Map, flatmap and reduce are your new best friends: simpler collections, concurrency, and big data

Higher-order functions such as map(), flatmap(), filter() and reduce() have their origins in mathematics and ancient functional programming languages such as Lisp. But today they have entered the mainstream and are available in languages such as JavaScript, Scala and Java 8. They are well on their way to becoming an essential part of every developer’s toolbox.

In this talk you will learn how these and other higher-order functions enable you to write simple, expressive and concise code that solve problems in a diverse set of domains. We will describe how you use them to process collections in Java and Scala. You will learn how functional Futures and Rx (Reactive Extensions) Observables simplify concurrent code. We will even talk about how to write big data applications in a functional style using libraries such as Scalding.

I’ve presented this talk at the following conferences:

• Slides for JAX Germany 2014
• Slides for Gluecon 2014
• Slides for OSCON 2014

Here is the latest version.