DataX(MySQL同步数据到Doris)-编程知识

1.场景

这里演示介绍的使用 Doris 的 Datax 扩展 DorisWriter实现从Mysql数据定时抽取数据导入到Doris数仓表里

2.编译 DorisWriter

这个的扩展的编译可以不在 doris 的 docker 编译环境下进行，本文是在 windows 下的 WLS 下进行编译的

首先从github上拉取源码

 git clone https://github.com/apache/incubator-doris.git

进入到incubator-doris/extension/DataX/ 执行编译

首先执行：

sh init_env.sh
这个脚本主要用于构建 DataX 开发环境，他主要进行了以下操作：

将 DataX 代码库 clone 到本地。
将 doriswriter/ 目录软链到 DataX/doriswriter 目录。
在 DataX/pom.xml 文件中添加 <module>doriswriter</module> 模块。
将 DataX/core/pom.xml 文件中的 httpclient 版本从 4.5 改为 4.5.13 httpclient v4.5 在处理 307 转发时有bug。
这个脚本执行后，开发者就可以进入 DataX/ 目录开始开发或编译了。因为做了软链，所以任何对 DataX/doriswriter 目录中文件的修改，都会反映到 doriswriter/ 目录中，方便开发者提交代码

2.1 开始编译
这里我为了加快编译速度去掉了很多无用的插件：这里直接在Datax目录下的pom.xml里注释掉就行

 hbase11xreaderhbase094xreadertsdbreaderoceanbasev10readerodpswriterhdfswriteradswriterocswriteroscarwriteroceanbasev10writer

然后进入到incubator-doris/extension/DataX/ 目录下的 Datax 目录，执行编译

这里我是执行的将 Datax 编译成 tar 包，和官方的编译命令不太一样。

 mvn -U clean package assembly:assembly -Dmaven.test.skip=true

编译完成以后，tar 包在 Datax/target 目录下，你可以将这tar包拷贝到你需要的地方，这里我是直接在 datax 执行测试，这里因为的 python 版本是 3.x版本，需要将 bin 目录下的三个文件换成 python 3能之别的版本，这个你可以去下面的地址下载：

https://github.com/WeiYe-Jing...
将下载的三个文件替换 bin 目录下的文件以后，整个编译，安装就完成了

如果你编译不成功也可以从我的百度网盘上下载编译好的包，注意我上边编译去掉的那些插件

链接: https://pan.baidu.com/s/1ObQ4Md0A_0ut4O6-_gPSQg

提取码: 424s

3.数据接入

这个时候我们就可以开始使用 Datax 的doriswriter扩展开始从 Mysql（或者其他数据源）直接将数据抽取出来导入到 Doris 表中了。

3.1 Mysql 数据库准备

下面是我数据库的建表脚本（mysql 8）：

CREATE TABLE `order_analysis` (`date` varchar(19) DEFAULT NULL,`user_src` varchar(9) DEFAULT NULL,`order_src` varchar(11) DEFAULT NULL,`order_location` varchar(2) DEFAULT NULL,`new_order` int DEFAULT NULL,`payed_order` int DEFAULT NULL,`pending_order` int DEFAULT NULL,`cancel_order` int DEFAULT NULL,`reject_order` int DEFAULT NULL,`good_order` int DEFAULT NULL,`report_order` int DEFAULT NULL) ENGINE=InnoDB DEFAULT CHARSET=utf8 ROW_FORMAT=COMPACT

示例数据:

INSERT INTO `sql12298540`.`order_analysis` (`date`, `user_src`, `order_src`, `order_location`, `new_order`, `payed_order`, `pending_order`, `cancel_order`, `reject_order`, `good_order`, `report_order`) VALUES ('2015-10-12 00:00:00', '广告二维码', 'Android APP', '上海', 15253, 13210, 684, 1247, 1000, 10824, 862);INSERT INTO `sql12298540`.`order_analysis` (`date`, `user_src`, `order_src`, `order_location`, `new_order`, `payed_order`, `pending_order`, `cancel_order`, `reject_order`, `good_order`, `report_order`) VALUES ('2015-10-14 00:00:00', '微信朋友圈H5页面', 'iOS APP', '广州', 17134, 11270, 549, 204, 224, 10234, 773);INSERT INTO `sql12298540`.`order_analysis` (`date`, `user_src`, `order_src`, `order_location`, `new_order`, `payed_order`, `pending_order`, `cancel_order`, `reject_order`, `good_order`, `report_order`) VALUES ('2015-10-17 00:00:00', '地推二维码扫描', 'iOS APP', '北京', 16061, 9418, 1220, 1247, 458, 13877, 749);INSERT INTO `sql12298540`.`order_analysis` (`date`, `user_src`, `order_src`, `order_location`, `new_order`, `payed_order`, `pending_order`, `cancel_order`, `reject_order`, `good_order`, `report_order`) VALUES ('2015-10-17 00:00:00', '微信朋友圈H5页面', '微信公众号', '武汉', 12749, 11127, 1773, 6, 5, 9874, 678);INSERT INTO `sql12298540`.`order_analysis` (`date`, `user_src`, `order_src`, `order_location`, `new_order`, `payed_order`, `pending_order`, `cancel_order`, `reject_order`, `good_order`, `report_order`) VALUES ('2015-10-18 00:00:00', '地推二维码扫描', 'iOS APP', '上海', 13086, 15882, 1727, 1764, 1429, 12501, 625);INSERT INTO `sql12298540`.`order_analysis` (`date`, `user_src`, `order_src`, `order_location`, `new_order`, `payed_order`, `pending_order`, `cancel_order`, `reject_order`, `good_order`, `report_order`) VALUES ('2015-10-18 00:00:00', '微信朋友圈H5页面', 'iOS APP', '武汉', 15129, 15598, 1204, 1295, 1831, 11500, 320);INSERT INTO `sql12298540`.`order_analysis` (`date`, `user_src`, `order_src`, `order_location`, `new_order`, `payed_order`, `pending_order`, `cancel_order`, `reject_order`, `good_order`, `report_order`) VALUES ('2015-10-19 00:00:00', '地推二维码扫描', 'Android APP', '杭州', 20687, 18526, 1398, 550, 213, 12911, 185);INSERT INTO `sql12298540`.`order_analysis` (`date`, `user_src`, `order_src`, `order_location`, `new_order`, `payed_order`, `pending_order`, `cancel_order`, `reject_order`, `good_order`, `report_order`) VALUES ('2015-10-19 00:00:00', '应用商店', '微信公众号', '武汉', 12388, 11422, 702, 106, 158, 5820, 474);INSERT INTO `sql12298540`.`order_analysis` (`date`, `user_src`, `order_src`, `order_location`, `new_order`, `payed_order`, `pending_order`, `cancel_order`, `reject_order`, `good_order`, `report_order`) VALUES ('2015-10-20 00:00:00', '微信朋友圈H5页面', '微信公众号', '上海', 14298, 11682, 1880, 582, 154, 7348, 354);INSERT INTO `sql12298540`.`order_analysis` (`date`, `user_src`, `order_src`, `order_location`, `new_order`, `payed_order`, `pending_order`, `cancel_order`, `reject_order`, `good_order`, `report_order`) VALUES ('2015-10-21 00:00:00', '地推二维码扫描', 'Android APP', '深圳', 22079, 14333, 5565, 1742, 439, 8246, 211);INSERT INTO `sql12298540`.`order_analysis` (`date`, `user_src`, `order_src`, `order_location`, `new_order`, `payed_order`, `pending_order`, `cancel_order`, `reject_order`, `good_order`, `report_order`) VALUES ('2015-10-22 00:00:00', 'UC浏览器引流', 'iOS APP', '上海', 28968, 18151, 7212, 2373, 1232, 10739, 578);

3.2 doris数据库准备

下面是我上面数据表在doris对应的建表脚本

CREATE TABLE `order_analysis` (`date` datetime DEFAULT NULL,`user_src` varchar(30) DEFAULT NULL,`order_src` varchar(50) DEFAULT NULL,`order_location` varchar(10) DEFAULT NULL,`new_order` int DEFAULT NULL,`payed_order` int DEFAULT NULL,`pending_order` int DEFAULT NULL,`cancel_order` int DEFAULT NULL,`reject_order` int DEFAULT NULL,`good_order` int DEFAULT NULL,`report_order` int DEFAULT NULL) ENGINE=OLAPDUPLICATE KEY(`date`,user_src)COMMENT "OLAP"DISTRIBUTED BY HASH(`user_src`) BUCKETS 1PROPERTIES ("replication_num" = "3","in_memory" = "false","storage_format" = "V2");

3.3 Datax Job JSON文件

创建并编辑datax job任务json文件，并保存到指定目录

 {"job": {"setting": {"speed": {"channel": 1},"errorLimit": {"record": 0,"percentage": 0}},"content": [{"reader": {"name": "mysqlreader","parameter": {"username": "root","password": "zh","column": ["date","user_src","order_src","order_location","new_order","payed_order"," pending_order"," cancel_order"," reject_order"," good_order"," report_order" ],"connection": [ { "table": [ "order_analysis" ], "jdbcUrl": [ "jdbc:mysql://localhost:3306/demo" ] } ] }},"writer": {"name": "doriswriter","parameter": {"feLoadUrl": ["fe:8030"],"beLoadUrl": ["be1:8040","be1:8040","be1:8040","be1:8040","be1:8040","be1:8040"],"jdbcUrl": "jdbc:mysql://fe:9030/","database": "test_2","table": "order_analysis","column": ["date","user_src","order_src","order_location","new_order","payed_order"," pending_order"," cancel_order"," reject_order"," good_order"," report_order"],"username": "root","password": "","postSql": [],"preSql": [],"loadProps": {},"maxBatchRows" : 10000,"maxBatchByteSize" : 104857600,"labelPrefix": "datax_doris_writer_demo_","lineDelimiter": "\n"}}}]}}

这块 Mysql reader 使用方式参照：

https://github.com/alibaba/DataX/blob/master/mysqlreader/doc/mysqlreader.md

doriswriter的使用及参数说明：

 https://github.com/apache/incubator-doris/blob/master/extension/DataX/doriswriter/doc/doriswriter.md

或者

{
"job": {
"setting": {
"speed": {
"channel": 1
},
"errorLimit": {
"record": 0,
"percentage": 0
}
},
"content": [
{
"reader": {
"name": "mysqlreader",
"parameter": {
"username": "root",
"password": "My",
"column": ["id","md5","eid","industry_code","start_date","end_date","is_valid","source","create_time ","update_time","row_update_time","local_row_update_time"],
"connection": [ { "table": [ "t_last_industry_all" ], "jdbcUrl": [ "jdbc:mysql://IP:3306/log" ] } ] }
},
"writer": {
"name": "doriswriter",
"parameter": {
"feLoadUrl": ["IP:8030"],
"beLoadUrl": ["IP:8040"],
"jdbcUrl": "jdbc:mysql://IP:9030/",
"database": "mysqltodoris",
"table": "t_last",
"column": ["id","md5","eid","industry_code","start_date","end_date","is_valid","source","create_time ","update_time","row_update_time","local_row_update_time"],
"username": "root",
"password": "123456",
"postSql": [],
"preSql": [],
"loadProps": {
},
"maxBatchRows" : 300000,
"maxBatchByteSize" : 20971520
}
}
}
]
}
}