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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

A structured approach to the performance

In practice, the performance of non-trivial applications is rarely a function of coincidence or prediction. For many projects, performance is not an option (it is rather a necessity), which is why this is even more important today. Capacity planning, determining performance objectives, performance modeling, measurement, and monitoring are key.

Tuning a poorly designed system to perform is significantly harder, if not practically impossible, than having a system well-designed from the start. In order to meet a performance goal, performance objectives should be known before the application is designed. The performance objectives are stated in terms of latency, throughput, resource utilization, and workload. These terms are discussed in the following section in this chapter.

The resource cost can be identified in terms of application scenarios, such as browsing of products, adding products to shopping cart, checkout, and more. Creating workload profiles that represent users performing various operations is usually helpful.

Performance modeling is a reality check for whether the application design will support the performance objectives. It includes performance objectives, application scenarios, constraints, measurements (benchmark results), workload objectives and if available, the performance baseline. It is not a replacement for measurement and load testing, rather, the model is validated using these. The performance model may include the performance test cases to assert the performance characteristics of the application scenarios.

Deploying an application to production almost always needs some form of capacity planning. It has to take into account the performance objectives for today and for the foreseeable future. It requires an idea of the application architecture, and an understanding of how the external factors translate into the internal workload. It also requires informed expectations about the responsiveness and the level of service to be provided by the system. Often, capacity planning is done early in a project to mitigate the risk of provisioning delays.

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