Matrix Multiplication with hadoop map reduce

 Driver Logic :

import org.apache.hadoop.fs.Path; 

import org.apache.hadoop.conf.*; 

import org.apache.hadoop.io.*;

import org.apache.hadoop.mapreduce.*;

import org.apache.hadoop.mapreduce.lib.input.FileInputFormat; 

import org.apache.hadoop.mapreduce.lib.input.TextInputFormat; 

import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat; 

import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;

public class MatrixDriver 

{

public static void main(String[] args) throws Exception 

{

Configuration conf = new Configuration();

// M is an m-by-n matrix; N is an n-by-p matrix. 

conf.set("m", "2");

conf.set("n", "2");

conf.set("p", "2");

Job job = Job.getInstance(conf, "MatrixMultiplication"); 

job.setJarByClass(MatrixDriver.class); 

job.setOutputKeyClass(Text.class); 

job.setOutputValueClass(Text.class);

job.setMapperClass(MatrixMapper.class); 

job.setReducerClass(MatrixReducer.class);

job.setInputFormatClass(TextInputFormat.class); 

job.setOutputFormatClass(TextOutputFormat.class);

FileInputFormat.addInputPath(job, new Path(args[0]));

FileOutputFormat.setOutputPath(job, new Path(args[1])); 

job.submit();

}

}

Reducer Logic : 

import java.io.IOException; 

import java.util.*;

import org.apache.hadoop.io.*;

import org.apache.hadoop.mapreduce.*;

public class MatrixReducer extends Reducer<Text, Text, Text, Text> 

{

public void reduce(Text key, Iterable<Text> values, Context context) throws IOException, InterruptedException 

{

String[] value;

HashMap<Integer, Float> hashA = new HashMap<Integer, Float>(); 

HashMap<Integer, Float> hashB = new HashMap<Integer, Float>(); 

for (Text val : values) 

{

value = val.toString().split(",");

if (value[0].equals("M"))

{

hashA.put(Integer.parseInt(value[1]), Float.parseFloat(value[2]));

} 

else

{

hashB.put(Integer.parseInt(value[1]), Float.parseFloat(value[2]));

}

}

int n = Integer.parseInt(context.getConfiguration().get("n")); float result = 0.0f;

float a_ij; float b_jk;

for (int j = 0; j < n; j++) 

{

a_ij = hashA.containsKey(j) ? hashA.get(j) : 0.0f; 

b_jk = hashB.containsKey(j) ? hashB.get(j) : 0.0f; 

result += a_ij * b_jk;

}

if (result != 0.0f) 

{

context.write(null, new Text(key.toString() + "," + Float.toString(result)));

}

}

}

Mapper Logic :

import java.io.IOException; 

import org.apache.hadoop.conf.*; 

import org.apache.hadoop.io.*;

import org.apache.hadoop.mapreduce.*;

public class MatrixMapper extends Mapper<LongWritable, Text, Text, Text> 

{

public void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException 

{

Configuration conf = context.getConfiguration(); 

int m = Integer.parseInt(conf.get("m"));

int p = Integer.parseInt(conf.get("p")); 

String line = value.toString();

String[] indicesAndValue = line.split(","); 

Text outputKey = new Text();

Text outputValue = new Text();

if (indicesAndValue[0].equals("M")) 

{ 

for (int k = 0; k < p; k++)

{

outputKey.set(indicesAndValue[1] + "," + k);

outputValue.set("M," + indicesAndValue[2] + "," + indicesAndValue[3]); 

context.write(outputKey, outputValue);

}

} 

else 

{

for (int i = 0; i < m; i++) 

{

outputKey.set(i + "," + indicesAndValue[2]);

outputValue.set("N," + indicesAndValue[1] + "," + indicesAndValue[3]); context.write(outputKey, outputValue);

}

}

}

}

Step by Step Procedure

source code files