Distributed applications running on Hadoop clusters can deliver powerful insights and results from the biggest data sets ever generated. But do you have to be a rocket scientist to use it? Fortunately, the answer is no. This tutorial will explain the theory of MapReduce and how to develop big data applications in Java and higher level languages such as Pig and Hive SQL. Using practical, real-world examples such as weblog processing, analytics, and text summarization, it will cover how to prototype, debug, monitor, test and optimize big data applications for Hadoop’s distributed processing platform. Attendees will get hands-on instruction and will leave with a solid understanding of how to analyze data on Hadoop clusters and practical examples they can use and build on after the tutorial.
Table of Contents
How to Develop Big Data Applications for Hadoop Part 1
How to Develop Big Data Applications for Hadoop Part 2
How to Develop Big Data Applications for Hadoop Part 3