• 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:
  • Start: September 23, 2019
  • End: December 7, 2019
• Class hours:
  • MSIS 2627-01 (92426) MW 5:45:00 PM 7:20:00 PM
  • MSIS 2627-02 (92427) MW 7:35:00 PM 9:10:00 PM
• Instructor: Mahmoud Parsian
• Class room: Lucas Hall 307
• Office: 216AA, 2nd Floor, Lucas Hall
• Office Hours: by appointment

• 1.PySpark Algorithms Book by Mahmoud Parsian
  • Buy from amazon.com -- PySpark Algorithms Book -- PDF Version
  • Buy from amazon.com -- PySpark Algorithms Book -- Kindle Version
  • Source code @github.com -- PySpark Algorithms Book by Mahmoud Parsian
• 2.Data-Intensive Text Processing with MapReduce by Jimmy Lin and Chris Dyer
• 3.Mining of Massive Datasets by Jure Leskovec, Anand Rajaraman, Jeffrey D. Ullman

• 1. A Very Brief Introduction to MapReduce by Diana MacLean
• 2. Introduction to MapReduce by Mahmoud Parsian

• Apache Spark Site
• Apache Spark Download

• MSIS 2627-01 (92426): Monday, 5:45:00 PM 7:20:00 PM, PST
• MSIS 2627-02 (92427): Monday, 7:35:00 PM 9:10:00 PM, PST

• Mon/Wed 5:45 pm classes
  • Monday, December 9, 2019, 5:45 – 7:45 pm, PST
• Mon/Wed 7:35 pm classes
  • Wednesday, December 11, 2019, 5:45 – 7:45 pm, PST

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
• Use Spark, Py-Spark, and Python to teach MapReduce and distributed computing
• SQL for NoSQL Data, How?
• Amazon Athena
• Amazon Athena, S3, Data Partitioning

PySpark Algorithms

Data Algorithms: Recipes for Scaling up with Hadoop and Spark