Performance Analysis of Modern Garbage Collectors using Big Data Benchmarks in the JDK 20 Environment

Garbage collection is a fundamental aspect of Java Virtual Machine (JVM) memory management, and choosing the optimal garbage collector is essential for attaining optimal application performance. In this work, we conduct experiments with the big data benchmarks from DaCapo and Renaissance benchmark suites in both fixed and variable heap environments to determine the efficacy of JDK 20's garbage collectors. The ZGC algorithm has the highest throughput and the shortest pause periods, whereas the Serial GC algorithm has the lowest throughput and the longest pause intervals. Additionally, it is discovered that the G1 algorithm manages the previous generation heap and metaspace less efficiently. Our work offers valuable insights into the efficacy of garbage collection algorithms and can aid application developers in selecting the optimal garbage collection algorithm. Our investigation can be expanded by analyzing additional benchmark suites and garbage collection algorithms across a broader range of heap sizes in future work.