Efficient and Accurate Stack Trace Sampling in the Java Hotspot Virtual Machine (Work In Progress Paper)

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.