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My focus is on optimizing complex algorithms and on advanced topics such as concurrency, the Java memory model, and garbage collection. Here on HappyCoders.eu, I want to help you become a better Java programmer.Read more about me here. By the way, you can find out if code is running in a virtual thread with Thread.currentThread().isVirtual().

  • In the case of IO-work (REST calls, database calls, queue, stream calls etc.) this will absolutely yield benefits, and at the same time illustrates why they won’t help at all with CPU-intensive work .
  • The suspend method allows passing information from the yield point to the continuation , and back from the continuation to the suspension point .
  • Of those 30 threads, 12 are worker threads that are there by default when using Coroutines and 1 thread is marked “VirtualThread-unparker” while the rest are related to IntelliJ and / or VisualVM.
  • In this article we will discuss extensions to the PHP type system introduced in PHP 8, 8.1, and 8.2.
  • The actor encloses over mutable state , to which access is protected.

In this post, we looked at what Loom will possibly bring to a future version of Java. The project is still in preview, and the APIs can change before we see it in production. But it’s nice to explore the new APIs and see what performance improvements it already gives us. Each platform thread had to process ten tasks sequentially, each lasting about one second. Since running tests from a local machine to a remote server may include fluctuations caused by network or local machine issues , we are now going to test with two servers in the same network. Additionally, since Opencart was quite slow and easily saturated, let’s try this time with nginx default index site which should get us a really fast response time.

Indeed, to use virtual threads effectively, there is more unlearning than learning to be done. To create a platform thread , you need to make a system call, and these are expensive. To create a virtual thread, you don’t have to make any system call, making these threads cheap to make when you need them. Behind the scenes, the JVM created a few platform threads for the virtual threads to run on. Since we are free of system calls and context switches, we can run thousands of virtual threads on just a few platform threads. Our team has been experimenting with Virtual Threads since they were called Fibers.

Project Loom: Fibers and Continuations for the Java Virtual Machine

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. Virtual threads could be a no-brainer replacement for all use cases where you use thread pools today. This will increase performance and scalability in most cases based on the benchmarks out there. Structured concurrency can help simplify the multi-threading or parallel processing use cases and make them less fragile and more maintainable. On my machine, the process hung after 14_625_956 virtual threads but didn’t crash, and as memory became available, it kept going slowly.

It also creates some circularity when writing schedulers, that need to implement threads by assigning them to threads . This means that we would need to expose the fiber’s continuation for use by the scheduler. 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.

Project Loom

Virtual threads are a lightweight implementation of Java threads, delivered as a preview feature in Java 19. 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. I’m a freelance software developer with more than two decades of experience in scalable Java enterprise applications.

Java Loom Project and Virtual Threads

It might very well be that your use-case requires a shared-memory approach, but it might also be that message-passing offers a simpler and less error-prone solution. What lightweight threads buy us here is that we can call .get() when and if we need the results. But having an abstraction over a computation running in the background is still valid. Let’s see how we can implement a basic actor implementation using Loom. Of course, it will come nowhere near production-grade actor implementations like Akka, which includes features such as supervision, error handling, remoting, location transparency, and more.

4. Virtual Threads look Promising

A thread in Java is just a small wrapper around a thread that is managed and scheduled by the OS. Project Loom adds a new type of thread to Java called a virtual thread, and these are managed and scheduled by the JVM. With sockets it was easy, because you could just set them to non-blocking. However, operating systems also allow you to put sockets into non-blocking mode, which return immediately when there is no data available. And then it’s your responsibility to check back again later, to find out if there is any new data to be read. When you open up the JavaDoc of inputStream.readAllBytes() , 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.

Java Loom Project and Virtual Threads

Use of Virtual Threads clearly is not limited to the direct reduction of memory footprints or an increase in concurrency. The introduction of Virtual Threads also prompts a broader revisit of decisions made for a runtime when only Platform Threads were available. So far, we have only been able to overcome this problem with reactive programming, as provided by frameworks like RxJava and Project https://globalcloudteam.com/ Reactor. Every test uses a thread group duration of 5 mins and each configuration is executed 3 times to ignore any potential outlier. This has significantly changed since OpenJDK team has announced the inclusion of the first preview of project Loom in its upcoming JDK 19 . He is currently building an ecosystem of frameworks and libraries from scratch to power the tech behind Alumonium.

Quiltflower decompiler support

Also, starting a virtual thread is the same as we are used to doing with platform threads by calling the start() method. Let’s now run some tests experimenting with different loads and deployment scenarios and see what differences we see between virtual and platform threads. (Note – virtual threads are only available as a preview in Java 19, and there may well be further preview releases as the feature’s APIs and implementation are refined, and feedback from users is addressed). It was recently announced that virtual threads, a new JDK feature developed by the OpenJDK project Loom, will be available as a preview feature in the forthcoming Java 19 release. You can create VTs that do not support TLs, though, and we are working on alternatives to TL that are more VT-friendly.

Java Loom Project and Virtual Threads

An important note about Loom’s fibers is that whatever changes are required to the entire Java system, they are not to break existing code. As you can imagine, this is a fairly Herculean task, and accounts for much of the time spent by the people working on Loom. Loom is a newer project in the Java/JVM ecosystem that attempts to address limitations in the traditional concurrency model.

Project Loom: Threads Vs Virtual Threads

In particular, Loom offers a lighter alternative to threads along with new language constructs for managing them. In addition, Java 19 introduces the Executors.newThreadPerTaskExecutor method, which can take a ThreadFactory that builds virtual threads. It is suggested that there is no need to replace synchronized blocks and methods that are used infrequently (e.g., only performed at startup) or that guard in-memory operations. There are two specific scenarios in which a virtual thread can block the platform thread . Greater control over thread dumps, such as those produced by jcmd, is provided to filter out virtual threads, group related virtual threads together, or produce dumps in machine-readable formats that can be post-processed for better observability. Nearly all blocking points in the JDK were made aware of virtual threads, and will unmount a virtual thread rather than blocking it.

What about the Thread.sleep example?

However, the CPU would be far from being utilized since it would spend most of its time waiting for responses from the external services, even if several threads are served per CPU core. Let’s start with the challenge that led to the development of virtual threads. Since our first release of jmeter-java-dsl we have always had in mind to combine all the benefits of JMeter with the ones provided by other existing performance testing tools like Gatling, Taurus, k6, etc. Filling a gap that we thought, and have proven after interacting with the community, would be beneficial for anybody who wants to do performance testing. In any event, a fiber that blocks its underlying kernel thread will trigger some system event that can be monitored with JFR/MBeans.

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. Many uses of synchronized only protect memory access and block for extremely short durations — so short that the issue can be ignored altogether. Similarly, for the use of Object.wait, which isn’t common in modern code, anyway , which uses j.u.c. It is also possible to split the implementation of these two building-blocks of threads between the runtime and the OS. For example, modifications to the Linux kernel done at Google , allow user-mode code to take over scheduling kernel threads, thus essentially relying on the OS just for the implementation of continuations, while having libraries handle the scheduling. This has the benefits offered by user-mode scheduling while still allowing native code to run on this thread implementation, but it still suffers from the drawbacks of relatively high footprint and not resizable stacks, and isn’t available yet.

What about Reactive?

When run with an argument, the code in Listing 3 will use a virtual thread; otherwise it will use conventional threads. The program spawns 50 thousand iterations of whichever thread type you choose. Then, it does some simple math with random numbers and tracks how long the execution takes. A similar API Thread.ofPlatform() exists for creating platform threads as well. Virtual threads do not support the stop(), suspend(), or resume() methods. These methods throw an UnsupportedOperationException when invoked on a virtual thread.

For instance, in an existing Java application using platform threads, you can easily switch to using virtual threads by replacing new Thread invocations with something like Thread.ofVirtual(). No need to change IO (Input/Output) operations, locks, or sleeps, OpenJDK team has already taken care of all such methods. Internally, a virtual thread assigned/mounted to a platform thread is suspended/unmounted when such operations are invoked and then re-assigned when the operation ends. Additionally, exceptions, stack traces, debugging tools, and other existing tools work out of the box, no need to worry about callbacks, chains of flow calls and observers, use some specific IO or concurrency library/API, etc. In terms of basic capabilities, fibers must run an arbitrary piece of Java code, concurrently with other threads , and allow the user to await their termination, namely, join them. Obviously, there must be mechanisms for suspending and resuming fibers, similar to LockSupport’s park/unpark.

Choose your language

The trick virtual threads use to achieve their performance gain is to temporarily detach and park a virtual thread whenever it is blocked, so the same platform thread can be used to run another virtual thread. Blocking operations include a) I/O, b) when a thread is explicitly put to sleep, and c) when a thread enters a synchronized block. In the current implementation of virtual threads, there is a limitation such that if a virtual thread is executing code in a synchronized block, it cannot be detached from its carrier platform thread – the virtual thread said to be ‘pinned’.

Libraries may also need to adjust their use of ThreadLocal in light of virtual threads. But the calculus changes dramatically with a few million threads that each only perform a single task, because there are potentially many more instances allocated and there is much java enhancement proposals pursue virtual threads less chance of each being reused. Using a ThreadLocal to amortize the creation cost of a costly resource across multiple tasks that may execute in the same thread is an ad-hoc form of pooling; if these things need to be pooled, they should be pooled explicitly.