Book Image

Scala Data Analysis Cookbook

By : Arun Manivannan
Book Image

Scala Data Analysis Cookbook

By: Arun Manivannan

Overview of this book

This book will introduce you to the most popular Scala tools, libraries, and frameworks through practical recipes around loading, manipulating, and preparing your data. It will also help you explore and make sense of your data using stunning and insightfulvisualizations, and machine learning toolkits. Starting with introductory recipes on utilizing the Breeze and Spark libraries, get to grips withhow to import data from a host of possible sources and how to pre-process numerical, string, and date data. Next, you’ll get an understanding of concepts that will help you visualize data using the Apache Zeppelin and Bokeh bindings in Scala, enabling exploratory data analysis. iscover how to program quintessential machine learning algorithms using Spark ML library. Work through steps to scale your machine learning models and deploy them into a standalone cluster, EC2, YARN, and Mesos. Finally dip into the powerful options presented by Spark Streaming, and machine learning for streaming data, as well as utilizing Spark GraphX.
Table of Contents (14 chapters)
Scala Data Analysis Cookbook
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

Getting Apache Spark


In this recipe, we'll take a look at how to bring Spark into our project (using SBT) and how Spark works internally.

Note

The code for this recipe can be found at https://github.com/arunma/ScalaDataAnalysisCookbook/blob/master/chapter1-spark-csv/build.sbt.

How to do it...

Let's now throw some Spark dependencies into our build.sbt file so that we can start playing with them in subsequent recipes. For now, we'll just focus on three of them: Spark Core, Spark SQL, and Spark MLlib. We'll take a look at a host of other Spark dependencies as we proceed further in this book:

  1. Under a brand new folder (which will be your project root), create a new file called build.sbt.

  2. Next, let's add the Spark libraries to the project dependencies.

  3. Note that Spark 1.4.x requires Scala 2.10.x. This becomes the first section of our build.sbt:

    organization := "com.packt"
    
    name := "chapter1-spark-csv"
    
    scalaVersion := "2.10.4"
    
    val sparkVersion="1.4.1"
    
    libraryDependencies ++= Seq(
      "org.apache.spark...