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Learning Concurrent Programming in Scala
Scala is a modern, multiparadigm programming language designed to express common programming patterns in a concise, elegant, and type-safe way. Scala smoothly integrates the features of object-oriented and functional languages.
In this second edition, you will find updated coverage of the Scala 2.12 platform. The Scala 2.12 series targets Java 8 and requires it for execution. The book starts by introducing you to the foundations of concurrent programming on the JVM, outlining the basics of the Java Memory Model, and then shows some of the classic building blocks of concurrency, such as the atomic variables, thread pools, and concurrent data structures, along with the caveats of traditional concurrency.
The book then walks you through different high-level concurrency abstractions, each tailored toward a specific class of programming tasks, while touching on the latest advancements of async programming capabilities of Scala. It also covers some useful patterns and idioms to use with the techniques described. Finally, the book presents an overview of when to use which concurrency library and demonstrates how they all work together, and then presents new exciting approaches to building concurrent and distributed systems.
In this second edition, you will find updated coverage of the Scala 2.12 platform. The Scala 2.12 series targets Java 8 and requires it for execution. The book starts by introducing you to the foundations of concurrent programming on the JVM, outlining the basics of the Java Memory Model, and then shows some of the classic building blocks of concurrency, such as the atomic variables, thread pools, and concurrent data structures, along with the caveats of traditional concurrency.
The book then walks you through different high-level concurrency abstractions, each tailored toward a specific class of programming tasks, while touching on the latest advancements of async programming capabilities of Scala. It also covers some useful patterns and idioms to use with the techniques described. Finally, the book presents an overview of when to use which concurrency library and demonstrates how they all work together, and then presents new exciting approaches to building concurrent and distributed systems.
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First published November 1, 2014
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About the author
Aleksandar Prokopec
2 books3 followersAleksandar Prokopec is a software developer and a concurrent and distributed programming researcher. He holds an MSc in Computing from the Faculty of Electrical Engineering and Computing, University of Zagreb, Croatia, and a PhD in Computer Science from the École Polytechnique Fédérale de Lausanne, Switzerland. As a doctoral assistant and member of the Scala team at EPFL, he actively contributed to the Scala programming language, and has worked on programming abstractions for concurrency, data-parallel programming support, and concurrent data structures for Scala. He created the Scala Parallel Collections framework, which is a library for high-level data-parallel programming in Scala, and participated in working groups for Scala concurrency libraries, such as Futures and Promises and ScalaSTM.
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Displaying 1 - 3 of 3 reviews
January 29, 2015
Here's a brief review of what I thought about the book ..
The preface of the book says “Its goal is to introduce important concurrency abstractions, and at the same time show how they work in real code”. The book is indeed a detailed one with 366 pages discussing concurrency paradigms in Scala. The author has organized the book very carefully, starting with the basics of concurrency and then building advanced materials on top of them.
Chapter 2 discusses all concurrency primitives on the JVM - processes, threads, monitors and synchronization, atomicity, reordering and the Java Memory Model. Even if you are not very familiar with these concepts, a run through this chapter will serve you good to know the basics. I liked this approach very much.
Chapter 3 builds on top of chapter 2 and teaches you how the bigger building blocks are built on top of the primitives. It discusses topics like the Executor framework, atomic variables, lazy values and concurrent collections. There is a section dedicated to lock free programming where the author discusses CAS based implementations and lock free operations. I think this section could have been a bit more detailed with comparisons of lock free programming and wait free programming or designing a lock free data structure.
Chapter 4 is perhaps the core chapter of the book which discusses the various asynchronous abstractions that Scala standard library offers like Futures, Promises, importance of non blocking operations and the scala async framework. The discussion on Futures and Promises is fairly comprehensive and contains code snippets illustrating the usage of each of them. However the examples shown in this chapter are quite basic ones - may be the book targets a basic learning of the tools (in fact the title of the book also says so). But adding a section for the advanced learners where we develop some interesting combinators that can be used for concurrent composition would have been great.
Chapter 5 discusses parallel collections and chapter 6 details the reactive extensions. Both of these chapters are well written and covers the basics pretty well. In chapter 6 the author discusses reactive programming and event driven programming. The sections on Observables, composing observables and writing custom observables give a very detailed account of the programming model. The reader should benefit from these discussions.
Chapter 7 discusses software transactional memory, though I am not sure how many people use that in Scala. The chapter discusses all the basics of STM as implemented in Scala. But a section on gotchas and pitfalls would have been very useful. In the summary section of this chapter there are a few good references on STM, but the performance issues that are there in the Scala STM needed to be highlighted a bit more.
Chapter 8 is all actors and Akka. Again the author discusses as much as possible to elaborate the features in one chapter. It’s fairly comprehensive as an introduction to the framework.
The core strength of the book is the breadth of topics that it covers. The reader should get an idea of the overall space of concurrency on the JVM in general and Scala in particular. In some parts of the book, the discussion may seem a bit prosaic and mechanical, sometimes you get the feeling that you are reading a text book. In some of the chapters I would have liked to see specific sections dedicated to discussing design patterns and idioms for using the techniques, and also gotchas and pitfalls. But overall the book looks quite comprehensive and is possibly the best reference material out there that touches upon so many topics of concurrency on the JVM.
The preface of the book says “Its goal is to introduce important concurrency abstractions, and at the same time show how they work in real code”. The book is indeed a detailed one with 366 pages discussing concurrency paradigms in Scala. The author has organized the book very carefully, starting with the basics of concurrency and then building advanced materials on top of them.
Chapter 2 discusses all concurrency primitives on the JVM - processes, threads, monitors and synchronization, atomicity, reordering and the Java Memory Model. Even if you are not very familiar with these concepts, a run through this chapter will serve you good to know the basics. I liked this approach very much.
Chapter 3 builds on top of chapter 2 and teaches you how the bigger building blocks are built on top of the primitives. It discusses topics like the Executor framework, atomic variables, lazy values and concurrent collections. There is a section dedicated to lock free programming where the author discusses CAS based implementations and lock free operations. I think this section could have been a bit more detailed with comparisons of lock free programming and wait free programming or designing a lock free data structure.
Chapter 4 is perhaps the core chapter of the book which discusses the various asynchronous abstractions that Scala standard library offers like Futures, Promises, importance of non blocking operations and the scala async framework. The discussion on Futures and Promises is fairly comprehensive and contains code snippets illustrating the usage of each of them. However the examples shown in this chapter are quite basic ones - may be the book targets a basic learning of the tools (in fact the title of the book also says so). But adding a section for the advanced learners where we develop some interesting combinators that can be used for concurrent composition would have been great.
Chapter 5 discusses parallel collections and chapter 6 details the reactive extensions. Both of these chapters are well written and covers the basics pretty well. In chapter 6 the author discusses reactive programming and event driven programming. The sections on Observables, composing observables and writing custom observables give a very detailed account of the programming model. The reader should benefit from these discussions.
Chapter 7 discusses software transactional memory, though I am not sure how many people use that in Scala. The chapter discusses all the basics of STM as implemented in Scala. But a section on gotchas and pitfalls would have been very useful. In the summary section of this chapter there are a few good references on STM, but the performance issues that are there in the Scala STM needed to be highlighted a bit more.
Chapter 8 is all actors and Akka. Again the author discusses as much as possible to elaborate the features in one chapter. It’s fairly comprehensive as an introduction to the framework.
The core strength of the book is the breadth of topics that it covers. The reader should get an idea of the overall space of concurrency on the JVM in general and Scala in particular. In some parts of the book, the discussion may seem a bit prosaic and mechanical, sometimes you get the feeling that you are reading a text book. In some of the chapters I would have liked to see specific sections dedicated to discussing design patterns and idioms for using the techniques, and also gotchas and pitfalls. But overall the book looks quite comprehensive and is possibly the best reference material out there that touches upon so many topics of concurrency on the JVM.
April 4, 2015
I really enjoyed reading this book. The Scala community needed a manual such as this for a while now. Before this book, documentation on concurrent programming in Scala consisted mostly of online SIP documents, tutorials scattered across multiple websites, Stackoverflow answers and random blog posts. This results in scattered, incomplete and often convoluted information about Scala concurrency. Learning Concurrent Programming in Scala constitutes a readable and authoritative manual on using these concurrency libraries, with everything needed to get you started in one place. Although I recommend getting acquainted with sequential programming in Scala first, people who want to write concurrent programs in Scala should definitely read this book. That does not mean that the book is valuable only for Scala programmers - as someone with 11 years of industry experience in Java, I can honestly say that the concurrency novelties described in this book will be interesting to programmers coming from backgrounds different than Scala - there was much going on in the Scala world in the recent years, in which Java is still lagging behind (in fact, I was able to convince one of my colleagues at work to give Scala a try after he saw the introduction to the Rx framework in this book).
The book starts by presenting the basics of JVM threading and memory model, which serves as the basic . Although this is more low-level than the rest of the concurrency frameworks in the book, the book does a good job arguing why you need to understand basic JVM concurrency, and when to use threads, locks and monitors. Chapter 3 shows the classic concurrency abstractions, such as concurrent data structures, atomics, and thread pools, and explains lock-free programming. Chapter 4 is where the fun begins - it explains the futures and promises concurrency package, shows how to use it for asynchronous programming, how to functionally compose asynchronous computations, how to write new future combinators using promises, shows how to do proper cancellation and blocking in futures, and explains the Scala Async framework. Chapter 5 introduces parallel collections, shows how they differ from normal collections, discusses operations that can be parallelized, shows how to implement custom parallel operations, and how to evaluate performance in your programs. Chapter 6 introduces Rx, asynchronous programming framework based on first-class event streams, and shows how Rx can be used to build user interfaces and streaming applications. Chapter 7 deals with software transactional memories, discusses how STMs work, shows how to avoid side-effects in transactions, how to execute transactions conditionally, explains how transactional collections work, and, importantly, illustrates how easy it is to create a custom transactional, thread-safe collection. Chapter 8 introduces actor programming using Akka, and covers asynchronous message sends, starting and looking up actors, the basics of actor supervision, as well distributing the application across multiple computers. While Akka is not completely covered in this book, as it is a big topic, this chapter teaches the essentials of Akka, and you will be able to write actor programs after you're done. Chapter 9 shows how to achieve scalability and top performance in concurrent applications, what are the common types of errors in concurrent applications, and how to debug them, and, finally, how to combine different concurrency technologies to build a real-world application - a remote file browser. This is the longest chapter, and arguably, it could have been split into two separate chapters.
This is a hands-on book. Every concurrency concept is introduced through a minimal, self-contained example, and you are encouraged to code and try the examples yourself. In almost all places in the book, there is a snippet or a minimal example program that demonstrates or proves the preceding claim. Terms like starvation, deadlock, false sharing and rollbacks are never introduced without the corresponding example program that shows how these effects manifest themselves in practice. These programs are minimal examples, but are realistic and capture the essence of the corresponding real-world programs. I'm sure that, after having written and run the examples, the reader will have no problem recognizing the same effects in practice.
Every chapter is concluded with a list of references, and practical program assignments, which test the knowledge from the corresponding chapter, and, in some cases, touch more advanced topics.
What I especially liked about this book is that the author shows how different concurrency libraries can be used together. As an occasional by-stander in the Scala world, I've often witnessed propaganda and bias towards specific concurrency technologies. This is not the case only with Scala and its concurrency libraries, but also more broadly, with most programming technologies - proponents of specific programming technologies need to ruthlessly advertise their own frameworks to survive. As a result, they sometimes claim that their technology is the best, applicable to every problem or superior to alternatives. The author dismisses such attitude in two ways. First, he explains the underlying motivations for various concurrency primitives and shows their typical use-cases and usage scenarios. In doing so, he teaches the reader what a specific concurrency construct is most appropriate for. Second, he shows that concurrency primitives coming from different frameworks are not incompatible or mutually exclusive, but that they can and should be used together to tackle a task. For example, futures are ideal for issuing remote procedure calls or asynchronous requests, but parallel collections are more efficient for data-intensive tasks. Actors are great for distributed applications, but software transactional memory composes complex state and allows concurrent access to data. Still, the future can start a data-parallel computation or a transaction, and an Rx stream can send messages to an actor - these primitives support each other.
What I'd wish to see more of are advanced concurrency concepts - how does one write his own concurrent data structure, or implement more advanced applications. The book touches performance engineering and achieving best program speeds, and, having read about it, I'd love to learn more. Perhaps a follow-up book about more advanced concurrent programming will address this. Still, this is overall a great book, and will teach you how to think about concurrent programming. I recommend it as an introductory book on concurrent programming, and modern concurrency paradigms.
The book starts by presenting the basics of JVM threading and memory model, which serves as the basic . Although this is more low-level than the rest of the concurrency frameworks in the book, the book does a good job arguing why you need to understand basic JVM concurrency, and when to use threads, locks and monitors. Chapter 3 shows the classic concurrency abstractions, such as concurrent data structures, atomics, and thread pools, and explains lock-free programming. Chapter 4 is where the fun begins - it explains the futures and promises concurrency package, shows how to use it for asynchronous programming, how to functionally compose asynchronous computations, how to write new future combinators using promises, shows how to do proper cancellation and blocking in futures, and explains the Scala Async framework. Chapter 5 introduces parallel collections, shows how they differ from normal collections, discusses operations that can be parallelized, shows how to implement custom parallel operations, and how to evaluate performance in your programs. Chapter 6 introduces Rx, asynchronous programming framework based on first-class event streams, and shows how Rx can be used to build user interfaces and streaming applications. Chapter 7 deals with software transactional memories, discusses how STMs work, shows how to avoid side-effects in transactions, how to execute transactions conditionally, explains how transactional collections work, and, importantly, illustrates how easy it is to create a custom transactional, thread-safe collection. Chapter 8 introduces actor programming using Akka, and covers asynchronous message sends, starting and looking up actors, the basics of actor supervision, as well distributing the application across multiple computers. While Akka is not completely covered in this book, as it is a big topic, this chapter teaches the essentials of Akka, and you will be able to write actor programs after you're done. Chapter 9 shows how to achieve scalability and top performance in concurrent applications, what are the common types of errors in concurrent applications, and how to debug them, and, finally, how to combine different concurrency technologies to build a real-world application - a remote file browser. This is the longest chapter, and arguably, it could have been split into two separate chapters.
This is a hands-on book. Every concurrency concept is introduced through a minimal, self-contained example, and you are encouraged to code and try the examples yourself. In almost all places in the book, there is a snippet or a minimal example program that demonstrates or proves the preceding claim. Terms like starvation, deadlock, false sharing and rollbacks are never introduced without the corresponding example program that shows how these effects manifest themselves in practice. These programs are minimal examples, but are realistic and capture the essence of the corresponding real-world programs. I'm sure that, after having written and run the examples, the reader will have no problem recognizing the same effects in practice.
Every chapter is concluded with a list of references, and practical program assignments, which test the knowledge from the corresponding chapter, and, in some cases, touch more advanced topics.
What I especially liked about this book is that the author shows how different concurrency libraries can be used together. As an occasional by-stander in the Scala world, I've often witnessed propaganda and bias towards specific concurrency technologies. This is not the case only with Scala and its concurrency libraries, but also more broadly, with most programming technologies - proponents of specific programming technologies need to ruthlessly advertise their own frameworks to survive. As a result, they sometimes claim that their technology is the best, applicable to every problem or superior to alternatives. The author dismisses such attitude in two ways. First, he explains the underlying motivations for various concurrency primitives and shows their typical use-cases and usage scenarios. In doing so, he teaches the reader what a specific concurrency construct is most appropriate for. Second, he shows that concurrency primitives coming from different frameworks are not incompatible or mutually exclusive, but that they can and should be used together to tackle a task. For example, futures are ideal for issuing remote procedure calls or asynchronous requests, but parallel collections are more efficient for data-intensive tasks. Actors are great for distributed applications, but software transactional memory composes complex state and allows concurrent access to data. Still, the future can start a data-parallel computation or a transaction, and an Rx stream can send messages to an actor - these primitives support each other.
What I'd wish to see more of are advanced concurrency concepts - how does one write his own concurrent data structure, or implement more advanced applications. The book touches performance engineering and achieving best program speeds, and, having read about it, I'd love to learn more. Perhaps a follow-up book about more advanced concurrent programming will address this. Still, this is overall a great book, and will teach you how to think about concurrent programming. I recommend it as an introductory book on concurrent programming, and modern concurrency paradigms.
July 29, 2017
Good overview of concurrency abstractions in Scala. Goes into enough details to be useful. The last chapter introduces http://reactors.io/, which looks very interesting.
Displaying 1 - 3 of 3 reviews