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Mastering High Performance with Kotlin
Mastering High Performance with Kotlin

Mastering High Performance with Kotlin: Overcome performance difficulties in Kotlin with a range of exciting techniques and solutions

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Mastering High Performance with Kotlin

Identifying Indicators of Performance Issues

So far, you have an understanding of what performance is. You also know which system bottlenecks lead to performance issues and how they do so. Now, we're ready to talk about how to identify these problems.

Different implementations of the same functionality can impact the performance of the whole application in different ways. It's hard to make the right choice between several approaches if you're guided by your assumptions. Therefore, we should measure performance but not make our choice based on a guess.

Measurement is a significant part of everyday management and technical activities. It's important because measurement gives us the numbers—the objective information—that we need to make informed decisions that improve performance. From the developer's point of view, performance measurement...

Benchmarking

It's difficult to compare the performance of algorithms simply by looking at their descriptions or pseudocode. It's better to run actual implementations on a real system. This method of measurement is called benchmarking. There are three categories of benchmark:

  • Microbenchmarks: These are metrics showing the performance of certain functions. They assume that a small piece of business logic is contained in a single function, and we simply measure how fast this function runs.
  • Macrobenchmarks: These are the opposite of microbenchmarks; they test the entire application.
  • Mesobenchmarks: These are something in-between, measuring features or workflows.

Large applications more or less contain certain critical pieces of code. The JVM is an adaptive virtual machine, meaning it optimizes running code in many ways. Obtaining metrics that are meaningful is actually...

General performance metrics

Benchmarking is a small part of performance testing. The main focus of performance testing is checking software:

  • Speed: To determine how fast the application responds
  • Scalability: To determine the maximum number of users that an application can handle
  • Stability: To determine how the application invokes its functions under different loads

Types of performance testing

The most common performance problems revolve around response time, speed, load time, and scalability. These issues impact the most important attribute of an application: speed. Therefore, the main purpose of performance testing is to make sure that your application runs fast enough to keep a user's attention. There are a lot...

Summary

In this chapter, we presented the most common identifiers, tools, and approaches for detecting performance issues during testing and the post-release stage. We'll use these approaches in the following chapters. We also provided an overview of performance testing tools for different purposes and platforms, and talked about performance testing types before delving into benchmarking.

In the next chapter, we'll introduce different tools and profilers for identifying performance issues.

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Key benefits

  • Apply modern Kotlin features to speed up processing and implement highly efficient and reliable codes.
  • Learn memory optimization, concurrency, multi-threading, scaling, and caching techniques to achieve high performance.
  • Learn how to prevent unnecessary overhead and use profiling tools to detect performance issues.

Description

The ease with which we write applications has been increasing, but with it comes the need to address their performance. A balancing act between easily implementing complex applications and keeping their performance optimal is a present-day requirement In this book, we explore how to achieve this crucial balance, while developing and deploying applications with Kotlin. The book starts by analyzing various Kotlin specifcations to identify those that have a potentially adverse effect on performance. Then, we move on to monitor techniques that enable us to identify performance bottlenecks and optimize performance metrics. Next, we look at techniques that help to us achieve high performance: memory optimization, concurrency, multi threading, scaling, and caching. We also look at fault tolerance solutions and the importance of logging. We'll also cover best practices of Kotlin programming that will help you to improve the quality of your code base. By the end of the book, you will have gained some insight into various techniques and solutions that will help to create high-performance applications in the Kotlin environment

Who is this book for?

This book is for Kotlin developers who would like to build reliable and high-performance applications. Prior Kotlin programming knowledge is assumed.

What you will learn

  • Understand the importance of high performance
  • Learn performance metrics
  • Learn popular design patterns currently being used in Kotlin
  • Understand how to apply modern Kotlin features to data processing
  • Learn how to use profling tools
  • Discover how to read bytecode
  • Learn to perform memory optimizations
  • Uncover approaches to the multithreading environment

Product Details

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Publication date : Jun 15, 2018
Length: 316 pages
Edition : 1st
Language : English
ISBN-13 : 9781788998352
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Product Details

Publication date : Jun 15, 2018
Length: 316 pages
Edition : 1st
Language : English
ISBN-13 : 9781788998352
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Languages :

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Mastering High Performance with Kotlin
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Learning Concurrency in Kotlin
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Table of Contents

11 Chapters
Identifying Performance Bottlenecks Chevron down icon Chevron up icon
Identifying Indicators of Performance Issues Chevron down icon Chevron up icon
Learning How to Use Profiling Tools Chevron down icon Chevron up icon
Functional Approach Chevron down icon Chevron up icon
Enhancing the Performance of Collections Chevron down icon Chevron up icon
Optimizing Access to Properties Chevron down icon Chevron up icon
Preventing Unnecessary Overhead Using Delegates Chevron down icon Chevron up icon
Ranges and Identifying Performance Issues Chevron down icon Chevron up icon
Multithreading and Reactive Programming Chevron down icon Chevron up icon
Best Practices Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon

Customer reviews

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GAUD Feb 22, 2019
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Realmente las recomendaciones del libro podrían caber en sólo 3 o 4 páginas, y el resto del libro consiste en ejemplos de código en Kotlin / Java / Bytecode para ilustrar cosas que en su mayoría son más bien obvias. De hecho el último capítulo del libro es un resumen de todos los anteriores, así que en lugar de leer el libro completo uno podría leer solamente el último capítulo.
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