DataX之MySQL数据写入Hive_datax写入hive

1、编写脚本mysql-to-hive.json

{
    "job": {
        "setting": {
            "speed": {
                 "channel": 3
            },
            "errorLimit": {
                "record": 0,
                "percentage": 0.02
            }
        },
        "content": [
            {
                "reader": {
                    "name": "mysqlreader",
                    "parameter": {
                        "username": "用户名",
                        "password": "密码",
                        "column": [
				"deptno",
				"dname",
				"loc"
                        ],
                        "connection": [
                            {
                                "table": [
                                    "dept"
                                ],
                                "jdbcUrl": [
					"jdbc:mysql://IP:3306/test"
                                ]
                            }
                        ]
                    }
                },
               "writer": {
                    "name": "hdfswriter",
                    "parameter": {
			"defaultFS": "hdfs://hdfs-ha",
		    "hadoopConfig":{
			"dfs.nameservices": "hdfs-ha",
			"dfs.ha.namenodes.hdfs-ha": "nn1,nn2",
			"dfs.namenode.rpc-address.hdfs-ha.nn1": "node01:8020",
			"dfs.namenode.rpc-address.hdfs-ha.nn2": "node02:8020",
			"dfs.client.failover.proxy.provider.hdfs-ha": "org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider"
			},
                        "fileType": "text",
                        "path": "/user/hive/warehouse/ods.db/datax_dept",
                        "fileName": "202104",
                        "column": [
                            {
                                "name": "deptno",
                                "type": "int"
                            },
                            {
                                "name": "dname",
                                "type": "varchar"
                            },
                            {
                                "name": "loc",
                                "type": "varchar"
                            }
                        ],
                        "writeMode": "append",
                        "fieldDelimiter": "\t"
                    }
                }
            }
        ]
    }
}

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2、执行脚本

/datax/bin/datax.py ./mysql-to-hive.json
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