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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

Applying back pressure


We discussed back pressure briefly in the last chapter. Without back pressure we cannot build a reasonable load-tolerant system with predictable stability and performance. In this section, we will see how to apply back pressure in different scenarios in an application. At a fundamental level, we should have a threshold of a maximum number of concurrent jobs in the system and, based on that threshold, we should reject new requests above a certain arrival rate. The rejected messages may either be retried by the client or ignored if there is no control over the client. When applying back pressure to user-facing services, it may be useful to detect system load and deny auxiliary services first in order to conserve capacity and degrade gracefully in the face of high load.

Thread pool queues

JVM thread pools are backed by queues, which means that when we submit a job into a thread pool that already has the maximum jobs running, the new job lands in the queue. The queue is...

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