DataX从Mysql导数据到Hive分区表案例

0、下载DataX并解压到对应目录
DataX安装包，开箱即用，无需配置。
https://datax-opensource.oss-cn-hangzhou.aliyuncs.com/202308/datax.tar.gz
相关参考文档
https://github.com/alibaba/DataX/blob/master/hdfswriter/doc/hdfswriter.md

1、Hive分区表DDL样例
注意分隔符号要和后续的DataX配置保持一致，同时在此将贴源层数据类型统一为String。

CREATE TABLE datax.fin_transaction_flow (
  transaction_id     STRING COMMENT '交易唯一ID（主键）',
  account_no         STRING COMMENT '账户号（外键 -> account_info.account_no）',
  transaction_code   STRING COMMENT '交易类型编码（外键 -> transaction_reference.transaction_code）',
  amount             STRING COMMENT '交易金额（格式：整数部分18位，小数2位）',
  currency           STRING COMMENT '币种（如CNY/USD）',
  counterparty_account STRING COMMENT '对手账户（外键 -> account_info.account_no）',
  transaction_time   STRING COMMENT '交易时间（格式：yyyy-MM-dd HH:mm:ss）',
  status             STRING COMMENT '交易状态（成功/失败）',
  channel            STRING COMMENT '交易渠道（ATM/网银）'
)
PARTITIONED BY (dt STRING)
ROW FORMAT DELIMITED FIELDS TERMINATED BY '\b'
STORED AS ORC ;

2、DataX Json配置样例
创建以下Json文件(mysql-hive.json)并放置到DataX节点合适目录下。

{
  "job": {
    "setting": {
      "speed": {
        "channel": 4
      }
    },
    "content": [
      {
        "reader": {
          "name": "mysqlreader",
          "parameter": {
            "username": "root",
            "password": "pwd",
            "connection": [
              {
                "querySql": [
                  "select  transaction_id,account_no,transaction_code,amount,currency,counterparty_account,transaction_time,status,channel from fin_transaction_flow where dt='20250416';"
                ],
                "jdbcUrl": [
                  "jdbc:mysql://chdp01:3306/bg2025"
                ]
              }
            ]
          }
        },
        "writer": {
          "name": "hdfswriter",
          "parameter": {
            "defaultFS": "hdfs://chdp01:9000",
            "fileType": "orc",
            "path": "/user/hive/warehouse/datax.db/fin_transaction_flow/dt=20250416",
            "fileName": "xxxx",
            "column": [
              {
                "name": "transaction_id",
                "type": "STRING"
              },
              {
                "name": "account_no",
                "type": "STRING"
              },
              {
                "name": "transaction_code",
                "type": "STRING"
              },
              {
                "name": "amount",
                "type": "STRING"
              },
              {
                "name": "currency",
                "type": "STRING"
              },
              {
                "name": "counterparty_account",
                "type": "STRING"
              },
              {
                "name": "transaction_time",
                "type": "STRING"
              },
              {
                "name": "status",
                "type": "STRING"
              },
              {
                "name": "channel",
                "type": "STRING"
              }
            ],
            "writeMode": "append",
            "fieldDelimiter": "\b",
            "compress": "NONE"
          }
        }
      }
    ]
  }
}

3、手动创建对应分区目录

hadoop fs -mkdir /user/hive/warehouse/datax.db/fin_transaction_flow/dt=20250416

4、执行DataX

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

看最终状态显示成功

hdfs目标目录里也有了对应文件

5、添加分区信息
经过上述操作还不能直接从hive表里查询出数据，因为元数据信息尚未构建起来。

ALTER TABLE datax.fin_transaction_flow ADD IF NOT EXISTS PARTITION (dt='20250416');

6、验证数据

7、问题：发现count数据为0

select count(*) from datax.fin_transaction_flow;

这个是因为hive未及时构建表分析信息导致，手动执行如下表分析sql即可

analyze table datax.fin_transaction_flow compute statistics;