DataX 实战案例 -- 使用datax实现将mysql数据导入到hdfs

• 需求: 将mysql表student的数据导入到hdfs的 /datax/mysql2hdfs/ 路径下面去。

• 1、创建mysql数据库和需要用到的表结构，并导入实战案例需要用到的数据

    [hadoop@hadoop02 ~] mysql -uroot -p123456
    mysql> create database datax;
    mysql> use datax;
    mysql> create table student(id int,name varchar(20),age int,createtime timestamp );
    mysql> insert into `student` (`id`, `name`, `age`, `createtime`) values(‘1‘,‘zhangsan‘,‘18‘,‘2021-05-10 18:10:00‘);
    mysql> insert into `student` (`id`, `name`, `age`, `createtime`) values(‘2‘,‘lisi‘,‘28‘,‘2021-05-10 19:10:00‘);
    mysql> insert into `student` (`id`, `name`, `age`, `createtime`) values(‘3‘,‘wangwu‘,‘38‘,‘2021-05-10 20:10:00‘);
  

• 2、创建作业的配置文件（json格式）

  • 查看配置模板，执行脚本命令

    [hadoop@hadoop03 datax]$ cd /bigdata/install/datax
    [hadoop@hadoop03 datax]$ python bin/datax.py -r mysqlreader -w hdfswriter
    
    DataX (DATAX-OPENSOURCE-3.0), From Alibaba !
    Copyright (C) 2010-2017, Alibaba Group. All Rights Reserved.
    
    Please refer to the mysqlreader document:
         https://github.com/alibaba/DataX/blob/master/mysqlreader/doc/mysqlreader.md 
    
    Please refer to the hdfswriter document:
         https://github.com/alibaba/DataX/blob/master/hdfswriter/doc/hdfswriter.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": "mysqlreader", 
                        "parameter": {
                            "column": [], 
                            "connection": [
                                {
                                    "jdbcUrl": [], 
                                    "table": []
                                }
                            ], 
                            "password": "", 
                            "username": "", 
                            "where": ""
                        }
                    }, 
                    "writer": {
                        "name": "hdfswriter", 
                        "parameter": {
                            "column": [], 
                            "compress": "", 
                            "defaultFS": "", 
                            "fieldDelimiter": "", 
                            "fileName": "", 
                            "fileType": "", 
                            "path": "", 
                            "writeMode": ""
                        }
                    }
                }
            ], 
            "setting": {
                "speed": {
                    "channel": ""
                }
            }
        }
    }
    

  • 其中hdfswriter插件文档
    • https://github.com/alibaba/DataX/blob/master/hdfswriter/doc/hdfswriter.md

• 3、根据模板写配置文件

  • 进入到 /bigdata/install/datax/job 目录，然后创建配置文件 mysql2hdfs.json, 文件内容如下：

    {
        "job": {
            "setting": {
                "speed": {
                     "channel":1
                }
            },
            "content": [
                {
                    "reader": {
                        "name": "mysqlreader",
                        "parameter": {
                            "username": "root",
                            "password": "123456",
                            "connection": [
                                {
                                    "querySql": [
                                        "select id,name,age,createtime from student where age < 30;"
                                    ],
                                    "jdbcUrl": [
                                        "jdbc:mysql://hadoop02:3306/datax"
                                    ]
                                }
                            ]
                        }
                    },
                      "writer": {
                        "name": "hdfswriter",
                        "parameter": {
                            "defaultFS": "hdfs://hadoop01:8020",
                            "fileType": "text",
                            "path": "/datax/mysql2hdfs/",
                            "fileName": "student.txt",
                            "column": [
                                {
                                    "name": "id",
                                    "type": "INT"
                                },
                                {
                                    "name": "name",
                                    "type": "STRING"
                                },
                                {
                                    "name": "age",
                                    "type": "INT"
                                },
                                {
                                    "name": "createtime",
                                    "type": "TIMESTAMP"
                                }
                            ],
                            "writeMode": "append",
                            "fieldDelimiter": "\t",
                            "compress":"gzip"
                        }
                    }
                }
            ]
        }
    }
    

• 4、启HDFS, 创建目标路径

  [hadoop@hadoop01 ~]$ start-dfs.sh 
  [hadoop@hadoop01 ~]$ hdfs dfs -mkdir -p /datax/mysql2hdfs
  

• 5、启动DataX

  [hadoop@hadoop03 bin]$ cd /bigdata/install/datax
  [hadoop@hadoop03 bin]$ python bin/datax.py job/mysql2hdfs.json 
  

• 6、观察控制台输出结果

  同步结束，显示日志如下：
  
  2021-06-18 01:41:26.452 [job-0] INFO  JobContainer - 
  任务启动时刻                    : 2021-06-18 01:41:14
  任务结束时刻                    : 2021-06-18 01:41:26
  任务总计耗时                    :                 11s
  任务平均流量                    :                3B/s
  记录写入速度                    :              0rec/s
  读出记录总数                    :                   2
  读写失败总数                    :                   0
  

• 7、查看HDFS上文件生成，并验证结果
  

  将上边结果下载解压后打开，可以看到里面的结果和mysql中结果对比
  

  

DataX 实战案例 -- 使用datax实现将mysql数据导入到hdfs

原文：https://www.cnblogs.com/tenic/p/14901689.html