JetBrainsRuntime VS Netty

Here you can see the work being done on IntelliJ Wayland:

https://github.com/JetBrains/JetBrainsRuntime/issues/242

https://youtrack.jetbrains.com/issue/JBR-3206/Native-Wayland...

JetBrains have their tweaks to the JRE available: https://github.com/JetBrains/JetBrainsRuntime

The major problems begin when you want to leverage the GPU or multimedia components in which case you would want something else.

Jetbrains Runtime – this is bundled with IntelliJ and Android Studio, but with patches focused on optimization for use within an Interactive Development Environment context – doing incremental builds, hot reload of class definition, and embedded Chromium in the runtime. I do not believe the added features are useful for building and archiving Android Applications for distribution, but it will work non-the-less.

https://github.com/JetBrains/JetBrainsRuntime

Also with 'Java on Truffle' on GraalVM you can use enhanced class reloading

However, I am running IntelliJ on Asahi since June already. They did not provide offical Linux arm64 support, but what since May, when they released the first 2022.2 EAP, they switched to JBR 17 (the JetBrains Java Runtime). JBR 17. Fortunatly, in May, they started to release JBR builds for Linux am64, starting with JBR 17.0.3-b463.3. That meant we had everything we needed to run IntelliJ on Asahi: I just had to set the env var IDEA_JDK=/path/to/arm64/jbr/ to make IntelliJ use the correct JBR. Besides that it was necessary to download a fsnotifier version that was build for arm64 and set the path in ~/.config/JetBrains/IntelliJIdea2022.3/idea.properties.

Have you tried the JetBrains Runtime with DCEVM? https://github.com/JetBrains/JetBrainsRuntime/releases/tag/jbr17.0.2b396.4

This project's key is replacing x86_64 Jetbrains Runtime (https://github.com/JetBrains/JetBrainsRuntime) to arm64 Jetbrains Runtime. Arctic Fox IntelliJ Core version is 2020.3.1, maybe google upgrade core version to 2021.1 as soon as possible. (IntelliJ Core version 2021.1 released at a few days ago.)

https://github.com/JetBrains/JetBrainsRuntime

Code of netty is here and using following library

We use Netty (https://netty.io/) as the source of the MQTT communication, and we build the MQTT features the MQTT broker should support ourselves on top of that.

In this space, we also have the somewhat related term blocking. Java's NIO library is one well-known non-blocking tool used for managing multiple tasks on a single Java thread. When listening to sockets, most of the time a thread is just blocked, doing nothing until it receives some data. So, it's efficient to use a single thread for monitoring many sockets, to increase the likelihood of the thread having some actual work to do. The Selector API does this but is notoriously challenging to program well. Instead, developers use frameworks like Netty which abstract some of NIO's complexity and layer on some best practices.

DirectByteBuffer exhibits an intriguing behavior: it deallocates its backing memory during the finalization process, which occurs after garbage collection (GC) cycles. This poses an issue if your system is conservative with on-heap allocations, leading to infrequent GC cycles. In such cases, there could be a significant delay between the time the memory becomes unreferenced and when it is actually deallocated. This behavior could, in some respects, mimic a memory leak.

This is why some libraries hacks into DirectByteBuffer to deallocate memory explicitly, bypassing the finalizer altogether. For instance, the Netty library has implemented such a workaround, see Netty as an [example](https://github.com/netty/netty/blob/795db4a866401aa172757b95...).

Apologies replying to myself, but Netty, which underpins many of the popular Java backend frameworks, see backward compatibility as more important than supporting green threads.

https://github.com/netty/netty/issues/12816

It'll be interesting to see who (if anyone) picks up Netty's mantle in the Project Loom world.

Looks fairly recent so I'm glad I had a pre oct22 build https://github.com/netty/netty/issues/12737

This is better? https://github.com/netty/netty/blob/4.1/pom.xml

Given the fact that Lettuce is built with Netty, we also immediately noticed quite an impact on the initialization time (cold start) of our lambda function. Netty is really fast while executing, but takes a bit of time to initialize. The new Lambda Snapstart functionality might help with that.