scala-bench
jmh
scala-bench | jmh | |
---|---|---|
1 | 26 | |
0 | 2,034 | |
- | 3.1% | |
0.0 | 6.3 | |
about 1 year ago | 6 days ago | |
Scala | Java | |
- | GNU General Public License v3.0 only |
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scala-bench
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Scala collections benchmark - revisited
Source code: https://github.com/scf37/scala-bench
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?
JMH - "Trust no one, bench everything." - sbt plugin for JMH (Java Microbenchmark Harness)
async-profiler - Sampling CPU and HEAP profiler for Java featuring AsyncGetCallTrace + perf_events [Moved to: https://github.com/async-profiler/async-profiler]
opentelemetry-java-instrumentation - OpenTelemetry auto-instrumentation and instrumentation libraries 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.
async-profiler - Sampling CPU and HEAP profiler for Java featuring AsyncGetCallTrace + perf_events
go - The Go programming language
Arthas - Alibaba Java Diagnostic Tool Arthas/Alibaba Java诊断利器Arthas
opentelemetry-java - OpenTelemetry Java SDK
jdk7u-jdk
JavaCPP - The missing bridge between Java and native C++
JNA - Java Native Access
compare-langs - Compare C/Java/Python Performance