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Scala and Spark for Big Data Analytics

You're reading from  Scala and Spark for Big Data Analytics

Product type Book
Published in Jul 2017
Publisher Packt
ISBN-13 9781785280849
Pages 796 pages
Edition 1st Edition
Languages
Concepts
Authors (2):
Md. Rezaul Karim Md. Rezaul Karim
Profile icon Md. Rezaul Karim
Sridhar Alla Sridhar Alla
Profile icon Sridhar Alla
View More author details

Table of Contents (19) Chapters

Preface 1. Introduction to Scala 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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