The programming model is much more intuitive than using classic threads and callbacks. For each created virtual thread, the JVM schedules its execution on a platform thread, temporarily copying the stack chunk for the virtual thread from the heap to the stack of the platform thread. We said that the platform thread java virtual threads becomes the carrier thread of the virtual thread. The problem with platform threads is that they are expensive from a lot of points of view. Whenever a platform thread is made, the OS must allocate a large amount of memory (megabytes) in the stack to store the thread context, native, and Java call stacks.

The following video shows how to test this application and, specifically, how to detect pinning. As of today, virtual threads are a preview API and disabled by default. Use $ java –source 19 –enable-preview Main.java to run the code. So we can say that virtual threads also improve the code quality by adapting the traditional syntax while having the benefits of reactive programming. 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.

Will your application benefit from Virtual Threads?

As expected, the two virtual threads share the same carrier thread. The two virtual threads run concurrently, and the main thread waits for them to terminate. We’ll explain all the information printed by the log in a while. For now, let’s focus solely on thread name and execution interleaving.

There are other ways of using Thread to spawn virtual threads, like Thread.ofVirtual().start(runnable). 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. One of the most far-reaching Java 19 updates is the introduction of virtual threads. Virtual threads are part of Project Loom, and are available in Java 19 as a preview.

No Time Slicing Between Virtual Threads

The minimum number of core threads not blocked allowed is half the pool size. The JVM maintains a pool of platform threads, created and maintained by a dedicated ForkJoinPool. Initially, the number of platform threads equals the number of CPU cores, and it cannot increase more than 256.

We are creating this task to keep the example simple so we can focus on the concept. Both threads seem to work in User Space and not in Kernel Space as Javas Native Threads do. See the Executors documentation for more about the executor methods. Listing 1 shows the changes I made to the Maven archetype’s POM file.

Playing with new features of Java 21

Also, synchronization and thread context copy should still be a problem of a similar size. Last, the method sets the runContinuation field, a Runnable object used to run the continuation. A virtual thread is mounted on its carrier thread when it is in the states colored green in the above diagram.

A virtual thread cannot run itself, but it stores the information of what must be run. In other words, it’s a pointer to the advance of an execution that can be yielded and resumed later. However, some scenarios could be help use something similar to ThreadLocal. For this reason, Java 20 will introduce scoped values, which enable the sharing of immutable data within and across threads.

All Tasks have to succeed if one fails there is no point in continuing

There will likely be far more virtual threads than threads in a thread pool, and now you have many more thread-local instances. The virtual thread scheduler mounts virtual threads onto carrier threads. By default, there are as many carrier threads as there are CPU cores. You can tune that count with the jdk.virtualThreadScheduler.parallelism VM option. When a result is not immediately available, you simply block in a virtual thread.

• Instead of passing the context from one method to another, the task code simply reads the thread-local variable whenever it needs to access the database.
• If you encounter specific issues in your own early experiments with Virtual Threads, please report them to the corresponding project.
• Both threads seem to work in User Space and not in Kernel Space as Javas Native Threads do.
• Now we will create 10,000 threads from this Runnable and execute them with virtual threads and platform threads to compare the performance of both.
• It just states that to scale up the throughput, we either have to proportionally scale down the latency or scale up the number of requests we can handle concurrently.
• The above example shows how we wrote concurrent programs that were constrained until now.

The methods for changing priority and daemon status are no-ops. The other primary way to start a virtual thread is with an executor. Executors are common in dealing with threads, offering a standard way to coordinate many tasks and thread pooling. For this demonstration, I’ve created a simple Java application with the Maven archetype. I’ve also made a few changes to enable virtual threads in the Java 19 preview.

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Note that in Java 21 [JEP-444], virtual threads now support thread-local variables all of the time. It is no longer possible, as it was in the preview releases, to create virtual threads that cannot have thread-local variables. Java thread pool was designed to avoid the overhead of creating new OS threads because creating them was a costly operation. But creating virtual threads is not expensive, so, there is never a need to pool them. It is advised to create a new virtual thread everytime we need one.

Spring Framework makes a lot of use of synchronized to implement locking, mostly around local data structures. Over the years, before Virtual Threads were available, we have revised synchronized blocks which might potentially interact with third-party resources, removing lock contention in highly concurrent applications. So Spring is in pretty good shape already owing to its large community and extensive feedback from existing concurrent applications. If one squints, the above behavior is not all that different from current scalable code that makes use of NIO channels and selectors – which can be found in many server-side frameworks and libraries. What is different with virtual threads is the programming model that is exposed to the developer.

3. Use ReentrantLock instead of Synchronized Blocks

Currently, we have no way of stopping a thread that no longer needs to run since its result became obsolete. We can only send the interrupt signal which eventually will be consumed and the thread stops. If function A calls function B and that is the last thing that A does then we can say that B is a continuation of A. It saves you the tedious boilerplate you have to write for chaining, subscribing, and managing the promises. Usually, you can mark a function as async and its result is internally wrapped in a promise. Unfortunately, because they were implemented as a separate class, it was very hard to migrate your whole codebase to it, and eventually, they disappeared and never got merged into the language.