Application performance problems often stem from critical process failures, which are particularly prominent in Java applications. Effective performance monitoring and tuning are critical to the stable operation of the system, and garbage collection (GC) logs are a key source of information for diagnosing and solving performance bottlenecks.
Deep in Java advanced GC technology
GC monitoring and tuning are not difficult, but it requires a deep understanding of the GC mechanism and JVM memory model. This includes obtaining and analyzing GC logs, adjusting JVM parameters based on log information, and selecting appropriate GC algorithms.
The main GC algorithms in Java:
- Serial GC: Single threaded GC, all other threads will be suspended during GC. The default algorithm before Java 4.
- Parallel GC: multi-threaded GC, some tasks are executed concurrently with application threads. Java 5 introduced.
- CMS (Concurrent Tag Scan): Performs most GC tasks concurrently with application threads, but there is a fragmentation problem. Deprecated.
- G1: The default algorithm of later versions of Java, most of the work is carried out concurrently and efficiently.
- ZGC: Optimized for large-scale memory scenarios, based on G1 improvements.
- Shenandoah: Similar to G1, improving performance in large memory scenarios.
- Epsilon: Mainly used to benchmark other GC algorithms.
Obtain and analyze GC logs
GC logs can be obtained through JVM parameters. Java 8 and below use -XX: PrintGCDetails -Xloggc:<gc-log-file-path></gc-log-file-path>
;Java 9 and above use -Xlog:gc*:file=<gc-log-file-path></gc-log-file-path>
.
Manually analyzing GC logs is time-consuming and labor-intensive. It is recommended to use tools such as Gceasy, which can quickly generate statistics, charts and tuning suggestions.
Key Performance Indicators:
- Throughput: The percentage of application runtime as total time. Critical systems should strive for more than 98% of the throughput.
- Delay: The time when the application thread is suspended due to GC. Focus on maximum and average latency.
- Memory usage: The amount of resources used by GC.
GC Logging Best Practices
- Regularly monitor GC logs to detect problems early.
- GC logging is always enabled in production environments.
- Monitor for at least 24 hours to observe GC behavior under different loads.
- Choose the right GC algorithm.
- Avoid using too many GC log parameters on the command line.
- Use a suffix with a timestamp (such as
%t
) to avoid log rotation causing information loss. - Use the appropriate tools to analyze the logs and take action based on the results.
GC algorithm tuning
The JVM provides a variety of parameters for tuning, such as:
- Resize the heap.
- Adjust the size ratio of the new generation/older generation.
- Control the speed at which the object is promoted to the elderly.
- Adjust the memory ratio of GC recycled.
- Adjust the number of concurrent and parallel GC threads.
- Enable or disable string deduplication.
- Change the GC algorithm.
Hardware upgrades may be required when resources are insufficient. Regular monitoring of GC logs helps to plan ahead. Code refactoring can also improve memory management. The tuning strategies of different GC algorithms are different, please refer to the relevant documents.
Summarize
Understanding Java garbage collection is essential to maintain application performance, especially in critical systems. Simple GC tuning can bring significant performance improvements. Effective GC management can also reduce resource costs in cloud environments. Continuous learning and practical performance tuning techniques will help improve system efficiency.
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