使用MapReduce将mysql数据导入HDFS

时间:2023-03-08 17:52:04
package com.zhen.mysqlToHDFS;

import java.io.DataInput;
import java.io.DataOutput;
import java.io.IOException;
import java.sql.PreparedStatement;
import java.sql.ResultSet;
import java.sql.SQLException; import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.conf.Configured;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.io.Writable;
import org.apache.hadoop.mapred.lib.db.DBWritable;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.lib.db.DBConfiguration;
import org.apache.hadoop.mapreduce.lib.db.DBInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner; /**
* @author FengZhen
* 将mysql数据导入hdfs
*/
public class DBInputFormatApp extends Configured implements Tool { /**
* JavaBean
* 需要实现Hadoop序列化接口Writable以及与数据库交互时的序列化接口DBWritable
* 官方API中解释如下:
* public class DBInputFormat<T extends DBWritable>
* extends InputFormat<LongWritable, T> implements Configurable
* 即Mapper的Key是LongWritable类型,不可改变;Value是继承自DBWritable接口的自定义JavaBean
*/
public static class BeanWritable implements Writable, DBWritable { private int id;
private String name;
private double height; public void readFields(ResultSet resultSet) throws SQLException {
this.id = resultSet.getInt();
this.name = resultSet.getString();
this.height = resultSet.getDouble();
} public void write(PreparedStatement preparedStatement) throws SQLException {
preparedStatement.setInt(, id);
preparedStatement.setString(, name);
preparedStatement.setDouble(, height);
} public void readFields(DataInput dataInput) throws IOException {
this.id = dataInput.readInt();
this.name = dataInput.readUTF();
this.height = dataInput.readDouble();
} public void write(DataOutput dataOutput) throws IOException {
dataOutput.writeInt(id);
dataOutput.writeUTF(name);
dataOutput.writeDouble(height);
} @Override
public String toString() {
return id + "\t" + name + "\t" + height;
} } /**
* Map
* 当Map的输出key为LongWritable,value为Text时,reduce可以省略不写,默认reduce也是输出LongWritable:Text
* */
public static class DBInputMapper extends Mapper<LongWritable, BeanWritable, LongWritable, Text> { private LongWritable outputKey;
private Text outputValue; @Override
protected void setup(Mapper<LongWritable, BeanWritable, LongWritable, Text>.Context context)
throws IOException, InterruptedException {
this.outputKey = new LongWritable();
this.outputValue = new Text();
} @Override
protected void map(LongWritable key, BeanWritable value,
Mapper<LongWritable, BeanWritable, LongWritable, Text>.Context context)
throws IOException, InterruptedException {
outputKey.set(key.get());;
outputValue.set(value.toString());
context.write(outputKey, outputValue);
} } public int run(String[] arg0) throws Exception {
Configuration configuration = getConf();
//配置当前作业需要使用的JDBC配置
DBConfiguration.configureDB(configuration, "com.mysql.jdbc.Driver", "jdbc:mysql://localhost:3306/hadoop",
"root", "123qwe");
Job job = Job.getInstance(configuration, DBInputFormatApp.class.getSimpleName()); job.setJarByClass(DBInputFormatApp.class);
job.setMapperClass(DBInputMapper.class);
job.setMapOutputKeyClass(LongWritable.class);
job.setMapOutputValueClass(Text.class); job.setOutputKeyClass(LongWritable.class);
job.setOutputValueClass(Text.class); //配置作业的输入数据格式
job.setInputFormatClass(DBInputFormat.class);
//配置当前作业需要查询的sql语句及接收sql语句的bean
DBInputFormat.setInput(
job,
BeanWritable.class,
"select * from people",
"select count(1) from people"); FileOutputFormat.setOutputPath(job, new Path(arg0[])); return job.waitForCompletion(true) ? : ;
} public static int createJob(String[] args) {
Configuration conf = new Configuration();
conf.set("dfs.datanode.socket.write.timeout", "");
conf.set("mapreduce.input.fileinputformat.split.minsize", "");
conf.set("mapreduce.input.fileinputformat.split.maxsize", "");
int status = ;
try { status = ToolRunner.run(conf,new DBInputFormatApp(), args);
} catch (Exception e) {
e.printStackTrace();
}
return status;
} public static void main(String[] args) {
args = new String[] { "/user/hadoop/mapreduce/mysqlToHdfs/people" };
int status = createJob(args);
System.exit(status);
}
}

在mysql新建一张表 people

CREATE TABLE `people` (
`id` int() NOT NULL,
`name` varchar() DEFAULT NULL,
`height` double DEFAULT NULL,
PRIMARY KEY (`id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8

写入几条测试数据。

将mapreduce作业打成jar包,上传到Hadoop集群服务器,执行。

hadoop jar /Users/FengZhen/Desktop/Hadoop/other/mapreduce_jar/MysqlToHDFS.jar com.zhen.mysqlToHDFS.DBInputFormatApp

因为代码中已经指定了写入HDFS的路径,所以此处不需要传参,只需指定job所在类即可。

在运行中如果提示mysql驱动找不到,如下

Caused by: java.lang.ClassNotFoundException: com.jdbc.mysql.Driver
at java.net.URLClassLoader$.run(URLClassLoader.java:)
at java.net.URLClassLoader$.run(URLClassLoader.java:)
at java.security.AccessController.doPrivileged(Native Method)
at java.net.URLClassLoader.findClass(URLClassLoader.java:)
at java.lang.ClassLoader.loadClass(ClassLoader.java:)
at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:)
at java.lang.ClassLoader.loadClass(ClassLoader.java:)
at java.lang.Class.forName0(Native Method)
at java.lang.Class.forName(Class.java:)
at org.apache.hadoop.mapreduce.lib.db.DBConfiguration.getConnection(DBConfiguration.java:)
at org.apache.hadoop.mapreduce.lib.db.DBInputFormat.createConnection(DBInputFormat.java:)
... more

解决办法:

将mysql jdbc驱动放入 .../hadoop/share/hadoop/mapreduce/lib下,然后重启集群再次执行即可。

使用MapReduce将HDFS数据导入MySql