Java Project Loom: Understand the new Java concurrency model

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• At this point, the carrier thread is free to run another virtual thread.
• In other words, it does not solve what’s known as the “colored function” problem.
• This will increase performance and scalability in most cases based on the benchmarks out there.
• The answer is both to make it easier for developers to understand, and to make it easier to move the universe of existing code.
• There’s nothing really exciting here, except from the fact that the foo function is wrapped in a continuation.
• The name is up for discussion, but I prefer “fiber” since it nicely denotes the fact that multiple fibers execute in a carrier thread.
• The only thing these kernel threads are doing is actually just scheduling, or going to sleep, but before they do it, they schedule themselves to be woken up after a certain time.

It’s easy to see how massively increasing thread efficiency, and dramatically reducing the resource requirements for handling multiple competing needs, will result in greater throughput for servers. Better handling of requests and responses is a bottom-line win for a whole universe of existing and to-be-built Java applications. This hasn’t been an issue for me because it seems easier to use something threadsafe, like a java.time formatter. But Project Loom has been pondering “scope local” objects—one those FiberScope are reactivated. The first time you call get in a given thread, the lambda in the constructor is called. From then on, the get method returns the instance belonging to the current thread.

Notice the blazing fast performance of virtual threads that brought down the execution time from 100 seconds to 1.5 seconds with no change in the Runnable code. Similar to traditional threads, a virtual thread is also an instance of java.lang.Thread https://globalcloudteam.com/ that runs its code on an underlying OS thread, but it does not block the OS thread for the code’s entire lifetime. Keeping the OS threads free means that many virtual threads can run their Java code on the same OS thread, effectively sharing it.

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Platform threads have always been easy to model, program and debug because they use the platform’s unit of concurrency to represent the application’s unit of concurrency. If you are doing the actual debugging, so you want to step over your code, you want to see, what are the variables? Because when your virtual thread runs, it’s a normal Java thread. It’s a normal platform thread because it uses carrier thread underneath.

In this article, author discusses data pipeline and workflow scheduler Apache DolphinScheduler and how ML tasks are performed by Apache DolphinScheduler using Jupyter and MLflow components. And so, even if we try to change the priority of a virtual thread, it will stay the same. The current implementation of light threads available in the OpenJDK build of the JDK is not entirely complete yet, but you can already have a good taste of how things will be shaping up. Note that the part that changed is only the thread scheduling part; the logic inside the thread remains the same. You can learn more about reactive programming here and in this free e-book by Clement Escoffier.

This article discusses the problems in Java’s current concurrency model and how the Java project Loom aims to change them. We also explored the tasks and schedulers in threads and how Fibers Class and pluggable user-mode schedulers can be an excellent alternative for traditional threads in project loom java Java. When these features are production ready, it should not affect regular Java developers much, as these developers may be using libraries for concurrency use cases. But it can be a big deal in those rare scenarios where you are doing a lot of multi-threading without using libraries.

a. Pluggable user-mode scheduler

Apart from Loom, the focus of this article, you should also keep an eye on Valhalla, which might double the performance of Java on some cases, and Graal, which does so many things that I don’t even know where to start! And of course, the language is becoming less verbose, thanks to Amber. One of the main goals of Project Loom is to actually rewrite all the standard APIs. For example, socket API, or file API, or lock APIs, so lock support, semaphores, CountDownLatches.

It came as a surprise to me that one of the pain points for the Project Loom implementors are ThreadLocal variables, as well as more esoteric things—context class loaders, AccessControlContext. I had no idea so much was riding along on threads. The Summer 2019 Project Loom API tackled cancellation.

It is not meant to be exhaustive, but merely present an outline of the design space and provide a sense of the challenges involved. We will call that feature unwind-and-invoke, or UAI. It is not the goal of this project to add an automatic tail-call optimization to the JVM.

Structured Concurrency

It is, in fact, expected to serve every user with a dedicated thread. Many of these threads might execute network operations , and these network operations are synchronous. We might serve a million of users with one machine with a lot of RAM, using simple, synchronous, network operations. It’s a very interesting language, much older than Java, with some shortcomings but also some impressive features. Erlang has native support for green threads, and in fact, the VM counts the operations and switch between green threads every now and then.

Indeed, some languages and language runtimes successfully provide a lightweight thread implementation, most famous are Erlang and Go, and the feature is both very useful and popular. One of Java’s most important contributions when it was first released, over twenty years ago, was the easy access to threads and synchronization primitives. Java threads provided a relatively simple abstraction for writing concurrent applications. A mismatch in several orders of magnitude has a big impact.

Continuation is a programming construct that was put into the JVM, at the very heart of the JVM. There are actually similar concepts in different languages. Continuation, the software construct is the thing that allows multiple virtual threads to seamlessly run on very few carrier threads, the ones that are actually operated by your Linux system.

Fibers

We can use the Thread.Builder reference to create and start multiple threads. Second good news, project loom allows you to spawn light thread at will, without the need to be worried about blacking out resources. Virtual Threads are actually well managed, and don’t crash the virtual machine by using too much resources, and so the ALTMRetinex filter processing finished.

Then we move on, and in line five, we run the continuation once again. Not really, it will jump straight to line 17, which essentially means we are continuing from the place we left off. Continuations are actually useful, even without multi-threading. The new java method from project loom to start a virtual thread is ..

These are all features or frameworks like Reactor, or Akka, or Akka streams, whatever, which are not addressed by Loom because Loom is actually quite low level. After all, it’s just a different way of creating threads. Continuations that you see in here are actually quite common in different languages.

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It voluntarily says that it no longer wishes to run because we asked that thread to sleep. Unparking or waking up means basically, that we would like ourselves to be woken up after a certain period of time. Before we put ourselves to sleep, we are scheduling an alarm clock. It will continue running our thread, it will continue running our continuation after a certain time passes by. In between calling the sleep function and actually being woken up, our virtual thread no longer consumes the CPU.

The call scope.close() blocks until all fibers finish. Once the scope is closed, you know for sure that the fibers have finished. As we want fibers to be serializable, continuations should be serializable as well. If they are serializable, we might as well make them cloneable, as the ability to clone continuations actually adds expressivity . Fibers are, then, what we call Java’s planned user-mode threads. This section will list the requirements of fibers and explore some design questions and options.

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If you have 4 physical threads, or platform threads doing that, you’re essentially just maxing your CPU. If instead you create 4 virtual threads, you will basically do the same amount of work. It doesn’t mean that if you replace 4 virtual threads with 400 virtual threads, you will actually make your application faster, because after all, you do use the CPU. There’s not much hardware to do the actual work, but it gets worse. Because if you have a virtual thread that just keeps using the CPU, it will never voluntarily suspend itself, because it never reaches a blocking operation like sleeping, locking, waiting for I/O, and so on.

A point to be noted is this suspension or resuming occurs in the application runtime instead of the OS. As a result, it prevents the expensive context switch between kernel threads. These threads cannot handle the level of concurrency required by applications developed nowadays.

Getting started with GraalVM

Fibry is my Actor System, designed to be small, flexible, simple-to-use, and, of course, take advantage of Loom. It works with any version of Java, starting from Java 8 onwards, and it has no dependencies, except requires Loom to use fibers. Actors are used in a multi-threaded environment to achieve concurrency in a relatively simple way. In particular, actors are single-threaded, so you do not have concurrency issue by definition, as long as they operate only on their state; you can alter the state of an actor sending messages to it. For years, we have been told that scalable servers require asynchronous operations, but that’s not completely true.