mapreduce中的序列号

Question

我已经编写了Java代码来创建Java中的RowId。但我需要将其转换为mapreduce。我是MapReduce的新手，需要你的帮助。

输入是在当地

example: Alex 23 M NY 

Alex 19 M NJ 

Alex 29 M DC 

Michael 20 M NY 

Michael 24 M DC 

计数文件提供为次输入 示例文件：

Alex 3 

Michael 2 

Desired Output: 
1 Alex 23 M NY 

2 Alex 19 M NJ 

3 Alex 29 M DC 

1 Michael 20 M NY 

2 Michael 24 M DC 

我在Java代码是在这里：

public class RowId 
        { 
public static void main(String [] args) throws IOException 
       { 
BufferReader in = null; 
BufferReader cnt = null; 
BufferWriter out = null; 
String in_line; 
String out_line; 
int frst_row_ind=1; 
int row_cnt=0; 
int new_col=0; 

try{ 
in= BufferReader(new FileReader ("file path in local"); 
File out_file = new File("o/p path in local"); 
if(!out_file.exists()){ 
out_file.createNewFile(); 
     } 

FileWriter fw = new FileWriter(out_file); 

out = new BufferWriter(fw); 
while((in_line = in.readLine())! = null) 
{ 

if (in_line!=null) 

{ 
String[] splitData = in_line.split("\\t"); 
cnt = new BufferReader(new FileReader("file path of countFile") 
while((cnt_line=cnt.readLine()) != null) 
{ 
String[] splitCount = cnt_line.split("\\t"); 
if ((splitCount[0]).equalsIgnoreCase(splitData[0])) 
{ 
if (frst_row_ind==1) 
{ 
row_cnt = Integer.parseInt(splitCount[1]); 
} 
new_col++ 
out.write(String.valueOf(new_col)); 
out.write("\\t"); 

for(int i= 0; i <splitData.length; i++) 
{ 
if (!(splitData[i] == null) || (splitData[i].length()== 0)) 
{ 
out.write(splitData[i].trim()); 
if (i!=splitData.length-1) 
{ 
out.write("\\t"); 
} 
} 
} 

row_cnt--; 
out.write("\r\n"); 
if(row_cnt==0) 
{ 
frst_row_ind=1; 
new_col=0; 
} 
else{ 
frst_row_ind=0; 
} 
out.flush(); 
break; 
} 
} 
} 
} 
} 
catch (IOException e) 
{ 
e.printStrackTrace(); 
} 
finally 
{ 
try{ 
if(in!=null) in.close(); 
if(cnt !=null) cnt.close(); 
} 
catch (IOException e) 
{ 
e.printStrackTrace(); 
} 
} 
} 
} 

请不要复归与你的想法（S）。

Answer 1

下面是你可以y = try的代码。注意：我没有执行相同的操作，但希望它能给你所需的输出。

public class StMApper extends Mapper<LongWritable,Text,Text,Text> 
{ 
Text outkey-new Text(); 
Text outvalue=new Text(); 

public void map(LongWritable key,Text values, Context context) 
{ 
    //Alex 19 M NJ 
    String []col=values.toString().split(" "); 
    outkey.set(cols[0]); 
    outvalue.set(values.toString()); 
    context.write(outkey,outvalue); 
} 
} 

public class StReducer extends Reducer<Text,Text,IntWritable,Text> 
{ 
IntWritable outkey=new IntWritable(); 
Text outvalue=new Text(); 
    ////Alex{Alex 19 M NJ , Alex 29 M DC,...} 
public void reduce(Text key,Iterable<Text> values,Context context) 
{ 
    int i=0; 
    for(Text val:values) 
    { 
     outkey.set(i); 
     outvalue.set(val); 
     i++; 
     context.write(outkey,outvalue); 
    } 
} 
}