wordpress自动连接插件,索引擎优化 seo,做网站的书知乎,用地方名字做网站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#xff0c;本文是在 windows 下的 WLS 下进行编译的
首先从github上拉取源码 … 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 moduledoriswriter/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.skiptrue 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) ENGINEInnoDB DEFAULT CHARSETutf8 ROW_FORMATCOMPACT
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) ENGINEOLAPDUPLICATE KEY(date,user_src)COMMENT OLAPDISTRIBUTED 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 } } } ] } }
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 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
