Abstract Performance analysis of Java applications requires a deep understanding of the Java virtual machine and the system on which it is running. An unexpected latency can be caused by a bug in the source code, a misconfiguration or an external factor like CPU or disk contention. Existing tools have difficulties finding the root cause of some latencies because they do not efficiently collect performance data from the different layers of the system. In this paper, we propose a multilevel analysis framework that uses Kernel and userspace tracing to help developers understand and evaluate the performance of their applications. Kernel tracing is used to gather information about thread scheduling, system calls, I/O operations, etc. and userspace tracing is used to monitor the internal components of the JVM such as the garbage collectors and the JIT compilers. By bridging the gap between kernel and userspace traces, our tool provides full visibility to developers and helps them diagnose difficult performance issues. We show the usefulness of our approach by using it to detect problems in different Java applications.

中文翻译：

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基于内核和用户空间痕迹的Java虚拟机多层次分析

摘要 Java 应用程序的性能分析需要深入了解 Java 虚拟机及其运行的系统。意外延迟可能由源代码中的错误、配置错误或 CPU 或磁盘争用等外部因素引起。现有工具很难找到某些延迟的根本原因，因为它们不能有效地从系统的不同层收集性能数据。在本文中，我们提出了一个多级分析框架，该框架使用内核和用户空间跟踪来帮助开发人员了解和评估其应用程序的性能。内核跟踪用于收集有关线程调度、系统调用、I/O 操作等的信息。用户空间跟踪用于监视 JVM 的内部组件，例如垃圾收集器和 JIT 编译器。通过弥合内核和用户空间跟踪之间的差距，我们的工具为开发人员提供了全面的可见性，并帮助他们诊断困难的性能问题。我们通过使用它来检测不同 Java 应用程序中的问题来展示我们的方法的有用性。