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Posted: January 31st, 2022
CSCE 5300 Introduction to Big data and Data Science
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Lesson Title: Hadoop MapReduce and Hadoop Distributed File System (HDFS)
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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 = .
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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/
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2. Breadth First Search using Map Reduce
3. Depth First Search using Map Reduce
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ICE-3 CSCE 5300 Introduction to Big Data and Data Science
Hadoop MapReduce and Hadoop Distributed File System are the titles of this lesson (HDFS)
Lesson Summary: An overview of the Hadoop and Map Reduce paradigms. The focus of the lesson is
map reduce apps through coding exercises followed by actual implementation
Exercise in class
1. Map Reduce Matrix Multiplication
Assume we have an I x j matrix M, with elements in row I and column j indicated and
a j x k matrix N, where each element in row j and column k is supplied by 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
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