Book Image

Clojure High Performance Programming

By : Shantanu Kumar
Book Image

Clojure High Performance Programming

By: Shantanu Kumar

Overview of this book

<p>Clojure is a young, dynamic, functional programming language that runs on the Java Virtual Machine. It is built with performance, pragmatism, and simplicity in mind. Like most general purpose languages, Clojure’s features have different performance characteristics that one should know in order to write high performance code.<br /><br />Clojure High Performance Programming is a practical, to-the-point guide that shows you how to evaluate the performance implications of different Clojure abstractions, learn about their underpinnings, and apply the right approach for optimum performance in real-world programs.<br /><br />This book discusses the Clojure language in the light of performance factors that you can exploit in your own code.</p> <p>You will also learn about hardware and JVM internals that also impact Clojure’s performance. Key features include performance vocabulary, performance analysis, optimization techniques, and how to apply these to your programs. You will also find detailed information on Clojure's concurrency, state-management, and parallelization primitives.</p> <p>This book is your key to writing high performance Clojure code using the right abstraction, in the right place, using the right technique.</p>
Table of Contents (15 chapters)
Clojure High Performance Programming
Credits
About the Author
Acknowledgments
About the Reviewers
www.PacktPub.com
Preface
Index

Parallelism with reducers


Reducers are a new abstraction introduced in Clojure 1.5 and are likely to have a wider impact on the rest of the Clojure implementation in future versions. They depict a different way of thinking about processing collections in Clojure—the key concept is to break down the notion that collections can be processed only sequentially, or only lazily, or only producing a seq, and so on. Moving away from such behavior guarantee raises the potential for eager and parallel operations on one hand while incurring constraints on the other hand. Reducers are compatible with the existing collections.

For an example, an observation of the regular map function reveals that its classic definition is tied to the mechanism (recursion), order (sequential), laziness (often), and representation (list/seq/other) aspects of producing the result. Most of this actually defines "how" the operation is performed rather than "what" needs to be done. In the case of map, the "what" is all about...