JMH
jmh
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JMH | jmh | |
---|---|---|
3 | 26 | |
782 | 2,016 | |
0.1% | 5.1% | |
7.0 | 6.3 | |
5 days ago | 5 days ago | |
Scala | Java | |
Apache License 2.0 | GNU General Public License v3.0 only |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
JMH
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Scala collections benchmark - revisited
Also, it has an amazing SBT plugin integration.
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Why is Scala so much slower than JavaScript/Node at running iterations?
Take a look at sbt-jhm for doing benchmarks. Java in particular is hard to measure because of optimizations that happen at run-time. jhm runs multiple iterations and gives tools to ensure that function calls and loops that may be optimized away are kept around and tested. You may also find some cases that are faster in node.js because the Javascript V8 engine is highly optimized.
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Help with making backtracking more efficient
Also, if you really want to know what the performance characteristics are you should use JMH (sbt plugin https://github.com/sbt/sbt-jmh). Not sure how you are evaluating the performance but things like JVM startup and warming can make a big difference. JMH will give you a better idea of real world performance when the JVM is already started and any relevant hot code has been JIT compiled.
jmh
- Experimenting with GC-less (heap-less) Java
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Any library you would like to recommend to others as it helps you a lot? For me, mapstruct is one of them. Hopefully I would hear some other nice libraries I never try.
JMH for benchmarks
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Scala collections benchmark - revisited
I would recommend using JMH instead.
- What are some advantages to Java devs learning assembly?
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Is calling a method with reflection slower than calling a method normally? If so, by how much?
Reflection is probably very roughly between 10 and 1000 times slower. Why don't you measure it yourself using JMH?
- I benchmarked kotlin rust and go. The results will shock you , or not.
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Need help navigating the Java ecosystem (coming from C++)
Aleksey Shipilev is another such leader, whom is especially knowledgeable about the internals of the JVM. His writings are invaluable. He is (was) the lead of the Java microbenchmark framework (JMH} which is how one would write small performance experiments in Java, and learn what really makes a difference or now.
- Are Long better than Integer as keys for a Map?
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Threads vs Coroutines - ParallelMap Performance
In the last episode we implemented a parallelMap operation using streams, raw threads, a threadpool with futures, and coroutines. At first glance the raw threads was quickest, followed by futures, coroutines and then streams. In this, part 56 of an exploration of where a Test Driven Development implementation of the Gilded Rose stock control system might take us in Kotlin, we investigate the performance of the different functions further, in particular digging down into why coroutines seem to be slow and finding a way to speed them up. We also find a way to use a particular ForkJoinPool to run the streams code, making it as fast as the others (bar the raw threads). Frankly we only use very rough benchmarks here, with no statistical testing except 'it looks like'. That's OK for gross differences, but is highly suspect when deciding which of two similarly performant approaches is faster. For that check out JMH and you could watch my video from KotlinConf 2017
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Just another way to run JMH benchmark with Eclipse
A few months ago, we started to use JMH in our project to test and find performance issues. The tool provides multiple modes and profilers, and we found this useful for our purposes.
What are some alternatives?
JITWatch - Log analyser / visualiser for Java HotSpot JIT compiler. Inspect inlining decisions, hot methods, bytecode, and assembly. View results in the JavaFX user interface.
async-profiler - Sampling CPU and HEAP profiler for Java featuring AsyncGetCallTrace + perf_events [Moved to: https://github.com/async-profiler/async-profiler]
honest-profiler - A sampling JVM profiler without the safepoint sample bias
opentelemetry-java-instrumentation - OpenTelemetry auto-instrumentation and instrumentation libraries for Java
Sniffy - Sniffy - interactive profiler, testing and chaos engineering tool for Java
OpenJ9 - Eclipse OpenJ9: A Java Virtual Machine for OpenJDK that's optimized for small footprint, fast start-up, and high throughput. Builds on Eclipse OMR (https://github.com/eclipse/omr) and combines with the Extensions for OpenJDK for OpenJ9 repo.
LatencyUtils - Utilities for latency measurement and reporting
async-profiler - Sampling CPU and HEAP profiler for Java featuring AsyncGetCallTrace + perf_events
sbt-sonatype - A sbt plugin for publishing Scala/Java projects to the Maven central.
go - The Go programming language
jHiccup - jHiccup is a non-intrusive instrumentation tool that logs and records platform "hiccups" - including the JVM stalls that often happen when Java applications are executed and/or any OS or hardware platform noise that may cause the running application to not be continuously runnable.
Arthas - Alibaba Java Diagnostic Tool Arthas/Alibaba Java诊断利器Arthas