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I get better performance when I use a thread pool with Executors.newCachedThreadPool(). Let’s look at some examples that show the power of virtual threads. OS threads are at the core of Java’s concurrency model and have a very mature ecosystem around them, but they also come with some drawbacks and are expensive computationally. Let’s look at the two most common use cases for concurrency and the drawbacks of the current Java concurrency model in these cases. If your application has clearly separated modules (could be microservices but monolithic applications can also be modularized), you can start by rewriting one module after another.

All of these APIs need to be rewritten so that they play well with Project Loom. However, there’s a whole bunch of APIs, most importantly, the file API. There’s a list of APIs that do not play well with Project Loom, so it’s easy to shoot loom java yourself in the foot. 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.

Concurrency Model of Java

To cater to these issues, the asynchronous non-blocking I/O were used. The use of asynchronous I/O allows a single thread to handle multiple concurrent connections, but it would require a rather complex code to be written to execute that. Much of this complexity is hidden from the user to make this code look simpler.

This was actually an experiment done by the team behind Jetty. After switching to Project Loom as an experiment, they realized that the garbage collection was doing way more work. The stack traces were actually so deep under normal load, that it didn’t really bring that much value. Do we have such frameworks and what problems and limitations can we reach here? Before we move on to some high level constructs, so first of all, if your threads, either platform or virtual ones have a very deep stack.

Blocking in Reactive code

Besides the actual stack, it actually shows quite a few interesting properties of your threads. For example, it shows you the thread ID and so-called native ID. It turns out, these IDs are actually known by the operating system. If you know the operating system’s utility called top, which is a built in one, it has a switch -H.

You can use these features by adding –enable-preview JVM argument during compilation and execution like in any other preview feature. 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.

Block states

This is actually a significant cost, every time you create a thread, that’s why we have thread pools. That’s why we were taught not to create too many threads on your JVM, because the context switching and memory consumption will kill us. « Before Loom, we had two options, neither of which was really good, » said Aurelio Garcia-Ribeyro, senior director of project management at Oracle, in a presentation at the Oracle DevLive conference this week.

loom java

This is just a minor addition to the API, and it may change. Well, as in any other benchmark it’s impossible to tell without having something to baseline of. So lets do the same processing using platform threads and see the comparison.

Note Blocks

The virtual threads play an important role in serving concurrent requests from users and other applications. An issue with that is that you are breaking the paradigm. While your project is reactive, some of your code isn’t and you are ending up with a codebase that uses reactive code for some parts and doesn’t for other parts. According to the project loom documentation virtual threads behave like normal threads while having almost zero cost and the ability to turn blocking calls into non-blocking ones.

loom java

It used to be simply a function that just blocks your current thread so that it still exists on your operating system. However, it no longer runs, so it will be woken up by your operating system. A new version that takes advantage of virtual threads, notice that if you’re currently running a virtual thread, a different piece of code is run. This is a main function that calls foo, then foo calls bar. There’s nothing really exciting here, except from the fact that the foo function is wrapped in a continuation. Wrapping up a function in a continuation doesn’t really run that function, it just wraps a Lambda expression, nothing specific to see here.

Learn about Project Loom and the lightweight concurrency for JavaJVM.

Once we reach the last line, it will wait for all images to download. Once again, confront that with your typical code, where you would have to create a thread pool, make sure it’s fine-tuned. Notice that with a traditional thread pool, all you had to do was essentially just make sure that your thread pool is not too big, like 100 threads, 200 threads, 500, whatever. You cannot download more than 100 images at once, if you have just 100 threads in your standard thread pool. It turns out that user threads are actually kernel threads these days. To prove that that’s the case, just check, for example, jstack utility that shows you the stack trace of your JVM.

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 (or make matters worse). So, don’t get your hopes high, thinking about mining Bitcoins in hundred-thousand virtual threads. The good https://www.globalcloudteam.com/ news for early adopters and Java enthusiasts is that Java virtual threads libraries are already included in the latest early access builds of JDK 19. The sole purpose of this addition is to acquire constructive feedback from Java developers so that JDK developers can adapt and improve the implementation in future versions.

What the Heck Is Project Loom for Java?

You can use this guide to understand what Java’s Project loom is all about and how its virtual threads (also called ‘fibers’) work under the hood. Before proceeding, it is very important to understand the difference between parallelism and concurrency. Concurrency is the process of scheduling multiple largely independent tasks on a smaller or limited number of resources. Whereas parallelism is the process of performing a task faster by using more resources such as multiple processing units. The job is broken down into multiple smaller tasks, executed simultaneously to complete it more quickly.