减速，MapReduce的，不显示错误，但没有给出所需的输出

Question

销售激励类

package mr.map; 

import org.apache.hadoop.conf.Configuration; 
import org.apache.hadoop.fs.Path; 
import org.apache.hadoop.mapreduce.Job; 
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat; 
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat; 

import org.apache.hadoop.io.Text; 
import org.apache.hadoop.io.FloatWritable; 
//import org.apache.hadoop.mapreduce.Mapper; 
//import org.apache.hadoop.mapreduce.Reducer; 

public class SalesDriver 
{ 
    public static void main(String args[]) throws Exception 
    { 
     Configuration c=new Configuration(); 
     Job j=new Job(c,"Sales"); 

     j.setJarByClass(SalesDriver.class); 
     j.setMapperClass(SalesMapper.class); 
     j.setReducerClass(SalesReducer.class); 

     //j.setNumReduceTasks(0); 
     j.setOutputKeyClass(Text.class); 
     j.setOutputValueClass(FloatWritable.class); 

     Path in=new Path(args[0]); 
     Path out=new Path(args[1]); 

     FileInputFormat.addInputPath(j, in); 
     FileOutputFormat.setOutputPath(j, out); 

     System.exit(j.waitForCompletion(true)?0:1); 
    } 
} 

销售映射类

package mr.map; 

import java.io.IOException; 

//import org.apache.hadoop.io.IntWritable; 
import org.apache.hadoop.io.FloatWritable; 
import org.apache.hadoop.io.LongWritable; 
//import org.apache.hadoop.io.DoubleWritable; 
import org.apache.hadoop.io.Text; 
import org.apache.hadoop.mapreduce.Mapper; 

public class SalesMapper extends Mapper<LongWritable, Text, Text, FloatWritable> 
{ 
    public void map(LongWritable k, Text v, Context con) throws IOException, InterruptedException 
    { 
     String w[]=v.toString().split(" "); 
     String product=w[3]; 
     //String store=w[2]; 
     //float cost=Integer.parseInt(w[4]); 
     float costx = Float.parseFloat(w[4]); 

     //String newline= product+","+store; //","+costx; 
     //String newline = product; 
     con.write(new Text(product), new FloatWritable(costx)); 
    } 
} 

销售减速类

package mr.map; 

import java.io.IOException; 

import org.apache.hadoop.io.FloatWritable; 
//import org.apache.hadoop.io.IntWritable; 
//import org.apache.hadoop.io.DoubleWritable; 
import org.apache.hadoop.io.Text; 
import org.apache.hadoop.mapreduce.Reducer; 

public class SalesReducer extends Reducer<Text, FloatWritable, Text, FloatWritable> 
{ 
    public void reduce(Text k, Iterable<FloatWritable>vlist, Context con) throws IOException, InterruptedException 
    { 
     int tot=0; 
     for (FloatWritable v:vlist) 
     { 
      tot += v.get(); 
     } 
     //int total= (int)tot; 
     con.write(new Text(k), new FloatWritable(tot)); 
    } 
} 

结果MapReduce

我不明白为什么所有的结果都出现在一个大的浮点数和全部数字5.7480884E7。

下面是输入到映射精简程序的例子：

2012-01-01 09:00 San Jose Men's Clothing 214.05 Amex    
    2012-01-01 09:00 Fort Worth Women's Clothing 153.57 Visa   
    2012-01-01 09:00 San Diego Music 66.08 Cash      
    2012-01-01 09:00 Pittsburgh Pet Supplies 493.51 Discover   
    2012-01-01 09:00 Omaha Children's Clothing 235.63 MasterCard  
    2012-01-01 09:00 Stockton Men's Clothing 247.18 MasterCard   
    2012-01-01 09:00 Austin Cameras 379.6 Visa       
    2012-01-01 09:00 New York Consumer Electronics 296.8 Cash   
    2012-01-01 09:00 Corpus Christi Toys 25.38 Discover    
    2012-01-01 09:00 Fort Worth Toys 213.88 Visa      
    2012-01-01 09:00 Las Vegas Video Games 53.26 Visa     
    2012-01-01 09:00 Newark Video Games 39.75 Cash      
    2012-01-01 09:00 Austin Cameras 469.63 MasterCard     
    2012-01-01 09:00 Greensboro DVDs 290.82 MasterCard     
    2012-01-01 09:00 San Francisco Music 260.65 Discover    
    2012-01-01 09:00 Lincoln Garden 136.9 Visa       
    2012-01-01 09:00 Buffalo Women's Clothing 483.82 Visa    
    2012-01-01 09:00 San Jose Women's Clothing 215.82 Cash    
    2012-01-01 09:00 Boston Cameras 418.94 Amex      
    2012-01-01 09:00 Houston Baby 309.16 Visa       
    2012-01-01 09:00 Las Vegas Books 93.39 Visa      
    2012-01-01 09:00 Virginia Beach Children's Clothing 376.11 Amex 
    2012-01-01 09:01 Riverside Consumer Electronics 252.88 Cash  
    2012-01-01 09:01 Tulsa Baby 205.06 Visa       
    2012-01-01 09:01 Reno Crafts 88.25 Visa       
    2012-01-01 09:01 Chicago Books 31.08 Cash       
    2012-01-01 09:01 Fort Wayne Men's Clothing 370.55 Amex    
    2012-01-01 09:01 San Bernardino Consumer Electronics 170.2 Cash 
    2012-01-01 09:01 Madison Men's Clothing 16.78 Visa     
    2012-01-01 09:01 Austin Sporting Goods 327.75 Discover    
    2012-01-01 09:01 Portland CDs 108.69 Amex       
    2012-01-01 09:01 Riverside Sporting Goods 15.41 Discover   
    2012-01-01 09:01 Reno Toys 80.46 Visa        
    2012-01-01 09:01 Anchorage Music 298.86 MasterCard  

Answer 1

变化减速器的输出值类型设置为文本，并转换浮动到预期的格式字符串。

String.format("%f",tot) 

按照以下职位详细信息格式化数字：
with scientific
without scientific notation

减速机：

public class SalesReducer extends Reducer<Text, FloatWritable, Text, Text> 
{ 
    public void reduce(Text k, Iterable<FloatWritable>vlist, Context con) throws IOException, InterruptedException 
    { 
     float tot=0; 
     for (FloatWritable v:vlist) 
     { 
      tot += v.get(); 
     } 
     //int total= (int)tot; 
     con.write(new Text(k), new Text(String.format("%f",tot))); 
    } 
} 

Answer 2

您存储int变量花车和的值。
现在第一件事是int不能在小数点后精确处理浮点值。其次，如果行数非常高，则总和值可能会超出可接受的范围 int。

请尝试将int变量从int更改为 float或 double。

double tot=0; 

这