一、介紹

本文主要介紹DataX的安裝與使用。

二、安裝

安裝：DataX/userGuid.md at master · alibaba/DataX · GitHub

六、案例

實現從MySQL同步數據到HDFS，然后使用Hive進行聚合計算并將結果存儲回MySQL。

步驟2：使用DataX同步MySQL數據到HDFS

創建一個DataX作業配置文件（例如mysql_to_hdfs.json），內容如下：

{"job": {"content": [{"reader": {"name": "mysqlreader","parameter": {"username": "your_mysql_username","password": "your_mysql_password","column": ["*"],"connection": [{"table": ["your_mysql_table"],"jdbcUrl": ["jdbc:mysql://your_mysql_host:3306/your_database"]}]}},"writer": {"name": "hdfswriter","parameter": {"defaultFS": "hdfs://your_hdfs_namenode:8020","fileType": "text","path": "/user/hive/warehouse/your_hdfs_directory","fileName": "your_file_name","column": [{"name": "column1","type": "string"},{"name": "column2","type": "string"},// 添加其他列],"writeMode": "append"}}}]}
}

運行DataX作業：

python datax.py ./mysql_to_hdfs.json

步驟3：使用Hive創建外部表映射到HDFS上的數據

在Hive中創建一個外部表，映射到HDFS上的數據文件：

CREATE EXTERNAL TABLE your_hive_table (column1 string,column2 string,// 添加其他列
)
ROW FORMAT DELIMITED
FIELDS TERMINATED BY ','
STORED AS TEXTFILE
LOCATION '/user/hive/warehouse/your_hdfs_directory';

步驟4：在Hive中進行聚合計算

在Hive中執行你的聚合查詢，例如：

INSERT OVERWRITE DIRECTORY '/user/hive/warehouse/your_hive_output_directory'
ROW FORMAT DELIMITED
FIELDS TERMINATED BY ','
SELECT column1, COUNT(column2)
FROM your_hive_table
GROUP BY column1;

步驟5：將Hive計算結果導出到MySQL

創建一個DataX作業配置文件（例如hdfs_to_mysql.json），內容如下：

{"job": {"content": [{"reader": {"name": "hdfsreader","parameter": {"path": "/user/hive/warehouse/your_hive_output_directory","defaultFS": "hdfs://your_hdfs_namenode:8020","column": [{"name": "column1","type": "string"},{"name": "count_column2","type": "long"}],"fileType": "text","encoding": "UTF-8","fieldDelimiter": ","}},"writer": {"name": "mysqlwriter","parameter": {"username": "your_mysql_username","password": "your_mysql_password","writeMode": "replace","column": ["column1", "count_column2"],"connection": [{"table": ["your_mysql_output_table"],"jdbcUrl": ["jdbc:mysql://your_mysql_host:3306/your_database"]}]}}}]}
}

運行DataX作業：

python datax.py ./hdfs_to_mysql.json