Angielski
Modern multicore processors offer immense opportunities to improve Java performance, but they also make Java performance tuning more complex than ever. Java Performance Companion helps you systematically improve Java performance by taking a proactive approach: identifying optimization opportunities, experimenting and accurately interpreting your results, and taking effective action. World-class Java performance experts present detailed information on common top-down (application-centric) tuning and bottom-up (hardware/OS centric) approaches, with solid coverage of Windows, Linux, and Solaris. They show how to improve performance by applying state-of-the-art software engineering practices, and how to avoid common mistakes that can mislead you into writing poorly performing software. Throughout, you'll find dozens of Java performance tips and tricks available nowhere else. Key topics include: * Monitoring Java performance at the OS level in Windows, Linux, and Oracle Solaris environments * Going under the hood with G1 and understanding it in unprecedented depth * Using modern Java Virtual Machine (JVM) and OS observability tools to profile running systems with almost no performance penalty * Integrating JVM-level and application monitoring * Mastering Java method and heap (memory) profiling * Tuning the Java HotSpot VM for startup, memory footprint, response time, and latency * Optimizing modern JVM JIT compilers * Using the HotSpot serviceability agent * Using Java Mission Control to improve latency, throughput, and footprint * Triaging JVM issues with the Serviceability Agent * Implementing best performance practices for using / writing Java Lambdas * Achieving optimal performance with dynamic languages on the JVM * Utilizing the newest Oracle and third-party tools for monitoring and measuring performance on diverse hardware architectures and operating systems Java Performance Companion can help you squeeze maximum performance and value from all your Java applications - no matter how complex they are, what platforms they're running on, or how long you've been running them.
