10 Best Books on Hadoop

“Hadoop in Practice” Book Review: This book provides a conceptual overview of Hadoop and MapReduce. It has 85 practical-tested techniques and examples which are present in a problem/solution format. It balances conceptual foundations with practical experiments for main problem areas like data ingress and egress, serialization, and LZO compression. The book illustrates each technique step by step and also helps to learn how to build specific solutions along with the thinking. In addition, the book gives various real-world examples which create a well-structured and understandable codebase. It requires the basic knowledge of Hadop as prerequisite.

“Pro Hadoop” Book Review: This book is designed to teach students about Hadoop. It covers various aspects such as MapReduce, cluster structure, Hadoop file system design, and implementation. Additionally, it explains how to create cloud-computing tasks using Hadoop. The book also provides information on how to avoid expensive errors that are commonly made when setting up a Hadoop system.

“Hadoop Essentials: A Quantitative Approach” Book Review: This book is helpful for developers and computer science students who want to learn Hadoop MapReduce programs quickly. It provides an example of how to mine client application patterns from a large amount of credit card data using Hadoop MapReduce. The book includes step-by-step instructions for setting up Hadoop environments on your computer. It uses Hadoop Java APIs, Hadoop configuration parameters, complete MapReduce programs, and their execution logs and outputs to explain how the Hadoop MapReduce framework works and how to write MapReduce programs. This textbook is an effective way for students to gain Hadoop skills, and it can be used as a supplement for a distributed computing or Hadoop course for upper-level computer science students.

“Apache Hadoop Yarn” Book Review: This book is about a technology called Hadoop that helps with processing large amounts of data. It teaches how to write code and create new applications in Hadoop. The book explains the design and structure of Hadoop yarn, which is a part of Hadoop that helps with managing resources and creating applications that can process huge amounts of data. It also shows how yarn makes Hadoop more efficient and allows for new programming models. The book covers topics like how to set up and manage yarn, and how to use it with other open source tools. It has many examples that show how to use Hadoop yarn and how to create applications that work with it. It also includes sample projects and case studies. This book is helpful for people who want to learn about Hadoop and its applications.

“Hadoop: The Definitive Guide” Book Review: This book is helpful for programmers who want to analyze large datasets and for administrators who want to create and manage Hadoop clusters. It includes new chapters on projects related to Hadoop, such as Parquet, Flume, Crunch, and Spark. The book explains the fundamental parts of Hadoop, like MapReduce, HDFS, and YARN. It provides guidance on setting up and maintaining a Hadoop cluster with HDFS and MapReduce on YARN. The book also gives a detailed explanation of MapReduce, including the steps for creating applications with it.

“Hadoop Operations” Book Review: This book is necessary for managing big and intricate Hadoop clusters. It shows all the possible scenarios, how they operate and what works in important deployments. The book offers an overview of Hadoop Distributed File System (HDFS) and MapReduce and explains their purpose and functionality. It assists in planning and understanding Hadoop implementation, from choosing hardware and operating systems to meeting network requirements. It also provides guidance on using various basic tools and methods to manage backup and handle disastrous situations.

“Hadoop in Action” Book Review: This book is helpful for students who want to learn how to use Hadoop and write MapReduce programs. It explains how to get Hadoop and set it up in a cluster, and how to write data analytic programs. The book teaches the fundamental concepts of MapReduce applications developed using Hadoop, including the framework components, and how to use Hadoop for different data analysis tasks. There are many examples provided. The book also teaches design patterns and practices for programming MapReduce. To understand the code examples in the book, you should have some basic knowledge of Java. If you know some statistical concepts, it will help you to understand the more advanced data processing examples.

“Expert Hadoop Administration: Managing, Tuning, and Securing Spark, YARN, and HDFS” Book Review: This book explains the structure of Hadoop and how to manage job workflows using Oozie and Hue. It covers topics such as HDFS commands, file permission, and storage management. It also teaches how to allocate resources, move data and schedule jobs using yarn. In addition, it provides information on running MapReduce and Spark applications in a Hadoop cluster.

“Moving Hadoop in the Cloud” Book review: This book is about setting up and managing cloud-based clusters effectively. It explains how to create clusters that work with cloud-provider features to avoid problems and take advantage of these services. The book also compares Amazon, Google, and Microsoft clouds, and teaches how to set up clusters in each of them. It explains how Hadoop clusters work in the cloud and their potential benefits and drawbacks. The book also covers important cloud provider concepts like computing capabilities, networking and security, and storage. Readers can learn to build a functional Hadoop cluster on cloud infrastructure and understand the requirements of major cloud providers. The book includes real-world examples like high availability, relational data with Hive, and complex analytics with Spark. Readers can also learn patterns and practices for running cloud clusters, including design for price and security and dealing with maintenance.

“Hadoop for Dummies” by Roman B Melnyk and Bruce Brown Book Review: This book is a beginner’s guide to Hadoop, a software used to manage and analyze large amounts of data. It explains the importance of big data and how Hadoop can be used to retrieve useful information from large datasets. The book covers the basics of Hadoop, including its environment and how to build and manage applications and clusters. It is written in an easy-to-understand way and is suitable for those who are new to Hadoop.