In our last PySpark Tutorial, we discussed the complete concept of PySpark. Today, we will see Top PySpark Books. While it comes to find best resources to get in-depth knowledge of PySpark, it’s not that easy.
So, here in this article, “Best 5 PySpark Books” we are listing best 5 Books for PySpark, which will help you to learn PySpark in detail. This list includes PySpark books for both freshers as well as experienced learners.
Here we are also mentioning some basic details of each book on PySpark, which will help you to select the book as per your needs.
Best 5 PySpark Books
Here is a list of best 5 PySpark Books:
1. The Spark for Python Developers
by Amit Nandi
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
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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
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
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
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.
Summary
Hence, in this PySpark tutorial, we have seen the best 5 PySpark books. Also, we have seen a little description of these books on PySpark which will help to select the book wisely.
These PySpark Books will help both freshers and experienced. Still, if any doubt, ask in the Comment tab. Keep reading, keep learning!