Hadoop自带的数据类型：

Intwritable,LongWritable,Text,xxWritable.

某些情况下：使用自定义的数据类型方便一些（类似java中的pojo）。

实现：

实现writableComparable接口即可。

场景例如：

成绩表：由语文，数学，英文组成。

上传到hdfs上score目录下一个score.txt文件--文件内容如下：

想让按照总成绩进行排名。如果成绩相同，则按照语文，数学，英文来排序。

一、自定义ScoreWritable实现writableComparable接口：

package com.day07;import org.apache.hadoop.io.WritableComparable;import java.io.*;
public class ScoreWritable implements WritableComparable<ScoreWritable> {int chinese;int math;int english;int sum;public ScoreWritable() {}public ScoreWritable(int chinese, int math, int english) {this.chinese = chinese;this.math = math;this.english = english;this.sum=chinese+english+math;}@Overridepublic String toString() {return "ScoreWritable{" +"chinese=" + chinese +", math=" + math +", english=" + english +", sum=" + sum +'}';}public int getChinese() {return chinese;}public void setChinese(int chinese) {this.chinese = chinese;}public int getMath() {return math;}public void setMath(int math) {this.math = math;}public int getEnglish() {return english;}public void setEnglish(int english) {this.english = english;}public int getSum() {return sum;}public void setSum(int sum) {this.sum = sum;}//比较public int compareTo(ScoreWritable that) {//先比较总成绩if (this.sum>that.getSum()){return -1;}else if(this.sum<that.getSum()){return 1;}else{if (this.chinese>that.getChinese()){return -1;}else if (this.chinese<that.getChinese()){return 1;}else {return -(this.math-that.getMath());}}}//序列化--dataOutput(data流)：可以自定义序列化对象，节省空间，hadoop用的就是这个流public void write(DataOutput out) throws IOException {out.writeInt(chinese);out.writeInt(math);out.writeInt(english);out.writeInt(sum);}//反序列化public void readFields(DataInput in) throws IOException {this.chinese = in.readInt();this.math = in.readInt();this.english = in.readInt();this.sum = in.readInt();}
}

注意：

最好实现toString方法。

二、编写ScoreJob类用于测试自定义的ScoreWritable

package com.day07;import com.day03.MaxSaleJob;
import com.google.common.io.Resources;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FSDataInputStream;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IOUtils;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;import java.io.IOException;public class ScoreJob {public static class ScoreMapper extends Mapper<LongWritable,Text,ScoreWritable,NullWritable>{@Overrideprotected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {//super.map(key, value, context);String[] grades = value.toString().split(",");ScoreWritable score = new ScoreWritable(Integer.parseInt(grades[0]), Integer.parseInt(grades[1]), Integer.parseInt(grades[2]));context.write(score,NullWritable.get());}}public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {Configuration coreSiteConf = new Configuration();coreSiteConf.addResource(Resources.getResource("core-site-local.xml"));//设置一个任务Job job = Job.getInstance(coreSiteConf, "score");//设置job的运行类job.setJarByClass(ScoreJob.class);//mrdemo/target/mrdemo-1.0-SNAPSHOT.jar//job.setJar("mrdemo/target/mrdemo-1.0-SNAPSHOT.jar");//设置Map和Reduce处理类job.setMapperClass(ScoreMapper.class);//map输出类型job.setMapOutputKeyClass(ScoreWritable.class);job.setMapOutputValueClass(NullWritable.class);//设置job/reduce输出类型/*job.setOutputKeyClass(Text.class);job.setOutputValueClass(NullWritable.class);*///设置任务的输入路径FileInputFormat.addInputPath(job, new Path("/score/"));FileSystem fileSystem = FileSystem.get(coreSiteConf);if(fileSystem.exists(new Path("/out/"))){fileSystem.delete(new Path("/out/"),true);};FileOutputFormat.setOutputPath(job, new Path("/out/"));//运行任务boolean flag = job.waitForCompletion(true);if(flag){FSDataInputStream open = fileSystem.open(new Path("/out/part-r-00000"));byte[] buffer = new byte[1024];IOUtils.readFully(open,buffer,0,open.available());System.out.println(new String(buffer));}}
}

三、测试结果，类似于一下内容