Book Image

Scala Programming Projects

By : Mikael Valot, Nicolas Jorand
Book Image

Scala Programming Projects

By: Mikael Valot, Nicolas Jorand

Overview of this book

Scala Programming Projects is a comprehensive project-based introduction for those who are new to Scala. Complete with step-by-step instructions and easy-to-follow tutorials that demonstrate best practices when building applications, this Scala book will have you building real-world projects in no time. Starting with the fundamentals of software development, you’ll begin with simple projects, such as developing a financial independence calculator, and then advance to more complex projects, such as a building a shopping application and a Bitcoin transaction analyzer. You’ll explore a variety of Scala features, including its OOP and FP capabilities, and learn how to write concise, reactive, and concurrent applications in a type-safe manner. You’ll also understand how to use libraries such as Akka and Play. Furthermore, you’ll be able to integrate your Scala apps with Kafka, Spark, and Zeppelin, along with deploying applications on a cloud platform. By the end of the book, you’ll have a firm foundation in Java programming that’ll enable you to solve a variety of real-world problems, and you’ll have built impressive projects to add to your professional portfolio.
Table of Contents (18 chapters)
Title Page
Copyright and Credits
Packt Upsell
Contributors
Preface
Index

Summary


By now, you should be more comfortable using Spark's Dataset API. Our little program is focused on fetching BCT/USD transactions, but it could be interesting to enhance it. For instance, you could fetch and save other currency pairs, such as ETH/EUR or XRP/USD. Use a different cryptocurrency exchange. This would allow you to compare prices in different exchanges, and possibly work out an arbitrage strategy. Arbitrage is a simultaneous purchase and sale of an asset in different marketplaces to profit from an imbalance in the price. You could get data for traditional currency pairs, such as EUR/USD, or use Frameless to refactor the Dataset manipulations and make them more type-safe. See the website for further clarification https://github.com/typelevel/frameless.

In the next chapter, we are going to exploit saved transaction data to perform some analytics queries.