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High Performance with Java

High Performance with Java

By : Dr. Edward Lavieri Jr.
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High Performance with Java

High Performance with Java

By: Dr. Edward Lavieri Jr.

Overview of this book

Building high performance into your applications is key to creating an optimal user experience, although it is not the only consideration for the performant nature of your apps. High performance applications can lead to cost-effective resource utilization, especially when scalability and cloud computing are involved. They can also provide highly reliable systems that are easier to maintain. High Performance with Java begins by helping you explore the Java Virtual Machine (JVM) and understand how to push it to its limits to further optimize your programs. You’ll take a hands-on approach to go through memory optimization strategies, input/output operations, concurrency, networking, as well as frameworks and libraries focused on performance. You’ll also learn key strategies and best practices by using industry-relevant examples to architect scalable and resource-efficient applications. The concluding chapters provide valuable insights on optimizing your Java code when interacting with databases and show you how to leverage artificial intelligence (AI) for high performance Java applications. By the end of this book, you’ll grasp the importance of developing high performance Java applications and gain practical experience in implementing key strategies to help ensure your Java applications perform optimally.
Table of Contents (26 chapters)
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1
Part 1: Code Optimization
7
Part 2: Memory Optimization and I/O Operations
11
Part 3: Concurrency and Networking
15
Part 4: Frameworks, Libraries, and Profiling
19
Part 5: Advanced Topics

Low time complexity

Time complexity refers to the measure of the time efficiency of any given algorithm. We want to determine the execution time of our Java applications and ensure our algorithms do not add time complexity to our applications. The overall goal is to reduce algorithm execution time. We should test our algorithms using a variety of possible inputs and environments.

In this section, we will look at specific strategies to help you reduce the time complexity of your algorithms. We will also address the common pitfalls associated with time complexity.

Strategies for reducing time complexity

There are several strategies we can adopt to help us reduce the time complexity of our algorithms. Perhaps the easiest strategy is to simply ensure our algorithms are not overly complicated. This strategy requires us to double-check our algorithmic logic and use the optimization techniques covered throughout this book. Reducing unnecessary calculations within a loop, especially...

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