This new lightweight concurrency model supports high throughput and aims to make it easier for Java coders to write, debug, and maintain concurrent Java applications. Project Loom, which is under active development and has recently been targeted for JDK 19 as a preview feature, has the goal of making it easier to write, debug, and maintain concurrent Java applications. Learn more about Project Loom’s concurrency model and virtual threads. You might think that it’s actually fantastic because you’re handling more load. It also may mean that you are overloading your database, or you are overloading another service, and you haven’t changed much. You just changed a single line that changes the way threads are created rather than platform, then you move to the virtual threads.
But this time, we will use a stream to get the results from the futures and see if one of the threads has failed. Fiber class would wrap the tasks in an internal user-mode continuation. This means the task will be suspended and resume in Java runtime instead of the operating system kernel.
I will stick to Linux, because that’s probably what you use in production. For example, when a kernel thread runs for too long, it will be preempted so that other threads can take over. It more or less voluntarily can give up the CPU and other threads may use that CPU. It’s much easier when you have multiple CPUs, but most of the time, this is almost always the case, you will never have as many CPUs as many kernel threads are running. This mechanism happens in the operating system level. A real implementation challenge, however, may be how to reconcile fibers with internal JVM code that blocks kernel threads.
With this approach with Project Loom, notice that I’m actually starting as many concurrent connections, as many concurrent virtual threads, as many images there are. I personally don’t pay that much price for starting these threads because all they do is just like being blocked on I/O. It’s absolutely fine to start 10,000 concurrent connections, because you won’t pay the price of 10,000 carrier or kernel threads, because these virtual threads will be hibernated anyway. Only when the data arrives, the JVM will wake up your virtual thread. However, you just have to be aware of the fact that the kernel threads of your thread pools were actually just natural like limit to concurrency. Just blindly switching from platform threads, the old ones, to virtual threads will change the semantics of your application.
It’s just that the API finally allows us to build in a much different, much easier way. In terms of basic capabilities, fibers must run an arbitrary piece of Java code, concurrently with other threads , and allow the user to await their termination, namely, join them. Obviously, there must be mechanisms for suspending and resuming fibers, similar to LockSupport’s park/unpark. We would also want to obtain a fiber’s stack trace for monitoring/debugging as well as its state (suspended/running) etc..
- Traditional Java concurrency is managed with the Thread and Runnable classes, as seen in Listing 1 .
- Not really, it will jump straight to line 17, which essentially means we are continuing from the place we left off.
- When your virtual thread is waiting on data to be available, another virtual thread can run on the carrier thread.
- Compare the below with Golang’s goroutines or Kotlin’s coroutines.
- It’s the low-level construct that makes virtual threads possible.
The introduction of Virtual Threads also prompts a broader revisit of decisions made for a runtime when only Platform Threads were available. The following Python snippets include the raw data and the matplot lib code to generate plots. A browser talks to a frontend web service, which talks to three separate backend web services for authentication, authorization, and database access. Loom has the upper hand when it comes to syntax familiarity and simpler types (no viral Future / IO wrappers).
Troubleshoot Live Code
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.
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. Besides the actual stack, it actually shows quite a few interesting properties https://globalcloudteam.com/ 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.
The solution is to introduce some kind of virtual threading, where the Java thread is abstracted from the underlying OS thread, and the JVM can more effectively manage the relationship between the two. That is what project Loom sets out to do, by introducing a new virtual thread class called a fiber. Loom is a newer project in the Java/JVM ecosystem that attempts to address limitations in the traditional concurrency model. In particular, Loom offers a lighter alternative to threads along with new language constructs for managing them.
Despite being a prime example of a distributed algorithm, there isn’t that much concurrency in Raft. For sure, there are multiple nodes running in parallel and exchanging messages, but this happens on separate nodes. As far as a single node is concerned, especially in our event-driven, actor-like implementation, concurrency is reduced—on purpose—to a minimum. QCon Plus brings together the world’s most innovative senior software engineers across multiple domains to share their real-world implementation of emerging trends and practices.
Java Developer Productivity Report
ZIO, on the other hand, wins in its interruption implementation, testing capabilities, and uniformity. When it comes to concurrency, to the degree that we’ve been using it, there haven’t been significant differences. Manual supervisionOtherRepresenting node role as a data structureAnd finally, summarising Loom vs ZIO—but only in the scope of the Saft implementation! Keep in mind that we do not aim to run a comprehensive comparison here. Raft is a single, specific use-case that doesn’t use both Loom’s and ZIO capabilities to their full extent. In Java, we could reify that requirement in the method’s signature by the lack of checked exceptions.
The goal is to allow most Java code to run inside fibers unmodified, or with minimal modifications. It is not a requirement of this project to allow native code called from Java code to run in fibers, although this may be possible in some circumstances. As to the question about when not to use virtual threads, there are some obvious cases. E.g. when your threads heavily interact with native code, which knows nothing about virtual threads, or when you depend on some detail that has changed for virtual threads, like the ability to subclass Thread.
Thanks to the nice syntax provided by our Loom.fork method , if we parsed these into sufficiently high-level abstract syntax trees, we would get the same result. What’s important to keep in mind is that the ZIO implementation came project loom java first, and the result might have been completely different had I started with Loom, and then translated to ZIO. The NewEntry request sent by clients to a Raft leader node deserves special treatment, as there’s no immediate reply.
This constraint means threads do not scale very well. In current Java versions one is very limited in the amount of threads that can be created not to mention the overhead when creating a new thread. This is because one thread in Java corresponds to a native thread on the operating system. It has been common to use some kind of thread pool where a lot of tasks are scheduled to be executed.
Listing 2. Creating a virtual thread
This is especially important when running an in-memory Saft simulation with multiple nodes running on a single JVM. But for that, we could have easily used a dedicated OS thread. The heart of Saft, that is the Node class, follows the same pattern as before. Events, including election/heartbeat timeouts, incoming requests from other nodes or clients, and responses to requests sent by the node itself, are read off a queue and processed one-by-one. Check out JEP 428 Structured Concurrency, which is also coming soon and makes handling concurrent tasks easier.
It’s just a different API, it’s just a different way of defining tasks that for most of the time are not doing much. They are sleeping blocked on a synchronization mechanism, or waiting on I/O. It’s just a different way of performing or developing software. I will not go into the API too much because it’s subject to change. You essentially say Thread.startVirtualThread, as opposed to new thread or starting a platform thread. A platform thread is your old typical user threads, that’s actually a kernel thread, but we’re talking about virtual threads here.
The Java Sessions: Project Loom
But let’s not get ahead of ourselves, and introduce the main actors. An important note about Loom’s fibers is that whatever changes are required to the entire Java system, they are not to break existing code. Existing threading code will be fully compatible going forward. As you can imagine, this is a fairly Herculean task, and accounts for much of the time spent by the people working on Loom.
To summarize, parallelism is about cooperating on a single task, whereas concurrency is when different tasks compete for the same resources. In Java, parallelism is done using parallel streams, and project Loom is the answer to the problem with concurrency. In this article, we will be looking into Project Loom and how this concurrent model works.
Beyond virtual threads
Because when your virtual thread runs, it’s a normal Java thread. It’s a normal platform thread because it uses carrier thread underneath. However, you just have to remember on the back of your head, that there is something special happening there, that there is a whole variety of threads that you don’t see, because they are suspended. As far as JVM is concerned, they do not exist, because they are suspended. Should you just blindly install the new version of Java whenever it comes out and just switch to virtual threads? First of all, the semantics of your application change.
If the scheduler is written in Java — as we want — every fiber even has an underlying Thread instance. If fibers are represented by the Fiber class, the underlying Thread instance would be accessible to code running in a fiber (e.g. with Thread.currentThread or Thread.sleep), which seems inadvisable. In order to suspend a computation, a continuation is required to store an entire call-stack context, or simply put, store the stack. To support native languages, the memory storing the stack must be contiguous and remain at the same memory address.