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Scala for Data Science

You're reading from   Scala for Data Science Leverage the power of Scala with different tools to build scalable, robust data science applications

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Product type Paperback
Published in Jan 2016
Publisher
ISBN-13 9781785281372
Length 416 pages
Edition 1st Edition
Languages
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Author (1):
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Pascal Bugnion Pascal Bugnion
Author Profile Icon Pascal Bugnion
Pascal Bugnion
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Table of Contents (17) Chapters Close

Preface 1. Scala and Data Science FREE CHAPTER 2. Manipulating Data with Breeze 3. Plotting with breeze-viz 4. Parallel Collections and Futures 5. Scala and SQL through JDBC 6. Slick – A Functional Interface for SQL 7. Web APIs 8. Scala and MongoDB 9. Concurrency with Akka 10. Distributed Batch Processing with Spark 11. Spark SQL and DataFrames 12. Distributed Machine Learning with MLlib 13. Web APIs with Play 14. Visualization with D3 and the Play Framework A. Pattern Matching and Extractors Index

The Play framework

The Play framework is a web framework built on top of Akka. It has a proven track record in industry, and is thus a reliable choice for building scalable web applications.

Play is an opinionated web framework: it expects you to follow the MVC architecture, and it has a strong opinion about the tools you should be using. It comes bundled with its own JSON and XML parsers, with its own tools for accessing external APIs, and with recommendations for how to access databases.

Web applications are much more complex than the command line scripts we have been developing in this book, because there are many more components: the backend code, routing information, HTML templates, JavaScript files, images, and so on. The Play framework makes strong assumptions about the directory structure for your project. Building that structure from scratch is both mind-numbingly boring and easy to get wrong. Fortunately, we can use Typesafe activators to bootstrap the project (you can also download...

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