Book Image

Learn By Example: Hadoop, MapReduce for Big Data problems [Video]

By : Loonycorn
Book Image

Learn By Example: Hadoop, MapReduce for Big Data problems [Video]

By: Loonycorn

Overview of this book

<p><span id="description" class="sugar_field">This course is a zoom-in, zoom-out, hands-on workout involving Hadoop, MapReduce and the art of thinking parallel. This course is both broad and deep. It covers the individual components of Hadoop in great detail and also gives you a higher level picture of how they interact with each other. It's a hands-on workout involving Hadoop, MapReduce. This course will get you hands-on with Hadoop very early on. You'll learn how to set up your own cluster using both VMs and the Cloud. All the major features of MapReduce are covered, including advanced topics like Total Sort and Secondary Sort. MapReduce completely changed the way people thought about processing Big Data. Breaking down any problem into parallelizable units is an art. The examples in this course will train you to think in parallel.</span></p> <h2><span class="sugar_field">Style and Approach</span></h2> <p><span class="sugar_field"><span id="trade_selling_points_c" class="sugar_field">Hands-on workout involving Hadoop, MapReduce.</span></span></p>
Table of Contents (15 chapters)
Free Chapter
1
Introduction
Chapter 9
The Inverted Index, Custom Data Types for Keys, Bigram Counts and Unit Tests!
Content Locked
Section 4
Represent a Bigram using a WritableComparable
A Bigram is a pair of adjacent words, use a special data type to represent a Bigram, it needs to be a WritableComparable to be serialized across the network and sorted and merged by Hadoop.