This is an API for thread handling, which provides an approach for cooperating tasks (often virtual threads) to be considered and managed collectively as a collection of subtasks. Launching 9000 platform threads didn’t really show much difference, the run time was the same, but one million threads test took eleven seconds (11s) which is more than double the time compared to virtual threads. In comes Project Loom with virtual threads that become the single unit of concurrency. 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. First, I should say that what we’re talking about there is explicit tail-calls.
This new lightweight concurrency model supports high throughput and aims to make it easier for Java coders to write, debug, and maintain concurrent Java applications. 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. Depending on the web application, these improvements may be achievable with no changes to the web application code. The primary driver for the performance difference between Tomcat’s standard thread pool and a virtual thread based executor is contention adding and removing tasks from the thread pool’s queue. It is likely to be possible to reduce the contention in the standard thread pool queue, and improve throughput, by optimising the current implementations used by Tomcat. Currently, thread-local data is represented by the (Inheritable)ThreadLocal class(es).
Other Approaches
Topics include the differences between concurrency and parallelism; what virtual threads are; current issues with JVM concurrency; the Loom developer experience; pluggable schedulers; structured concurrency; and more. On one extreme, each of these cases will need to be made fiber-friendly, i.e., block only the fiber rather than the underlying kernel thread if triggered by a fiber; on the other extreme, all cases may continue to block the underlying kernel thread. In between, we may make some constructs fiber-blocking while leaving others kernel-thread-blocking. There is good reason to believe that many of these cases can be left unchanged, i.e. kernel-thread-blocking. For example, class loading occurs frequently only during startup and only very infrequently afterwards, and, as explained above, the fiber scheduler can easily schedule around such blocking.
At a high level, a continuation is a representation in code of the execution flow. In other words, a continuation allows the developer to manipulate the execution flow by calling functions. The Loom docs present the example seen in Listing 3, which provides a good mental picture of how this works. This model is fairly easy to understand in simple cases, and Java offers a wealth of support for dealing with it. The world of Java development is continually evolving, and Project Loom is just one example of how innovation and community collaboration can shape the future of the language.
Implementation
To remove the extension from Google Chrome, right-click on the Red Pinwheel Loom Logo and select Remove to delete it from your browser. Once the extension has been removed, you should restart your browser and download the latest Loom Google Chrome extension version. Should you still experience problems with the Loom Desktop Client, the next step is to see if the application requires an update.
Why go to this trouble, instead of just adopting something like ReactiveX at the language level? 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.
A Code-ful Goodbye to Dying Languages
During the lifetime of the run(…) call, the lambda expression, or any method called directly or indirectly from that expression, can read the scoped value via the value’s get() method. A good example of data you would like to store per request / per thread, access from different points in code, and destroy when loom java the thread gets destroyed is the user that initiated the web request. Conveniently you can store some data in the entry point of the request handler and use that data all across the workload of the request being executed without having to explicitly pass that data as a method argument across your codebase.
And this is actually how we’re supposed to write concurrent code, it’s just that we haven’t been doing the right thing because threads have been so costly. Now we need to go back and rethink how to program when threads aren’t cheap. So, it’s kind of funny, I say, in terms of project Loom, you don’t really need to learn anything new. For platform threads, you will use one of the thread pool executors.
Revolutionizing Concurrency in Java with a Friendly Twist
Parking (blocking) a virtual thread results in yielding its continuation, and unparking it results in the continuation being resubmitted to the scheduler. The scheduler worker thread executing a virtual thread (while its continuation is mounted) is called a carrier thread. To conclude this article, we should also point out that classes that represent continuations and other low-level building blocks for virtual threads and other components do exist in Java 21. However, they are in the package jdk.internal.vm and so are not intended for direct use by Java programmers as of this release. Prevalent issue with the current thread implementation is that it can limit the applications bandwidth to well below what the modern hardware can handle. Meaning in todays Java applications, especially web based software, what can cap your throughput is not CPU, memory or network but the amount of OS threads available to you, since Java threads directly wrap around operating system threads.
But, even if that were a win experienced developers are a rare(ish) and expensive commodity; the heart of scalability is really financial. We get the same behavior (and hence performance) as manually written asynchronous code, but instead avoiding the boiler-plate to do the same thing. A simple, synchronous web server will be able to handle many more requests without requiring more hardware.
Benefits of Lightweight Threads in Java
It allows you to gradually adopt fibers where they provide the most value in your application while preserving your investment in existing code and libraries. Even though good,old Java threads and virtual threads share the name…Threads, the comparisons/online discussions feel a bit apple-to-oranges to me. To cut a long story short, your file access call inside the virtual thread, will actually be delegated to a (….drum roll….) good-old operating system thread, to give you the illusion of non-blocking file access. When you open up the JavaDoc of inputStream.readAllBytes() (or are lucky enough to remember your Java 101 class), it gets hammered into you that the call is blocking, i.e. won’t return until all the bytes are read – your current thread is blocked until then.
- Usually, it is the operating system’s job to schedule and manage threads depending on the performance of the CPU.
- A blocking read or write is a lot simpler to write than the equivalent Servlet asynchronous read or write – especially when error handling is considered.
- Developers often grapple with complex and error-prone aspects of thread creation, synchronization, and resource management.
- But why would user-mode threads be in any way better than kernel threads, and why do they deserve the appealing designation of lightweight?
- And if you have a million threads, it’s nicer to give the users a very clear mechanism of let’s say herding them.
- First and foremost, fibers are not tied to native threads provided by the operating system.
Simply put the idea is to bring the simplicity of single-threaded code to the multi-threaded workflows when possible. Another possible solution is the use of asynchronous concurrent APIs. CompletableFuture and RxJava are quite commonly used APIs, to name a few.
What does this mean to Java library developers?
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. To cater to these issues, the asynchronous non-blocking I/O were used. The use of asynchronous I/O allows a single thread to handle multiple concurrent connections, but it would require a rather complex code to be written to execute that. Much of this complexity is hidden from the user to make this code look simpler.
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