Santa Clara University

Big-Data-MapReduce-Course

Course Information: Fall 2018

• Graduate School, Leavey School of Business
• Department of Information Systems & Analytics
• Course MSIS 2627: Big Data Modeling & Analytics
• Big-Data-MapReduce Course @ Santa Clara University
• Class Meeting dates: 09/18/2018 - 12/7/2018
• Class hours:
  • Tuesday 5:45PM - 7:00PM PST
  • Thursday 5:45PM - 7:00PM PST
• Class room: Lucas Hall 210
• Office: 321 T, Lucas Hall

Required Books and Papers

• 1. A
 Very
Brief 
Introduction
 to 
MapReduce by Diana 
MacLean
• 2. Introduction to MapReduce by Mahmoud Parsian
• 3. Data-Intensive Text Processing with MapReduce by Jimmy Lin and Chris Dyer
• 4. Mining of Massive Datasets by Jure Leskovec, Anand Rajaraman, Jeffrey D. Ullman

Syllabus

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Midterm Exam

• Midterm Exam Date: Thursday, October 18, 2018
• Midterm Exam Time: 5:45PM - 7:00PM PST

Final Exam

• Final Exam Date: Thursday, December 6, 2018
• Final Exam Time: 5:45PM - 7:45PM PST

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Course Description

The main focus of this class is to cover the following concepts:

• Concepts of Big Data
• Distributed File Systems
• Distributed Computing
• Distributed and Parallel Algorithms
• MapReduce Paradigm
• MapReduce Algorithms
• Scale-out Architectures (using Hadoop, Spark, PySpark)
• Apache Spark: http://spark.apache.org/
• Use Spark, Py-Spark, Hadoop, and Java to teach MapReduce and distributed computing
• SQL for NoSQL Data, How?

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My latest book:

Data Algorithms Book

Data Algorithms: Recipes for Scaling up with Hadoop and Spark