hadoop与MySQL结合

一般的hadoop的mapreduce操作都是对文本文件或者在hdfs上的数据，如何在数据库中读取数据进行操作。

首先需要自定义一个DBWritable类。

package com.huawei.hdfs.com.huawei.mysql;

import org.apache.hadoop.io.Writable;
import org.apache.hadoop.mapreduce.lib.db.DBWritable;

import java.io.DataInput;
import java.io.DataOutput;
import java.io.IOException;
import java.sql.PreparedStatement;
import java.sql.ResultSet;
import java.sql.SQLException;

public class MyDBWritable implements DBWritable, Writable {

    private String name;
    private int age;

    private String p_name;
    private int p_age;


    public MyDBWritable(){

    }
    public MyDBWritable(String name, int age) {
        this.name = name;
        this.age = age;
        this.p_name=p_name;
        this.p_age=p_age;
    }

    public void write(DataOutput out) throws IOException {
        out.writeUTF(name);
        out.writeInt(age);
        out.writeUTF(p_name);
        out.writeInt(p_age);
    }

    public void readFields(DataInput in) throws IOException {
        name=in.readUTF();
        age=in.readInt();
        p_name=in.readUTF();
        p_age=in.readInt();
    }

    //DB写数据的过程
    public void write(PreparedStatement statement) throws SQLException {
        statement.setString(1,p_name);
        statement.setInt(2,p_age);
    }

    //DBdu读数据的过程
    public void readFields(ResultSet resultSet) throws SQLException {
        name=resultSet.getString(1);
        age=resultSet.getInt(2);
    }

    public String getName() {
        return name;
    }

    public void setName(String name) {
        this.name = name;
    }

    public int getAge() {
        return age;
    }

    public void setAge(int age) {
        this.age = age;
    }

    public String getP_name() {
        return p_name;
    }

    public void setP_name(String p_name) {
        this.p_name = p_name;
    }

    public int getP_age() {
        return p_age;
    }

    public void setP_age(int p_age) {
        this.p_age = p_age;
    }
}

Mapper类

package com.huawei.hdfs.com.huawei.mysql;

import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;

import java.io.IOException;

public class SQLMapper extends Mapper<LongWritable,MyDBWritable,Text,IntWritable>{
    @Override
    protected void map(LongWritable key, MyDBWritable value, Context context) throws IOException, InterruptedException {

        context.write(new Text(value.getName()),new IntWritable(value.getAge()));
    }
}

Reducer类

package com.huawei.hdfs.com.huawei.mysql;

import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer;

import java.io.IOException;

public class SQLReducer extends Reducer<Text,IntWritable,MyDBWritable,NullWritable>{
    @Override
    protected void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException {
        MyDBWritable myDBWritable=new MyDBWritable();
        for(IntWritable it:values){
            myDBWritable.setP_name(key.toString());
            myDBWritable.setP_age(it.get()+100);
            context.write(myDBWritable,NullWritable.get());
        }

    }
}

运行类

package com.huawei.hdfs.com.huawei.mysql;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.lib.db.DBConfiguration;
import org.apache.hadoop.mapreduce.lib.db.DBInputFormat;
import org.apache.hadoop.mapreduce.lib.db.DBOutputFormat;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;

import java.io.IOException;

public class SQL_Test {

    public static void main(String[] args) throws Exception {
        Configuration conf=new Configuration();
        conf.set("fs.defaultFS","file:///");
        Job job=Job.getInstance(conf);

        FileSystem fs=FileSystem.get(conf);
        if(fs.exists(new Path(args[0]))){
            fs.delete(new Path(args[0]),true);
        }
        job.setJobName("SQL_TEST");
        job.setJarByClass(SQL_Test.class);
        job.setMapperClass(SQLMapper.class);
        job.setReducerClass(SQLReducer.class);

        //配置数据库信息
        String driveclass="com.mysql.jdbc.Driver";
        String url="jdbc:mysql://localhost:3306/bigtable";
        String username="root";
        String password="root";
        DBConfiguration.configureDB(job.getConfiguration(),driveclass,url,username,password);

        //设置数据库输入
        //需要通过总的记录数来计算切片
        DBInputFormat.setInput(job,MyDBWritable.class,"select name,age from persion","select count(*) from persion");

       //设置数据库输出
        DBOutputFormat.setOutput(job,"state","p_name","p_age");

        job.setMapOutputKeyClass(Text.class);
        job.setMapOutputValueClass(IntWritable.class);

        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(IntWritable.class);

        job.waitForCompletion(true);
    }
}

其中查看自己MySQL远程调用的接口的方法：

show global variables like 'port';

如果要在集群中运行该jar，那么要保证在集群中有mysql-connector-java-5.1.17.jar这个包，可以放在hadoop文件夹中/hadoop/share/hadoop/common/lib目录下。

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