jmh
Disruptor
jmh | Disruptor | |
---|---|---|
26 | 30 | |
2,025 | 17,029 | |
2.7% | 0.4% | |
6.3 | 5.4 | |
3 days ago | 4 months ago | |
Java | Java | |
GNU General Public License v3.0 only | Apache License 2.0 |
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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.
Disruptor
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Gnet is the fastest networking framework in Go
https://lmax-exchange.github.io/disruptor/#_what_is_the_disr.... Unfortunately IIUC writing this in Go still prevents the spin-locked acceptor thread from achieving the kind of performance you could get in a non-GC language, unless you chose to disable GC, so I'd guess Envoy is still faster.
https://gnet.host/docs/quickstart/ it's nice that you can use this simply though. Envoy is kind of tricky to setup with custom filters, so most of the time it's just a standalone binary.
[0] https://blog.envoyproxy.io/envoy-threading-model-a8d44b92231...
[1] https://lmax-exchange.github.io/disruptor/#_what_is_the_disr...
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A lock-free ring-buffer with contiguous reservations (2019)
See also the Java LMAX Disruptor https://github.com/LMAX-Exchange/disruptor
I've built a similar lock-free ring buffer in C++11 https://github.com/posterior/loom/blob/master/doc/adapting.m...
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JEP Draft: Deprecate Memory-Access Methods in Sun.misc.Unsafe for Removal
"Why we chose Java for our High-Frequency Trading application"
https://medium.com/@jadsarmo/why-we-chose-java-for-our-high-...
LMAX Disruptor customers
https://lmax-exchange.github.io/disruptor/
Among many other examples.
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LMAX Disruptor – High Performance Inter-Thread Messaging Library
Current documentation
https://lmax-exchange.github.io/disruptor/
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Progress on No-GIL CPython
LMAX Disruptor has on their wiki that average latency to send a message from one thread to another at 53 nanoseconds. For comparison a mutex is like 25 nanoseconds and more if Contended but a mutex is point to point synchronization.
The great thing about it is that multiple threads can receive the same message without much more effort.
https://github.com/LMAX-Exchange/disruptor/wiki/Performance-...
https://gist.github.com/rmacy/2879257
I am dreaming of language that is similar to Smalltalk that stays single threaded until it makes sense to parallise.
I am looking for problems to parallelism that are not big data. Parallelism is like adding more cars to the road rather than increasing the speed of the car. But what does a desktop or mobile user need to do locally that could take advantage of the mathematical power of a computer? I'm still searching.
- Disruptor 4.0.0 Released
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Anything can be a message queue if you use it wrongly enough
Database config should be two connection strings, 1 for the admin user that creates the tables and anther for the queue user. Everything else should be stored in the database itself. Each queue should be in its own set of tables. Large blobs may or may not be referenced to an external file.
Shouldn't a message send be worst case a CAS. It really seems like all the work around garbage collection would have some use for in-memory high speed queues.
Are you familiar with the LMAX Disruptor? Is is a Java based cross thread messaging library used for day trading applications.
https://lmax-exchange.github.io/disruptor/
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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.
Disruptor for inter-thread messaging
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Measuring how much Rust's bounds checking actually costs
I have never worked in any industries where a perf margin was that small. It is funny, in HFT there are folks using Lmax (Java) and then you have folks writing their own TCP/IP stacks on FPGAs to do trading.
What are some alternatives?
async-profiler - Sampling CPU and HEAP profiler for Java featuring AsyncGetCallTrace + perf_events [Moved to: https://github.com/async-profiler/async-profiler]
JCTools
opentelemetry-java-instrumentation - OpenTelemetry auto-instrumentation and instrumentation libraries for Java
Agrona - High Performance data structures and utility methods 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.
fastutil - fastutil extends the Java™ Collections Framework by providing type-specific maps, sets, lists and queues.
async-profiler - Sampling CPU and HEAP profiler for Java featuring AsyncGetCallTrace + perf_events
MPMCQueue.h - A bounded multi-producer multi-consumer concurrent queue written in C++11
go - The Go programming language
Eclipse Collections - Eclipse Collections is a collections framework for Java with optimized data structures and a rich, functional and fluent API.
Arthas - Alibaba Java Diagnostic Tool Arthas/Alibaba Java诊断利器Arthas
Javolution