Chapter 6. Functional Programming in Scala

It is better to have 100 functions operate on one data structure than 10 functions on 10 data structures.

Alan J. Perlis

Every decade or two, a major computing idea goes mainstream. The idea may have lurked in the background of academic Computer Science research or in obscure corners of industry, perhaps for decades. The transition to mainstream acceptance comes in response to a perceived problem for which the idea is well suited. Object-oriented programming (OOP), which was invented in the 1960s, went mainstream in the 1980s, arguably in response to the emergence of graphical user interfaces, for which the OOP paradigm is a natural fit.

Functional programming (FP) is going through a similar breakout. Long the topic of research and actually much older than OOP, FP offers effective techniques for three major challenges of our time:

  1. The need for pervasive concurrency, so we can scale our applications horizontally and improve their resiliency against service disruptions. Hence, concurrent programming is now an essential skill for every developer to master.

  2. The need to write data-centric (e.g., “Big Data”) applications. Of course, at some level all programs are about data, but the recent Big Data trend has highlighted the importance of effective techniques for working with large data sets.

  3. The need to write bug-free applications. Of course, this is a challenge as old as programming itself, but FP gives us new tools, from mathematics, ...

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