Big Data Processing With Hadoop

Big Data Processing With Hadoop

T. Revathi (Mepco Schlenk Engineering College, India), K. Muneeswaran (Mepco Schlenk Engineering College, India) and M. Blessa Binolin Pepsi (Mepco Schlenk Engineering College, India)
Release Date: November, 2018|Copyright: © 2019 |Pages: 244
ISBN13: 9781522537908|ISBN10: 1522537902|EISBN13: 9781522537915|DOI: 10.4018/978-1-5225-3790-8


Due to the increasing availability of affordable internet services, the number of users, and the need for a wider range of multimedia-based applications, internet usage is on the rise. With so many users and such a large amount of data, the requirements of analyzing large data sets leads to the need for further advancements to information processing.

Big Data Processing With Hadoop is an essential reference source that discusses possible solutions for millions of users working with a variety of data applications, who expect fast turnaround responses, but encounter issues with processing data at the rate it comes in. Featuring research on topics such as market basket analytics, scheduler load simulator, and writing YARN applications, this book is ideally designed for IoT professionals, students, and engineers seeking coverage on many of the real-world challenges regarding big data.

Topics Covered

The many academic areas covered in this publication include, but are not limited to:

  • API
  • Architecture Components
  • Customer Analytics
  • Hadoop Architecture
  • HDFS
  • MapReduce Programming
  • Market Basket Analytics
  • Pseudo-Distributed Operation
  • Scheduler Load Simulator
  • Writing YARN Applications

Promotional Video

Table of Contents and List of Contributors

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