Books

5 Best Hadoop Books From Beginner To Advanced

Hadoop is a java-based open-source software framework used for storing and processing big data.

In this article, we will tell you about the best Hadoop books. Let’s learn a bit more about Hadoop first.

Hadoop is developed by Doug Cutting and Michale J. and is managed by Apache Software Foundation and is written in Java language.

It is great for businesses as it uses commodity hardware to store large quantities of data and therefore it requires less money to store and process the data.

Hadoop is important as it has the ability to store and process large amounts of data very quickly.

Hadoop is used by companies to understand their customer’s requirements by analyzing big data.

So here is the list of best Hadoop books.


Top Hadoop Books

1. Hadoop: The Definitive Guide: Storage and Analysis at Internet Scale

Hadoop: The Definitive Guide: Storage and Analysis at Internet Scale
Hadoop: The Definitive Guide by Tom White

It is a good book that provides a good overview of the Hadoop ecosystem.

It is targeted at programmers who are looking to analyze large datasets size and also for administrators who want to learn how to set up and run Hadoop clusters.

In this book, you will learn how to build and maintain reliable, scalable, and distributed systems by using Apache Hadoop.

You will get lots of assignments that will help you understand the Hadoop Real-time functionality.

What You Will Learn

  • The fundamental components such as MapReduce, YARN, and HDFS.
  • How to set-up and maintain a Hadoop cluster running HDFS and MapReduce on YARN.
  • How to use data ingestion tools like Flume and Sqoop.
  • Learn data formats such as Avro for data serialization and Parquet for nested data.
  • How high-level data processing tools such as Pig, Hive, Crunch, and Spark work along with Hadoop.
  • Learn about HBase distributed database and ZooKeeper distributed configuration service.

All in all, a very comprehensive and well-developed book that will give you a nice introduction to large data management using Hadoop.

A well-written book and is highly recommended.

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2. Sams Teach Yourself Hadoop in 24 Hours

Sams Teach Yourself Hadoop in 24 Hours

This book is a great resource for getting started in the field of Big Data.

It is a very well-organized book that covers the core concepts of Hadoop and the Hadoop ecosystem such as Apache Spark, Pig, Hive.

The book provides you with some real-time examples to master Hadoop.

What You Will Learn

  • Learn about Hadoop and the Hadoop Distributed File System (HDFS).
  • How to import data into Hadoop and then process this data.
  • Learn MapReduce Java programming, and how to use advanced MapReduce API concepts.
  • Learn about Apache Pig and Apache Hive.
  • How to implement and administer YARN.
  • How to manage Hadoop clusters with Apache Ambari.
  • How to work with the Hadoop User Environment (HUE).
  • How to scale, secure, and troubleshoot Hadoop environments.
  • Learn how to integrate Hadoop into the enterprise level.
  • How to deploy Hadoop in the cloud.
  • How to get started with Apache Spark.

Good book for beginners.

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3. Data Analytics with Hadoop: An Introduction for Data Scientists

Data Analytics with Hadoop is an excellent book to understand Data warehousing techniques and higher-order workflows that the Hadoop framework can perform for doing data analytics.

Data Analytics with Hadoop: An Introduction for Data Scientists

This book will teach you the core concepts behind Hadoop and cluster computing.

What You Will Learn

  • How to use design patterns and parallel analytical algorithms for creating distributed data analysis jobs.
  • Understanding of data management, data mining, and data warehousing in a distributed context using Apache Hive and HBase.
  • Use Sqoop (for bulk data transfer) and Apache Flume (for data streaming) to ingest data from relational databases.
  • How to program Hadoop and Spark applications using Apache Pig and Spark DataFrames.
  • How to do machine learning techniques such as classification, clustering, and collaborative filtering by using Ampache Spark’s MLlib.

It is a really nice book to learn about Hadoop systems and MapReduce.

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4. Hadoop Application Architectures: Designing Real-World Big Data Applications

Hadoop Application Architectures: Designing Real-World Big Data Applications

It is a good book to advance your career in Big Data systems by learning Hadoop.

It is a well-written book on Hadoop designing, whether you are designing a new Hadoop application or are planning to integrate Hadoop into your existing data infrastructure.

What You Will Learn

  • How to use Hadoop to store and model data.
  • Learn about the data processing frameworks such as MapReduce, Spark, and Hive.
  • Learn about Giraph, GraphX, and many other tools for large graph processing on Hadoop.
  • How to use workflow orchestration and scheduling tools like Apache Oozie.
  • Examples of Architecture for clickstream analysis, fraud detection, and data warehousing.

Great book for getting started with Hadoop Application Architectures.

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5. Mastering Hadoop 3: Big data processing at scale to unlock unique business insights 

Mastering Hadoop 3: Big data processing at scale to unlock unique business insights

Mastering Hadoop 3 is a comprehensive guide for mastering the most advanced Hadoop 3 concepts.

It is a well-written, comprehensive and great book for learning the latest Hadoop.

This book is ideal for beginners as well as advanced users of Hadoop.

What You Will Learn

  • Get a basic understanding of distributed computing using Hadoop 3.
  • How to develop enterprise-grade applications using Apache Spark and Flink.
  • How to build scalable and high-performance Hadoop data pipelines with security, monitoring, and data governance.
  • Learn about batch data processing patterns and how to model data in Hadoop.
  • Learn about the security aspects of Hadoop such as authorization and authentication.

Highly recommended to learn the Hadoop 3 ecosystem.

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Conclusion

So these are the 5 Best Hadoop Books to learn Hadoop from scratch.

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