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java - Hadoop Mapreduce实践

转载 作者:行者123 更新时间:2023-12-02 21:34:54 25 4
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Input data file:

name,month,category,expenditure

hitesh,1,A1,10020  
hitesh,2,A2,10300
hitesh,3,A3,10400
hitesh,4,A4,11000
hitesh,5,A1,21000
hitesh,6,A2,5000
hitesh,7,A3,9000
hitesh,8,A4,1000
hitesh,9,A1,111000
hitesh,10,A2,12000
hitesh,11,A3,71000
hitesh,12,A4,177000
kuwar,1,A1,10700
kuwar,2,A2,17000
kuwar,3,A3,10070
kuwar,4,A4,10007
以人为单位的总支出,并计算支出的独特类别。 (输出需要看起来像:名称,总支出,唯一类别的总数)
我尝试过的.....我的代码
人-明智的总支出
public class Emp   
{
public static class MyMap extends Mapper<LongWritable,Text,Text,IntWritable>
{
public void map(LongWritable k,Text v, Context con)
throws IOException, InterruptedException
{
String line = v.toString();
String[] w=line.split(",");
String person=w[0];
int exp=Integer.parseInt(w[3]);
con.write(new Text(person), new IntWritable(exp));
}
}
public static class MyRed extends Reducer<Text,IntWritable,Text,IntWritable>
{
public void reduce(Text k, Iterable<IntWritable> vlist, Context con)
throws IOException , InterruptedException
{
int tot =0;
for(IntWrit

able v:vlist)
tot+=v.get();
con.write(k,new IntWritable(tot));
}
}
public static void main(String[] args) throws Exception
{
Configuration c = new Configuration();
Job j= new Job(c,"person-wise");
j.setJarByClass(Emp.class);
j.setMapperClass(MyMap.class);
j.setReducerClass(MyRed.class);
j.setOutputKeyClass(Text.class);
j.setOutputValueClass(IntWritable.class);
Path p1 = new Path(args[0]);
Path p2 = new Path(args[1]);
FileInputFormat.addInputPath(j,p1);
FileOutputFormat.setOutputPath(j,p2);
System.exit(j.waitForCompletion(true) ? 0:1);
}

}
如何在此程序中获取唯一类别的总数,以及如何使输出看起来像名称,总支出,唯一类别的总数。
谢谢

最佳答案

在您的代码中做了修改。希望这是有用的。

 public class Emp   
{
public static class MyMap extends Mapper<LongWritable,Text,Text,Text>
{
public void map(LongWritable k,Text v, Context con)
throws IOException, InterruptedException
{
String line = v.toString();
String[] w=line.split(",");
String person=w[0];
int exp=Integer.parseInt(w[3]);
con.write(new Text(person), new Text(line));
}
}
public static class MyRed extends Reducer<Text,Text,Text,Text>
{
public void reduce(Text k, Iterable<Text> vlist, Context con)
throws IOException , InterruptedException
{
int tot =0;
Set<String> cat = new HashSet<String>();
for(Text v:vlist){
String data = v.toString();
String[] dataArray = data.Split(",");
tot+ = Integer.parseInt((dataArray[3]); //calculating the total spend
cat.add(dataArray[2]);// finding the number of unique categories

}
con.write(k,new Text(tot.toString()+","+cat.size().toString()));// writing the name,total spend and total unique categories to the output
}
public static void main(String[] args) throws Exception
{
Configuration c = new Configuration();
Job j= new Job(c,"person-wise");
j.setJarByClass(Emp.class);
j.setMapperClass(MyMap.class);
j.setReducerClass(MyRed.class);
j.setOutputKeyClass(Text.class);
j.setOutputValueClass(IntWritable.class);
Path p1 = new Path(args[0]);
Path p2 = new Path(args[1]);
FileInputFormat.addInputPath(j,p1);
FileOutputFormat.setOutputPath(j,p2);
System.exit(j.waitForCompletion(true) ? 0:1);
}

}

关于java - Hadoop Mapreduce实践,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/32988353/

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