DataX(MySQL同步数据到Doris)

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:

  1. 将 DataX 代码库 clone 到本地。
  2. 将 doriswriter/ 目录软链到 DataX/doriswriter 目录。
  3. 在 DataX/pom.xml 文件中添加 doriswriter 模块。
  4. 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。
  5. 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

 hbase11xreader
 hbase094xreader
 tsdbreader
 oceanbasev10reader
 odpswriter
 hdfswriter
 adswriter
 ocswriter
 oscarwriter
 oceanbasev10writer

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

DataX(MySQL同步数据到Doris)_第1张图片

DataX(MySQL同步数据到Doris)_第2张图片

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=OLAP
 DUPLICATE KEY(`date`,user_src)
 COMMENT "OLAP"
 DISTRIBUTED BY HASH(`user_src`) BUCKETS 1
 PROPERTIES (
 "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
                    }
                }
            }
        ]
    }
}

4.执行Datax数据导入任务

python bin/datax.py doris.json
然后就可以看到执行结果:

DataX(MySQL同步数据到Doris)_第3张图片

再去 Doris 数据库中查看你的表,数据就已经导入进去了,任务执行结束

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