概述
一·需求描述:
要求从给出的数据中寻找所关心的数据,它是对原始数据所包含信息的挖掘。下面进入这个实例。
实例中给出child-parent(孩子——父母)表,要求输出grandchild-grandparent(孙子——爷奶)表。
=================样本输入:===================
child
parent
Tom
Lucy
Tom
Jack
Jone
Lucy
Jone
Jack
Lucy
Mary
Lucy
Ben
Jack
Alice
Jack
Jesse
Terry
Alice
Terry
Jesse
Philip
Terry
Philip
Alma
Mark
Terry
Mark
Alma
Tom
Lucy
Tom
Jack
Jone
Lucy
Jone
Jack
Lucy
Mary
Lucy
Ben
Jack
Alice
Jack
Jesse
Terry
Alice
Terry
Jesse
Philip
Terry
Philip
Alma
Mark
Terry
Mark
Alma
家族树状关系谱:
=================样本输出:===================
grandchild
grandparent
Tom
Alice
Tom
Jesse
Jone
Alice
Jone
Jesse
Tom
Mary
Tom
Ben
Jone
Mary
Jone
Ben
Philip
Alice
Philip
Jesse
Mark
Alice
Mark
Jesse
Tom
Alice
Tom
Jesse
Jone
Alice
Jone
Jesse
Tom
Mary
Tom
Ben
Jone
Mary
Jone
Ben
Philip
Alice
Philip
Jesse
Mark
Alice
Mark
Jesse
二·设计思路:
取一对样本为例:
child parent
Tom Lucy
Lucy Mary
mapper代码片段:
context.write(new Text(values[0]), new Text(values[1]+"_1"));//key是value的小孩 key:Tom value:Lucy_1
context.write(new Text(values[1]), new Text(values[0]+"_2"));//key是value的父母 key:Lucy value:Tom_2
即mapper读取文件的每一行都输出正反,并进行标记
三·程序代码:
mapper.java
package com.company.family;
import java.io.IOException;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;
public class FamilyMapper extends Mapper<LongWritable, Text, Text, Text>{
@Override
protected void map(LongWritable key, Text value, Mapper<LongWritable, Text, Text, Text>.Context context)
throws IOException, InterruptedException {
//value:"Tom Lucy"
String line = value.toString();
String[] values = line.split("
");
context.write(new Text(values[0]), new Text(values[1]+"_1"));//key是value的小孩 key:Tom value:Lucy_1
context.write(new Text(values[1]), new Text(values[0]+"_2"));//key是value的父母 key:Lucy value:Tom_2
}
}
//value:"Tom Lucy"
String line = value.toString();
String[] values = line.split("
");
context.write(new Text(values[0]), new Text(values[1]+"_1"));//key是value的小孩 key:Tom value:Lucy_1
context.write(new Text(values[1]), new Text(values[0]+"_2"));//key是value的父母 key:Lucy value:Tom_2
}
}
reducer.java
package com.company.family;
import java.io.IOException;
import java.util.ArrayList;
import java.util.List;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer;
public class FamilyReducer extends Reducer<Text, Text, Text, Text>{
@Override
protected void reduce(Text key, Iterable<Text> values, Reducer<Text, Text, Text, Text>.Context context)
throws IOException, InterruptedException {
//key:Lucy values:{Tom_2,Jone_2,Marry_1,Ben_1}
List<String> yeyelist = new ArrayList<String>();
List<String> children = new ArrayList<String>();
for(Text val:values){
if(val.toString().endsWith("_1")){
yeyelist.add(val.toString());
}else if(val.toString().endsWith("_2")){
children.add(val.toString());
}
}
//Tom Marry
//Tom Ben
//Jone Marry
//Jone Ben
for(String child:children){
for(String yeye:yeyelist){
context.write(new Text(child.substring(0, child.length()-2)), new Text(yeye.substring(0, yeye.length()-2)));
}
}
}
}
//key:Lucy values:{Tom_2,Jone_2,Marry_1,Ben_1}
List<String> yeyelist = new ArrayList<String>();
List<String> children = new ArrayList<String>();
for(Text val:values){
if(val.toString().endsWith("_1")){
yeyelist.add(val.toString());
}else if(val.toString().endsWith("_2")){
children.add(val.toString());
}
}
//Tom Marry
//Tom Ben
//Jone Marry
//Jone Ben
for(String child:children){
for(String yeye:yeyelist){
context.write(new Text(child.substring(0, child.length()-2)), new Text(yeye.substring(0, yeye.length()-2)));
}
}
}
}
runner.java
package com.company.family;
import java.io.IOException;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
public class FamilyRunner {
public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
Configuration conf = new Configuration();
Job job = Job.getInstance(conf);
//对任务job的描述
//job的jar路径
job.setJarByClass(FamilyRunner.class);
//job对应的Mapper
job.setMapperClass(FamilyMapper.class);
//job的Reducer
job.setReducerClass(FamilyReducer.class);
//Mapper的输出类型
job.setMapOutputKeyClass(Text.class);
job.setMapOutputValueClass(Text.class);
//Reducer的输出类型
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(Text.class);
//job 处理文件路径
FileInputFormat.setInputPaths(job, new Path("/Users/xuran/Desktop/week"));
//job 处理之后文件路径
FileOutputFormat.setOutputPath(job, new Path("/Users/xuran/Desktop/week/result"));
//提交job
boolean waitForCompletion = job.waitForCompletion(true);
System.exit(waitForCompletion?0:1);
}
}
//对任务job的描述
//job的jar路径
job.setJarByClass(FamilyRunner.class);
//job对应的Mapper
job.setMapperClass(FamilyMapper.class);
//job的Reducer
job.setReducerClass(FamilyReducer.class);
//Mapper的输出类型
job.setMapOutputKeyClass(Text.class);
job.setMapOutputValueClass(Text.class);
//Reducer的输出类型
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(Text.class);
//job 处理文件路径
FileInputFormat.setInputPaths(job, new Path("/Users/xuran/Desktop/week"));
//job 处理之后文件路径
FileOutputFormat.setOutputPath(job, new Path("/Users/xuran/Desktop/week/result"));
//提交job
boolean waitForCompletion = job.waitForCompletion(true);
System.exit(waitForCompletion?0:1);
}
}
最后再贡献出一张图:
最后
以上就是壮观纸鹤为你收集整理的实例中给出child-parent(孩子——父母)表,要求输出grandchild-grandparent(孙子——爷奶)表的全部内容,希望文章能够帮你解决实例中给出child-parent(孩子——父母)表,要求输出grandchild-grandparent(孙子——爷奶)表所遇到的程序开发问题。
如果觉得靠谱客网站的内容还不错,欢迎将靠谱客网站推荐给程序员好友。
发表评论 取消回复