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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

Future trends in Java profiling

The software development landscape is ever-shifting, and profiling tools and techniques are equally dynamic. As technological innovations emerge, so do tools to help developers address and manage them. This final section explores future trends in Java profiling, with a focus on profiling tools and integration with AI and ML. The section ends with a list of emerging standards and best practices.

Advances in profiling tools

Current profiling tools continue to be improved, with new versions frequently being released. It is also common for new profiling tools to be introduced periodically. The key advancements with profiling tools are in the following five areas:

  • Improved user interfaces: We should see more intuitive interfaces and better visualizations.
  • Cloud-native profiling: Cloud computing and distributed computing are the norm, and profiling tools are apt to cater to these environments to a greater extent.
  • Enhanced real-time profiling...
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High Performance with Java
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