MapReduce Implementation Matrix multiplication: implementation code

Programming Environment:

Java Version "1.7.0_40"

Eclipse Kepler

Windows7 x64

Ubuntu 12.04 LTS

Hadoop2.2.0

Vmware 9.0.0 build-812388

Enter data:

A matrix store address: Hdfs://singlehadoop:8020/workspace/dataguru/hadoopdev/week09/matrixmultiply/matrixa/matrixa

A matrix content:
3 4 6
4 0 8

The Matrixa file has been processed as a (x,y,value) format:

0 0 3

0 1 4

0 2 6

1 0 4

1 1 0

1 2 8

B-Matrix storage address: HDFS://SINGLEHADOOP:8020/WORKSPACE/DATAGURU/HADOOPDEV/WEEK09/MATRIXMULTIPLY/MATRIXB/MATRIXB

B Matrix Content:
2 3
3 0
4 1

The MATRIXB file has been processed as a (x,y,value) format:

0 0 2

0 1 3

1 0 3

1 1 0

2 0 4

2 1 1

Implementation code:

Altogether three classes:

Driver Class Mmdriver

Map Class Mmmapper

Reduce class Mmreducer

More Wonderful content: http://www.bianceng.cnhttp://www.bianceng.cn/Programming/sjjg/

You can combine them into one class based on your personal habits.

Package dataguru.matrixmultiply;  
Import org.apache.hadoop.conf.Configuration;  
Import Org.apache.hadoop.fs.FileSystem;  
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 Mmdriver {public static void main (string[] args) throws Exception {//Set configuration configuration  
      
conf = new Configuration ();  
Create job Job Job = new Job (conf, "matrixmultiply");  
Job.setjarbyclass (Dataguru.matrixmultiply.MMDriver.class);  
Specify Mapper & Reducer Job.setmapperclass (Dataguru.matrixmultiply.MMMapper.class);  
Job.setreducerclass (Dataguru.matrixmultiply.MMReducer.class);  
Specify output types of mapper and reducer Job.setoutputkeyclass (Text.class);  
Job.setoutputvalueclass (Text.class);  
Job.setmapoutputkeyclass (Text.class); Job.setmapouTputvalueclass (Text.class); Specify input and output directories path Inpatha = new Path ("hdfs://singlehadoop:8020/workspace/dataguru/hadoopdev/w  
Eek09/matrixmultiply/matrixa ");  
Path INPATHB = new Path ("Hdfs://singlehadoop:8020/workspace/dataguru/hadoopdev/week09/matrixmultiply/matrixb");  
Path Outpath = new Path ("Hdfs://singlehadoop:8020/workspace/dataguru/hadoopdev/week09/matrixmultiply/matrixc");  
Fileinputformat.addinputpath (Job, Inpatha);  
Fileinputformat.addinputpath (Job, INPATHB);  
      
Fileoutputformat.setoutputpath (Job,outpath);  
Delete Output Directory try{filesystem HDFs = Outpath.getfilesystem (conf);  
if (hdfs.exists (Outpath)) Hdfs.delete (Outpath);  
Hdfs.close ();  
catch (Exception e) {e.printstacktrace ();  
return;  
}//Run the Job System.exit (Job.waitforcompletion (true)? 0:1); }  
}

Package dataguru.matrixmultiply;  
      
Import java.io.IOException;  
      
      
      
Import Java.util.StringTokenizer;  
      
Import Org.apache.hadoop.io.Text;  
      
Import Org.apache.hadoop.mapreduce.Mapper;  
      
      
      
Import Org.apache.hadoop.mapreduce.lib.input.FileSplit;  
      
      
public class Mmmapper extends Mapper<object, text, text, text> {private String tag;//current Matrix private int crow = number of rows of 2;//a matrix private int ccol = 2;//b matrix @Override Prote CTED void Setup throws IOException, interruptedexception {//TODO get InputPath of INP  
      
UT data, set to tag Filesplit fs = (Filesplit) context.getinputsplit ();  
      
Tag = Fs.getpath (). GetParent (). GetName ();  }/** * input data include two matrix files/public void map (Object key, Text value, Context context) throws IOexception, interruptedexception {stringtokenizer str = new StringTokenizer (value.tostring ()); if ("Matrixa". Equals (Tag)) {//left matrix,output key:x,y while (Str.hasmoretokens ()) {String CurrentX = Str.nexttoken ();  
      
X,y,value of current item String currenty = Str.nexttoken ();  
      
String CurrentValue = Str.nexttoken ();  
      
for (int i = 0; i < Ccol i++) {Text Outkey = new Text (currentx+ "," +i);  
      
Text Outvalue = new text ("A," +currenty+ "," +currentvalue);  
      
Context.write (Outkey, Outvalue); System.out.println (outkey+) |  
      
"+outvalue); }}else if ("Matrixb". Equals (Tag)) {while (Str.hasmoretokens ()) {String cur Rentx = Str.nexttoken ();  
      
X,y,value of current item String currenty = Str.nexttoken ();  
      
String CurrentValue = Str.nexttoken (); for (int i = 0; i < Crow i++) {Text Outkey = new Text (i+ "," +currEnty);  
      
Text Outvalue = new text ("B," +currentx+ "," +currentvalue);  
      
Context.write (Outkey, Outvalue); System.out.println (outkey+) |  
      
"+outvalue); }  
      
}  
      
      
}  
      
}  
      
}

Package dataguru.matrixmultiply;  
Import java.io.IOException;  
Import Java.util.HashMap;  
Import Java.util.Iterator;  
Import Java.util.Map;  
      
Import Java.util.StringTokenizer;  
Import org.apache.hadoop.io.IntWritable;  
Import Org.apache.hadoop.io.Text;  
Import Org.apache.hadoop.mapreduce.Reducer;  
      
Import Org.apache.hadoop.mapreduce.Reducer.Context; public class Mmreducer extends Reducer<text, text, text, text> {public void reduce (text key, iterable<t Ext> values, Context context) throws IOException, interruptedexception {map<string,string> Matrixa =  
New Hashmap<string,string> ();  
map<string,string> MATRIXB = new hashmap<string,string> (); for (Text val:values) {//values example:b,0,2 or a,0,4 stringtokenizer str = new StringTokenizer (val.tostring (), ","  
);  
String Sourcematrix = Str.nexttoken ();  if ("a". Equals (Sourcematrix)) {Matrixa.put (Str.nexttoken (), Str.nexttoken ());//(0,4)}
if ("B". Equals (Sourcematrix)) {Matrixb.put (Str.nexttoken (), Str.nexttoken ());//(0,2)}} int result = 0;  
Iterator<string> iter = Matrixa.keyset (). iterator ();  
while (Iter.hasnext ()) {String Mapkey = Iter.next ();  
result = Integer.parseint (Matrixa.get (Mapkey)) * Integer.parseint (Matrixb.get (Mapkey));  
} context.write (Key, New Text (string.valueof)); }  
}

Final output results:

0,042
0,115
1,040
1,120

Author: csdn Blog u014512124