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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
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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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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

References


MongoDB: The Definitive Guide, by Kristina Chodorow, is a good introduction to MongoDB. It does not cover interacting with MongoDB in Scala at all, but Casbah is intuitive enough for anyone familiar with MongoDB.

Similarly, the MongoDB documentation (https://docs.mongodb.org/manual/) provides an in-depth discussion of MongoDB.

Casbah itself is well-documented (http://mongodb.github.io/casbah/3.0/). There is a Getting Started guide that is somewhat similar to this chapter and a complete reference guide that will fill in the gaps left by this chapter.

This gist, https://gist.github.com/switzer/4218526, implements type classes to serialize and deserialize objects in the domain model to DBObjects. The premise is a little different from the suggested usage of type classes in this chapter: we are converting from Scala types to AnyRef to be used as values in DBObject. However, the two approaches are complementary: one could imagine a set of type classes to convert from User or Repo to...

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