Best 5 PySpark Books for Newbies & Experienced Learners

1. The Spark for Python Developers

by Amit Nandi

Well, if you are a Python developer who wants to work with Spark engine, then you can go for this book. It will be a great companion for you. However, not for newbies but this is the best book for those who have good knowledge of Spark as well as Python.

At very first, this book will help to learn the most effective way to install the Python development environment. Then, it will teach the way to connect with data stores like MySQL, MongoDB, Cassandra, and Hadoop.
Further, with getting familiarized with the various data sources, you’ll expand your skills throughout. Also, using iPython Notebook, you’ll explore datasets and moreover, you will discover how to optimize the data models and pipeline. After completing the book, you’ll get to know the way to create training datasets and also to train the machine learning models.

2. Interactive Spark using PySpark

by Benjamin Bengfort & Jenny Kim

This book is one of the great PySpark books for those who are familiar with writing Python applications as well as some familiarity with bash command-line operations. Moreover, those who have a basic understanding of simple functional programming constructs in Python.

Basically, this book compares the different components which are offered by Spark, and also the use cases in which they fit. It also teaches to use RDDs (resilient distributed datasets) with PySpark. Moreover, it gives the introduction to the Spark computing framework.

Hence, we can say for a Python developer those who don’t know about Java or Scala but they need to leverage the distributed computing resources available on a Hadoop cluster can go for this book.

3. Learning PySpark

by Tomasz Drabas & Denny Lee

So, even if you are a newbie, this book will help a lot. Especially, for those who want to leverage the power of Python and make the use of it in the Spark ecosystem must go for this book. This book starts by giving a basic knowledge of the Spark 2.0 architecture along with knowledge to set up a Python environment for Spark.

With this book, you will learn about the modules available in PySpark. Also, it teaches to abstract data with RDDs and DataFrames and makes you learn the streaming capabilities of the tool PySpark. Moreover, with the use of the spark-submit command, it teaches you to deploy your applications to the cloud.

So, we can say, this book will make you understand the Spark Python API and also teach you the way it can be used to build data-intensive applications.

4. PySpark Recipes: A Problem-Solution Approach with PySpark2

by Raju Kumar Mishra

Here in this PySpark book, word recipes mean Solutions to problems. So, this book gives solutions to all common programming problems which you may encounter at the time of processing big data. Basically, here in the popular problem-solution format, content is presented. At first, see for the programming problem that you want to solve, do read the solution then apply the solution directly in your own code. In this way, your Problem will solve!

This book covers, content on Hadoop as well as its shortcomings. Moreover, it includes the architecture of Spark, PySpark, as well as RDD. Also, this book will help you to learn about applying RDD concepts to solve day-to-day big data problems. However, to understand and adopt the model, Python and NumPy are included which make it easy for new learners of PySpark.

5. Frank Kane’s Taming Big Data with Apache Spark and Python

by Frank Kane

While it comes to learn Apache Spark in a hands-on manner, this book is one of your companions. Initially, it teaches to set up Spark on a single system or on a cluster. Further, it will teach you to analyze large data sets with the help of Spark RDD. Then you will learn to develop and run effective Spark jobs quickly with the help of Python.

The best part of this book is, it covers over 15 interactive, fun-filled examples relevant to the real world, and the examples will help you to easily understand the Spark ecosystem and also to implement production-grade real-time Spark projects without any difficulty.

So, this was all about PySpark Books. Hope you like our explanation.