39-学习笔记尚硅谷数仓搭建-将ADS层分析好的数据通过DataX传入MySQL

Gain_chance2026-02-10 11:05

目录

一、创建数据库和表

二、编写DataX配置文件

三、编写数据导出脚本

四、查看数据是否导出成功

备注在传数据前要取保ADS层有数据

没有的话按照下面中博客的脚本执行一遍

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38-学习笔记尚硅谷数仓搭建-ADS层流量、用户、商品、优惠卷主题建表语句数据装载及ADS层数据装载脚本-CSDN博客

一、创建数据库和表

1.创建库，在MySQL新建下面的查询语句创建gmall_report库

sql 复制代码 
CREATE DATABASE IF NOT EXISTS gmall_report DEFAULT CHARSET utf8 COLLATE utf8_general_ci;

2.创建表

sql 复制代码 
DROP TABLE IF EXISTS `ads_traffic_stats_by_channel`;
CREATE TABLE `ads_traffic_stats_by_channel`  (
  `dt` date NOT NULL COMMENT '统计日期',
  `recent_days` bigint(20) NOT NULL COMMENT '最近天数,1:最近1天,7:最近7天,30:最近30天',
  `channel` varchar(16) CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL COMMENT '渠道',
  `uv_count` bigint(20) NULL DEFAULT NULL COMMENT '访客人数',
  `avg_duration_sec` bigint(20) NULL DEFAULT NULL COMMENT '会话平均停留时长，单位为秒',
  `avg_page_count` bigint(20) NULL DEFAULT NULL COMMENT '会话平均浏览页面数',
  `sv_count` bigint(20) NULL DEFAULT NULL COMMENT '会话数',
  `bounce_rate` decimal(16, 2) NULL DEFAULT NULL COMMENT '跳出率',
  PRIMARY KEY (`dt`, `recent_days`, `channel`) USING BTREE
) ENGINE = InnoDB CHARACTER SET = utf8 COLLATE = utf8_general_ci COMMENT = '各渠道流量统计' ROW_FORMAT = DYNAMIC;

DROP TABLE IF EXISTS `ads_page_path`;
CREATE TABLE `ads_page_path`  (
  `dt` date NOT NULL COMMENT '统计日期',
  `source` varchar(64) CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL COMMENT '跳转起始页面ID',
  `target` varchar(64) CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL COMMENT '跳转终到页面ID',
  `path_count` bigint(20) NULL DEFAULT NULL COMMENT '跳转次数',
  PRIMARY KEY (`dt`, `source`, `target`) USING BTREE
) ENGINE = InnoDB CHARACTER SET = utf8 COLLATE = utf8_general_ci COMMENT = '页面浏览路径分析' ROW_FORMAT = DYNAMIC;

DROP TABLE IF EXISTS `ads_user_change`;
CREATE TABLE `ads_user_change`  (
  `dt` date NOT NULL COMMENT '统计日期',
  `user_churn_count` varchar(16) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '流失用户数',
  `user_back_count` varchar(16) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '回流用户数',
  PRIMARY KEY (`dt`) USING BTREE
) ENGINE = InnoDB CHARACTER SET = utf8 COLLATE = utf8_general_ci COMMENT = '用户变动统计' ROW_FORMAT = DYNAMIC;

DROP TABLE IF EXISTS `ads_user_retention`;
CREATE TABLE `ads_user_retention`  (
  `dt` date NOT NULL COMMENT '统计日期',
  `create_date` varchar(16) CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL COMMENT '用户新增日期',
  `retention_day` int(20) NOT NULL COMMENT '截至当前日期留存天数',
  `retention_count` bigint(20) NULL DEFAULT NULL COMMENT '留存用户数量',
  `new_user_count` bigint(20) NULL DEFAULT NULL COMMENT '新增用户数量',
  `retention_rate` decimal(16, 2) NULL DEFAULT NULL COMMENT '留存率',
  PRIMARY KEY (`dt`, `create_date`, `retention_day`) USING BTREE
) ENGINE = InnoDB CHARACTER SET = utf8 COLLATE = utf8_general_ci COMMENT = '用户留存率' ROW_FORMAT = DYNAMIC;

DROP TABLE IF EXISTS `ads_user_stats`;
CREATE TABLE `ads_user_stats`  (
  `dt` date NOT NULL COMMENT '统计日期',
  `recent_days` bigint(20) NOT NULL COMMENT '最近n日,1:最近1日,7:最近7日,30:最近30日',
  `new_user_count` bigint(20) NULL DEFAULT NULL COMMENT '新增用户数',
  `active_user_count` bigint(20) NULL DEFAULT NULL COMMENT '活跃用户数',
  PRIMARY KEY (`dt`, `recent_days`) USING BTREE
) ENGINE = InnoDB CHARACTER SET = utf8 COLLATE = utf8_general_ci COMMENT = '用户新增活跃统计' ROW_FORMAT = DYNAMIC;

DROP TABLE IF EXISTS `ads_user_action`;
CREATE TABLE `ads_user_action`  (
  `dt` date NOT NULL COMMENT '统计日期',
  `home_count` bigint(20) NULL DEFAULT NULL COMMENT '浏览首页人数',
  `good_detail_count` bigint(20) NULL DEFAULT NULL COMMENT '浏览商品详情页人数',
  `cart_count` bigint(20) NULL DEFAULT NULL COMMENT '加购人数',
  `order_count` bigint(20) NULL DEFAULT NULL COMMENT '下单人数',
  `payment_count` bigint(20) NULL DEFAULT NULL COMMENT '支付人数',
  PRIMARY KEY (`dt`) USING BTREE
) ENGINE = InnoDB CHARACTER SET = utf8 COLLATE = utf8_general_ci COMMENT = '用户行为漏斗分析' ROW_FORMAT = DYNAMIC;

DROP TABLE IF EXISTS `ads_new_order_user_stats`;
CREATE TABLE `ads_new_order_user_stats`  (
  `dt` date NOT NULL COMMENT '统计日期',
  `recent_days` bigint(20) NOT NULL COMMENT '最近n日,1:最近1日,7:最近7日,30:最近30日',
  `new_order_user_count` bigint(20) NULL DEFAULT NULL COMMENT '新增下单用户数',
  PRIMARY KEY (`recent_days`, `dt`) USING BTREE
) ENGINE = InnoDB CHARACTER SET = utf8 COLLATE = utf8_general_ci COMMENT = '新增下单用户统计' ROW_FORMAT = Dynamic;

DROP TABLE IF EXISTS `ads_order_continuously_user_count`;
CREATE TABLE `ads_order_continuously_user_count`  (
  `dt` date NOT NULL COMMENT '统计日期',
  `recent_days` bigint(20) NOT NULL COMMENT '最近天数,7:最近7天',
  `order_continuously_user_count` bigint(20) NULL DEFAULT NULL COMMENT '连续3日下单用户数',
  PRIMARY KEY (`dt`, `recent_days`) USING BTREE
) ENGINE = InnoDB CHARACTER SET = utf8 COLLATE = utf8_general_ci COMMENT = '最近7日内连续3日下单用户数统计' ROW_FORMAT = Dynamic;

DROP TABLE IF EXISTS `ads_repeat_purchase_by_tm`;
CREATE TABLE `ads_repeat_purchase_by_tm`  (
  `dt` date NOT NULL COMMENT '统计日期',
  `recent_days` bigint(20) NOT NULL COMMENT '最近天数,30:最近30天',
  `tm_id` varchar(16) CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL COMMENT '品牌ID',
  `tm_name` varchar(32) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '品牌名称',
  `order_repeat_rate` decimal(16, 2) NULL DEFAULT NULL COMMENT '复购率',
  PRIMARY KEY (`dt`, `recent_days`, `tm_id`) USING BTREE
) ENGINE = InnoDB CHARACTER SET = utf8 COLLATE = utf8_general_ci COMMENT = '最近30日各品牌复购率统计' ROW_FORMAT = DYNAMIC;

DROP TABLE IF EXISTS `ads_order_stats_by_tm`;
CREATE TABLE `ads_order_stats_by_tm`  (
  `dt` date NOT NULL COMMENT '统计日期',
  `recent_days` bigint(20) NOT NULL COMMENT '最近天数,1:最近1天,7:最近7天,30:最近30天',
  `tm_id` varchar(16) CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL COMMENT '品牌ID',
  `tm_name` varchar(32) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '品牌名称',
  `order_count` bigint(20) NULL DEFAULT NULL COMMENT '下单数',
  `order_user_count` bigint(20) NULL DEFAULT NULL COMMENT '下单人数',
  PRIMARY KEY (`dt`, `recent_days`, `tm_id`) USING BTREE
) ENGINE = InnoDB CHARACTER SET = utf8 COLLATE = utf8_general_ci COMMENT = '各品牌商品下单统计' ROW_FORMAT = DYNAMIC;

DROP TABLE IF EXISTS `ads_order_stats_by_cate`;
CREATE TABLE `ads_order_stats_by_cate`  (
  `dt` date NOT NULL COMMENT '统计日期',
  `recent_days` bigint(20) NOT NULL COMMENT '最近天数,1:最近1天,7:最近7天,30:最近30天',
  `category1_id` varchar(16) CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL COMMENT '一级品类ID',
  `category1_name` varchar(64) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '一级品类名称',
  `category2_id` varchar(16) CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL COMMENT '二级品类ID',
  `category2_name` varchar(64) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '二级品类名称',
  `category3_id` varchar(16) CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL COMMENT '三级品类ID',
  `category3_name` varchar(64) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '三级品类名称',
  `order_count` bigint(20) NULL DEFAULT NULL COMMENT '下单数',
  `order_user_count` bigint(20) NULL DEFAULT NULL COMMENT '下单人数',
  PRIMARY KEY (`dt`, `recent_days`, `category1_id`, `category2_id`, `category3_id`) USING BTREE
) ENGINE = InnoDB CHARACTER SET = utf8 COLLATE = utf8_general_ci COMMENT = '各品类商品下单统计' ROW_FORMAT = DYNAMIC;

DROP TABLE IF EXISTS `ads_sku_cart_num_top3_by_cate`;
CREATE TABLE `ads_sku_cart_num_top3_by_cate`  (
  `dt` date NOT NULL COMMENT '统计日期',
  `category1_id` varchar(16) CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL COMMENT '一级品类ID',
  `category1_name` varchar(64) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '一级品类名称',
  `category2_id` varchar(16) CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL COMMENT '二级品类ID',
  `category2_name` varchar(64) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '二级品类名称',
  `category3_id` varchar(16) CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL COMMENT '三级品类ID',
  `category3_name` varchar(64) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '三级品类名称',
  `sku_id` varchar(16) CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL COMMENT 'SKU_ID',
  `sku_name` varchar(128) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT 'SKU名称',
  `cart_num` bigint(20) NULL DEFAULT NULL COMMENT '购物车中商品数量',
  `rk` bigint(20) NULL DEFAULT NULL COMMENT '排名',
  PRIMARY KEY (`dt`, `sku_id`, `category1_id`, `category2_id`, `category3_id`) USING BTREE
) ENGINE = InnoDB CHARACTER SET = utf8 COLLATE = utf8_general_ci COMMENT = '各品类商品购物车存量Top3' ROW_FORMAT = DYNAMIC;

DROP TABLE IF EXISTS `ads_sku_favor_count_top3_by_tm`;
CREATE TABLE `ads_sku_favor_count_top3_by_tm`  (
  `dt` date NOT NULL COMMENT '统计日期',
  `tm_id` varchar(20) CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL COMMENT '品牌ID',
  `tm_name` varchar(128) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '品牌名称',
  `sku_id` varchar(20) CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL COMMENT 'SKU_ID',
  `sku_name` varchar(128) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT 'SKU名称',
  `favor_count` bigint(20) NULL DEFAULT NULL COMMENT '被收藏次数',
  `rk` bigint(20) NULL DEFAULT NULL COMMENT '排名',
  PRIMARY KEY (`dt`, `tm_id`, `sku_id`) USING BTREE
) ENGINE = InnoDB CHARACTER SET = utf8 COLLATE = utf8_general_ci COMMENT = '各品牌商品收藏次数Top3' ROW_FORMAT = Dynamic;

DROP TABLE IF EXISTS `ads_order_to_pay_interval_avg`;
CREATE TABLE `ads_order_to_pay_interval_avg`  (
  `dt` date NOT NULL COMMENT '统计日期',
  `order_to_pay_interval_avg` bigint(20) NULL DEFAULT NULL COMMENT '下单到支付时间间隔平均值',
  PRIMARY KEY (`dt`) USING BTREE
) ENGINE = InnoDB CHARACTER SET = utf8 COLLATE = utf8_general_ci COMMENT '下单到支付时间间隔平均值统计' ROW_FORMAT = Dynamic;

DROP TABLE IF EXISTS `ads_order_by_province`;
CREATE TABLE `ads_order_by_province`  (
  `dt` date NOT NULL COMMENT '统计日期',
  `recent_days` bigint(20) NOT NULL COMMENT '最近天数,1:最近1天,7:最近7天,30:最近30天',
  `province_id` varchar(16) CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL COMMENT '省份ID',
  `province_name` varchar(16) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '省份名称',
  `area_code` varchar(16) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '地区编码',
  `iso_code` varchar(16) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '旧版国际标准地区编码',
  `iso_code_3166_2` varchar(16) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '新版国际标准地区编码',
  `order_count` bigint(20) NULL DEFAULT NULL COMMENT '订单数',
  `order_total_amount` decimal(16, 2) NULL DEFAULT NULL COMMENT '订单金额',
  PRIMARY KEY (`dt`, `recent_days`, `province_id`) USING BTREE
) ENGINE = InnoDB CHARACTER SET = utf8 COLLATE = utf8_general_ci COMMENT = '各省份交易统计' ROW_FORMAT = DYNAMIC;

DROP TABLE IF EXISTS `ads_coupon_stats`;
CREATE TABLE `ads_coupon_stats`  (
  `dt` date NOT NULL COMMENT '统计日期',
  `coupon_id` varchar(20) CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL COMMENT '优惠券ID',
  `coupon_name` varchar(128) CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL COMMENT '优惠券名称',
  `used_count` bigint(20) NULL DEFAULT NULL COMMENT '使用次数',
  `used_user_count` bigint(20) NULL DEFAULT NULL COMMENT '使用人数',
  PRIMARY KEY (`dt`, `coupon_id`) USING BTREE
) ENGINE = InnoDB CHARACTER SET = utf8 COLLATE = utf8_general_ci COMMENT '优惠券使用统计' ROW_FORMAT = Dynamic;

3.创建完成后可以看到有16张空的表

二、编写DataX配置文件

1.修改configuration.properties

sql 复制代码 
cd /opt/module/gen_datax_config/
vim configuration.properties

将里面的内容替换为下面的

sql 复制代码 
mysql.username=root
mysql.password=000000
mysql.host=hadoop102
mysql.port=3306
mysql.database.import=gmall
# 从HDFS导出进入的 MySQL 数据库名称
mysql.database.export=gmall_report
mysql.tables.import=activity_info,activity_rule,base_trademark,cart_info,base_category1,base_category2,base_category3,coupon_info,sku_attr_value,sku_sale_attr_value,base_dic,sku_info,base_province,spu_info,base_region,promotion_pos,promotion_refer
# MySQL 库中需要导出的表，空串表示导出库的所有表
mysql.tables.export=
is.seperated.tables=0
hdfs.uri=hdfs://hadoop102:8020
import_out_dir=/opt/module/datax/job/import
# DataX 导出配置文件存放路径
export_out_dir=/opt/module/datax/job/export

2.执行配置文件生成器

sql 复制代码 
java -jar datax-config-generator-1.0-SNAPSHOT-jar-with-dependencies.jar

3.查看配置文件生成，在/opt/module/datax/job/export路径下应该有16个配置文件

三、编写数据导出脚本

1.创建脚本

sql 复制代码 
cd /home/atguigu/bin
vim hdfs_to_mysql.sh

添加下面的脚本内容

sql 复制代码 
#! /bin/bash

DATAX_HOME=/opt/module/datax

#DataX导出路径不允许存在空文件，该函数作用为清理空文件
handle_export_path(){
  for i in `hadoop fs -ls -R $1 | awk '{print $8}'`; do
    hadoop fs -test -z $i
    if [[ $? -eq 0 ]]; then
      echo "$i文件大小为0，正在删除"
      hadoop fs -rm -r -f $i
    fi
  done
}

#数据导出
export_data() {
  datax_config=$1
  export_dir=$2
  handle_export_path $export_dir
  $DATAX_HOME/bin/datax.py -p"-Dexportdir=$export_dir" $datax_config
}

case $1 in
  "ads_coupon_stats")
    export_data /opt/module/datax/job/export/gmall_report.ads_coupon_stats.json /warehouse/gmall/ads/ads_coupon_stats
  ;;
  "ads_new_order_user_stats")
    export_data /opt/module/datax/job/export/gmall_report.ads_new_order_user_stats.json /warehouse/gmall/ads/ads_new_order_user_stats
  ;;  
  "ads_order_by_province")
    export_data /opt/module/datax/job/export/gmall_report.ads_order_by_province.json /warehouse/gmall/ads/ads_order_by_province
  ;;
  "ads_order_continuously_user_count")
    export_data /opt/module/datax/job/export/gmall_report.ads_order_continuously_user_count.json /warehouse/gmall/ads/ads_order_continuously_user_count
  ;;
  "ads_order_stats_by_cate")
    export_data /opt/module/datax/job/export/gmall_report.ads_order_stats_by_cate.json /warehouse/gmall/ads/ads_order_stats_by_cate
  ;;
  "ads_order_stats_by_tm")
    export_data /opt/module/datax/job/export/gmall_report.ads_order_stats_by_tm.json /warehouse/gmall/ads/ads_order_stats_by_tm
  ;;  
  "ads_order_to_pay_interval_avg")
    export_data /opt/module/datax/job/export/gmall_report.ads_order_to_pay_interval_avg.json /warehouse/gmall/ads/ads_order_to_pay_interval_avg
  ;;
  "ads_page_path")
    export_data /opt/module/datax/job/export/gmall_report.ads_page_path.json /warehouse/gmall/ads/ads_page_path
  ;;
  "ads_repeat_purchase_by_tm")
    export_data /opt/module/datax/job/export/gmall_report.ads_repeat_purchase_by_tm.json /warehouse/gmall/ads/ads_repeat_purchase_by_tm
  ;;
  "ads_sku_cart_num_top3_by_cate")
    export_data /opt/module/datax/job/export/gmall_report.ads_sku_cart_num_top3_by_cate.json /warehouse/gmall/ads/ads_sku_cart_num_top3_by_cate
  ;;  
  "ads_sku_favor_count_top3_by_tm")
    export_data /opt/module/datax/job/export/gmall_report.ads_sku_favor_count_top3_by_tm.json /warehouse/gmall/ads/ads_sku_favor_count_top3_by_tm
  ;;
  "ads_traffic_stats_by_channel")
    export_data /opt/module/datax/job/export/gmall_report.ads_traffic_stats_by_channel.json /warehouse/gmall/ads/ads_traffic_stats_by_channel
  ;;
  "ads_user_action")
    export_data /opt/module/datax/job/export/gmall_report.ads_user_action.json /warehouse/gmall/ads/ads_user_action
  ;;
  "ads_user_change")
    export_data /opt/module/datax/job/export/gmall_report.ads_user_change.json /warehouse/gmall/ads/ads_user_change
  ;;  
  "ads_user_retention")
    export_data /opt/module/datax/job/export/gmall_report.ads_user_retention.json /warehouse/gmall/ads/ads_user_retention
  ;;
  "ads_user_stats")
    export_data /opt/module/datax/job/export/gmall_report.ads_user_stats.json /warehouse/gmall/ads/ads_user_stats
  ;;
  "all")
    export_data /opt/module/datax/job/export/gmall_report.ads_coupon_stats.json /warehouse/gmall/ads/ads_coupon_stats
    export_data /opt/module/datax/job/export/gmall_report.ads_new_order_user_stats.json /warehouse/gmall/ads/ads_new_order_user_stats
    export_data /opt/module/datax/job/export/gmall_report.ads_order_by_province.json /warehouse/gmall/ads/ads_order_by_province
    export_data /opt/module/datax/job/export/gmall_report.ads_order_continuously_user_count.json /warehouse/gmall/ads/ads_order_continuously_user_count
    export_data /opt/module/datax/job/export/gmall_report.ads_order_stats_by_cate.json /warehouse/gmall/ads/ads_order_stats_by_cate
    export_data /opt/module/datax/job/export/gmall_report.ads_order_stats_by_tm.json /warehouse/gmall/ads/ads_order_stats_by_tm
    export_data /opt/module/datax/job/export/gmall_report.ads_order_to_pay_interval_avg.json /warehouse/gmall/ads/ads_order_to_pay_interval_avg
    export_data /opt/module/datax/job/export/gmall_report.ads_page_path.json /warehouse/gmall/ads/ads_page_path
    export_data /opt/module/datax/job/export/gmall_report.ads_repeat_purchase_by_tm.json /warehouse/gmall/ads/ads_repeat_purchase_by_tm
    export_data /opt/module/datax/job/export/gmall_report.ads_sku_cart_num_top3_by_cate.json /warehouse/gmall/ads/ads_sku_cart_num_top3_by_cate
    export_data /opt/module/datax/job/export/gmall_report.ads_sku_favor_count_top3_by_tm.json /warehouse/gmall/ads/ads_sku_favor_count_top3_by_tm
    export_data /opt/module/datax/job/export/gmall_report.ads_traffic_stats_by_channel.json /warehouse/gmall/ads/ads_traffic_stats_by_channel
    export_data /opt/module/datax/job/export/gmall_report.ads_user_action.json /warehouse/gmall/ads/ads_user_action
    export_data /opt/module/datax/job/export/gmall_report.ads_user_change.json /warehouse/gmall/ads/ads_user_change
    export_data /opt/module/datax/job/export/gmall_report.ads_user_retention.json /warehouse/gmall/ads/ads_user_retention
    export_data /opt/module/datax/job/export/gmall_report.ads_user_stats.json /warehouse/gmall/ads/ads_user_stats
  ;;
esac

添加权限

sql 复制代码 
chmod +x hdfs_to_mysql.sh

执行脚本

sql 复制代码 
hdfs_to_mysql.sh all

四、查看数据是否导出成功

如图：

到此数据仓库整个流程已经完成，剩下的就是利用数据库的数据进行可视化

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