java Using Virtual Threads Project Loom with Spring WebFlux Reactor Reactive libraries

Virtual threads are a powerful new feature in JDK 21 that allow developers to create lightweight threads that are managed by the JVM rather than the operating system. In other words, the mutiny environment is a safe environment for virtual threads. The only changes are in the way we define if a thread we create represents a virtual or platform thread.

With virtual thread, a program can handle millions of threads with a small amount of physical memory and computing resources, otherwise not possible with traditional platform threads. It will also lead to better-written programs when combined with structured concurrency. The idea behind this is to create a Java Thread that https://globalcloudteam.com/ is not attached to the platform thread. This virtual thread does not occupy OS resources and CPU until it needs to do so. However, when there is a long-running, CPU-intensive thread then it will pin to the platform thread and create a bottleneck. This is because virtual threads are not faster than standard threads.

Unleashing the Power of Lightweight Concurrency: A Comprehensive Guide to Java Virtual Threads (Part

Java has been a language that has tried to strive for simplicity since its inception. In concurrent programming, we should write programs as if they were sequential. In fact, the more straightforward way to write concurrent programs in Java is to create a new thread for every concurrent task.

They are not designed to speed up computation and gain low latency. The standard way of handling parallel and concurrency computations in Java is to use threads. While technically possible via some wizardry, its more straight forward in Java to make a helper method.

Virtual threads architecture

Listing 1 shows the changes I made to the Maven archetype’s POM file. Note that I also set the compiler to use Java 19 and added a line to the .mvn/jvm.config. The stream decoders and encoders used by InputStreamReader and OutputStreamWriter now use the same lock as the enclosing InputStreamReader or OutputStreamWriter. In a future release we may be able to remove the first limitation above, namely pinning inside synchronized. The second limitation is required for proper interaction with native code.

• In this scenario thread pool limit and vertx worker pool size were both set to 10 threads.
• One of them creates a traditional platform thread by using Thread.Builder.ofPlatform() method.
• This ForkJoinPool is distinct from the common pool which is used, for example, in the implementation of parallel streams, and which operates in LIFO mode.
• Until the common backend frameworks support virtual threads, we will have to be patient for a while.
• That’s the recommend first step to start using Virtual Threads if using the Executor Service.
• To do so, it suffices to add the @RunOnVirtualThread annotation to the endpoint.

If your application creates millions of virtual threads and each virtual thread has its own ThreadLocal variable, then it can quickly consume java heap memory space. Thus, you want to be cautious of the size of data that is stored as ThreadLocal variables. In this article, we will provide an overview of virtual threads in Java and their use in concurrent programming.

Creating and Running a Virtual

A server application like this, with straightforward blocking code, scales well because it can employ a large number of virtual threads. Virtual threads help to improve the throughput of typical server applications precisely because such applications consist of a great number of concurrent tasks that spend much of their time waiting. Things would be very different if this program used an ExecutorService that creates a new platform thread for each task, such as Executors.newCachedThreadPool(). The ExecutorService would attempt to create 10,000 platform threads, and thus 10,000 OS threads, and the program might crash, depending on the machine and operating system. Today, every instance of java.lang.Thread in the JDK is a platform thread. A platform thread runs Java code on an underlying OS thread and captures the OS thread for the code’s entire lifetime.

However, when using the smallrye-mutiny-vertx-sqlclient it is possible to use a variant method that will await for the completion of the transaction, mimicking a blocking behaviour. It can be fairly easy to avoid these situations in our own code, but it is hard to verify every dependency we use. Typically, while experimenting with virtual-threads, we realized that using the postgresql-JDBC driverresults in frequent pinning. The previous example is trivial and doesn’t capture how imperative style can simplify complex reactive operations. The endpoints must now fetch all the fortunes in the database, then append a quote to each fortune before finally returning the result to the client.

Executing virtual threads

If they need to serialize some data to JSON they will end up creating as many instances of FastThreadLocal, resulting on a massive memory consumption as well as exacerbated pressure on the garbage collector. This will eventually affect the performance of the application and inhibit its scalability. Another change is the inclusion of a new ExecutorService, this new executor service can be instantiated by running Executors.newVirtualThreadPerTaskExecutor() method.