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Scala and Spark for Big Data Analytics

You're reading from   Scala and Spark for Big Data Analytics Explore the concepts of functional programming, data streaming, and machine learning

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Product type Paperback
Published in Jul 2017
Publisher Packt
ISBN-13 9781785280849
Length 796 pages
Edition 1st Edition
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Authors (2):
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Sridhar Alla Sridhar Alla
Author Profile Icon Sridhar Alla
Sridhar Alla
Md. Rezaul Karim Md. Rezaul Karim
Author Profile Icon Md. Rezaul Karim
Md. Rezaul Karim
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Table of Contents (19) Chapters Close

Preface 1. Introduction to Scala FREE CHAPTER 2. Object-Oriented Scala 3. Functional Programming Concepts 4. Collection APIs 5. Tackle Big Data – Spark Comes to the Party 6. Start Working with Spark – REPL and RDDs 7. Special RDD Operations 8. Introduce a Little Structure - Spark SQL 9. Stream Me Up, Scotty - Spark Streaming 10. Everything is Connected - GraphX 11. Learning Machine Learning - Spark MLlib and Spark ML 12. My Name is Bayes, Naive Bayes 13. Time to Put Some Order - Cluster Your Data with Spark MLlib 14. Text Analytics Using Spark ML 15. Spark Tuning 16. Time to Go to ClusterLand - Deploying Spark on a Cluster 17. Testing and Debugging Spark 18. PySpark and SparkR

SBT and other build systems

It's necessary to use a build tool for any enterprise software project. There are lots of build tools that you can choose from, such as Maven, Gradle, Ant, and SBT. A good choice of build tool is the one which will let you focus on coding rather than compilation complexities.

Build with SBT

Here, we are going to give a brief introduction to SBT. Before going any further, you need to install SBT using the installation method that fits your system from their official installations methods (URL: http://www.scala-sbt.org/release/docs/Setup.html).

So, let's begin with SBT to demonstrate the use of SBT in a terminal. For this build tool tutorial, we assume that your source code files are in...

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