Concurrent and parallel programming have progressed from niche disciplines, of interest only to kernel programming and high-performance computing, to something that every competent programmer must know. As parallel and distributed computing systems are now the norm, most applications are concurrent, be it for increasing the performance or for handling asynchronous events.

So far, most developers are unprepared to deal with this revolution. Maybe they have learned the traditional concurrency model, which is based on threads and locks, in school, but this model has become inadequate for dealing with massive concurrency in a reliable manner and with acceptable productivity. Indeed, threads and locks are hard to use and harder to get right. To make progress, one needs to use concurrency abstractions that are at a higher level and composable.

15 years ago, I worked on a predecessor of Scala: "Funnel" was an experimental programming language that had a concurrent semantics at its core. All the programming concepts were explained in this language as syntactic sugar on top of "functional nets", an object-oriented variant of "join calculus". Even though join calculus is a beautiful theory, we realized after some experimentation that the concurrency problem is more multifaceted than what can be comfortably expressed in a single formalism. There is no silver bullet for all concurrency issues; the right solution depends on what one needs to achieve. Do you want to define asynchronous computations that react to events or streams of values? Or have autonomous, isolated entities communicating via messages? Or define transactions over a mutable store? Or, maybe the primary purpose of parallel execution is to increase the performance? For each of these tasks, there is an abstraction that does the job: futures, reactive streams, actors, transactional memory, or parallel collections.

This brings us to Scala and this book. As there are so many useful concurrency abstractions, it seems unattractive to hardcode them all in a programming language. The purpose behind the work on Scala was to make it easy to define high-level abstractions in user code and libraries. This way, one can define modules handling the different aspects of concurrent programming. All of these modules would be built on a low-level core that is provided by the host system. In retrospect, this approach has worked well. Scala has today some of the most powerful and elegant libraries for concurrent programming. This book will take you on a tour of the most important ones, explaining the use case for each, and the application patterns.

The book could not have a more expert author. Aleksandar Prokopec contributed to some of the most popular Scala libraries for concurrent and parallel programming. He also invented some of the most intricate data structures and algorithms. With this book, he created a readable tutorial at the same time and an authoritative reference for the area that he had worked in. I believe that Learning Concurrent Programming in Scala will be a mandatory reading for everyone who writes concurrent and parallel programs in Scala. I expect to also see it on the bookshelves of many people who just want to find out about this fascinating and fast moving area of computing.

Martin Odersky

Professor at EPFL, the creator of Scala