The Generational Z Garbage Collector (ZGC)

The Generational Z Garbage Collector (GenZGC) in JDK 21 represents a significant evolution in Java’s approach to garbage collection, aiming to enhance application performance through more efficient memory management. This advancement builds upon the strengths of the Z Garbage Collector (ZGC) by introducing a generational approach to garbage collection within the JVM.

Design Rationale and Operational Mechanics

Generational Hypothesis: Generational ZGC leverages the “weak generational hypothesis,” which posits that most objects die young. By dividing the heap into young and old regions, GenZGC can focus its efforts on the young region where most objects become unreachable, thereby optimizing garbage collection efficiency and reducing CPU overhead

Heap Division and Collection Cycles: The heap is divided into two logical parts: the young generation and the old generation. Newly allocated objects are placed in the young generation, which is frequently scanned for garbage collection. Objects that survive several collection cycles are then promoted to the old generation, which is scanned less often. This division allows for more frequent collection of short-lived objects while reducing the overhead of collecting long-lived objects.

Performance Implications

Throughput and Latency Internal performance tests have shown that Generational ZGC offers about a 10% improvement in throughput over its single-generation predecessors in both JDK 17 and JDK 21, despite a slight regression in average latency measured in microseconds. However, the most notable improvement is observed in maximum pause times, with a 10-20% improvement in P99 pause times. This reduction in pause times significantly enhances the predictability and responsiveness of applications, particularly those requiring low latency.

Allocation Stalls

A crucial advantage of Generational ZGC is its ability to mitigate allocation stalls, which occur when the rate of object allocation outpaces the garbage collector’s ability to reclaim memory. This capability is particularly beneficial in high-throughput applications, such as those using Apache Cassandra, where Generational ZGC maintains performance stability even under high concurrency levels.

Practical Considerations and Adoption

Transition and Adoption: While JDK 21 introduces Generational ZGC, single-generation ZGC remains the default for now. Developers can opt into using Generational ZGC through JVM arguments (`-XX:+UseZGC -XX:+ZGenerational`). The plan is for Generational ZGC to eventually become the default, with single-generation ZGC being deprecated and removed. This phased approach allows developers to gradually adapt to the new system.

Diagnostic and Profiling Tools: For those evaluating or transitioning to Generational ZGC, tools like GC logging and JDK Flight Recorder (JFR) offer valuable insights into GC behavior and performance. GC logging, accessible via the `-Xlog` argument, and JFR data can be analyzed in JDK Mission Control (JMC) to assess garbage collection behavior and application performance implications.

Conclusion

Generational ZGC represents a significant step forward in Java’s garbage collection technology, offering improved throughput, reduced pause times, and enhanced overall application performance. Its design reflects a deep understanding of application memory management needs, particularly the efficient collection of short-lived objects. As Java applications continue to grow in complexity and scale, the adoption of Generational ZGC could be a pivotal factor in achieving the performance goals of modern, high-demand applications.

The transition from Java 17 to Java 21 heralds a new era of Java development, characterized by significant improvements in performance, security, and developer-friendly features. The API changes and enhancements discussed above are just the tip of the iceberg, with Java 21 offering a wealth of other features and improvements designed to cater to the evolving needs of modern application development.  As developers, embracing Java 21 and leveraging its new features and improvements can significantly impact the efficiency, performance, and security of Java applications. Whether it’s through the enhanced I/O capabilities, improved serialization exception handling, or the new Unicode support in the `Character` class, Java 21 offers a compelling upgrade path from Java 17, promising to enhance the Java ecosystem for years to come.  In conclusion, the evolution from Java 17 to Java 21 is a testament to the ongoing commitment to advancing Java as a language and platform. By exploring and adopting these new features, developers can ensure their Java applications remain cutting-edge, secure, and performant in the face of future challenges.

Alexius Dionysius Diakogiannis

Passionate Archer, Runner, Linux lover and JAVA Geek! That's about everything! Alexius Dionysius Diakogiannis is a Senior Java Solutions Architect and Squad Lead at the European Investment Bank. He has over 20 years of experience in Java/JEE development, with a strong focus on enterprise architecture, security and performance optimization. He is proficient in a wide range of technologies, including Spring, Hibernate and JakartaEE. Alexius is a certified Scrum Master and is passionate about agile development. He is also an experienced trainer and speaker, and has given presentations at a number of conferences and meetups. In his current role, Alexius is responsible for leading a team of developers in the development of mission-critical applications. He is also responsible for designing and implementing the architecture for these applications, focusing on performance optimization and security.