The Shenandoah garbage collector (GC) is an exciting addition to the Java Virtual Machine (JVM), designed to reduce pauses and improve overall application performance. However, to fully leverage its benefits, proper parameter tuning is essential. In this blog post, we will explore the different aspects of Shenandoah GC tuning and provide guidance for achieving optimal performance.
Table of Contents
- Introduction
- Understanding Shenandoah GC
- Tuning Shenandoah GC Parameters
- Monitoring and Iterative Tuning
- Conclusion
- References
Introduction
Garbage collection is a critical aspect of memory management in Java applications. While traditional garbage collectors such as the Concurrent Mark Sweep (CMS) and G1 GC have made significant improvements, they still suffer from noticeable pause times when cleaning up memory. Shenandoah GC aims to address this challenge by introducing concurrent processing of both marking and cleanup phases, leading to shorter and more predictable pause times.
Understanding Shenandoah GC
Before diving into parameter tuning, it’s important to understand the key components of Shenandoah GC. Here’s a brief overview:
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Concurrent marking: Shenandoah performs marking concurrently with the application threads, minimizing the pause time for marking.
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Scaling marking threads: Shenandoah allows configuring the number of threads used for concurrent marking. This helps achieve good throughput by utilizing multiple CPU cores effectively.
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Concurrent cleanup: Shenandoah performs cleanup concurrently with application threads, reducing the overall pause time.
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Region-based collection: Unlike traditional GCs that operate at the object or card level, Shenandoah divides the Java heap into regions, making it easier to manage and collect memory. Each region contains multiple objects, allowing for more efficient memory management.
Tuning Shenandoah GC Parameters
To optimize performance with Shenandoah GC, several important parameters need to be considered. Let’s explore them one by one:
Pause Time Goal
The PauseTimeGoal parameter determines the maximum desired pause time. It’s crucial to align this value with your application’s requirements. Setting this too low may increase garbage collection overhead, while setting it too high may result in longer pause times. It’s recommended to start with a conservative value and gradually adjust it based on application behavior.
-XX:ShenandoahPauseTimeGoal=<value>
Concurrent Threads
Shenandoah GC allows specifying the number of threads used for concurrent marking and cleanup. It’s crucial to set the right balance based on your hardware specifications and workload characteristics. Increasing the number of threads helps achieve better throughput but may increase CPU usage.
-XX:ShenandoahConcurrentGCThreads=<value>
Evacuation Failure Threshold
The EvacuationFailureThreshold parameter determines the evacuation failure percentage. When the evacuation failure percentage exceeds this threshold, Shenandoah GC will attempt to shrink the heap size. It’s essential to set an appropriate value based on your application to avoid frequent heap size adjustments.
-XX:ShenandoahGCHeuristics=evacuation-failure-threshold=<value>
Region Size
The RegionSize parameter defines the size of each region in Shenandoah GC. It plays a crucial role in GC overhead and pause times. Smaller regions lead to lower pause times but higher GC overhead, while larger regions have the opposite effect. Consider your application’s memory usage patterns and adjust this parameter accordingly.
-XX:ShenandoahRegionSize=<value>
Heap Size
The overall heap size is also an important parameter to consider. Shenandoah GC introduces some overhead compared to traditional collectors, so it’s recommended to increase the heap size accordingly. This helps ensure better garbage collection efficiency and reduces the frequency of GC cycles.
-Xmx<size>
Monitoring and Iterative Tuning
Once you have configured the initial set of parameters, it’s crucial to monitor the GC behavior and performance metrics. Tools like VisualVM, JConsole, or Grafana can help you analyze GC pauses, throughput, CPU utilization, and memory usage. Based on these observations, you can fine-tune the GC parameters iteratively until you achieve the desired performance.
Conclusion
Tuning Shenandoah GC parameters can significantly impact the performance of your Java applications. By adjusting parameters such as the pause time goal, concurrent threads, evacuation failure threshold, region size, and heap size, you can optimize the GC behavior to match your application’s requirements. Regular monitoring and iterative tuning are essential to achieve optimal performance.
References
#java #garbagecollector