一、Datax介绍
官网： DataX/introduction.md at master · alibaba/DataX · GitHub
DataX 是阿里云 DataWorks数据集成 的开源版本，在阿里巴巴集团内被广泛使用的
离线数据同步工具/平台。DataX 实现了包括 MySQL、Oracle、OceanBase、SqlServer、Postgre、HDFS、Hive、ADS、HBase、TableStore(OTS)、MaxCompute(ODPS)、Hologres、DRDS, databend 等各种异构数据源之间高效的数据同步功能。
Datax架构说明
Datax数据处理流程
二、Datax的使用说明
Datax在使用是主要编写json文件，在json中定义read如何读取 write如何写入
-
格式
{
"job": {
"setting": {
"speed": {
"channel": 3
},
"errorLimit": {
"record": 0,
"percentage": 0.02
}
},
"content": [
{
"reader": {
"name": "mysqlreader",
"parameter": {
"username": "root",
"password": "123456",
"column": [
"id",
"name"
],
"splitPk": "db_id",
"connection": [
{
"table": [
"table"
],
"jdbcUrl": [
"jdbc:mysql://127.0.0.1:3306/database"
]
}
]
}
},
"writer": {
"name": "streamwriter",
"parameter": {
"print":true
}
}
}
]
}
}
简单使用
读取mysql数据在终端中输出结果
-- 在mysql中创建库表 create database itcast charset=utf8; use itcast; create table student( id int, name varchar(20), age int, gender varchar(20) ); insert into student values(1,'张三',20,'男'), (2,'李四',21,'男'), (3,'王五',19,'男'), (4,'赵六',22,'男');
编写datax的json文件
{
"job": {
"setting": {
"speed": {
"channel": 3
},
"errorLimit": {
"record": 0,
"percentage": 0.02
}
},
"content": [
{
"reader": {
"name": "mysqlreader",
"parameter": {
"username": "root",
"password": "123456",
"column": [
"id",
"name",
"age",
"gender"
],
"splitPk": "id",
"connection": [
{
"table": [
"student"
],
"jdbcUrl": [
"jdbc:mysql://192.168.88.80:3306/itcast"
]
}
]
}
},
"writer": {
"name": "streamwriter",
"parameter": {
"print":true
}
}
}
]
}
}
在datax的job目录下创建json文件
cd /export/server/datax/job/
执行json文件中的配置信息
cd /export/server/datax/bin python datax.py ../job/mysql_data.json
Mysql使用sql语句读取数据
sql语句可以实现对数据的筛选过滤
{
"job": {
"setting": {
"speed": {
"channel":1
}
},
"content": [
{
"reader": {
"name": "mysqlreader",
"parameter": {
"username": "root",
"password": "123456",
"connection": [
{
"querySql": [
"select * from student where id>=3;"
],
"jdbcUrl": [
"jdbc:mysql://192.168.88.80:3306/itcast"
]
}
]
}
},
"writer": {
"name": "streamwriter",
"parameter": {
"print": true,
"encoding": "UTF-8"
}
}
}
]
}
}
三、Mysql数据导入HDFS
读取mysql数据
写入到hdfs
{
"job": {
"setting": {
"speed": {
"channel":1
}
},
"content": [
{
"reader": {
"name": "mysqlreader",
"parameter": {
"username": "root",
"password": "123456",
"column": [
"id",
"name",
"age",
"gender"
],
"splitPk": "id",
"connection": [
{
"table": [
"student"
],
"jdbcUrl": [
"jdbc:mysql://192.168.88.80:3306/itcast"
]
}
]
}
},
"writer": {
"name": "hdfswriter",
"parameter": {
"defaultFS": "hdfs://192.168.88.80:8020",
"fileType": "text",
"path": "/data",
"fileName": "student",
"column": [
{
"name": "id",
"type": "int"
},
{
"name": "name",
"type": "string"
},
{
"name": "age",
"type": "INT"
},
{
"name": "gender",
"type": "string"
}
],
"writeMode": "append",
"fieldDelimiter": "\t"
}
}
}
]
}
}
使用sql语句导入需要指定jdbc连接参数
当数据中有中文是需要增加参数
jdbc:mysql://192.168.88.80:3306/itcast?useSSL=false&characterEncoding=utf8
{
"job": {
"setting": {
"speed": {
"channel":1
}
},
"content": [
{
"reader": {
"name": "mysqlreader",
"parameter": {
"username": "root",
"password": "123456",
"connection": [
{
"querySql": [
"select * from student where gender='男';"
],
"jdbcUrl": [
"jdbc:mysql://192.168.88.80:3306/itcast?useSSL=false&characterEncoding=utf8"
]
}
]
}
},
"writer": {
"name": "hdfswriter",
"parameter": {
"defaultFS": "hdfs://192.168.88.80:8020",
"fileType": "text",
"path": "/data",
"fileName": "student",
"column": [
{
"name": "id",
"type": "int"
},
{
"name": "name",
"type": "string"
},
{
"name": "age",
"type": "INT"
},
{
"name": "gender",
"type": "string"
}
],
"writeMode": "append",
"fieldDelimiter": "\t"
}
}
}
]
}
}
四、Mysql数据导入Hive表
hive的表是由两部分构成的
表的元数据 hive的metastore管理
表的行数据 hdfs上以文件的方式存储
导入hive表的数据本质就是将mysql中的数据导入hdfs中，将数据按照hive表的路径进行导入
1-启动hive服务 metastore hiveserve2
2-配置datagrip连接
3-创建hive表
show databases ; create database itcast; use itcast; create table stu( id int, name string, age int, gender string )row format delimited fields terminated by ','; select * from stu;
4-hive表的数据导入，本质就是将数据写入hdfs的表目录中
编写json文件
{
"job": {
"setting": {
"speed": {
"channel":1
}
},
"content": [
{
"reader": {
"name": "mysqlreader",
"parameter": {
"username": "root",
"password": "123456",
"column": [
"id",
"name",
"age",
"gender"
],
"splitPk": "id",
"connection": [
{
"table": [
"student"
],
"jdbcUrl": [
"jdbc:mysql://192.168.88.80:3306/itcast"
]
}
]
}
},
"writer": {
"name": "hdfswriter",
"parameter": {
"defaultFS": "hdfs://192.168.88.80:8020",
"fileType": "text",
"path": "/user/hive/warehouse/itcast.db/stu",
"fileName": "stu",
"column": [
{
"name": "id",
"type": "int"
},
{
"name": "name",
"type": "string"
},
{
"name": "age",
"type": "INT"
},
{
"name": "gender",
"type": "string"
}
],
"writeMode": "append",
"fieldDelimiter": ","
}
}
}
]
}
}
五、Datax-web介绍
GitHub - WeiYe-Jing/datax-web: DataX集成可视化页面，选择数据源即可一键生成数据同步任务，支持RDBMS、Hive、HBase、ClickHouse、MongoDB等数据源，批量创建RDBMS数据同步任务，集成开源调度系统，支持分布式、增量同步数据、实时查看运行日志、监控执行器资源、KILL运行进程、数据源信息加密等。
datax-web是基于datax进行的二次开发，提供了一个可视化web页面，方便开发人员定义datax任务，并且能自动生成json文件
六、Datax-Web使用
6-1 启动服务
/export/server/datax-web-2.1.2/bin/start-all.sh
6-2 访问页面
http://hadoop01:9527/index.html
6-3 使用
6-3-1 创建项目
6-3-2 创建数据源连接
6-3-3 任务管理的模板生成
可以设置定时执行
6-3-4 生成datax任务
6-3-5 任务执行
6-3-6 定时执行
