ETL异构数据源Datax_工具部署

ETL异构数据源Datax_工具部署_02

接上一篇：(企业内部) ETL异构数据源Datax_部署前置环境_01
https://gblfy.blog.csdn.net/article/details/118081253

文章目录

- - - - 一、直接下载DataX
      - 二、下载DataX源码，自己编译
      - 2.1.下载DataX源码
        2.2. 通过maven打包
      - 三、配置示例
      - 3.1. 创建作业的配置文件（json格式）
        3.2. 根据模板配置json
        3.3. 执行测试

一、直接下载DataX

：DataX下载地址

下载后解压至本地某个目录，进入bin目录，即可运行同步作业：

tar zxvf datax.tar.gz
cd  { YOUR_DATAX_HOME}/bin
python datax.py { YOUR_JOB.json}

自检脚本：

python { YOUR_DATAX_HOME}/bin/datax.py { YOUR_DATAX_HOME}/job/job.json

二、下载DataX源码，自己编译

DataX源码

2.1.下载DataX源码

git clone git@github.com:alibaba/DataX.git

2.2. 通过maven打包

cd  { DataX_source_code_home}
mvn -U clean package assembly:assembly -Dmaven.test.skip=true

打包成功，日志显示如下：

[INFO] BUILD SUCCESS
[INFO] -----------------------------------------------------------------
[INFO] Total time: 08:12 min
[INFO] Finished at: 2021-12-13T16:26:48+08:00
[INFO] Final Memory: 133M/960M
[INFO] -----------------------------------------------------------------

打包成功后的DataX包位于 {DataX_source_code_home}/target/datax/datax/ ，结构如下：

bin        conf        job        lib        log        log_perf    plugin        script        tmp

三、配置示例

从stream读取数据并打印到控制台

3.1. 创建作业的配置文件（json格式）

可以通过命令查看配置模板： 
python datax.py -r { YOUR_READER} -w { YOUR_WRITER}
cd  { YOUR_DATAX_HOME}/bin
python datax.py -r streamreader -w streamwriter
----------------------------------------------------------
# 查看常用作业的配置文件模板
python datax.py -r streamreader -w streamwriter
python datax.py -r oraclereader -w mysqlwriter
python datax.py -r mysqlreader -w oraclewriter
控制台输出
```bash
DataX (DATAX-OPENSOURCE-3.0), From Alibaba !
Copyright (C) 2010-2017, Alibaba Group. All Rights Reserved.
Please refer to the streamreader document:
     https://github.com/alibaba/DataX/blob/master/streamreader/doc/streamreader.md 
Please refer to the streamwriter document:
     https://github.com/alibaba/DataX/blob/master/streamwriter/doc/streamwriter.md 
Please save the following configuration as a json file and  use
     python { DATAX_HOME}/bin/datax.py { JSON_FILE_NAME}.json 
to run the job.
{ 
    "job": { 
        "content": [
            { 
                "reader": { 
                    "name": "streamreader", 
                    "parameter": { 
                        "column": [], 
                        "sliceRecordCount": ""
                    }
                }, 
                "writer": { 
                    "name": "streamwriter", 
                    "parameter": { 
                        "encoding": "", 
                        "print": true
                    }
                }
            }
        ], 
        "setting": { 
            "speed": { 
                "channel": ""
            }
        }
    }
}

3.2. 根据模板配置json

vim stream2stream.json
添加内容如下：
{ 
  "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
       }
    }
  }
}

3.3. 执行测试

启动DataX

cd { YOUR_DATAX_DIR_BIN}
python datax.py ./stream2stream.json
同步结束，显示日志如下：
...
2021-06-23 09:43:14.869 [job-0] INFO  StandAloneJobContainerCommunicator - Total 50 records, 950 bytes | Speed 95B/s, 5 records/s | Error 0 records, 0 bytes |  All Task WaitWriterTime 0.000s |  All Task WaitReaderTime 0.000s | Percentage 100.00%
2021-06-23 09:43:14.872 [job-0] INFO  JobContainer - 
任务启动时刻                    : 2021-06-23 09:43:04
任务结束时刻                    : 2021-06-23 09:43:14
任务总计耗时                    :                 10s
任务平均流量                    :               95B/s
记录写入速度                    :              5rec/s
读出记录总数                    :                  50
读写失败总数                    :                   0