Short Bio

Dr. Reza Farivar is a senior software development engineer at the Yahoo! Inc. He received his B.S. degree in Electrical Engineering from the AmirKabir University of Technology in 2003, and his M.S. degree in Computer Engineering from the Sharif University of Technology in 2005. He received his PhD in Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign in 2012 focusing on big data programming models.. He was a postdoctoral research associate at the Institute of Genomic Biology at the University of Illinois, with his research focusing on the application of Big Data computing platforms, and cloud technologies in bioinformatics.

His major research interests include parallel programming models in cloud computing environments, Big Data computing platforms, heterogeneous computing algorithms (specifically with GPUs) and combining GPUs and cloud computing paradigms. His past research interests included reliability and security as well as ubiquitous computing. He has been involved in developing and teaching full-semester courses and short classes on cloud computing, Big Data and operating systems at the University of Illinois since 2011.

Cloud Computing and Big Data Course Syllabus

Session 1: Introduction

• Introduction: Importance of Clouds and Big Data
• Cloudonomics: Economics basis of cloud computing
• Amazon Web Services: A collection of cloud technologies
• OpenStack: How to deploy your own cloud infrastructure

Session 2: Programming in MapReduce

• MapReduce programming concept
• Thinking in MapReduce: team-based exercises
• The Apache Hadoop Project

Lab 1: HadoopMapReduce

• Try writing a program in Hadoop

Session 3: Databases in the cloud:Pig, Hive, BigTable, Hbase, Cassandra

• Higher level abstracts
  • PIG scripting language
  • Hive querying language (HQL)
• NoSQL Databases
• Eventual Consistency model, CAP theorem
• Introduction to the BigTable and HBase systems design
• Cassandra: Using consistent hashing for key placement

Session 4: Cloud Streaming Engines: S4 and Storm

• The need for Big Data streaming computing platforms
• Thinking in streams
• Counting Words in data streams
• Brief introduction to S4
• Detailed introduction to Apache Storm

Lab 2: Storm

• Working with streams in Storm