datax可以理解為sqoop的優(yōu)化版，

速度比sqoop快

因為sqoop底層是map任務，而datax底層是基于內存

DataX 是一個異構數據源離線同步工具，致力于實現包括關系型數據庫(MySQL、Oracle等)、HDFS、Hive、ODPS、HBase、FTP等各種異構數據源之間穩(wěn)定高效的數據同步功能

datax 是讓你編寫 json

flume 是讓你編寫 conf

azkaban 是讓你編寫 flow

sqoop 是讓你寫命令

將mysql中的數據導入到hdfs上

{"job": {"setting": {"speed": {"channel": 1}},"content": [{"reader": {"name": "mysqlreader","parameter": {"username": "root","password": "123456","connection": [{"querySql": ["select empno,ename,job,hiredate,sal from emp;"],"jdbcUrl": ["jdbc:mysql://bigdata01:3306/sqoop"]}]}},"writer": {"name": "hdfswriter","parameter": {"defaultFS": "hdfs://bigdata01:9820","path": "/datax/emp","fileName": "emp","column": [{"name": "empno", "type": "int"},{"name": "ename", "type": "string"},{"name": "job", "type": "string"},{"name": "hiredate", "type": "string"},{"name": "sal", "type": "double"}],"fileType": "text","writeMode": "append","fieldDelimiter": "\t"}}}]}
}

將hdfs上的數據導入到mysql中

{"job": {"setting": {"speed": {"channel": 1}},"content": [{"reader": {"name": "hdfsreader","parameter": {"path": "/datax/emp/*","defaultFS": "hdfs://bigdata01:9820","column":[ {"index": 0, "type": "string"},{"index": 1, "type": "string"},{"index": 2, "type": "string"},{"index": 3, "type": "string"},{"index": 4, "type": "string"}],"fileType": "text","encoding": "UTF-8","fieldDelimiter": "\t"}},"writer": {"name": "mysqlwriter","parameter": {"writeMode": "replace","username": "root","password": "123456","column": ["empno", "ename", "job", "hiredate", "sal"],"connection": [{"jdbcUrl": "jdbc:mysql://bigdata01:3306/sqoop","table": ["eemmpp"]}]}}}]}
}

使用注意

注意點：

1）指定字段的類型時，datax中的類型只有下面幾種，而不是像java一樣的

2）默認的分隔符，即 "fieldDelimiter": "xxx" 不指定或者不寫的時候，默認為 ' , ' 分割

3）

將mysql 中的數據導入hive（重要）*

說是把mysql中的數據導入hive，其實本質還是將mysql中的數據導入hdfs中

首先先創(chuàng)建一個hive表 指定到hdfs的路徑上，再將mysql中的數據導入到這個路徑即可

1）首先先創(chuàng)建一個hive表

reate external table if not exists ods_01_base_area ( id int COMMENT 'id標識', area_code string COMMENT '省份編碼', province_name string COMMENT '省份名稱', iso string COMMENT 'ISO編碼' )row format delimited fields terminated by ',' stored as TextFile location '/data/nshop/ods/ods_01_base_area/'; -- 指定到hdfs的路徑

2）將mysql的數據通過datax導入hdfs

注意指定路徑和分隔符 ！ 一定要與創(chuàng)建hive表指定的路徑一致 且 分隔符也保持一致

{"job": {"setting": {"speed": {"channel": 1}},"content": [{"reader": {"name": "mysqlreader","parameter": {"username": "root","password": "123456","column": ["id","area_code","province_name","iso"],"splitPk": "id","connection": [{"table": ["base_area"],"jdbcUrl": ["jdbc:mysql://bigdata01:3306/datax"]}]}},"writer": {"name": "hdfswriter","parameter": {"defaultFS": "hdfs://bigdata01:9820","path": "/data/nshop/ods/ods_01_base_area/","fileName": "base_area","column": [{"name": "id","type": "int"},{"name": "area_code","type": "string"},{"name": "province_name","type": "string"},{"name": "iso","type": "string"}],"fileType": "text","writeMode": "append","fieldDelimiter": ","}}}]}
}

3） 導入完成，此時hive表中就有了數據