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

Concurrent pipelines


Imagine a situation where we have to carry out jobs at a certain throughput, such that each job includes the same sequence of a differently sized I/O task (task A), a memory-bound task (task B), and again an I/O task (task C). A naive approach would be to create a thread pool and run each job off it, but soon we realize that this is not optimum because we cannot ascertain the utilization of each I/O resource due to unpredictability of the threads being scheduled by the OS. We also observe that even though several concurrent jobs have similar I/O tasks, we are unable to batch them in our first approach.

As the next iteration, we split each job in to stages (A, B, and C) such that each stage corresponds to one task. Since the tasks are well known, we create one thread pool of appropriate size per stage and execute tasks in them. The result of task A is required by task B, and B's result is required by task C—we enable this communication via queues. Now, we can tune the...