Run benchmarks and update the results in the Javadoc of the benchmark classes:

mise run update-benchmarks

The full benchmark suite takes approximately 2 hours with JMH defaults. For faster iterations, use these preset configurations:

java -jar ./benchmarks/target/benchmarks.jar

Run only one specific benchmark:

java -jar ./benchmarks/target/benchmarks.jar CounterBenchmark

You can pass custom JMH arguments:

# Quick run: 1 fork, 1 warmup iteration, 3 measurement iterations
mise run update-benchmarks -- --jmh-args "-f 1 -wi 1 -i 3"

# Standard CI: 3 forks, 3 warmup iterations, 5 measurement iterations
mise run update-benchmarks -- --jmh-args "-f 3 -wi 3 -i 5"

JMH parameter reference:

• -f N: Number of forks (JVM restarts)
• -wi N: Number of warmup iterations
• -i N: Number of measurement iterations
• -w Ns: Warmup iteration time (default: 10s)
• -r Ns: Measurement iteration time (default: 10s)

See Javadoc of the benchmark classes:

• CounterBenchmark
• HistogramBenchmark
• TextFormatUtilBenchmark

concurrent updates of metrics in multi-threaded applications. If your application is single-threaded and uses only one processor core, your application isn't performance critical anyway. If your application is designed to use all available processor cores for maximum performance, then you want a metric library that doesn't slow your application down. Prometheus client Java metrics support concurrent updates and scrapes. This shows in benchmarks with multiple threads recording data in shared metrics.

To test the benchmark creation script, run:

python ./.mise/tasks/test_update-benchmarks.py

The src/main/archive/ directory contains the old benchmarks from 0.16.0 and earlier. It will be removed as soon as all benchmarks are ported to the 1.0.0 release.