Cloud computing has recently seen a lot of attention from research and industry for applications that can be parallelized on shared-nothing architectures and have a need for elastic scalability. As a consequence, new data management requirements have emerged with multiple solutions to address them. This course will look at the principles behind data management in the cloud as well as discuss actual cloud data management systems that are currently in use or being developed. The topics covered in the course range from novel data processing paradigms (MapReduce, Scope, DryadLINQ), to commercial cloud data management platforms (Google BigTable, Microsoft Azure, Amazon S3 and Dynamo, Yahoo PNUTS) and open-source NoSQL databases (Cassandra, MongoDB, Neo4J). The world of cloud data management is currently very diverse and heterogeneous. Therefore, our course will also report on efforts to classify, compare and benchmark the various approaches and systems. Students in this course will gain broad knowledge about the current state of the art in cloud data management and, through a course project, practical experience with a specific system.
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Students must have a knowledge of database design, implementation, and query languages (CS 386, CS 586 or equivalent) and must be comfortable programming in a language appropriate for systems implementation, such as C/C++, Java, or C#.
There will be weekly reading assignments, plus a course project consisting of study questions, a programming project, and a 3 page paper.
There will be no exams in this class.
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[Excerpt from the 2010-2011 PSU Catalog, page 34]