And of course, there would have to be some actual I/O or other thread parking for Loom to bring benefits. In addition, Java 19 introduced the Executors.newThreadPerTaskExecutor(ThreadFactory threadFactory) method, which can take a ThreadFactory that builds virtual threads. Such a factory can be obtained with Thread.ofVirtual().factory(). A similar API Thread.ofPlatform() exists for creating platform threads as well.

  • Whenever a thread invokes an async API, the platform thread is returned to the pool until the response comes back from the remote system or database.
  • Spring Framework makes a lot of use of synchronized to implement locking, mostly around local data structures.
  • Thread locals can be a problem when migrating to virtual threads.
  • Since then and still with the release of Java 19, a limitation was prevalent, leading to Platform Thread pinning, effectively reducing concurrency when using synchronized.
  • With regular threads, it is difficult to reach high levels of concurrency with blocking calls due to context switch overhead.

We made some examples of pinned threads, and finally, we saw how some old best practices are no longer valid when using virtual threads. In this section, we’ll introduce the implementation of continuation in Java virtual threads. We’re not going into too much detail, but we’ll try to give a general idea of how the virtual threads are implemented. As for ThreadLocal, the possible high number of virtual threads created by an application is why using ThreadLocal may not be a good idea. The JVM added a new carrier thread to the pool when it found no carrier thread.

Few words on the Java Concurrency model

In fact, those threads were what we now call platform threads, and the reason was that creating such threads was quite expensive operation. 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. Moreover, whenever the scheduler preempts a thread from execution, this enormous amount of memory must be moved around.

java virtual threads

However, using such an approach, we can easily reach the limit of the number of threads we can create. 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.

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

This works, we can now handle as many requests as we like if we pay enough to our cloud vendor, but with cloud technologies, one of the main driving factors is reducing the cost of operation. Sometimes we can’t afford the extra spending and we end up with a slow and barely usable system. At its core it performs a basic event loop that monitors all of the synchronous networking read, connect, and accept operations that are not immediately ready when invoked in a virtual thread. When the I/O operation becomes ready, the poller will be notified and subsequently unpark the appropriate parked virtual thread. That’s why Golang made its way into the industry (besides Google support).

java virtual threads

Such channels are typically registered with an I/O event notification mechanism like a Selector, and do not perform blocking system calls. So this leaves the socket types and the NIO channels configured in blocking mode. Virtual threads are a big change under the hood, but they are intentionally easy to apply to an existing codebase.

Using the Thread Class and the Thread.Builder Interface to Create a Virtual Thread

We will use the Duration.between() api to measure the elapsed time in executing all the tasks. Reactive style programming solved the problem of platform threads waiting for responses from other systems. The asynchronous APIs do not wait for the response, rather they work through the callbacks. Whenever a thread invokes an async API, the platform thread is returned to the pool until the response comes back from the remote system or database. Later, when the response arrives, the JVM will allocate another thread from the pool that will handle the response and so on.

java virtual threads

Virtual threads improve application throughput since you can have many more concurrent tasks than with platform threads. That can put pressure on the services that the tasks invoke. For example, a web service may not tolerate huge numbers of concurrent requests. Project Loom is intending to deliver Java VM features and APIs to support easy-to-use, high-throughput lightweight concurrency and new programming models on the Java platform. This brings many interesting and exciting prospects, one of which is to simplify code that interacts with the network.

Virtual threads introduce an abstraction layer between operating-system processes and application-level concurrency. Said differently, virtual threads can be used to schedule tasks that the Java virtual machine orchestrates, so the JVM mediates between the operating system and the program. There are two specific scenarios in which a virtual thread can block the platform thread (called pinning of OS threads). In this way, Executor will be able to run 100 tasks at a time and other tasks will need to wait. As we have 10,000 tasks so the total time to finish the execution will be approximately 100 seconds.

In the ideal case the thread count should stay close to the CPU core count, this way we will be able to minimize the CPU context switching. The first category, asynchronous, initiate I/O operations which complete at some later time, possibly on a thread other than the thread that initiated the I/O operation. By definition, these APIs do not result in blocking system calls, and therefore require no special treatment when run in a virtual thread. However, if the virtual thread makes a blocking file system call – that does not unmount the virtual thread.