mapreduce统计数据库中的单词个数

1、建立数据库表

2、导入jar包

mysql-connector-java-5.1.38.jar

3、创建实体类

package com.cr.jdbc;

import org.apache.hadoop.io.Writable;
import org.apache.hadoop.mapred.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 id;
    private String name;
    private String txt;

    public String getId() {
        return id;
    }

    public void setId(String id) {
        this.id = id;
    }

    public String getName() {
        return name;
    }

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

    public String getTxt() {
        return txt;
    }

    public void setTxt(String txt) {
        this.txt = txt;
    }


    @Override
    public boolean equals(Object o) {
        if (this == o) return true;
        if (o == null || getClass() != o.getClass()) return false;

        MyDBWritable that = (MyDBWritable) o;

        if (id != null ? !id.equals(that.id) : that.id != null) return false;
        if (name != null ? !name.equals(that.name) : that.name != null) return false;
        return txt != null ? txt.equals(that.txt) : that.txt == null;
    }

    @Override
    public int hashCode() {
        int result = id != null ? id.hashCode() : 0;
        result = 31 * result + (name != null ? name.hashCode() : 0);
        result = 31 * result + (txt != null ? txt.hashCode() : 0);
        return result;
    }

    //串行化
    @Override
    public void write(DataOutput out) throws IOException {
        out.writeUTF(id);
        out.writeUTF(name);
        out.writeUTF(txt);
    }

    //反串行化
    @Override
    public void readFields(DataInput in) throws IOException {
        id = in.readUTF();
        name = in.readUTF();
        txt = in.readUTF();

    }

    //写入DB
    @Override
    public void write(PreparedStatement ps) throws SQLException {
        ps.setString(1,id);
        ps.setString(2,name);
        ps.setString(3,txt);
    }

    //从DB读取
    @Override
    public void readFields(ResultSet rs) throws SQLException {
        id = rs.getString(1);
        name = rs.getString(2);
        txt = rs.getString(3);


    }
}

4、mapper读取数据库内容，获取需要统计的字段，转换输出格式为text---intwritable

package com.cr.jdbc;

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 JDBCMapper extends Mapper<LongWritable, MyDBWritable,Text,IntWritable> {
    @Override
    protected void map(LongWritable key, MyDBWritable value, Context context) throws IOException, InterruptedException {
        System.out.println("key--->"+key);
        String line = value.getTxt();
        System.out.println(value.getId() + "-->" + value.getName()+"--->"+value.getTxt());
        String[] arr = line.split(" ");
        for(String s : arr){
            context.write(new Text(s),new IntWritable(1));
        }
    }
}

5、reducer进行聚合统计单词的个数

package com.cr.jdbc;

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

import java.io.IOException;


public class JDBCReducer extends Reducer<Text,IntWritable,Text,IntWritable> {
    @Override
    protected void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException {
        int count = 0;
        for(IntWritable iw:values){
            count += iw.get();
        }
        context.write(key,new IntWritable(count));
    }
}

6、设置主类app

package com.cr.jdbc;

import com.cr.skew.SkewMapper;
import com.cr.skew.SkewReducer;
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.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.input.TextInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.mortbay.jetty.security.UserRealm;

import java.io.IOException;

public class JDBCApp {

    public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {

        //单例作业
        Configuration conf = new Configuration();
        conf.set("fs.defaultFS","file:///");
        Job job = Job.getInstance(conf);
        System.setProperty("hadoop.home.dir","E:\hadoop-2.7.5");

        //设置job的各种属性
        job.setJobName("MySQLApp");                 //设置job名称
        job.setJarByClass(JDBCApp.class);              //设置搜索类
        job.setInputFormatClass(DBInputFormat.class);

        String driverClass = "com.mysql.jdbc.Driver";
        String url = "jdbc:mysql://localhost:3306/test_mysql";
        String userName = "root";
        String passWord = "root";
        //设置数据库配置
        DBConfiguration.configureDB(job.getConfiguration(),driverClass,url,userName,passWord);
        //设置数据输入内容
        DBInputFormat.setInput(job,MyDBWritable.class,"select id,name,txt from student","select count(*) from student");

        //设置输出路径
        Path path = new Path("D:\db\out");
        FileSystem fs = FileSystem.get(conf);
        if (fs.exists(path)) {
            fs.delete(path, true);
        }
        FileOutputFormat.setOutputPath(job,path);

        job.setMapperClass(JDBCMapper.class);               //设置mapper类
        job.setReducerClass(JDBCReducer.class);               //设置reduecer类

        job.setMapOutputKeyClass(Text.class);            //设置之map输出key
        job.setMapOutputValueClass(IntWritable.class);   //设置map输出value

        job.setOutputKeyClass(Text.class);               //设置mapreduce 输出key
        job.setOutputValueClass(IntWritable.class);      //设置mapreduce输出value


        job.setNumReduceTasks(3);
        job.waitForCompletion(true);

    }

}

7、运行结果

part-r-00000

txt1 1

part-r-00001

sun 1
tom 1
txt2 1

part-r-00002

hello 3
is 2
sun1 1

8、将统计的结果写入数据库中

建立输出数据表

在实体类中添加字段

    //导出字段
    private String word = "";
    private int count = 0;

修改串行化和反串行化方法，以及修改数据库的写入方法

    //串行化
    @Override
    public void write(DataOutput out) throws IOException {
        out.writeUTF(id);
        out.writeUTF(name);
        out.writeUTF(txt);
        out.writeUTF(word);
        out.writeInt(count);


    }

    //反串行化
    @Override
    public void readFields(DataInput in) throws IOException {
        id = in.readUTF();
        name = in.readUTF();
        txt = in.readUTF();
        word = in.readUTF();
        count = in.readInt();

    }

    //写入DB
    @Override
    public void write(PreparedStatement ps) throws SQLException {

        ps.setString(1,word);
        ps.setInt(2,count);
    }

    //从DB读取
    @Override
    public void readFields(ResultSet rs) throws SQLException {
        id = rs.getString(1);
        name = rs.getString(2);
        txt = rs.getString(3);


    }

修改reducer，修改输出类型为dbwritable，nullwritable

public class JDBCReducer extends Reducer<Text,IntWritable,MyDBWritable,NullWritable> {
    @Override
    protected void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException {
        int count = 0;
        for(IntWritable iw:values){
            count += iw.get();
        }
        MyDBWritable keyOut = new MyDBWritable();
        keyOut.setWord(key.toString());
        keyOut.setCount(count);
        context.write(keyOut, NullWritable.get());
    }
}

在主类app中修改输出路径

 //设置数据库输出
        DBOutputFormat.setOutput(job,"word_count","word","count");

运行

9、运行于Hadoop集群

1、导出jar包，放到集群

2、为每个节点分发MySQL-connector驱动jar包

3、运行jar包

[xiaoqiu@s150 /home/xiaoqiu]$ hadoop jar wordcounter.jar com.cr.jdbc.JDBCApp

4、结果