离线数仓数据导出-hive数据同步到mysql

MySQL建库建表
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。
datax支持hive同步MySQL：仅仅支持hive存储的hdfs文件导出。所以reader选hdfs-reader，writer选mysql-writer。

在这里插入图片描述
null值在hive和mysql里的存储格式不一样，需要告诉DataX应该如何转换。

MySQL建库建表

12.1.1 创建数据库

CREATE DATABASE IF NOT EXISTS gmall_report DEFAULT CHARSET utf8 COLLATE utf8_general_ci;

建mysql表的，
1字段个数要和hive中的ads层数据保持一致，
2字段类型要和hive对等替换，
3字段顺序也要一致
每张表要有主键

1）各活动补贴率
dt activity_id activity_name 三个主键联合而成

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;

数据导出

DataX配置文件生成脚本
方便起见，此处提供了DataX配置文件批量生成脚本，脚本内容及使用方式如下。
1）在~/bin目录下创建gen_export_config.py脚本
[atguigu@hadoop102 bin]$ vim ~/bin/gen_export_config.py
脚本内容如下

# 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:])

在~/bin目录下创建gen_export_config.sh脚本
[atguigu@hadoop102 bin]$ vim ~/bin/gen_export_config.sh
脚本内容如下。

#!/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
[atguigu@hadoop102 bin]$ chmod +x ~/bin/gen_export_config.sh
4）执行gen_export_config.sh脚本，生成配置文件
[atguigu@hadoop102 bin]$ gen_export_config.sh
5）观察生成的配置文件

[atguigu@hadoop102 bin]$ ls /opt/module/datax/job/export/

编写每日导出脚本
（1）在hadoop102的/home/atguigu/bin目录下创建hdfs_to_mysql.sh
[atguigu@hadoop102 bin]$ vim 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