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Best Spark Books You Must Read

In this post, we have prepared a curated top list of reading recommendations for beginners and experienced. This hand-picked list of the best Spark books and tutorials can help fill your brain this April and ensure you’re getting smarter. We have also mentioned the brief introduction of each book based on the relevant Amazon or Reddit descriptions.

1. Advanced Analytics with Spark: Patterns for Learning from Data at Scale (2017)

In the second edition of this practical book, four Cloudera data scientists present a set of self-contained patterns for performing large-scale data analysis with Spark. The authors bring Spark, statistical methods, and real-world data sets together to teach you how to approach analytics problems by example. Updated for Spark 2.1, this edition acts as an introduction to these techniques and other best practices in Spark programming.You’ll start with an introduction to Spark and its ecosystem, and then dive into patterns that apply…

Author(s): Sandy Ryza, Uri Laserson

2. Spark: The Definitive Guide: Big Data Processing Made Simple (2018)

Learn how to use, deploy, and maintain Apache Spark with this comprehensive guide, written by the creators of this open-source cluster-computing framework. With an emphasis on improvements and new features in Spark 2.0, authors Bill Chambers and Matei Zaharia break down Spark topics into distinct sections, each with unique goals. 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…


Author(s): Bill Chambers, Matei Zaharia

3. High Performance Spark (2017)

Apache Spark is amazing when everything clicks. But if you haven’t seen the performance improvements you expected, or still don’t feel confident enough to use Spark in production, this practical book is for you. Authors Holden Karau and Rachel Warren demonstrate performance optimizations to help your Spark queries run faster and handle larger data sizes, while using fewer resources. Ideal for software engineers, data engineers, developers, and system administrators working with large-scale data applications, this book describes…

Author(s): Holden Karau, Rachel Warren

4. Scala and Spark for Big Data Analytics (2017)

Anyone who wishes to learn how to perform data analysis by harnessing the power of Spark will find this book extremely useful. No knowledge of Spark or Scala is assumed, although prior programming experience (especially with other JVM languages) will be useful to pick up concepts quicker. Scala has been observing wide adoption over the past few years, especially in the field of data science and analytics. Spark, built on Scala, has gained a lot of recognition and is being used widely in productions.

Author(s): Md. Rezaul Karim, Sridhar Alla

5. A collection of Advanced Data Science and Machine Learning (2015)

A collection of Machine Learning interview questions in Python and Spark


Author(s): Dr Antonio Gulli

6. Learning Spark: Lightning-Fast Big Data Analysis (2015)

Data in all domains is getting bigger. How can you work with it efficiently? Recently updated for Spark 1.3, this book introduces Apache Spark, the open source cluster computing system that makes data analytics fast to write and fast to run. With Spark, you can tackle big datasets quickly through simple APIs in Python, Java, and Scala. This edition includes new information on Spark SQL, Spark Streaming, setup, and Maven coordinates.Written by the developers of Spark, this book will have data scientists and engineers up and running in…


Author(s): Holden Karau, Andy Konwinski

7. PySpark Recipes (2017)

Quickly find solutions to common programming problems encountered while processing big data. Content is presented in the popular problem-solution format. Look up the programming problem that you want to solve. Read the solution. Apply the solution directly in your own code. Problem solved! PySpark Recipes covers Hadoop and its shortcomings. The architecture of Spark, PySpark, and RDD are presented. You will learn to apply RDD to solve day-to-day big data problems. Python and NumPy are included and make it easy for new learners of PySpark to understand…

Author(s): Raju Kumar Mishra

8. SPARK 2014 User’s Guide (2017)

SPARK 2014 is a programming language and a set of verification tools designed to meet the needs of high-assurance software development. SPARK 2014 is based on Ada 2012, both subsetting the language to remove features that defy verification, but also extending the system of contracts and aspects to support modular, formal verification.The new aspects support abstraction and refinement and facilitate deep static analysis to be performed including flow analysis and formal verification of an implementation against a specification.

Author(s): AdaCore Team, Altran UK Ltd

9. Big Data Analytics with Spark (2015)

Big Data Analytics with Spark is a step-by-step guide for learning Spark, which is an open-source fast and general-purpose cluster computing framework for large-scale data analysis. You will learn how to use Spark for different types of big data analytics projects, including batch, interactive, graph, and stream data analysis as well as machine learning. In addition, this book will help you become a much sought-after Spark expert.Spark is one of the hottest Big Data technologies. The amount of data generated today by devices, applications and users is exploding.

Author(s): Mohammed Guller

10. Apache Spark in 24 Hours (2016)

Apache Spark is a fast, scalable, and flexible open source distributed processing engine for big data systems and is one of the most active open source big data projects to date. In just 24 lessons of one hour or less, Sams Teach Yourself Apache Spark in 24 Hours helps you build practical Big Data solutions that leverage Spark’s amazing speed, scalability, simplicity, and versatility.This book’s straightforward, step-by-step approach shows you how to deploy, program, optimize, manage, integrate, and extend Spark–now…

Author(s): Jeffrey Aven

11. Mastering Azure Analytics (2017)

Microsoft Azure has over 20 platform-as-a-service (PaaS) offerings that can act in support of a big data analytics solution. So which one is right for your project? This practical book helps you understand the breadth of Azure services by organizing them into a reference framework you can use when crafting your own big data analytics solution. You’ll not only be able to determine which service best fits the job, but also learn how to implement a complete solution that scales, provides human fault tolerance, and supports future…

Author(s): Zoiner Tejada

12. Spark GraphX in Action (2016)

Spark GraphX in Action starts out with an overview of Apache Spark and the GraphX graph processing API. This example-based tutorial then teaches you how to configure GraphX and how to use it interactively. Along the way, you’ll collect practical techniques for enhancing applications and applying machine learning algorithms to graph data.GraphX is a powerful graph processing API for the Apache Spark analytics engine that lets you draw insights from large datasets.

Author(s): Michael Malak, Robin East

You might also be interested in: Javascript, Vaadin, Delphi, Agile, JavaFX, Salesforce, Flask, PyQT, Shopify, ADO.NET Books.

We highly recommend you to buy all paper or e-books in a legal way, for example, on Amazon. But sometimes it might be a need to dig deeper beyond the shiny book cover. Before making a purchase, you can visit resources like Genesis and download some Spark books mentioned below at your own risk. Once again, we do not host any illegal or copyrighted files, but simply give our visitors a choice and hope they will make a wise decision.

Big Data Processing Using Spark in Cloud

Author(s): Mamta Mittal ; Valentina E. Balas ; Lalit Mohan Goyal ; Raghvendra Kumar
Publisher: Springer, Year: 2019, Size: 8 Mb, Ext: pdf
ID: 2235586

Practical Apache Spark: Using the Scala API

Author(s): Subhashini Chellappan, Dharanitharan Ganesan
Publisher: Apress, Year: 2019, Size: 23 Mb, Ext: pdf
ID: 2296972

The Beginner’s Guide to Intermittent Keto: Combine the Powers of Intermittent Fasting with a Ketogenic Diet to Lose Weight and Feel Great

Author(s): Jennifer Perillo
Publisher: Little, Brown Spark, Year: 2019, Size: 5 Mb, Ext: epub
ID: 2319842

Neue Erlösquellen oder Konsolidierung? – Geschäftsmodelle der Banken und Sparkassen auf dem Prüfstand: Beiträge des Duisburger Banken-Symposiums

Author(s): Werner Böhnke, Bernd Rolfes (eds.)
Publisher: Gabler Verlag, Year: 2018, Size: 10 Mb, Ext: pdf
ID: 2156230

Sparks from the Spirit : From Science to Innovation, Development, and Sustainability

Author(s): Yathavong, Yongyuth
Publisher: , Year: 2018, Size: 83 Mb, Ext: pdf
ID: 2205554

Spark: The Definitive Guide: Big Data Processing Made Simple

Author(s): Bill Chambers, Matei Zaharia
Publisher: O’Reilly Media, Year: 2018, Size: 8 Mb, Ext: pdf
ID: 2214777

Nephrology secrets

Author(s): Edgar V. Lerma, Matthew A. Sparks, Joel Topf (editors)
Publisher: Elsevier, Year: 2018, Size: 44 Mb, Ext: pdf
ID: 2239468

Inspiration for Every Day: 365 Ideas to Spark Creativity

Author(s): Lizzie Cornwall
Publisher: Summersdale Publishers, Year: 2018, Size: 5 Mb, Ext: azw3
ID: 2258994

Trouble the Water

Author(s): Jacqueline Friedland
Publisher: SparkPress, Year: 2018, Size: 4 Mb, Ext: epub
ID: 2262304

Joyful: The Surprising Power of Ordinary Things to Create Extraordinary Happiness

Author(s): Ingrid Fetell Lee
Publisher: Little, Brown Spark, Year: 2018, Size: 10 Mb, Ext: epub
ID: 2262518

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Top 25 Best Big Data Books You Should Read Posted on June 14, 2018 by Timothy King in Best Practices. With Spark, you can tackle big datasets quickly through simple APIs in Python, Java, and Scala. This edition includes new information on Spark SQL, Spark Streaming, setup, and Maven coordinates. Written by the developers of Spark, this book 1 How to Quit Your Job and Travel the World After 40 2 The 25 Best Self Improvement Books to Read No Matter How Old You Are 3 25 Truly Amazing Places To Visit Before You Die 4 30 Fun Things to Do at Home 5 10 Benefits of Reading: Why You Should Read Every Day Want to know which books you should read this year? Today I’ve got 10 recommendations, covering topics ranging from productivity to career skills to personal finance (and more). Spark – http 20 Books You Really Should Have Read By Now. Have you read these books everyone lies about reading? some of the best scenes in the popular Greek myth-inspired kids’ series BBC Believes You Only Read 6 of These Books… 300 Books Everyone Should Read at Least Once Amazon’s 100 Books to Read in a Lifetime 50 Books to Read Before You Die Books You’ll Never Brag About Having Read The Rory Gilmore Reading Challenge NPR’s Top 100 Science Fiction & Fantasy Books 99 Classic Books Challenge BBC’s Top 100 Books You Need to Read Before You Die 101 Best Selling Books of All …