Best Hadoop Books 2023 | Must Read to Master The Technology

best hadoop books

Big data applications are the future of the IT industry. Hadoop is one of the most used technologies for developing big data applications. But learning Hadoop and working with it is not that easy. To master this technology and become a successful developer, you must follow some good books on Hadoop.

In this article, I have cataloged a set of best Hadoop books in 2023. With these guides, you can learn this technology quite easily and become a successful developer of big data platforms. So hurry up and check the books!

HADOOP BASICS: PROGRAMMING FOR BEGINNERS: Learn Coding Fast! HADOOP Crash Course, A QuickStart Guide, Tutorial Book by Program Examples, In Easy Steps!
Author: KING, J
Published at: 24/05/2020

HADOOP FOR BEGINNERS” covers all essential HADOOP language knowledge. You can learn complete primary skills of HADOOP programming fast and easily. The book includes practical examples for beginners.

What You'll Learn From This Book:

  • Using Apache Ambari to set up and deploy your big data environment.
  • Designing effective streaming data pipelines for your enterprise search solutions.
  • Building analytics solutions from historical data and visualize them using Apache Superset.
  • Developing large scale data processing solutions using Spark.
  • Various mechanisms to protect data in Hadoop clusters in transit and at rest.
  • Integrating Hadoop data ingest with the enterprise-wide security structures.
  • Providing data extraction and client access security.

Architecting Modern Data Platforms: A Guide to Enterprise Hadoop at Scale
Author: Jan Kunigk,Ian Buss,Paul Wilkinson,Lars George
Published at: 03/01/2019
ISBN: 149196927X

If you are an enterprise architect, IT manager, or data engineer who wants to build an end-to-end enterprise data platform, then Architecting Modern Data Platforms is a must-have guide for you. With practical and real-world use cases, this book teaches you how to splice big data technologies like Hadoop into your big data application.

It also shows you how to overcome the many challenges that you may face during a Hadoop project. By reading this book, you'll be able to build a big data structure both on-premises and in the cloud and successfully architect a modern data platform.

What You'll Learn From This Book:

  • Fundamental concepts of big data technology
  • Developing cluster infrastructures for your project
  • Various computing and storage techniques
  • Network architectures and network integration
  • Provisioning your clusters from unauthorized access
  • Managing your application's security
  • Integrating your application with identity management providers
  • Accessing and interacting with clusters
  • Maintaining high availability
  • Basics of visualization for Hadoop

Mastering Hadoop 3: Big data processing at scale to unlock unique business insights
Author: Singh, Chanchal
Published at: 28/02/2019
ISBN: 1788620445

Here you'll have a complete understanding of how components in the Hadoop ecosystem are effectively integrated to implement a fast and reliable data pipeline, and you'll be equipped to tackle a range of real-world problems in data pipelines.

What you will learn

  • Gain an in-depth understanding of distributed computing using Hadoop 3
  • Develop enterprise-grade applications using Apache Spark, Flink, and more
  • Build scalable and high-performance Hadoop data pipelines with security, monitoring, and data governance
  • Explore batch data processing patterns and how to model data in Hadoop
  • Master best practices for enterprises using or planning to use, Hadoop 3 as a data platform
  • Understand security aspects of Hadoop, including authorization and authentication

Hadoop: The Definitive Guide: Storage and Analysis at Internet Scale
Author: Tom White
Published at: 11/04/2015
ISBN: 1491901632

Hadoop: The Definitive Guide is an ideal guide for programmers who want to analyze datasets of any size, and for administrators looking to set up and run Hadoop clusters. This comprehensive guide will teach you how to build and maintain reliable, scalable, distributed systems with Apache Hadoop.

With new chapters on YARN and several Hadoop related projects including Parquet, Flume, Crunch, and Spark, you'll discover the power of Hadoop for building distributed datasets.

What You'll Learn From This Book:

  • Using fundamental components of Hadoop including MapReduce, HDFS, and YARN
  • Developing applications with MapReduce
  • Setting up a Hadoop cluster running HDFS and MapReduce on YARN
  • Data serialization using AVRO data format
  • Working with nested data using Parquet
  • Using Flume for manipulating streaming data
  • Developing a bulk data transfer application using Sqoop
  • Integrating high-level data processing tools like Pig, Hive, Crunch, and Spark with Hadoop
  • Working with the HBase distributed database
  • Using the ZooKeeper distributed configuration service in your application

Hadoop Explained
Author: Aravind Shenoy
Published at: 16/06/2014

Hadoop Explained is an immensely important tool to store and analyze data. It allows small and medium-sized companies to store huge amounts of data on cheap commodity servers in racks.

This Hadoop book introduces you to Hadoop and teaches you the fundamental concepts of Hadoop. If you want to learn the basics of Hadoop with ease, you should try this book. 

What You'll Learn From This Book:

  • Fundamentals of Hadoop components
  • How to use MapReduce
  • Working with Rack Awareness
  • Basics of Yarn
  • Using the HDFS Federation
  • Discovering the Advantages of Hadoop
  • How Hadoop handles huge data with care

Programming Hive: Data Warehouse and Query Language for Hadoop
Author: Edward Capriolo,Dean Wampler,Jason Rutherglen
Published at: 06/10/2012
ISBN: 1449319335

Programming Hive is a comprehensive guide to learn Hive to move your relational database application to Hadoop. With this example-driven guide, you'll understand how Hive works within the Hadoop ecosystem and learn how to set up and configure Hive in your environment.

This Hadoop book provides real-world case studies that will help how to solve unique problems involving a huge amount of data.

What You'll Learn From This Book:

  • Using Hive-QL to perform SQL operations in Hive
  • Customizing your data formats and storage options
  • Using conventional query methods including  loading and extracting data from tables, grouping, filtering, and joining
  • Creating user-defined functions(UDFs)
  • Understanding Hive patterns and anti-patterns for better performance of your application
  • Integrating Hive with other data processing tools
  • Working with storage handlers for NoSQL databases and other data stores
  • Running and maintaining Hive on  Amazon’s Elastic MapReduce

Modern Big Data Processing with Hadoop: Expert techniques for architecting end-to-end Big Data solutions to get valuable insights
Author: V. Naresh Kumar,Prashant Shindgikar
Published at: 30/03/2018
ISBN: 178712276X

Modern Big Data Processing with Hadoop offers an in-depth view of the Hadoop ecosystem. With a comprehensive, step-by-step explanation about the components, you'll be able to design, build and execute effective big data strategies using Hadoop.

If you want to become an expert Hadoop architect, this book is a must-read for you.

What You'll Learn From This Book:

  • Enterprise data architecture principles
  • Using Hadoop with various big data frameworks including Apache Spark and Elasticsearch
  • Using Apache Ambari to set up and deploy your big data environment
  • Designing effective streaming data pipelines for your enterprise search solutions
  • Building analytics solutions from historical data and visualize them using Apache Superset
  • Developing large scale data processing solutions using Spark
  • Creating scalable enterprise applications using Cloud Infrastructure
  • Understanding Hadoop Administration and Cluster Deployment

Hadoop Security: Protecting Your Big Data Platform
Author: Ben Spivey,Joey Echeverria
Published at: 16/07/2015
ISBN: 1491900989

Hadoop Security is a practical guide to learn how to protect Hadoop data from unauthorized access. It shows the perfect way to limit the ability of an attacker to corrupt or modify data in the event of a security breach.

With in-depth explanations and real-world examples of security concepts, you'll understand all the ways to apply these concepts to your applications. If you are concerned about the security of your application with Hadoop, you should read this book.

What You'll Learn From This Book:

  • Discovering the challenges of distributed system security especially Hadoop
  • Building Hadoop cluster hardware as securely as possible
  • Understanding the Kerberos network authentication protocol
  • Working with the authorization and accounting principles associated with Hadoop
  • Various mechanisms to protect data in Hadoop clusters in transit and at rest
  • Integrating Hadoop data ingest with the enterprise-wide security structures
  • Providing data extraction and client access security

Data Analytics with Hadoop: An Introduction for Data Scientists
Author: Benjamin Bengfort,Jenny Kim
Published at: 18/06/2016
ISBN: 1491913703

If you are a data scientist or a data analyst, then you should check Data Analytics with Hadoop. This practical book shows you how to utilize Hadoop to use statistical and machine-learning techniques across large data sets.

With this guide, you can avoid developing a particular system for your project, instead, you'll focus on particular analyses you can build and the data warehousing techniques that Hadoop provides. You'll also get help for higher-order data workflows this framework can produce.

What You'll Learn From This Book:

  • Understanding the fundamental concepts of Hadoop and cluster computing
  • Using design patterns and parallel analytical algorithms to develop data analysis tools
  • In-memory computing with Spark
  • Performing data mining and warehousing using Apache Hive and HBase
  • Analytics using higher-level APIs including Pig and Spark higher-level API
  • Data ingestion using Sqoop and Apache Flume
  • Machine learning using Spark's MLlib

Expert Hadoop Administration: Managing, Tuning, and Securing Spark, YARN, and HDFS (Addison-Wesley Data & Analytics Series)
Author: Sam R. Alapati
Published at: 16/12/2016
ISBN: 0134597192

Expert Hadoop Administration is a great book for Hadoop administrators who want to create, configure, secure, manage and optimize Hadoop clusters in any environment.

This book demystifies complex Hadoop environments and shows you what exactly happens behind the scene when you administer your cluster. It offers action-oriented advice with carefully researched explanations of both problems and solutions.

If you want to develop high-value administration skills, you should read this book.

What You'll Learn From This Book:

  • The fundamentals aspects of Hadoop architecture from an administrator's viewpoint
  • Developing fully distributed clusters
  • Using MapReduce and Spark into a Hadoop cluster
  • Protecting Hadoop data with high availability
  • Understanding HDFS commands, file permissions, and storage management
  • Working with YARN to allocate resources and schedule jobs
  • Managing your application's job workflow with Oozie and Hue
  • Troubleshooting various problems in Hadoop

Practical Hive: A Guide to Hadoop's Data Warehouse System
Author: Scott Shaw,Andreas François Vermeulen,Ankur Gupta,David Kjerrumgaard
Published at: 28/08/2016
ISBN: 1484202724

Practical Hive is a useful guide for anyone who wants to move their relational database to Hadoop. This book introduces you to Hive-SQL, the SQL-like language specific to Hive and teaches you how to analyze, export, and massage the data stored across your Hadoop environment.

With this book, you'll get a detailed overview of the software and become a successful developer.

What You'll Learn From This Book:

  • Setting your environment with Hive
  • Basic functionalities of Hive
  • Understanding Hive architecture
  • Working with Hive tables DDL
  • Data manipulation language for Hive
  • Loading data into Hive
  • Querying semi-structured data
  • Providing security to your database
  • Increasing the performance of your application

Hadoop 2.x Administration Cookbook: Administer and maintain large Apache Hadoop clusters
Author: Gurmukh Singh
Published at: 26/05/2017
ISBN: 1787126730

This is a cookbook style practical guide that will teach you every aspect of Hadoop. With step by step explanations with examples, this guide will teach you how to import and export data into Hive and manage workflow with Oozie.

It also offers practical recipes to plan and secure your Hadoop cluster and make it highly available. With this helpful guide, you'll be able to overcome the common problems in Hadoop and become an expert developer.

What You'll Learn From This Book:

  • Setting up the Hadoop environment in your platform
  • Configuring and managing a Hadoop cluster on HDFS, YARN, and MapReduce
  • Making your application highly available with Zookeeper and Journal Node
  • Ingesting data using Flume
  • Configuring Oozie to run various workflows
  • Tuning the Hadoop for better performance
  • Using the Fair and Capacity Scheduler to schedule jobs

Practical Data Science with Hadoop and Spark: Designing and Building Effective Analytics at Scale (Addison-Wesley Data & Analytics)
Author: Mendelevitch, Ofer
Published at: 12/12/2016
ISBN: 0134024141

This guide provides a strong technical foundation for those who want to do practical data science and also presents business-driven guidance on how to apply Hadoop and Spark to optimize ROI of data science initiatives.


  • What data science is, how it has evolved, and how to plan a data science career
  • How data volume, variety, and velocity shape data science use cases
  • Hadoop and its ecosystem, including HDFS, MapReduce, YARN, and Spark
  • Data importation with Hive and Spark
  • Data quality, preprocessing, preparation, and modelling
  • Visualization: surfacing insights from huge data sets
  • Machine learning: classification, regression, clustering, and anomaly detection
  • Algorithms and Hadoop tools for predictive modelling
  • Cluster analysis and similarity functions
  • Large-scale anomaly detection
  • NLP: applying data science to human language

Spark: The Definitive Guide: Big Data Processing Made Simple
Author: Chambers, Bill
Published at: 20/03/2018
ISBN: 1491912219

You’ll explore the basic operations and common functions of Spark’s structured APIs, as well as Structured Streaming, a new high-level API for building end-to-end streaming applications. Developers and system administrators will learn the fundamentals of monitoring, tuning, and debugging Spark, and explore machine learning techniques and scenarios for employing MLlib, Spark’s scalable machine-learning library.

  • Get a gentle overview of big data and Spark
  • Learn about DataFrames, SQL, and Datasets—Spark’s core APIs—through worked examples
  • Dive into Spark’s low-level APIs, RDDs, and execution of SQL and DataFrames
  • Understand how Spark runs on a cluster
  • Debug, monitor, and tune Spark clusters and applications
  • Learn the power of Structured Streaming, Spark’s stream-processing engine
  • Learn how you can apply MLlib to a variety of problems, including classification or recommendation

Hadoop Application Architectures: Designing Real-World Big Data Applications
Author: Grover, Rajat (Mark)
Published at: 04/08/2015
ISBN: 1491900083

This book covers:

  • Factors to consider when using Hadoop to store and model data
  • Best practices for moving data in and out of the system
  • Data processing frameworks, including MapReduce, Spark, and Hive
  • Common Hadoop processing patterns, such as removing duplicate records and using windowing analytics
  • Giraph, GraphX, and other tools for large graph processing on Hadoop
  • Using workflow orchestration and scheduling tools such as Apache Oozie
  • Near-real-time stream processing with Apache Storm, Apache Spark Streaming, and Apache Flume
  • Architecture examples for clickstream analysis, fraud detection, and data warehousing

Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems
Author: Kleppmann, Martin
Published at: 18/04/2017
ISBN: 1449373321

In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. The software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications.

  • Peer under the hood of the systems you already use and learn how to use and operate them more effectively
  • Make informed decisions by identifying the strengths and weaknesses of different tools
  • Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity
  • Understand the distributed systems research upon which modern databases are built
  • Peek behind the scenes of major online services, and learn from their architectures

Hadoop 2 Quick-Start Guide: Learn the Essentials of Big Data Computing in the Apache Hadoop 2 Ecosystem (Addison-wesley Data & Analytics Series)
Author: Eadline, Douglas
Published at: 26/10/2015
ISBN: 0134049942

This guide is ideal if you want to learn about Hadoop 2 without getting mired in technical details. Douglas Eadline will bring you up to speed quickly, whether you’re a user, admin, Develop specialist, programmer, architect, analyst, or data scientist. This book includes:

  • Understanding what Hadoop 2 and YARN do, and how they improve on Hadoop 1 with MapReduce
  • Understanding Hadoop-based Data Lakes versus RDBMS Data Warehouses
  • Installing Hadoop 2 and core services on Linux machines, virtualized sandboxes, or clusters
  • Exploring the Hadoop Distributed File System (HDFS)
  • Understanding the essentials of MapReduce and YARN application programming
  • Simplifying programming and data movement with Apache Pig, Hive, Sqoop, Flume, Oozie, and HBase
  • Observing application progress, controlling jobs, and managing workflows
  • Managing Hadoop efficiently with Apache Ambari–including recipes for HDFS to NFSv3 gateway, HDFS snapshots, and YARN configuration
  • Learning basic Hadoop 2 troubleshooting, and installing Apache Hue and Apache Spark

Hadoop in Practice: Includes 104 Techniques
Author: Holmes, Alex
Published at: 12/10/2014
ISBN: 1617292222

It's always a good time to upgrade your Hadoop skills! Hadoop in Practice, Second Edition provides a collection of 104 tested, instantly useful techniques for analyzing real-time streams, moving data securely, machine learning, managing large-scale clusters, and taming big data using Hadoop. This completely revised edition covers changes and new features in the Hadoop core, including MapReduce 2 and YARN. You'll pick up hands-on best practices for integrating Spark, Kafka, and Impala with Hadoop, and get new and updated techniques for the latest versions of Flume, Sqoop, and Mahout. In short, this is the most practical, up-to-date coverage of Hadoop available. Readers need to know a programming language like Java and have basic familiarity with Hadoop.

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