vivekrajyaguru/big-data-mapreduce-course

Big Data Modeling, MapReduce, Spark, PySpark @ Santa Clara University

Big Data Modeling & Analytics

Santa Clara University

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Fall Quarter 2022

Course Information:

• 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 9, 2022
  • End: December 9, 2022
• Class hours:
  • Tuesday 5:45 PM - 7:20 PM PST (TBDL/online/via Zoom)
  • Thursday 5:45 PM - 7:20 PM PST (TBDL/online/via Zoom)
• Instructor: Mahmoud Parsian
• Class room: Lucas Hall 210
• Office: 216AA, 2nd Floor, Lucas Hall (not used due to covid-19)
• Office Hours: TBDL (or by appointment)
• Office Hours ethics: if you are planning to attend an office hour, then you should send me an email

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Instructor:

• Adjunct Professor: Mahmoud Parsian
  • Ph.D in Computer Science
  • Lead Big Data Architect @Illumina
  • LinkedIn Profile
  • Email address

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Big Data Modeling Class Web Site

• Class Web Site GitHub

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Required Books

• 1.Data Algorithms with Spark by Mahmoud Parsian
  • Source code @github.com -- Data Algorithms with Spark by Mahmoud Parsian
• 2.Data-Intensive Text Processing with MapReduce by Jimmy Lin and Chris Dyer

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Required Introduction to MapReduce and Spark

• 1. A Very Brief Introduction to MapReduce by Diana MacLean
• 2. Introduction to MapReduce by Mahmoud Parsian
• 3. MapReduce: Simplified Data Processing on Large Clusters, Jeffrey Dean and Sanjay Ghemawat

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Additional Optional Books and References

• 1. PySpark Algorithms by Mahmoud Parsian
• 2. Source code @github.com -- PySpark Algorithms by Mahmoud Parsian
• 3. Mining of Massive Datasets by Jure Leskovec, Anand Rajaraman, Jeffrey D. Ullman
• 4. Big Data Now -- book
• 5. Designing Good Mapreduce Algorithms by Ullman
• 6: Bigtable: A Distributed Storage System for Structured Data
• 7. Relational Algebra and MapReduce
• 8. MapReduce examples
• 9. MapReduce and relational algebra
• 10. Spark Streaming Tutorial
• 11. Billion Taxi Rides on Amazon Athena

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Required Software:

• Apache Spark Site
• Apache Spark Download, Use version 3.2.1

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Syllabus, Fall Quarter 2022

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Grading and Class Conduct

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Midterm Exam:

🍏 Date: Thursday, October 27, 2022

🍏 Time: 5:45 PM - 7:20 PM PST

🍏 Midterm exam is closed book/notes/friends/internet/phone/software

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Final Exam:

🍎 Date: Thursday, December 8, 2022

🍎 Time: 5:45 PM - 7:45 PM PST

🍎 Final exam is closed book/notes/friends/internet/phone/software

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Course Description (High-Level)

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

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Mahmoud Parsian's Latest Books:

Data Algorithms with Spark

PySpark Algorithms

Data Algorithms