Top 10 Books For Learning Apache Spark
Apache Spark is one of the most active open-sourced big data projects. It is fast, flexible, and scalable, which makes it a very popular and useful project. In this article, we jot down the 10 best books to gain insights into this general-purpose cluster-computing framework. 1| Beginning Apache Spark 2: With Resilient Distributed Datasets, Spark SQL, Structured Streaming And Spark Machine Learning Library By Hien Luu Overview: In this book, you will understand Spark unified data processing platform, how to run Spark in Spark Shell or Databricks, learn to use and manipulate RDDs. You will also learn to deal with structured data using Spark SQL through its operations and advanced functions, build real-time applications using Spark Structured Streaming alo\ng with developing intelligent applications with the Spark Machine Learning library. Cost: You can buy both the Kindle edition and paperback version of this book from Amazon which will cost you ₹2,396 and ₹2,390 respectively. Click here to buy the book. 2| Advanced Analytics with Spark: Patterns for Learning from Data at Scale By Sandy Ryza Overview: This is a practical book where the authors display a set of self-contained patterns for performing large-scale data analysis with Spark and you will learn about the Spark programming model, understand the Spark ecosystem, learn the basics in data science, gain insights with the machine learning tools. Practical examples of Spark, statistical methods and real-world data set together to learn how to approach analytical problems. Cost: You can buy both the Kindle edition and paperback version of this book from Amazon which will cost you ₹689 and ₹725 respectively. Click here to buy the book from Amazon. 3| Spark: The Definitive Guide: Big Data Processing Made Simple By Bill Chambers Overview: This book is a comprehensive guide of how to use, deploy and maintain Apache Spark. You will understand the basic operations and common functions of Spark’s structured APIs, as well as Structured Streaming which is a new high-level API for building end-to-end streaming applications. Here, you will get a basic overview of big data and Spark, learn about DataFrames, SQL, Spark’s core APIs, learn how to debug, monitor, and tune Spark clusters and applications including how you can apply MLlib to a variety of problems, including classification or recommendation. Cost: You can buy both the Kindle edition and paperback version of this book from Amazon which will cost you ₹ 1,520 and ₹ 1,600 respectively. Click here to buy the book from Amazon. 4| Apache Spark in 24 Hours, Sams Teach Yourself By Jeffrey Aven Overview: This book is a step-by-step guide which helps you to learn how to deploy, program, optimize, manage, integrate, and extend Spark–now, and for years to come, you will learn how to create powerful solutions encompassing cloud computing, real-time stream processing, machine learning, etc. You will learn how to discover the function of Apache Spark, what it does, how it fits into big data, how to deploy and run it locally or in the cloud. You will also learn how to program with the Spark API, including transformations and actions, apply practical data engineering/analysis approaches designed for Spark, imply  Spark with SQL (via Spark SQL) and with NoSQL (via Cassandra), etc. Cost: You can buy both the Kindle edition and paperback version of this book from Amazon which will cost you ₹1,972 and ₹2,681 respectively. Click here to buy the book from Amazon. 5| Learning Apache Spark 2 By Muhammad Asif Abbasi Overview: This book is a guide which includes fast data processing using Apache Spark. You will learn how to explore and exploit various possibilities with Apache Spark using real-world use cases, get an overview of big data analytics and its importance for organizations and data professionals, how to deploy Spark with YARN, MESOS or a Stand-alone cluster manager, understand the architecture of Spark MLLib while discussing some of the off-the-shelf algorithms that come with Spark, etc. Cost: You can buy the paperback version of this book from Amazon which will cost you ₹828. Click here to buy the book from Amazon. 6| Hands-On Deep Learning with Apache Spark: Build and deploy distributed deep learning applications on Apache Spark By Guglielmo Iozzia Overview: This book addresses the complexity of technical as well as analytical parts including the sped at which deep learning solutions can be implemented on Apache Spark. It will help you understand the fundamentals of Apache Spark and also how to set up Spark for deep learning, learn principles of distributed modelling including the neural networks, implement deep learning models such as CNN, RNN, and LSTM on Spark, etc. Cost: You can buy both the Kindle edition and paperback version of this book from Amazon which will cost you ₹674 and ₹912 respectively. Click here to buy the book from Amazon. 7| Apache Spark Deep Learning Cookbook By Ahmed Sharif and Amrith Ravindra Overview: This book will guide you to set up Apache Spark for deep learning to implement different types of neural net, you will get access to deep learning codes within Spark, learn how to stream, cluster your data with Spak, how to implement and deploy deep learning models using popular libraries such as Keras and Tensorflow, and other relevant topics. Cost: You can buy both the Kindle edition and paperback version of this book from Amazon which will cost you ₹460 and ₹1,078 respectively. Click here to buy the book from Amazon. 8| Apache Spark 2.x Machine Learning Cookbook By Siamak Amirghodsi Overview: This book will provide a solid knowledge of machine learning as well as hands-on experience of implementing these algorithms with Scala. You will also learn how Scala and Spark provide benefit for the developers, learn how to build a recommendation engine that scales Spark, how to build unsupervised clustering systems to classify data in Spark, implement text analytics for search engines in Spark, and other relevant topics. Cost: You can buy both the Kindle edition and paperback version of this book from Amazon which will cost you ₹860 and ₹1,327 respectively. Click here to buy the book from Amazon. 9| Learning Spark: Lightning-Fast Big Data Analysis By Holden Karau, Andy Konwinski, Patrick Wendell, and Matei Zaharia Overview: This edition of the book introduces Spark and shows how to tackle big data sets through simple APIs in Python, Java, and Scala. You will learn Spark SQL, Spark Streaming, setup and Maven coordinates, distributed datasets, in-memory caching, etc. You will also learn to connect to data sources including HDFS, Hive, JSON, and S3. Cost: You can buy both the Kindle edition and paperback version of this book from Amazon which will cost you ₹1,178 and ₹575 respectively. Click here to buy the book from Amazon. 10| Fast Data Processing with Spark By Krishna Sankar and Holden Karau Overview: This is the second edition of the book written by the chief data scientist, Krishna Sankar which is a solution for the software developers who are eager to learn how to distributed programs with Apache Spark. This book will help developers who are facing complex problems in their programs. Cost: You can buy both the Kindle edition and paperback version of this book from Amazon which will cost you ₹398 and ₹497 respectively. Click here to buy the book from Amazon.
Apache Spark is one of the most active open-sourced big data projects. It is fast, flexible, and scalable, which makes it a very popular and useful project. In this article, we jot down the 10 best books to gain insights into this general-purpose cluster-computing framework. 1| Beginning Apache Spark 2: With Resilient Distributed Datasets, Spark […]
Apache Spark is one of the most active open-sourced big data projects. It is fast, flexible, as well as open-sourced
["Apache Spark", "spark nosql"]
["data science", "machine learning", "Keras", "AI", "neural network", "TensorFlow", "ML", "cloud computing", "Apache Spark", "deep learning", "analytics", "spark nosql"]
["AI", "machine learning", "ML", "deep learning", "neural network", "data science", "analytics", "TensorFlow", "Keras", "cloud computing"]
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