Readings

Map Reduce and Hadoop

Two recommended academic texts on MapReduce are the Lin-Dyer book and the Leskovec-Rajaraman-Ullman Book. For each of these books, Chapter 2 is recommended reading. The material can be found by looking at the Content area on the ICON site for this course. Whereas MapReduce is the "big idea" of the framework originated by Google, we have to use a particular system to actually run MapReduce jobs in a practical language like Java or Python. We'll use the Hadoop and Spark systems primarily in this course.

The Course Overview page lists a few of the many trade books now available for learning Hadoop, which is the most commonly available way to run MapReduce jobs (the last book is on Spark, another framework also based on Hadoop's file system).

Readings (last edited 2015-08-10 21:38:52 by Ted Herman)