Course info
Sep 22, 2016
1h 48m

Processing millions of records requires that you first understand the art of breaking down your tasks into parallel processes. The MapReduce programming model, part of the Hadoop eco-system, gives you a framework to define your solution in terms of parallel tasks, which are then combined to give you the final desired result. In this course, Understanding the MapReduce Programming Model, you'll get an introduction to the MapReduce paradigm. First, you'll learn how it helps you visualize how data flows through the map, partition, shuffle, and sort phases before it gets to the reduce phase and gives you the final result. Next, it will guide you through your very first MapReduce program in Java. Finally, you'll learn to extend the framework Mapper and Reducer classes to plug in your own logic and then run this code on your local machine without using a Hadoop cluster. By the end of this course, you will be able to break big data problems into parallel tasks to help tackle large-scale data munging operations.

About the author
About the author

A problem solver at heart, Janani has a Masters degree from Stanford and worked for 7+ years at Google. She was one of the original engineers on Google Docs and holds 4 patents for its real-time collaborative editing framework.

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