Efficient and accurate stack trace sampling in the Java hotspot virtual machine

Peter Hofer, H. Mössenböck
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引用次数: 5

Abstract

Sampling is a popular approach to collecting data for profiling and monitoring, because it has a small impact on performance and does not modify the observed application. When sampling stack traces, they can be merged into a calling context tree that shows where the application spends its time and where performance problems lie. However, Java VM implementations usually rely on safepoints for sampling stack traces. Safepoints can cause inaccuracies and have a considerable performance impact. We present a new approach that does not use safepoints, but instead relies on the operating system to take snapshots of the stack at arbitrary points. These snapshots are then asynchronously decoded to call traces, which are merged into a calling context tree. We show that we are able to decode over 90% of the snapshots, and that our approach has very small impact on performance even at high sampling rates.
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在Java热点虚拟机中高效准确的堆栈跟踪采样
抽样是为分析和监视收集数据的常用方法,因为它对性能的影响很小,而且不会修改观察到的应用程序。在对堆栈跟踪进行采样时,它们可以合并到一个调用上下文树中,该树显示应用程序在哪里花费时间以及性能问题在哪里。然而,Java VM实现通常依赖于安全点来采样堆栈跟踪。安全点可能导致不准确,并对性能产生相当大的影响。我们提出了一种新的方法,它不使用安全点,而是依赖于操作系统在任意点对堆栈进行快照。然后将这些快照异步解码为调用跟踪,并将其合并到调用上下文树中。我们表明,我们能够解码超过90%的快照,并且即使在高采样率下,我们的方法对性能的影响也很小。
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