一、介绍
本文主要介绍DataX的安装与使用。
二、安装
安装:DataX/userGuid.md at master · alibaba/DataX · GitHub
六、案例
实现从MySQL同步数据到HDFS,然后使用Hive进行聚合计算并将结果存储回MySQL。
步骤2:使用DataX同步MySQL数据到HDFS
创建一个DataX作业配置文件(例如mysql_to_hdfs.json
),内容如下:
{"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"}}}]}
}
运行DataX作业:
python datax.py ./mysql_to_hdfs.json
步骤3:使用Hive创建外部表映射到HDFS上的数据
在Hive中创建一个外部表,映射到HDFS上的数据文件:
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';
步骤4:在Hive中进行聚合计算
在Hive中执行你的聚合查询,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;
步骤5:将Hive计算结果导出到MySQL
创建一个DataX作业配置文件(例如hdfs_to_mysql.json
),内容如下:
{"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"]}]}}}]}
}
运行DataX作业:
python datax.py ./hdfs_to_mysql.json