This was the most efficient approach when application performance was typically limited by the capacity of server CPUs, but as CPUs have become more powerful, applications are limited by I/O, according to the number of operating system threads available. Thread dumps currently do not contain data about locks held by or blocking virtual threads. Accordingly, they do not show deadlocks between virtual threads or between a virtual thread and a platform thread. The carrier thread pool is a ForkJoinPool – that is, a pool where each thread has its own queue and “steals” tasks from other threads’ queues should its own queue be empty. Its size is set by default to Runtime.getRuntime().availableProcessors() and can be adjusted with the VM option jdk.virtualThreadScheduler.parallelism. Our team has been experimenting with Virtual Threads since they were called Fibers.
Hence implementing virtual threads that, per Oracle, align perfectly with everything that currently exist in Java and in the future it should be the number one approach when building high scale thread-per-request style programs in Java. The second experiment compared the performance obtained using Servlet asynchronous I/O with a standard thread pool to the performance obtained using simple blocking I/O http://protyazhno.ru/anpagelin90-1.html with a virtual thread based executor. 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. Despite the slower performance of the virtual threading compared to Kotlin’s coroutines, it is important to remember that the Project Loom code is very new and “green” compared to the Kotlin Coroutine library.
How to Use Virtual Threads With Quarkus?
The alternative method Thread.ofPlatform() returns a PlatformThreadBuilder via which we can start a platform thread. An unexpected result seen in the thread pool tests was that, more noticeably for the smaller response bodies, 2 concurrent users resulted in fewer average requests per second than a single user. Investigation identified that the additional delay occurred between the task being passed to the Executor and the Executor calling the task’s run() method. This difference reduced for 4 concurrent users and almost disappeared for 8 concurrent users.
Let’s look at the two most common use cases for concurrency and the drawbacks of the current Java concurrency model in these cases. 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. A good example of data you would like to store per request / per thread, access from different points in code, and destroy when the thread gets destroyed is the user that initiated the web request.
Project Loom
When these features are production ready, it will be a big deal for libraries and frameworks that use threads or parallelism. Library authors will see huge performance and scalability improvements while simplifying the codebase and making it more maintainable. Most Java projects using thread pools and platform threads will benefit from switching to virtual threads. Candidates include Java server software like Tomcat, Undertow, and Netty; and web frameworks like Spring and Micronaut. I expect most Java web technologies to migrate to virtual threads from thread pools. Java web technologies and trendy reactive programming libraries like RxJava and Akka could also use structured concurrency effectively.
Stored data is only available to the current thread, and lives and dies with said thread, meaning the data will be cleared up by the Garbage Collector when the thread is done executing either by completing the request successfully or abruptly stopping for any reason. “It would allow a web server to handle more requests at a given time while I/O bound, waiting for a database or another service,” Hellberg said. “Java is used very heavily on the back end in business applications, which is where we focus on helping businesses. … If we want to maintain and help people build new stuff, it’s important that the language keeps up with that.” This week’s Java 20 release revised two Project Loom features that experts expect to have far-reaching effects on the performance of Java apps, should they become standard in September’s long-term support version.