Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
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

Arrow left icon
Product type Paperback
Published in Jan 2016
Publisher
ISBN-13 9781785281372
Length 416 pages
Edition 1st Edition
Languages
Arrow right icon
Author (1):
Arrow left icon
Pascal Bugnion Pascal Bugnion
Author Profile Icon Pascal Bugnion
Pascal Bugnion
Arrow right icon
View More author details
Toc

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

Do I need a backend?

In the previous chapter, we learned about the client-server model that underpins how the internet works: when you enter a website URL in your browser, the server serves HTML, CSS, and JavaScript to your browser, which then renders it in the appropriate manner.

What does this all mean for you? Arguably the second question that you should be asking yourself when building a web application is whether you need to do any server-side processing (right after "is this really going to be worth the effort?"). Could you just create an HTML web-page with some JavaScript?

You can get away without a backend if the data needed to build the whole application is small enough: typically a few megabytes. If your application is larger, you will need a backend to transfer just the data the client currently needs. Surprisingly, you can often build visualizations without a backend: while data science is accustomed to dealing with terabytes of data, the goal of the data science process...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime