大数据作业之利用MapRedeuce实现简单的数据操作
Map/Reduce编程作业
现有student.txt和student_score.txt。将两个文件上传到hdfs上。使用Map/Reduce框架完成下面的题目
student.txt
2016001,王毅 2016002,张小明 2016003,李学彭 2016004,王东 2016005,王笑笑
student_score.txt
2016001,操作系统,60 2016001,数据库,88 2016001,大数据概论,85 2016002,操作系统,91 2016002,大数据概论,91 2016003,大数据概论,56 2016003,操作系统,88 2016004,数据库,90 2016004,大数据概论,82 2016004,操作系统,78 2016005,操作系统,69 2016005,大数据概论,70 2016005,数据库,89
1）将stduent.txt和student_score.txt连接，输出学号、姓名、课程、分数字段。
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2）统计每个同学的平均成绩，显示学号、姓名和平均成绩，并按照成绩高低降序排序。
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3）统计每门课的最高分、最低分和平均分。
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问题一：
StudentScore1.java
import java.io.IOException;
import java.lang.reflect.InvocationTargetException;
import java.util.ArrayList;
import java.util.List;
import org.apache.commons.beanutils.BeanUtils;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
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.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
public class StudentScore1 {
public static void main(String[] args) throws IllegalArgumentException, IOException, ClassNotFoundException, InterruptedException {
Configuration conf=new Configuration();
Job job=Job.getInstance(conf,"StudentScore1");
job.setJarByClass(StudentScore1.class);
job.setMapperClass(ScoreMapper.class);
//Map的输出，避免程序不确定Map输出的值的类型不确定
job.setMapOutputKeyClass(Text.class);
job.setMapOutputValueClass(SC.class);
job.setReducerClass(ScoreReduce.class);
//输出类型
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(NullWritable.class);
//数据来源
FileInputFormat.addInputPath(job,new Path("/StudentInput"));
//输出位置
FileOutputFormat.setOutputPath(job, new Path("/Output1"));
System.exit(job.waitForCompletion(true)?0:1);
}
public static class ScoreMapper extends Mapper<Object, Text, Text, SC>{
@Override
protected void map(Object key, Text value, Mapper<Object, Text, Text, SC>.Context context)
throws IOException, InterruptedException {
//以“,”分割字符串
//Student 2016001,王毅 [2016001,王毅]
//Student_score 2016001,操作系统,60 [2016001,操作系统,60]
String[] words=value.toString().split(",");
//记录学号
String Sid=words[0];
SC sc=new SC();
//区分字符串属于那个类型
if(words.length==2) {//长度为2的记录信息是 学生
sc.setSid(Sid);
sc.setName(words[1]);
sc.setTable("Student");
context.write(new Text(Sid), sc);
}else {//长度为3的记录信息是 学科成绩
sc.setSid(Sid);
sc.setCourse(words[1]);
sc.setScore(Integer.parseInt(words[2]));
sc.setTable("Student_score");
context.write(new Text(Sid), sc);
}
}
}
public static class ScoreReduce extends Reducer<Text, SC, Text, NullWritable>{
@Override
protected void reduce(Text key, Iterable<SC> values,
Reducer<Text, SC, Text,NullWritable>.Context context) throws IOException, InterruptedException {
List<SC> list=new ArrayList<SC>();
String Name="";
//遍历结果集的value
for(SC value:values) {
if(value.getTable().equals("Student")) {//只有姓名信息的记录下来
Name=value.getName();
}else {//否则，将其添加到待输出list中
SC sc=new SC();
try {
BeanUtils.copyProperties(sc, value);
list.add(sc);
} catch (IllegalAccessException e) {
// TODO Auto-generated catch block
e.printStackTrace();
} catch (InvocationTargetException e) {
// TODO Auto-generated catch block
e.printStackTrace();
}
}
}
//遍历list
for(SC sc:list) {
sc.setName(Name);
context.write(new Text(sc.toString()), NullWritable.get());
}
}
}
}
SC.java
import java.io.DataInput;
import java.io.DataOutput;
import java.io.IOException;
import org.apache.hadoop.io.Writable;
public class SC implements Writable{
private String Name="";
private String Sid="";
private String Course="";
private String Table="";
private int Score=0;
public String getName() {
return Name;
}
public void setName(String name) {
Name = name;
}
public String getSid() {
return Sid;
}
public void setSid(String sid) {
Sid = sid;
}
public String getCourse() {
return Course;
}
public void setCourse(String course) {
Course = course;
}
public String getTable() {
return Table;
}
public void setTable(String table) {
Table = table;
}
public int getScore() {
return Score;
}
public void setScore(int score) {
Score = score;
}
@Override
public String toString() {
return Sid + "," + Name + "," + Course + "," + Score;
}
@Override
public void readFields(DataInput in) throws IOException {
this.Sid=in.readUTF();
this.Name=in.readUTF();
this.Course=in.readUTF();
this.Table=in.readUTF();
this.Score=in.readInt();
}
@Override
public void write(DataOutput out) throws IOException {
out.writeUTF(Sid);
out.writeUTF(Name);
out.writeUTF(Course);
out.writeUTF(Table);
out.writeInt(Score);
}
}
结果：
2016001,王毅,操作系统,60 2016001,王毅,数据库,88 2016001,王毅,大数据概论,85 2016002,张小明,操作系统,91 2016002,张小明,大数据概论,91 2016003,李学彭,操作系统,88 2016003,李学彭,大数据概论,56 2016004,王东,大数据概论,82 2016004,王东,操作系统,78 2016004,王东,数据库,90 2016005,王笑笑,数据库,89 2016005,王笑笑,操作系统,69 2016005,王笑笑,大数据概论,70
问题二：
Average2.java
import java.io.IOException;
import java.util.Comparator;
import java.util.TreeMap;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.DoubleWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
public class Average2 {
public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
Configuration conf=new Configuration();
Job job=Job.getInstance(conf,"Average2");
job.setJarByClass(Average2.class);
job.setMapperClass(Average2Mapper.class);
job.setMapOutputKeyClass(Text.class);
job.setMapOutputValueClass(DoubleWritable.class);
job.setReducerClass(Average2Reduce.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(DoubleWritable.class);
FileInputFormat.addInputPath(job, new Path("/Output1"));
FileOutputFormat.setOutputPath(job, new Path("/Output2"));
System.exit(job.waitForCompletion(true)?0:1);
}
public static class Average2Mapper extends Mapper<Object,Text,Text,DoubleWritable>{
@Override
protected void map(Object key, Text value, Mapper<Object, Text, Text, DoubleWritable>.Context context)
throws IOException, InterruptedException {
//分割
String[] words=value.toString().split(",");
//keybuf=[2016001,王毅,]
StringBuffer keybuf=new StringBuffer();
keybuf.append(words[0]).append(",").append(words[1]).append(",");
//score用来记录成绩
Double score=Double.parseDouble(words[3]);
context.write(new Text(keybuf.toString()), new DoubleWritable(score));
}
}
public static class Average2Reduce extends Reducer<Text,DoubleWritable,Text,DoubleWritable>{
//new Comparetor<Double> 的方法 倒叙（从高到低）排序
private TreeMap<Double, String> treeMap=new TreeMap<Double, String>(new Comparator<Double>() {
@Override
public int compare(Double x, Double y) {
return y.compareTo(x);
}
});
@Override
protected void reduce(Text key, Iterable<DoubleWritable> values,
Reducer<Text, DoubleWritable, Text, DoubleWritable>.Context context)
throws IOException, InterruptedException {
//reduce的操作对象是[key,<value1,value2...>]
Double sumscore=0.0;
int num=0;
for(DoubleWritable value:values) {
num++;
sumscore=sumscore+value.get();
}
Double avg= sumscore/num;
//得到的结果先不输出，到treepMap里面先排个序
treeMap.put(avg, key.toString());
}
//输出
protected void cleanup(Context context) throws IOException, InterruptedException {
for(Double key:treeMap.keySet()) {
context.write(new Text(treeMap.get(key)), new DoubleWritable(key));
}
}
}
}
结果：
2016002,张小明, 91.0 2016004,王东, 83.33333333333333 2016001,王毅, 77.66666666666667 2016005,王笑笑, 76.0 2016003,李学彭, 72.0
问题三：
Course3.java
import java.io.IOException;
import org.apache.hadoop.conf.Configuration;
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.Mapper;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
public class Course3 {
public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
Configuration conf=new Configuration();
Job job=Job.getInstance(conf,"Course3");
job.setJarByClass(Course3.class);
job.setMapperClass(Course3Mapper.class);
job.setMapOutputKeyClass(Text.class);
job.setMapOutputValueClass(IntWritable.class);
job.setReducerClass(Course3Reduce.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(Text.class);
FileInputFormat.addInputPath(job, new Path("/Output1"));
FileOutputFormat.setOutputPath(job, new Path("/Output3"));
System.exit(job.waitForCompletion(true)?0:1);
}
public static class Course3Mapper extends Mapper<Object,Text,Text,IntWritable>{
@Override
protected void map(Object key, Text value, Mapper<Object, Text,Text, IntWritable>.Context context)
throws IOException, InterruptedException {
//分割
String[] words=value.toString().split(",");
int Score=Integer.parseInt(words[3]);
//key=课程 value=某人某科成绩
context.write(new Text(words[2]), new IntWritable(Score));
}
}
public static class Course3Reduce extends Reducer<Text,IntWritable,Text,Text>{
@Override
protected void reduce(Text key, Iterable<IntWritable> values,
Reducer<Text, IntWritable, Text, Text>.Context context) throws IOException, InterruptedException {
int mmax=0;//最大值
int mmin=101;//最小值
double avg=0;//平均成绩
int num=0;//每科人数
for(IntWritable value:values) {
num++;
if(value.get()>mmax) mmax=value.get();
if(value.get()<mmin) mmin=value.get();
avg=avg+value.get();
}
avg=avg/num;
String score=String.valueOf(mmax)+","+String.valueOf(mmin)+","+String.valueOf(avg);
context.write(key,new Text(score));
}
}
}
结果：
大数据概论 91,56,76.8 操作系统 91,60,77.2 数据库 90,88,89.0
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