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  • Book Overview & Buying Clojure High Performance Programming, Second Edition
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Clojure High Performance Programming, Second Edition

Clojure High Performance Programming, Second Edition - Second Edition

By : Kumar
4.4 (5)
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Clojure High Performance Programming, Second Edition

Clojure High Performance Programming, Second Edition

4.4 (5)
By: Kumar

Overview of this book

Clojure treats code as data and has a macro system. It focuses on programming with immutable values and explicit progression-of-time constructs, which are intended to facilitate the development of more robust programs, particularly multithreaded ones. It is built with performance, pragmatism, and simplicity in mind. Like most general purpose languages, various Clojure features have different performance characteristics that one should know in order to write high performance code. This book shows you how to evaluate the performance implications of various Clojure abstractions, discover their underpinnings, and apply the right approach for optimum performance in real-world programs. It starts by helping you classify various use cases and the need for them with respect to performance and analysis of various performance aspects. You will also learn the performance vocabulary that experts use throughout the world and discover various Clojure data structures, abstractions, and their performance characteristics. Further, the book will guide you through enhancing performance by using Java interoperability and JVM-specific features from Clojure. It also highlights the importance of using the right concurrent data structure and Java concurrency abstractions. This book also sheds light on performance metrics for measuring, how to measure, and how to visualize and monitor the collected data. At the end of the book, you will learn to run a performance profiler, identify bottlenecks, tune performance, and refactor code to get a better performance.
Table of Contents (10 chapters)
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9
Index

Precomputing and caching


While processing data, we usually come across instances where few common computation steps precede several kinds of subsequent steps. That is to say, some amount of computation is common and the remaining is different. For high-latency common computations (I/O to access the data and memory/CPU to process it), it makes a lot of sense to compute them once and store in digest form, such that the subsequent steps can simply use the digest data and proceed from that point onward, thus resulting in reduced overall latency. This is also known as staging of semi-computed data and is a common technique to optimize processing of non-trivial data.

Clojure has decent support for caching. The built-in clojure.core/memoize function performs basic caching of computed results with no flexibility in using specific caching strategies and pluggable backends. The Clojure contrib library core.memoize offsets the lack of flexibility in memoize by providing several configuration options...

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