Book Image

Scala for Data Science

By : Pascal Bugnion
Book Image

Scala for Data Science

By: Pascal Bugnion

Overview of this book

Scala is a multi-paradigm programming language (it supports both object-oriented and functional programming) and scripting language used to build applications for the JVM. Languages such as R, Python, Java, and so on are mostly used for data science. It is particularly good at analyzing large sets of data without any significant impact on performance and thus Scala is being adopted by many developers and data scientists. Data scientists might be aware that building applications that are truly scalable is hard. Scala, with its powerful functional libraries for interacting with databases and building scalable frameworks will give you the tools to construct robust data pipelines. This book will introduce you to the libraries for ingesting, storing, manipulating, processing, and visualizing data in Scala. Packed with real-world examples and interesting data sets, this book will teach you to ingest data from flat files and web APIs and store it in a SQL or NoSQL database. It will show you how to design scalable architectures to process and modelling your data, starting from simple concurrency constructs such as parallel collections and futures, through to actor systems and Apache Spark. As well as Scala’s emphasis on functional structures and immutability, you will learn how to use the right parallel construct for the job at hand, minimizing development time without compromising scalability. Finally, you will learn how to build beautiful interactive visualizations using web frameworks. This book gives tutorials on some of the most common Scala libraries for data science, allowing you to quickly get up to speed with building data science and data engineering solutions.
Table of Contents (22 chapters)
Scala for Data Science
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

Fetcher actors


The workhorse of our application is the fetcher, the actor responsible for fetching the follower details from GitHub. In the first instance, our actor will accept a single message, Fetch(user). It will fetch the followers corresponding to user and log the response to screen. We will use the recipes developed in Chapter 7, Web APIs, to query the GitHub API with an OAuth token. We will inject the token through the actor constructor.

Let's start with the companion object. This will contain the definition of the Fetch(user) message and two factory methods to create the Props instances. You can find the code examples for this section in the chap09/fetchers_alone directory in the sample code provided with this book (https://github.com/pbugnion/s4ds):

// Fetcher.scala
import akka.actor._
import scalaj.http._
import scala.concurrent.Future

object Fetcher {
  // message definitions
  case class Fetch(login:String)

  // Props factory definitions
  def props(token:Option[String]):Props...