Feb 21, 2025 · for (int k = 0; k < 2; k++) { // Assuming matrix B has 2 columns. outputKey.set(row + "," + k); outputValue.set("A," + col + "," + val); context.write(outputKey, outputValue); } else if...

Nov 30, 2011 · It may be a primitive suggestion but, you may need to change log filename with /tmp/Matrix\ Multiply/out/_logs. Spaces in directory names may not be handled automatically and I assumed you are working on Linux.

Feb 10, 2021 · I'm working on the matrix multiplication using mapreduce. I built a jar file using the code below. the code works perfectly fine with smaller matrices but when the files becomes large the mapping phase will stop at 67% then it will give me this errors below: at MatrixMult$mapper.map(MatrixMult.java:44) at Matrix$mapper.map(MatrixMult.java:1)

Jun 15, 2019 · In this post, we will be writing a map-reduce program to do Matrix Multiplication. Requirements. You need Hadoop’s HDFS and map-reduce framework to test the program.

Mar 15, 2012 · I was running the MapReduce Matrix Multiplication program found at http://www.norstad.org/matrix-multiply/index.html. I found out that this implementation doesn't work properly when there are 0's in the input matrices. But I don't understand why, and how do I modify the program to make it work?

import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat; import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat; public class TwoStepMatrixMultiplication {

Feb 16, 2015 · I developed mapper and reducer classes as Map.java and Reduce.java as well as the main application class called MatrixMultiply.java. As it seen in MatrixMultiply.java code below, in main method the configuration parameters are being set as well as the input/output directories of MapReduce job [2].

Matrix Multiplications via MapReduce: realized by using Hadoop in Java. 1) A Hadoop MapReduce program, TwoPhase.java, that computes the multiplication of two large-scale matrices using the two-phase approach (https://adhoop.wordpress.com/2012/03/28/matrix_multiplication_2_step/).

Mar 12, 2018 · MapReduce is made of three steps. Reduce: Aggregare, summarize, filter or transform and then give the output. In this post, I’ll explain how to accomplish a matrix multiplication task with map reduce model. There are two ways of doing this. In one Map and Reduce part, or using two Map and Reduce tasks.

This document describes how to perform matrix multiplication using MapReduce on Hadoop. It involves the following steps: 1. Installing Hadoop in standalone mode and configuring Java settings. 2. Developing MapReduce programs including mappers, reducers, and a driver class for matrix multiplication.