async-profiler
JDK
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async-profiler | JDK | |
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10 | 191 | |
7,112 | 18,393 | |
2.8% | 2.4% | |
8.7 | 10.0 | |
11 days ago | 5 days ago | |
C++ | 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.
async-profiler
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JVM Profiling in Action
We'll use async-profiler and flame graphs for profiling. To simplify the process, we'll run the code using JBang.
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The Return of the Frame Pointers
JIT'ed code is sadly poorly supported, but LLVM has had great hooks for noting each method that is produced and its address. So you can build a simple mixed-mode unwinder, pretty easily, but mostly in process.
I think Intel's DNN things dump their info out to some common file that perf can read instead, but because the *kernels* themselves reuse rbp throughout oneDNN, it's totally useless.
Finally, can any JVM folks explain this claim about DWARF info from the article:
> Doesn't exist for JIT'd runtimes like the Java JVM
that just sounds surprising to me. Is it off by default or literally not available? (Google searches have mostly pointed to people wanting to include the JNI/C side of a JVM stack, like https://github.com/async-profiler/async-profiler/issues/215).
- FLaNK Stack 29 Jan 2024
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Tracking Java Native Memory with JDK Flight Recorder
debugging native calls in itself is also painful. I have switched to using async-profiler (https://github.com/async-profiler/async-profiler) instead of JFR for most of my usecases.
A. it tracks native calls by default
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Show HN: Javaflame – Simple Flamegraph for your Java application
https://github.com/async-profiler/async-profiler#flame-graph...
Ok, Windows is not supported. But IntelliJ made a fork which works on Windows.
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Lettuce (Redis) + Mybatis (MySQL) take up most of the CPU in production - Is it normal? Did you observe that in your environment? Any ways to optimize it?
Hi, today I used async-profiler to check the CPU usage of my Spring Boot app (just a normal backend) in production. Surprisingly, Lettuce (Redis) + Mybatis (MySQL) take up most of the CPU time. I am not talking about wall time here, but CPU time, since I know database requests need to wait for milliseconds and thus wall time will be very long. Therefore, I wonder:
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A question about Http4s new major version
You can use async-profiler to see what is happening under the hood.
- Reducing code size in (Rust) librsvg by removing an unnecessary generic struct
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what is your favorite programming trick/tool that not many People know about?
I have used visual vm quite a bit. https://github.com/async-profiler/async-profiler is also amazing... Throw the binary on the system and fire it up. It also profiles down into native code as well if you do that kind of thing.
JDK
- JEP draft: Exception handling in switch
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Java 23: The New Features Are Officially Announced
Completely gutted from the OpenJDK, last I checked. See here for the culprit PR: https://github.com/openjdk/jdk/pull/18688
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macOS 14.4 might break Java on your machine
> Yes, they're changing one aspect of signal handler use to work around this problem. They're not stopping the use of signal handlers in general. Hotspot continues to use signals for efficiency in general. See https://github.com/openjdk/jdk/blob/9059727df135dc90311bd476...
This whole thread is about SIGSEGV, and specifically their SIGSEGV handling. However, catching normal signals is not about efficiency.
Some of their exception handling is still odd: There is no reason for a program that receives SIGILL to ever attempt continuing. But others is fine, like catching SIGFPE to just forward an exception to the calling code.
(Sure, you could construct an argument to say that this is for efficiency if you considered the alternative to be implementing floating point in software so that all exceptions exist in user-space, but hardware floating point is the norm and such alternative would be wholly unreasonable.)
> The wonderful thing about choosing not to care about facts is having whatever opinions you want.
I appreciate the irony of you making such statement, proudly thinking that your opinion equals fact, and therefore any other opinion is not.
This discussion is nothing but subjective opinion vs. subjective opinion. Facts are (hopefully, as I can only speak for myself) inputs to both our opinions, but no opinion about "good" or "bad", "nasty" or not can ever be objective. Objective code quality does not exist.
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The Return of the Frame Pointers
I remember talking to Brendan about the PreserveFramePointer patch during my first months at Netflix in 2015. As of JDK 21, unfortunately it is no longer a general purpose solution for the JVM, because it prevents a fast path being taken for stack thawing for virtual threads: https://github.com/openjdk/jdk/blob/d32ce65781c1d7815a69ceac...
- JDK-8180450: secondary_super_cache does not scale well
- The One Billion Row Challenge
- AVX2 intrinsics for Arrays.sort methods (int, float arrays)
- A gentle introduction to two's complement
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Java JEP 461: Stream Gatherers
Map doesn't implement the Collection interface.
https://github.com/openjdk/jdk/blob/master/src/java.base/sha...
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C++23: Removing garbage collection support
C++ lets you write anything you can imagine, and the language features and standard library often facilitate that. The committee espouses the view that they want to provide many "zero [runtime] cost," abstractions. Anybody can contribute to the language, although the committee process is often slow and can be political, each release the surface area and capability of the language gets larger.
I believe Hazard Pointers are slated for C++26, and these will add a form "free later, but not quite garbage collection" to the language. There was a talk this year about using hazard pointers to implement a much faster std::shared_ptr.
It's a language with incredible depth because so many different paradigms have been implemented in it, but also has many pitfalls for new and old users because there are many different ways of solving the same problem.
I feel that in C++, more than any other language, you need to know the actual implementation under the hood to use it effectively. This means knowing not just what the language specifies, but can occaissionally require knowing what GCC or Clang generate on your particular hardware.
Many garbage collected languages are written in or have parts of their implementations in C++. See JS (https://github.com/v8/v8)and Java GC (https://github.com/openjdk/jdk/tree/36de19d4622e38b6c00644b0...)
I am not an expert on Java (or C++), so if someone knows better or can add more please correct me.
What are some alternatives?
jmh - https://openjdk.org/projects/code-tools/jmh
Graal - GraalVM compiles Java applications into native executables that start instantly, scale fast, and use fewer compute resources 🚀
container-jfr - Secure JDK Flight Recorder management for containerized JVMs
aircraft - The A32NX & A380X Project are community driven open source projects to create free Airbus aircraft in Microsoft Flight Simulator that are as close to reality as possible.
jfr-libraries - a list of libraries that generate JFR events
steam-runtime - A runtime environment for Steam applications
Arthas - Alibaba Java Diagnostic Tool Arthas/Alibaba Java诊断利器Arthas
OkHttp - Square’s meticulous HTTP client for the JVM, Android, and GraalVM.
opentelemetry-java-instrumentation - OpenTelemetry auto-instrumentation and instrumentation libraries for Java
kitten - A statically typed concatenative systems programming language.
junit-jfr - a JUnit 5 extension that generates JFR events
intellij-community - IntelliJ IDEA Community Edition & IntelliJ Platform