Best Apache Spark Books : For Beginners & Experienced

1. Spark Books – Objective

“If you only read the books that everyone else is reading, you can only think what everyone else is thinking”. So to learn apache spark efficiently, you can read best books on same. This blog carries the information of top 10 apache spark books.

For learning spark these books are better, there is all type of books of spark in this post. Few of them are for beginners and remaining are of the advance level. This blog also covers a brief description of best apache spark books, to select each as per requirements. Some famous books of spark are Learning Spark, Apache Spark in 24 Hours – Sams Teach You, Mastering Apache Spark etc.

Spark Books

Best Spark Books

2. List Of  Supreme Apache Spark Books

2.1. Learning Spark: Lightning-Fast Big Data Analysis

A book “Learning Spark” is written by Holden Karau, a software engineer at IBM’s spark technology. This book has been rapidly adopted as a de-facto reference for spark fundamentals by many. The best thing about the book is how author focuses on one single API for singular programmers. It is not mandatory to pick up Hadoop or Java+Scala to get this working. In fact, it’s up to us to choose any language we are good at and be willing to hit stack overflow for answers along the way.

Learning spark explains core principles such as RDDs, in-memory processing, and persistence. It also teaches how to use the spark interactive shell. We will study a lot of theory behind the spark framework and what makes it tick. This book is perfect for beginners. It teaches, why spark is so important to big data world. Through this book, beginners will learn the value of distributed datasets also. Actually, more we practice, more it becomes easier with prior experience in programming.  

2.2. Apache Spark in 24 Hours, Sams Teach Yourself

This book makes much sense to beginners. As beginners seem to be very impatient about learning spark, this book is meant for them. This book “Apache Spark in 24 Hours” written by Jeffrey Aven. It contains the fundamentals of big data web apps those connects the spark framework. The first part of the book contains spark’s architecture and its relationship with Hadoop. Finally, how to install Apache Spark.

In addition, we will also learn the basics of spark programming. It includes RDDs, and how to use them using Scala Programming Language. By the end, it will focus more on the “extensions of Spark” (Spark SQL, Spark R, etc). Afterwards, we will learn how to administrate, monitor and improve the spark performance. As a fact, it’s an overall intro to spark made for complete beginners. Ultimately, it’s the best intro book anyone can find in the market.

2.3. High-Performance Spark: Best Practices for Scaling and Optimizing Apache Spark

The book “High-Performance Spark” has proven itself to be a solid read. This book is again written by Holden Karau, discussed above. In the book, by using a range of spark libraries, she focuses on data manipulation techniques. Also, covers technologies above and beyond core RDD manipulation.

Apache Spark is not easy to optimize. It’s typically just one part of a larger ecosystem, with other programs running on the server itself. So, if you’re designing more complex data flows, this book will be a great companion. Hence, this is one of the great spark books for both beginners as well as experienced.

2.4. Advanced Analytics with Spark by Sandy Ryza, Uri Laserson, Sean Owen and Josh Wills

As we know, there are plenty of books on machine learning theory. And, also enough of references covering the use Hadoop ecosystem tools. Even so, there is not much which specifically targeting the overlap between the two.  Still, no one focusing on use cases and examples rather than being a manual. Ultimately,  this book is a modest attempt to meet that need. That’s why we see turn up frequently among learners and in the community.

This book is written by 4 Cloudera data scientists. It presents set of self-contained patterns to perform large-scale data analysis with spark. Firstly, it starts with an introduction to spark and spark ecosystem. Afterwards, it teaches patterns that apply common techniques. Such as classification, collaborative filtering, and anomaly detection in depth. In this book, different chapters appeal to different levels of experience. On highlighting, as the second chapter is on record linkage, basics of using scala and spark to work with data. Whereas, the eighth chapter, estimates financial risk through Monte Carlo simulation. With a just basic understanding of probability and statistics.

We can say this book is targeted the data scientist or aspiring data scientist. Apart from data scientists, It will also help people who want to learn basics of machine learning. It will be a piece of cake for those who more interested in its application than the theory.

2.5. Spark in Action

Book “Spark in Action” skips theory, but rely on practical implementations with spark. This book guides us through writing spark applications. It includes applications with python and scala. It also helps in understanding the APIs in depth as well as spark app deployment options.

2.6. Mastering Apache Spark

As a matter of fact, this is not possible to master a framework. But by studying a book like mastering apache spark we are very near to mastering one. The writer of the book is Mike Frampton. In spite of its name, it’s also a beginners book. This book contains a lot of spark examples, with various spark principles and techniques. By using screen-shots and shell output, it explains each thing beautifully to know what is going on.

A major part of the book contains 3rd party extensions for building on top of the spark foundation. Likewise

We will learn how to merge spark apps with cassandra and HBase.

2.7.Spark: Big Data Cluster Computing in Production

This book teaches production deployment for spark apps. The ideal reader of this book will be a data engineer. Those want to learn more about production deployment, this book is a good start. With this book, we will learn how to monitor your spark clusters. This covers how to work with metrics, resource allocation, serialization with kryo, more. It also includes file format details, for example, sequence files.

As the authors of this book are all experts in big data, so they’re worthwhile instructors on this topic. This book not only covers how to launch but also how to enhance security.  It also focuses on ways to optimize our spark environment for better performance.

2.8. Pro Spark Streaming: The Zen of Real-Time Analytics Using Apache Spark

Spark introduces real-time data processing as its major component. It is important to dive into this concept to learn spark efficiently. When we talk to learn exclusively real-time spark use, this book strikes. The writer of book Zubair Nabi enables us to become an expert in applications. It teaches us the key features of DStreams, micro-batch processing, and functional programming.

Book also covers social media, the sharing economy, finance, and online advertising. On closing, it includes ready-to-deploy examples and actual code. This book actually acts as the bible of spark streaming.

2.9. Spark GraphX in Action

The Book “Spark GraphX in Action” exclusively focus on graphX. Most probably it is the most in-depth book on graphX. A graph processing API for spark: graphX. It offers high performance with high flexibility.

At first, this book starts with basics of graphX. Moving forward, includes practical examples of graph processing and machine learning. Ultimately, it is a great overview of the framework. Also, turned out as it is one of the great spark books.

2.10. Spark Cookbook

In the first place, the ideal readers of this book are existing data scientists or data engineers. Those who are looking to start utilizing spark for the first time must refer this book. It is one of the good spark books for starting with spark. In the first part, it covers the basics of getting started with spark. Furthermore, it teaches implement machine learning algorithms and graph processing applications. In the end, it also covers topics like monitoring and optimization.

3.Spark Books – Conclusion

This blog covers top 10 Spark books. It will definitely help you for learning spark efficiently. Some of this book we can download free from any browser in a PDF and e-book form. Don’t stress if things may not clear in one go. Although, always remember, A good book never reveal its all secrets at once. Keep studying and keep learning. Hope these Spark books help to succeed.

Reference – Apache Spark

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