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Key benefits

Learn Scala’s sophisticated type system that combines Functional Programming and object-oriented concepts

Work on a wide array of applications, from simple batch jobs to stream processing and machine learning

Explore the most common as well as some complex use-cases to perform large-scale data analysis with Spark

Description

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. Thus, if you want to leverage the power of Scala and Spark to make sense of big data, this book is for you. The first part introduces you to Scala, helping you understand the object-oriented and functional programming concepts needed for Spark application development. It then moves on to Spark to cover the basic abstractions using RDD and DataFrame. This will help you develop scalable and fault-tolerant streaming applications by analyzing structured and unstructured data using SparkSQL, GraphX, and Spark structured streaming. Finally, the book moves on to some advanced topics, such as monitoring, configuration, debugging, testing, and deployment. You will also learn how to develop Spark applications using SparkR and PySpark APIs, interactive data analytics using Zeppelin, and in-memory data processing with Alluxio. By the end of this book, you will have a thorough understanding of Spark, and you will be able to perform full-stack data analytics with a feel that no amount of data is too big.

What you will learn

Understand object-oriented & functional programming concepts of Scala

In-depth understanding of Scala collection APIs

Work with RDD and DataFrame to learn Spark's core abstractions

Analysing structured and unstructured data using SparkSQL and GraphX

Scalable and fault-tolerant streaming application development using Spark structured streaming

Learn machine-learning best practices for classification, regression, dimensionality reduction, and recommendation system to build predictive models with widely used algorithms in Spark MLlib & ML

Build clustering models to cluster a vast amount of data

Understand tuning, debugging, and monitoring Spark applications

Deploy Spark applications on real clusters in Standalone, Mesos, and YARN

What do you get with Print?

Instant access to your digital copy whilst your Print order is Shipped

Paperback book shipped to your preferred address

Redeem a companion digital copy on all Print orders

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

Frequently bought together

€53.99

Scala for Machine Learning, Second Edition

€49.99

€41.99

Total € 145.97

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Amazon verified reviews

Verified Amazon Customer Jul 27, 2017

Fantastic book! I purchased this book yesterday and already read some chapters and had a quick look to other chapters too. It contains everything needed for learning big data analytics with Spark. It elaborately covers the Scala programming, Sparks basic operations, many machine learning algorithms (classification, regression, clustering, recommendation system), NLP, graph analytics, structured streaming, and of course some other advanced topics of Spark such as tuning, debugging and cluster deployment.More interestingly, it also discussed PySpark, SparkR, Alixuio, and Zeppelin so I don't need to switch to something else. So in summary, it contains everything I was looking for few months.

Amazon Verified review

Md Ashiqur Rahman Nov 16, 2017

This is a fantastic book for getting a real understanding about how to develop big data processing applications using Scala and Spark. This book is very up to date containing wide coverage of all the APIs such as Spark SQL, structured streaming, graphX, Spark MLib and more.

Amazon Customer Aug 01, 2017

I am a scala enthusiastic, also professional java programmer, now a days im into bigdata stack. I've read the entire book more or less. I would highly recommend this book if someone working in java area but want to write java code in functional (scala) way to solve bigdata problems - scala makes spark processing much easier. I would also recommend this book who is yet to start bigdata coding using scala for spark processing. This book includes a lot of nice, small and real life bigdata analytics problems and how to solve them easily using scala on top of hadoop ecosystem.Thanks to authors for such an useful book - its not just only concepts but also guide to implement concepts.

Ariel Herrera Oct 03, 2018

What I love about this book is that the author explains each concept very well and provides numerous examples. Yes, it is a large read however you can jump around in the book based on your need and it is sufficient.

Julio Bregeiro Nov 18, 2023

Aprovadi

Scala and Spark for Big Data Analytics: Explore the concepts of functional programming, data streaming, and machine learning

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