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Scala and Spark for Big Data Analytics

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Description

Harness the power of Scala to program Spark and analyse tonnes of data in the blink of an eye! About This Book * 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 Who This Book Is For 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. What You Will Learn * Understand the basics of Scala and explore Functional programming. *Get familiar with Collections API, one of the most prominent features of the standard library. *Work with RDDs, the basic abstractions behind Apache Spark. *Use Spark for the analysis of structured and unstructured data and work with SparkSQL's APIs. *Take advantage of Spark for the analysis of streaming data and explore interoperability with streaming software like Apache Kafka. *Use common Machine Learning techniques like Dimensionality Reduction and One Hot Encoding and build a predictive model using Spark. *Use Bayesian inference to build another kind of classification model and understand when the Decision Tree algorithm should be used. *Build a Clustering model and use it to make predictions. *Tune your application and use Spark Testing Base. *Deploy a full Spark application on a cluster using Mesos. In Detail Scala has been observing a steady rise in adoption over the past few years, especially in the field of data science and analytics. Going hand in hand with Scala, is Apache Spark, which is built on Scala, and is widely used in the field of Analytics. If you want to leverage the power of both, Scala and Spark, to make sense of Big Data, then this book is for you. This book is divided into three parts. In the first part, it will introduce you to Scala programming, helping you understand its fundamentals and be able to program with Spark. It will then move on to introducing you to Spark and the design choices beneath it and show you how to perform data analysis with it. Finally to shake things up, the book moves onto Advanced Spark and teach you advanced topics, like monitoring, configuration, debugging, testing and finally deployment. By the end of this book, you will be able to perform full stack data analysis with Spark and feel that no amount of data is too big.

Author Biography:

Stefano Baghino has worked as a Software Engineer to help address the needs of several industries (power generation, energy automation, finance, advertising) with a diverse range of technologies. He started working with Scala in 2012 and contributed to Apache Flink. He's currently working as a Backend API Engineer at Teralytics to create a scalable analytics platform that leverages Apache Spark. Andrea Bessi is a software developer with a keen interest in Data Science. After a Bachelor's thesis on Data Mining and a Master's thesis on Business Intelligence, Databiz allowed him to delve deeper into Machine Learning. He is always amazed at how Apache Spark and Scala ease his everyday job. Bertrand Bossy is a software engineer at Teralytics and is a huge fan of Spark. He is a major contributor towards Spark and contributed to fix the bugs in core for Spark 1.1.
Release date Australia
July 25th, 2017
Pages
786
Audience
  • General (US: Trade)
Publisher
Packt Publishing Limited
Country of Publication
United Kingdom
Imprint
Packt Publishing Limited
ISBN-13
9781785280849
Product ID
26873920

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