Hadoop读写mysql

需求

两张表，一张click表记录某广告某一天的点击量，另一张total_click表记录某广告的总点击量

建表

CREATE TABLE `click` (
  `id` int(20) NOT NULL AUTO_INCREMENT,
  `ad_id` int(20) DEFAULT NULL, -- 广告ID
  `click_num` int(30) DEFAULT NULL, -- 某天的点击数量
  `day` date,
  PRIMARY KEY (`id`)
);

CREATE TABLE `total_click` (
  `id` int(20) NOT NULL AUTO_INCREMENT,
  `ad_id` int(20) DEFAULT NULL, -- 广告ID
  `total_click_num` int(50) DEFAULT NULL, -- 总点击数量
  PRIMARY KEY (`id`)
)

pom依赖

<dependencies>
        <dependency>
            <groupId>org.apache.hadoop</groupId>
            <artifactId>hadoop-client</artifactId>
            <version>2.7.3</version>
        </dependency>

        <dependency>
            <groupId>junit</groupId>
            <artifactId>junit</artifactId>
            <version>4.11</version>
        </dependency>

        <dependency>
            <groupId>log4j</groupId>
            <artifactId>log4j</artifactId>
            <version>1.2.17</version>
        </dependency>

        <dependency>
            <groupId>mysql</groupId>
            <artifactId>mysql-connector-java</artifactId>
            <version>5.1.45</version>
        </dependency>
    </dependencies>

代码

自定义类

Writable是为了与MapReduce进行对接，而DBWritable是为了与MySQL进行对接。

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 ad_id;
    private int click_num;
    private int total_click_num;

    public MyDBWritable(){

    }
    public MyDBWritable(String name, int age) {
        this.ad_id = name;
        this.click_num = age;
        this.total_click_num = total_click_num;
    }

    public void write(DataOutput out) throws IOException {
        out.writeUTF(ad_id);
        out.writeInt(click_num);
        out.writeInt(total_click_num);
    }

    //写数据的过程
    public void write(PreparedStatement statement) throws SQLException {
        //要和SQL_Run类的DBOutputFormat.setOutput(job,"total_click","ad_id","total_click_num")语句里字段的顺序保持一致
        statement.setString(1,ad_id);
        statement.setInt(2, total_click_num);
    }

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

    public void readFields(DataInput in) throws IOException {
        ad_id =in.readUTF();
        click_num =in.readInt();
        total_click_num =in.readInt();
    }

    public String getAd_id() {
        return ad_id;
    }

    public void setAd_id(String ad_id) {
        this.ad_id = ad_id;
    }

    public int getClick_num() {
        return click_num;
    }

    public void setClick_num(int click_num) {
        this.click_num = click_num;
    }

    public int getTotal_click_num() {
        return total_click_num;
    }

    public void setTotal_click_num(int total_click_num) {
        this.total_click_num = total_click_num;
    }

}

Map

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.getAd_id()),new IntWritable(value.getClick_num()));
    }

}

Reduce

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 {
        int total = 0;
        for(IntWritable i :values) {
            total+= i.get();
        }
        MyDBWritable myDBWritable = new MyDBWritable();
        myDBWritable.setAd_id(key.toString());
        myDBWritable.setTotal_click_num(total);
        context.write(myDBWritable,NullWritable.get());
    }
}

App

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.NullWritable;
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;

public class SQL_Run {
    public static void main(String[] args) throws Exception {

        Configuration conf=new Configuration();

        //假如是本地测试，需要设置fs.defaultFS
        conf.set("fs.defaultFS","file:///");

        Job job = Job.getInstance(conf);

        FileSystem fs=FileSystem.get(conf);

        job.setJobName("SQL_TEST");
        job.setJarByClass(SQL_Run.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://192.168.0.8:3306/bigdata";
        String username="root";
        String password="123456";
        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 ad_id,click_num from click","select count(id) from click");

        //设置数据库输出  //total_click是表名，后面参数是字段值（可以多个）
        DBOutputFormat.setOutput(job,"total_click","ad_id","total_click_num");

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

        job.setOutputKeyClass(MyDBWritable.class);
        job.setOutputValueClass(NullWritable.class);

        job.waitForCompletion(true);
    }
}