適 拍錯 不想買了 其他
mock.refund.reason-rate=30:10:20:5:15:5:5
- 並在該目錄下執行,如下命令,生成2020-03-10 日期數據:
java -jar gmall-mock-db-2020-03-16-SNAPSHOT.jar
4 同步策略
4.1 全量同步策略
- 每天存儲一份完整的數據,適用於數據量不大,且每天既有新數據插入,也會有舊數據修改的場景。
4.2 增量同步數據
- 每天存儲一份增量數據,適用於數據量大,且每天只會有新數據插入的場景。
4.3 新增及變化策略
- 存儲創建時間和操作時間都是當天的數據
4.4 特殊策略
- 只同步一遍就可以的數據。如客觀世界維度,日期維度,地區維度的數據。
5 mysql->sqoop->hdfs腳本編寫
- 在
/home/atguigu/bin
目錄下創建mysql_to_hdfs.sh
#! /bin/bash
sqoop=/opt/module/sqoop/bin/sqoop
do_date=`date -d '-1 day' +%F`
if [[ -n "$2" ]]; then
do_date=$2
fi
import_data(){
$sqoop import \
--connect jdbc:mysql://hadoop102:3306/gmall \
--username root \
--password root \
--target-dir /origin_data/gmall/db/$1/$do_date \
--delete-target-dir \
--query "$2 and \$CONDITIONS" \
--num-mappers 1 \
--fields-terminated-by '\t' \
--compress \
--compression-codec lzop \
--null-string '\\N' \
--null-non-string '\\N'
hadoop jar /opt/module/hadoop-2.7.2/share/hadoop/common/hadoop-lzo-0.4.20.jar com.hadoop.compression.lzo.DistributedLzoIndexer /origin_data/gmall/db/$1/$do_date
}
import_order_info(){
import_data order_info "select
id,
final_total_amount,
order_status,
user_id,
out_trade_no,
create_time,
operate_time,
province_id,
benefit_reduce_amount,
original_total_amount,
feight_fee
from order_info
where (date_format(create_time,'%Y-%m-%d')='$do_date'
or date_format(operate_time,'%Y-%m-%d')='$do_date')"
}
import_coupon_use(){
import_data coupon_use "select
id,
coupon_id,
user_id,
order_id,
coupon_status,
get_time,
using_time,
used_time
from coupon_use
where (date_format(get_time,'%Y-%m-%d')='$do_date'
or date_format(using_time,'%Y-%m-%d')='$do_date'
or date_format(used_time,'%Y-%m-%d')='$do_date')"
}
import_order_status_log(){
import_data order_status_log "select
id,
order_id,
order_status,
operate_time
from order_status_log
where
date_format(operate_time,'%Y-%m-%d')='$do_date'"
}
import_activity_order(){
import_data activity_order "select
id,
activity_id,
order_id,
create_time
from activity_order
where
date_format(create_time,'%Y-%m-%d')='$do_date'"
}
import_user_info(){
import_data "user_info" "select
id,
name,
birthday,
gender,
email,
user_level,
create_time,
operate_time
from user_info
where (DATE_FORMAT(create_time,'%Y-%m-%d')='$do_date'
or DATE_FORMAT(operate_time,'%Y-%m-%d')='$do_date')"
}
import_order_detail(){
import_data order_detail "select
od.id,
order_id,
user_id,
sku_id,
sku_name,
order_price,
sku_num,
od.create_time
from order_detail od
join order_info oi
on od.order_id=oi.id
where
DATE_FORMAT(od.create_time,'%Y-%m-%d')='$do_date'"
}
import_payment_info(){
import_data "payment_info" "select
id,
out_trade_no,
order_id,
user_id,
alipay_trade_no,
total_amount,
subject,
payment_type,
payment_time
from payment_info
where
DATE_FORMAT(payment_time,'%Y-%m-%d')='$do_date'"
}
import_comment_info(){
import_data comment_info "select
id,
user_id,
sku_id,
spu_id,
order_id,
appraise,
comment_txt,
create_time
from comment_info
where date_format(create_time,'%Y-%m-%d')='$do_date'"
}
import_order_refund_info(){
import_data order_refund_info "select
id,
user_id,
order_id,
sku_id,
refund_type,
refund_num,
refund_amount,
refund_reason_type,
create_time
from order_refund_info
where
date_format(create_time,'%Y-%m-%d')='$do_date'"
}
import_sku_info(){
import_data sku_info "select
id,
spu_id,
price,
sku_name,
sku_desc,
weight,
tm_id,
category3_id,
create_time
from sku_info where 1=1"
}
import_base_category1(){
import_data "base_category1" "select
id,
name
from base_category1 where 1=1"
}
import_base_category2(){
import_data "base_category2" "select
id,
name,
category1_id
from base_category2 where 1=1"
}
import_base_category3(){
import_data "base_category3" "select
id,
name,
category2_id
from base_category3 where 1=1"
}
import_base_province(){
import_data base_province "select
id,
name,
region_id,
area_code,
iso_code
from base_province
where 1=1"
}
import_base_region(){
import_data base_region "select
id,
region_name
from base_region
where 1=1"
}
import_base_trademark(){
import_data base_trademark "select
tm_id,
tm_name
from base_trademark
where 1=1"
}
import_spu_info(){
import_data spu_info "select
id,
spu_name,
category3_id,
tm_id
from spu_info
where 1=1"
}
import_favor_info(){
import_data favor_info "select
id,
user_id,
sku_id,
spu_id,
is_cancel,
create_time,
cancel_time
from favor_info
where 1=1"
}
import_cart_info(){
import_data cart_info "select
id,
user_id,
sku_id,
cart_price,
sku_num,
sku_name,
create_time,
operate_time,
is_ordered,
order_time
from cart_info
where 1=1"
}
import_coupon_info(){
import_data coupon_info "select
id,
coupon_name,
coupon_type,
condition_amount,
condition_num,
activity_id,
benefit_amount,
benefit_discount,
create_time,
range_type,
spu_id,
tm_id,
category3_id,
limit_num,
operate_time,
expire_time
from coupon_info
where 1=1"
}
import_activity_info(){
import_data activity_info "select
id,
activity_name,
activity_type,
start_time,
end_time,
create_time
from activity_info
where 1=1"
}
import_activity_rule(){
import_data activity_rule "select
id,
activity_id,
condition_amount,
condition_num,
benefit_amount,
benefit_discount,
benefit_level
from activity_rule
where 1=1"
}
import_base_dic(){
import_data base_dic "select
dic_code,
dic_name,
parent_code,
create_time,
operate_time
from base_dic
where 1=1"
}
case $1 in
"order_info")
import_order_info
;;
"base_category1")
import_base_category1
;;
"base_category2")
import_base_category2
;;
"base_category3")
import_base_category3
;;
"order_detail")
import_order_detail
;;
"sku_info")
import_sku_info
;;
"user_info")
import_user_info
;;
"payment_info")
import_payment_info
;;
"base_province")
import_base_province
;;
"base_region")
import_base_region
;;
"base_trademark")
import_base_trademark
;;
"activity_info")
import_activity_info
;;
"activity_order")
import_activity_order
;;
"cart_info")
import_cart_info
;;
"comment_info")
import_comment_info
;;
"coupon_info")
import_coupon_info
;;
"coupon_use")
import_coupon_use
;;
"favor_info")
import_favor_info
;;
"order_refund_info")
import_order_refund_info
;;
"order_status_log")
import_order_status_log
;;
"spu_info")
import_spu_info
;;
"activity_rule")
import_activity_rule
;;
"base_dic")
import_base_dic
;;
"first")
import_base_category1
import_base_category2
import_base_category3
import_order_info
import_order_detail
import_sku_info
import_user_info
import_payment_info
import_base_province
import_base_region
import_base_trademark
import_activity_info
import_activity_order
import_cart_info
import_comment_info
import_coupon_use
import_coupon_info
import_favor_info
import_order_refund_info
import_order_status_log
import_spu_info
import_activity_rule
import_base_dic
;;
"all")
import_base_category1
import_base_category2
import_base_category3
import_order_info
import_order_detail
import_sku_info
import_user_info
import_payment_info
import_base_trademark
import_activity_info
import_activity_order
import_cart_info
import_comment_info
import_coupon_use
import_coupon_info
import_favor_info
import_order_refund_info
import_order_status_log
import_spu_info
import_activity_rule
import_base_dic
;;
esac
- 說明1:
[ -n 變量值]
判斷變量的值,是否爲空- 變量的值,非空,返回
true
- 變量的值,爲空,返回
false
- 變量的值,非空,返回
- 修改腳本權限
chmod 777 mysql_to_hdfs.sh
- 初次導入
mysql_to_hdfs.sh first 2020-03-10
- 每日導入
mysql_to_hdfs.sh all 2020-03-11
5.1 項目經驗
- Hive 中的
Null
在底層是以“\N”
來存儲,而MySQL 中的Null
在底層就是Null
,爲了保證數據兩端的一致性。在導出數據時採用--input-null-string
和--input-null-non-string
兩個參數。導入數據時採用--null-string
和--null-non-string
。