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forax loom-fiber: Continuation & Fiber examples using the OpenJDK project Loom prototype

One feature introduced by Project Loom is virtual threads. In this blog post, we’ll be exploring what virtual threads mean for web applications using some simple web applications deployed on Apache Tomcat. So in a thread-per-request model, the throughput will be limited by the number of OS threads available, which depends on the number of physical cores/threads available on the hardware. To work around this, you have to use shared thread pools or asynchronous concurrency, both of which have their drawbacks. Thread pools have many limitations, like thread leaking, deadlocks, resource thrashing, etc. Asynchronous concurrency means you must adapt to a more complex programming style and handle data races carefully.

Usually, it is the operating system’s job to schedule and manage threads depending on the performance of the CPU. This post looked at the benefits of structured concurrency to the Java language and how it is implemented in Loom. We went over how to create a scope for your threads and have them closed in a specific order. We also saw what happens when
one of the virtual threads in a scope throws an error. Surely you can use thread pools, but if you need to execute long operations this can be a problem, and in fact you might need to use asynchronous network operations to scale. Even a simple logic can be split in several callbacks and create endless issues.

Beyond virtual threads

They are lightweight and cheap to create, both in terms of memory and the time needed to switch contexts. In a JDK with virtual threads enabled, a java loom Thread instance can represent either a platform thread or a virtual one. The API is the same—but the cost of running each varies significantly.

This new class is used both to create Fiber and the ThreadFactory. Overall, a server can handle millions of concurrent open sockets. But the problem is that the current Java runtime limits the server to a few thousand concurrent open sockets.

Fibers: Virtual threads in Java

Very simple benchmarking on a Intel CPU (i5–6200U) shows half a second (0.5s) for creating 9000 threads and only five seconds (5s) for launching and executing one million virtual threads. Should you just blindly install the new version of Java whenever it comes out and just switch to virtual threads? You no longer have this natural way of throttling because you have a limited number of threads. Also, the profile of your garbage collection will be much different. It is too early to be considering using virtual threads in production but now is the time to include Project Loom and virtual threads in your planning so you are ready when virtual threads are generally available in the JRE. Loom is a newer project in the Java/JVM ecosystem (hosted by OpenJDK) that attempts to address limitations in the traditional concurrency model.

Virtual threads offer an exciting solution to improve performance and scalability for Spring developers. With little or no code changes required, it’s worth exploring how virtual threads can benefit your applications. Be sure to check out the Spring blog posts to learn more about embracing virtual threads and their performance analysis. Note that after using the virtual threads, our application may be able to handle millions of threads, but other systems or platforms handle only a few requests at a time. For example, we can have only a few database connections or network connections to other servers.

Featured in Culture & Methods

The answer is both to make it easier for developers to understand, and to make it easier to move the universe of existing code. For example, data store drivers can be more easily transitioned to the new model. Before looking more closely at Loom’s solution, it should be mentioned that a variety of approaches have been proposed for concurrency handling.

java loom

As it would be impossible to execute methods of the actor while blocking it,
a convenient synchronous actor can be used inside the transaction. Please check the unit tests for examples on how to use these transactions. Other than code simplicity, what’s really powerful here is a unified way of handing error scenarios of different executions running in the completely different (virtual or platform) threads.

Evolution of Concurrency in Java

«If you write code in this way, then the error handling and cancellation can be streamlined and it makes it much easier to read and debug.» Loom and Java in general are prominently devoted to building web applications. Obviously, Java is used in many other areas, and the ideas introduced by Loom may well be useful in these applications. 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.

  • With Structured concurrency, we want the same kind of rules as with structured programming.
  • «Leveraging that model, you could build apps that, in terms of utilizing resources, are on par with an asynchronous or reactive programming model,» he said.
  • Note that the following syntax is part of structured concurrency, another new feature proposed in Project Loom.
  • A thread supports the concurrent execution of instructions in modern high-level programming languages and operating systems.
  • Something that other languages like Go or Erlang had for years or decades.
  • I will not go into the API too much because it’s subject to change.

The moment the thread has to use I/O, the operating system tries to distribute the resources needed for this thread and to create another thread. Creating more threads enables the usage of resources simultaneously to perform more than just one task. In addition, the database drivers and drivers for other external services must also support the asynchronous, non-blocking model. https://www.globalcloudteam.com/ So far, we have only been able to overcome this problem with asynchronous programming – for example, with CompletableFuture or reactive frameworks like RxJava and Project Reactor. Instead, use semaphores to make sure only a specified number of threads are accessing that resource. Also, we have to adopt a new programming style away from typical loops and conditional statements.

Simple Git Hooks with Create React App, ESLint and Husky

In a way, from the kernel’s perspective, file operations never block in a way that socket operations do. And because of that, all kernel APIs for accessing files are ultimately blocking (in the sense we defined at the beginning). While this won’t let you avoid thread pinning, you can at least identify when it happens and if needed, adjust the problematic code paths accordingly. While Scoped Values is a brand new thing the two following features we’ll discuss are the Second Preview of Record Patterns and the Second Incubator of Structured Concurrency.

java loom

As we can see, using traditional threads created 10,000 system threads on my machine, while the same program using virtual threads created only 24 system threads. Virtual threads, as the primary part of the Project loom, are currently targeted to be included in JDK 19 as a preview feature. If it gets the expected response, the preview status of the virtual threads will then be removed by the time of the release of JDK21. With Structured concurrency, we want the same kind of rules as with structured programming.

User Threads and Kernel Threads

As far as JVM is concerned, they do not exist, because they are suspended. The results show that, generally, the overhead of creating a new virtual thread to process a request is less than the overhead of obtaining a platform thread from a thread pool. Still, while code changes to use virtual threads are minimal, Garcia-Ribeyro said, there are a few that some developers may have to make — especially to older applications. As mentioned, the new Fiber class represents a virtual thread. Why go to this trouble, instead of just adopting something like ReactiveX at the language level?

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