Big Data with Hadoop MapReduce: A Classroom Approach

The authors provide a comprehensive understanding of big data and MapReduce, with over 100 illustrations and worked-out examples. It covers almost all the necessary information for certification exams and helps readers understand other big data processing tools such as Spark and Storm.

Format: Paperback / softback
Length: 406 pages
Publication date: 09 March 2022
Publisher: Apple Academic Press Inc.

The authors offer a comprehensive and accessible guide to big data and MapReduce, presenting the fundamental terminologies and concepts with clarity. Through the use of over 100 illustrations and numerous worked-out examples, they effectively convey the concepts and methodologies employed in big data, the inner workings of MapReduce, and the installation of single-node and multi-node configurations on physical and virtual machines. This book serves as an essential resource for preparing for most online certification exams related to Hadoop MapReduce. Upon completing this comprehensive guide, readers will gain a deep understanding of big data and its various aspects. They will acquire a firm grasp of MapReduce's inner workings, which are crucial for certification exams. Furthermore, readers will explore the features and limitations of MapReduce, learn how to set up Hadoop clusters with hundreds of physical and virtual machines, and develop virtual machines on AWS. The book also provides a straightforward approach to writing MapReduce with Eclipse, enabling readers to apply their knowledge effectively. Additionally, readers will gain insights into other big data processing tools and their applications, expanding their knowledge and expertise in the field. By leveraging the wealth of information provided in this book, readers will be well-equipped to navigate the complexities of big data and leverage its power for their professional endeavors.

Weight: 784g
Dimension: 234 x 156 (mm)
ISBN-13: 9781774634844