This course will be a mix of lecture, paper presentation and a project. The course will introduce the students to the world of Big Data Systems and Analytics Frameworks. Instructor will first discuss the limitation of the prior technologies that were not sufficient to process Big Data, followed by the introduction and in-depth discussion of the technologies that were developed as part of Big Data Processing. Later part of the course will consists of discussion on classical and recent papers on big data systems and analytics frameworks. Each student have to present at least a paper. Student will work on a semester long project, and also have to work on a few home assignments.
Keywords: Big Data, Map-reduce, Spark, NoSQL Store, Data Consistency, Batch Analytics, Stream Analytics, Data Parallel Systems
Requirements: Database Management System or Instructor’s permission
Textbook: Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems by Martin Kleppmann
Syllabus and Class Schedule: Pending