Introduction to Big data and Data Science

Lesson Title: Hadoop MapReduce and Hadoop Distributed File System (HDFS)

Lesson Description: Overview of Hadoop and Map Reduce Paradigm. The Lesson focuses on
map reduce applications with coding exercises by actual implementation

In class exercise

1. Matrix Multiplication in Map Reduce

Suppose we have a i x j matrix M, whose element in row i and column j will be denoted and
a j x k matrix N whose element in row j and column k is donated by then the product P = MN
will be i x k matrix P whose element in row i and column k will be donated by ,
where = .

1. Create a Map-Reduce Program to perform the task of matrix multiplication

Reference:
https://lendap.wordpress.com/2015/02/16/matrix-multiplication-with-mapreduce/

2. Breadth First Search using Map Reduce
3. Depth First Search using Map Reduce
4. Apply Map reduce problem using K-Means Clustering Technique. A view
   point of the such algorithms are presented in the screenshot.
   Convert this into code and use right dataset to implement this scenario.

Marks will be distributed between logic, implementation and UI

Programming elements:
Hadoop MapReduce and HDFS

Source Code:

Given in canvas.