1. 官网

• 地址如下：
  https://github.com/alibaba/DataX/blob/master/userGuid.md.
• 简介
  
  

2. 工具部署（通过下载DataX工具包）

2.1 下载、解压

• 因为官网很详细，这里就简单记录一下：
  下载 datax.tar.gz ，然后解压，命令如下：

  tar -zxvf datax.tar.gz
  

  
• 查看解压后的目录
  

2.2 配置

2.2.1 查看配置模版

• 命令如下：

  python datax.py -r streamreader -w streamwriter
  

  

2.2.2 根据模版配置json

• 创建stream2stream.json文件，如下：

  cd /Users/susu/study_down/about_datax/datax/jobvim stream2stream.json
  

• stream2stream.json 内容如下：

  #stream2stream.json
  {"job": {"content": [{"reader": {"name": "streamreader","parameter": {"sliceRecordCount": 10,"column": [{"type": "long","value": "10"},{"type": "string","value": "hello，你好，世界-DataX"}]}},"writer": {"name": "streamwriter","parameter": {"encoding": "UTF-8","print": true}}}],"setting": {"speed": {"channel": 5}}}
  }
  

2.2.3 启动DataX

• 启动命令，开始同步，如下：

  python ../bin/datax.py stream2stream.json
  

  
  
• 同步结束，查看日志如下：
  

3. datax的简单使用

• 环境有限，下面就以mysql为主了，mysql_to_别的数据库，后续有机会再做介绍

3.1 mysql2stream

• 使用命令先查看模版：

  python datax.py -r mysqlreader -w streamwriter
  

• mysql2stream.json 如下：

  {"job": {"setting": {"speed": {"channel": 3},"errorLimit": {"record": 0,"percentage": 0.02}},"content": [{"reader": {"name": "mysqlreader","parameter": {"username": "root","password": "susu@123","column": ["dog_num","dog_name"],"splitPk": "dog_num","connection": [{"table": ["dog"],"jdbcUrl": ["jdbc:mysql://127.0.0.1:3306/datax_1"]}]}},"writer": {"name": "streamwriter","parameter": {"print": true}}}]}
  }

• 效果如下：

  python ../bin/datax.py mysql2stream.json
  

  

3.2 mysql2mysql

• 使用命令先查看模版：

  python datax.py -r mysqlreader -w mysqlwriter
  

3.2.1 拼接where的

• mysql2mysql_where.json文件如下：

  {"job": {"content": [{"reader": {"name": "mysqlreader","parameter": {"column": ["*"],"connection": [{"jdbcUrl": ["jdbc:mysql://127.0.0.1:3306/datax_1"],"table": ["dog"]}],"username": "root","password": "susu@123","where": "dog_num=1000003"}},"writer": {"name": "mysqlwriter","parameter": {"column": ["*"],"connection": [{"jdbcUrl": "jdbc:mysql://127.0.0.1:3306/datax_2","table": ["dog"]}],"username": "root","password": "susu@123","writeMode": "insert"}}}],"setting": {"speed": {"channel": "1"}}}
  }

• 效果如下：

  python ../bin/datax.py mysql2mysql_where.json
  

  
  

3.2.2 直接写查询的sql语句的

• 使用querySql参数（注意querySql 和 SQL 只能保留一个），如下：
  
  
• mysql2mysql_query.json 文件代码如下：

  {"job": {"content": [{"reader": {"name": "mysqlreader","parameter": {"connection": [{"jdbcUrl": ["jdbc:mysql://127.0.0.1:3306/datax_1"],"querySql": ["select t.dog_num,t.dog_name,t.db_source from dog t where dog_num=1000004"]}],"username": "root","password": "susu@123"}},"writer": {"name": "mysqlwriter","parameter": {"column": ["*"],"connection": [{"jdbcUrl": "jdbc:mysql://127.0.0.1:3306/datax_2","table": ["dog"]}],"username": "root","password": "susu@123","writeMode": "insert"}}}],"setting": {"speed": {"channel": "1"}}}
  }

• 效果如下：

  python ../bin/datax.py mysql2mysql_query.json
  

  
  

4. 解释

4.1 json中seeting说明

• 关于seeting

  settingspeed表示控制并发数channel设置并发的数量如果设置的print为true，则会打印slicRecordCount*channel次如果是从mysql导入hdfs等其他操作，则会是真正代表并发数，而不是打印多少次
  

4.2 参数说明（以mysql为例）

• 其他的，从官网截图来看吧：
  https://github.com/alibaba/DataX/blob/master/mysqlreader/doc/mysqlreader.md.