Mr.IAP Course Description

This is the course announcement from the IAP Course Guide












Indexing the web, training spam filters over millions of documents, running weather simulations, solving protein folding problems, sorting a billion strings... Do you want to learn how to write programs that do these things, using a large distributed network and with only a small amount of problem-specific code?

These applications and many more can be written using MapReduce, a paradigm for distributed computation in widespread use at Google. In this three-day intensive class, you will study both the theory and practice of MapReduce: how to recognize a MapReduce, what it's good for, what it's not good for, advanced tips and techniques, and how it fits into the wide world of distributed computing. The class will include programming exercises using Hadoop, an open- source implementation of MapReduce, on Google's academic datacenter cluster. The class will be taught by Google engineers.

Prereq: Some experience with computer programming, preferably in Java. No previous knowledge of distributed computation is assumed.

Participants will be expected to attend all sessions. Lunch will be provided. Continued access to the cluster (and mentorship) will be available following the course for students wanting to complete larger projects. Registration limited, so preregistration is strongly encouraged.

Faculty Sponsor: Daniel Jackson

To preregister, email