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文章目录
- 一、报表数据导出
- 1.1 MySQL建库建表
- 1.1.1 创建数据库
- 1.1.2 创建表
- 1.2 数据导出
- 1.2.1 DataX配置文件生成脚本
- 1.2.2 编写每日导出脚本
一、报表数据导出
为方便报表应用使用数据，需将ads各指标的统计结果导出到MySQL数据库中
1.1 MySQL建库建表
1.1.1 创建数据库
CREATE DATABASE IF NOT EXISTS gmall_report DEFAULT CHARSET utf8 COLLATE utf8_general_ci;
1.1.2 创建表
1、各活动补贴率
DROP TABLE IF EXISTS `ads_activity_stats`;
CREATE TABLE `ads_activity_stats` (`dt` date NOT NULL COMMENT '统计日期',`activity_id` varchar(16) CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL COMMENT '活动ID',`activity_name` varchar(64) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '活动名称',`start_date` varchar(16) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '活动开始日期',`reduce_rate` decimal(16, 2) NULL DEFAULT NULL COMMENT '补贴率',PRIMARY KEY (`dt`, `activity_id`) USING BTREE
) ENGINE = InnoDB CHARACTER SET = utf8 COLLATE = utf8_general_ci COMMENT = '活动统计' ROW_FORMAT = Dynamic;```2、各优惠券补贴率```sql
DROP TABLE IF EXISTS `ads_coupon_stats`;
CREATE TABLE `ads_coupon_stats` (`dt` date NOT NULL COMMENT '统计日期',`coupon_id` varchar(16) CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL COMMENT '优惠券ID',`coupon_name` varchar(64) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '优惠券名称',`start_date` varchar(16) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '发布日期',`rule_name` varchar(64) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '优惠规则，例如满100元减10元',`reduce_rate` decimal(16, 2) NULL DEFAULT NULL COMMENT '补贴率',PRIMARY KEY (`dt`, `coupon_id`) USING BTREE
) ENGINE = InnoDB CHARACTER SET = utf8 COLLATE = utf8_general_ci COMMENT = '优惠券统计' ROW_FORMAT = Dynamic;
3、新增交易用户统计
DROP TABLE IF EXISTS `ads_new_buyer_stats`;
CREATE TABLE `ads_new_buyer_stats` (`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',`new_order_user_count` bigint(20) NULL DEFAULT NULL COMMENT '新增下单人数',`new_payment_user_count` bigint(20) NULL DEFAULT NULL COMMENT '新增支付人数',PRIMARY KEY (`dt`, `recent_days`) USING BTREE
) ENGINE = InnoDB CHARACTER SET = utf8 COLLATE = utf8_general_ci COMMENT = '新增交易用户统计' ROW_FORMAT = Dynamic;
4、各省份订单统计
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 '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 '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 = '各地区订单统计' ROW_FORMAT = Dynamic;
5、用户路径分析
DROP TABLE IF EXISTS `ads_page_path`;
CREATE TABLE `ads_page_path` (`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',`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`, `recent_days`, `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;
6、各品牌复购率
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,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_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 = '各品牌复购率统计' ROW_FORMAT = Dynamic;
7、各品类商品购物车存量TopN
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 '一级分类ID',`category1_name` varchar(64) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '一级分类名称',`category2_id` varchar(16) CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL COMMENT '二级分类ID',`category2_name` varchar(64) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '二级分类名称',`category3_id` varchar(16) CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL COMMENT '三级分类ID',`category3_name` varchar(64) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '三级分类名称',`sku_id` varchar(16) CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL COMMENT '商品id',`sku_name` varchar(128) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '商品名称',`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 = '各分类商品购物车存量Top10' ROW_FORMAT = Dynamic;
8、交易综合统计
DROP TABLE IF EXISTS `ads_trade_stats`;
CREATE TABLE `ads_trade_stats` (`dt` date NOT NULL COMMENT '统计日期',`recent_days` bigint(255) NOT NULL COMMENT '最近天数,1:最近1日,7:最近7天,30:最近30天',`order_total_amount` decimal(16, 2) NULL DEFAULT NULL COMMENT '订单总额,GMV',`order_count` bigint(20) NULL DEFAULT NULL COMMENT '订单数',`order_user_count` bigint(20) NULL DEFAULT NULL COMMENT '下单人数',`order_refund_count` bigint(20) NULL DEFAULT NULL COMMENT '退单数',`order_refund_user_count` bigint(20) NULL DEFAULT NULL COMMENT '退单人数',PRIMARY KEY (`dt`, `recent_days`) USING BTREE
) ENGINE = InnoDB CHARACTER SET = utf8 COLLATE = utf8_general_ci COMMENT = '交易统计' ROW_FORMAT = Dynamic;
9、各品类商品交易统计
DROP TABLE IF EXISTS `ads_trade_stats_by_cate`;
CREATE TABLE `ads_trade_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 '一级分类id',`category1_name` varchar(64) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '一级分类名称',`category2_id` varchar(16) CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL COMMENT '二级分类id',`category2_name` varchar(64) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '二级分类名称',`category3_id` varchar(16) CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL COMMENT '三级分类id',`category3_name` varchar(64) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '三级分类名称',`order_count` bigint(20) NULL DEFAULT NULL COMMENT '订单数',`order_user_count` bigint(20) NULL DEFAULT NULL COMMENT '订单人数',`order_refund_count` bigint(20) NULL DEFAULT NULL COMMENT '退单数',`order_refund_user_count` bigint(20) NULL DEFAULT NULL COMMENT '退单人数',PRIMARY KEY (`dt`, `recent_days`, `category1_id`, `category2_id`, `category3_id`) USING BTREE
) ENGINE = InnoDB CHARACTER SET = utf8 COLLATE = utf8_general_ci COMMENT = '各分类商品交易统计' ROW_FORMAT = Dynamic;
10、各品牌商品交易统计
DROP TABLE IF EXISTS `ads_trade_stats_by_tm`;
CREATE TABLE `ads_trade_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 '订单数',`order_user_count` bigint(20) NULL DEFAULT NULL COMMENT '订单人数',`order_refund_count` bigint(20) NULL DEFAULT NULL COMMENT '退单数',`order_refund_user_count` bigint(20) NULL DEFAULT NULL COMMENT '退单人数',PRIMARY KEY (`dt`, `recent_days`, `tm_id`) USING BTREE
) ENGINE = InnoDB CHARACTER SET = utf8 COLLATE = utf8_general_ci COMMENT = '各品牌商品交易统计' ROW_FORMAT = Dynamic;
11、各渠道流量统计
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;
12、用户行为漏斗分析
DROP TABLE IF EXISTS `ads_user_action`;
CREATE TABLE `ads_user_action` (`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',`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 '加入购物车人数',`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`, `recent_days`) USING BTREE
) ENGINE = InnoDB CHARACTER SET = utf8 COLLATE = utf8_general_ci COMMENT = '漏斗分析' ROW_FORMAT = Dynamic;
13、用户变动统计
DROP TABLE IF EXISTS `ads_user_change`;
CREATE TABLE `ads_user_change` (`dt` varchar(16) CHARACTER SET utf8 COLLATE utf8_general_ci 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;
14、用户留存率
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 = '留存率' ROW_FORMAT = Dynamic;
15、用户新增活跃统计
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;
1.2 数据导出
数据导出工具选用DataX，选用HDFSReader和MySQLWriter
1.2.1 DataX配置文件生成脚本
1、在/home/zhm/bin目录下创建gen_export_config.py脚本
vim ~/bin/gen_export_config.py
2、提交如下内容
# coding=utf-8
import json
import getopt
import os
import sys
import MySQLdb#MySQL相关配置，需根据实际情况作出修改
mysql_host = "hadoop102"
mysql_port = "3306"
mysql_user = "root"
mysql_passwd = "000000"#HDFS NameNode相关配置，需根据实际情况作出修改
hdfs_nn_host = "hadoop102"
hdfs_nn_port = "8020"#生成配置文件的目标路径，可根据实际情况作出修改
output_path = "/opt/module/datax/job/export"def get_connection():return MySQLdb.connect(host=mysql_host, port=int(mysql_port), user=mysql_user, passwd=mysql_passwd)def get_mysql_meta(database, table):connection = get_connection()cursor = connection.cursor()sql = "SELECT COLUMN_NAME,DATA_TYPE from information_schema.COLUMNS WHERE TABLE_SCHEMA=%s AND TABLE_NAME=%s ORDER BY ORDINAL_POSITION"cursor.execute(sql, [database, table])fetchall = cursor.fetchall()cursor.close()connection.close()return fetchalldef get_mysql_columns(database, table):return map(lambda x: x[0], get_mysql_meta(database, table))def generate_json(target_database, target_table):job = {"job": {"setting": {"speed": {"channel": 3},"errorLimit": {"record": 0,"percentage": 0.02}},"content": [{"reader": {"name": "hdfsreader","parameter": {"path": "${exportdir}","defaultFS": "hdfs://" + hdfs_nn_host + ":" + hdfs_nn_port,"column": ["*"],"fileType": "text","encoding": "UTF-8","fieldDelimiter": "\t","nullFormat": "\\N"}},"writer": {"name": "mysqlwriter","parameter": {"writeMode": "replace","username": mysql_user,"password": mysql_passwd,"column": get_mysql_columns(target_database, target_table),"connection": [{"jdbcUrl":"jdbc:mysql://" + mysql_host + ":" + mysql_port + "/" + target_database + "?useUnicode=true&characterEncoding=utf-8","table": [target_table]}]}}}]}}if not os.path.exists(output_path):os.makedirs(output_path)with open(os.path.join(output_path, ".".join([target_database, target_table, "json"])), "w") as f:json.dump(job, f)def main(args):target_database = ""target_table = ""options, arguments = getopt.getopt(args, '-d:-t:', ['targetdb=', 'targettbl='])for opt_name, opt_value in options:if opt_name in ('-d', '--targetdb'):target_database = opt_valueif opt_name in ('-t', '--targettbl'):target_table = opt_valuegenerate_json(target_database, target_table)if __name__ == '__main__':main(sys.argv[1:])
注意：
（1）安装python_Mysql驱动
由于需要使用Python去访问mysql数据库，所以到安装驱动，命令如下：
sudo yum install -y MySQL-python
（2）脚本使用说明
python gen_export_config.py -d database -t table
通过-d传入MySQL数据库名，-t传入MySQL表名，执行上述命令即可生成该表的DataX同步配置文件。
2、在/home/zhm/bin目录下创建gen_export_config.sh脚本
vim gen_export_config.sh
添加如下内容
#!/bin/bashpython ~/bin/gen_export_config.py -d gmall_report -t ads_activity_stats
python ~/bin/gen_export_config.py -d gmall_report -t ads_coupon_stats
python ~/bin/gen_export_config.py -d gmall_report -t ads_new_buyer_stats
python ~/bin/gen_export_config.py -d gmall_report -t ads_order_by_province
python ~/bin/gen_export_config.py -d gmall_report -t ads_page_path
python ~/bin/gen_export_config.py -d gmall_report -t ads_repeat_purchase_by_tm
python ~/bin/gen_export_config.py -d gmall_report -t ads_sku_cart_num_top3_by_cate
python ~/bin/gen_export_config.py -d gmall_report -t ads_trade_stats
python ~/bin/gen_export_config.py -d gmall_report -t ads_trade_stats_by_cate
python ~/bin/gen_export_config.py -d gmall_report -t ads_trade_stats_by_tm
python ~/bin/gen_export_config.py -d gmall_report -t ads_traffic_stats_by_channel
python ~/bin/gen_export_config.py -d gmall_report -t ads_user_action
python ~/bin/gen_export_config.py -d gmall_report -t ads_user_change
python ~/bin/gen_export_config.py -d gmall_report -t ads_user_retention
python ~/bin/gen_export_config.py -d gmall_report -t ads_user_stats
3、为gen_export_config.sh脚本增加执行权限
chmod +x gen_export_config.sh
4、执行gen_export_config.sh脚本，生产配置文件
gen_export_config.sh
5、观察生成的配置文件
ls /opt/module/datax/job/export/
1.2.2 编写每日导出脚本
1、在hadoop102的/home/zhmbin目录下创建hdfs_to_mysql.sh
2、编写如下内容
#! /bin/bashDATAX_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(){target_file=$1for i in `hadoop fs -ls -R $target_file | awk '{print $8}'`; dohadoop fs -test -z $iif [[ $? -eq 0 ]]; thenecho "$i文件大小为0，正在删除"hadoop fs -rm -r -f $ifidone}#数据导出
export_data() {datax_config=$1export_dir=$2hadoop fs -test -e $export_dirif [[ $? -eq 0 ]]thenhandle_export_path $export_dirfile_count=$(hadoop fs -ls $export_dir | wc -l)if [ $file_count -gt 0 ]thenset -e;$DATAX_HOME/bin/datax.py -p"-Dexportdir=$export_dir" $datax_configset +e;else echo "$export_dir 目录为空，跳过~"fielseecho "路径 $export_dir 不存在，跳过~"fi
}case $1 in"ads_new_buyer_stats")export_data /opt/module/datax/job/export/gmall_report.ads_new_buyer_stats.json /warehouse/gmall/ads/ads_new_buyer_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_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_trade_stats")export_data /opt/module/datax/job/export/gmall_report.ads_trade_stats.json /warehouse/gmall/ads/ads_trade_stats;;"ads_trade_stats_by_cate")export_data /opt/module/datax/job/export/gmall_report.ads_trade_stats_by_cate.json /warehouse/gmall/ads/ads_trade_stats_by_cate;;"ads_trade_stats_by_tm")export_data /opt/module/datax/job/export/gmall_report.ads_trade_stats_by_tm.json /warehouse/gmall/ads/ads_trade_stats_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;;"ads_activity_stats")export_data /opt/module/datax/job/export/gmall_report.ads_activity_stats.json /warehouse/gmall/ads/ads_activity_stats;;"ads_coupon_stats")export_data /opt/module/datax/job/export/gmall_report.ads_coupon_stats.json /warehouse/gmall/ads/ads_coupon_stats;;"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;;"all")export_data /opt/module/datax/job/export/gmall_report.ads_new_buyer_stats.json /warehouse/gmall/ads/ads_new_buyer_statsexport_data /opt/module/datax/job/export/gmall_report.ads_order_by_province.json /warehouse/gmall/ads/ads_order_by_provinceexport_data /opt/module/datax/job/export/gmall_report.ads_page_path.json /warehouse/gmall/ads/ads_page_pathexport_data /opt/module/datax/job/export/gmall_report.ads_repeat_purchase_by_tm.json /warehouse/gmall/ads/ads_repeat_purchase_by_tmexport_data /opt/module/datax/job/export/gmall_report.ads_trade_stats.json /warehouse/gmall/ads/ads_trade_statsexport_data /opt/module/datax/job/export/gmall_report.ads_trade_stats_by_cate.json /warehouse/gmall/ads/ads_trade_stats_by_cateexport_data /opt/module/datax/job/export/gmall_report.ads_trade_stats_by_tm.json /warehouse/gmall/ads/ads_trade_stats_by_tmexport_data /opt/module/datax/job/export/gmall_report.ads_traffic_stats_by_channel.json /warehouse/gmall/ads/ads_traffic_stats_by_channelexport_data /opt/module/datax/job/export/gmall_report.ads_user_action.json /warehouse/gmall/ads/ads_user_actionexport_data /opt/module/datax/job/export/gmall_report.ads_user_change.json /warehouse/gmall/ads/ads_user_changeexport_data /opt/module/datax/job/export/gmall_report.ads_user_retention.json /warehouse/gmall/ads/ads_user_retentionexport_data /opt/module/datax/job/export/gmall_report.ads_user_stats.json /warehouse/gmall/ads/ads_user_statsexport_data /opt/module/datax/job/export/gmall_report.ads_activity_stats.json /warehouse/gmall/ads/ads_activity_statsexport_data /opt/module/datax/job/export/gmall_report.ads_coupon_stats.json /warehouse/gmall/ads/ads_coupon_statsexport_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;;
esac
3、增加脚本执行权限
4、脚本用法
hdfs_to_mysql.sh all
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