Project Loom: Lightweight Java threads

A possible solution to such problems isthe use of asynchronous concurrent APIs. Provided that such APIs don’t block the kernel thread, it gives an application a finer-grained concurrency construct on top of Java threads. Most concurrent applications need some synchronization between threads for every request. Due to this, an expensive context switch happens between OS threads. It’s worth mentioning that virtual threads are a form of “cooperative multitasking”.

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.

Structured Concurrency

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.

Be as effective as asynchronous or reactive programming, but in a way that one can program in the familiar, sequential command sequence? Oracle’s Project Loom aims to explore exactly this option with a modified JDK. It brings a new lightweight construct for concurrency, named virtual threads. This piece of code is quite interesting, because what it does is it calls yield function. It voluntarily says that it no longer wishes to run because we asked that thread to sleep. Unparking or waking up means basically, that we would like ourselves to be woken up after a certain period of time.

With sockets it was easy, because you could just set them to non-blocking. QCon London brings together the world’s most innovative senior software engineers across multiple domains to share their real-world implementation of emerging trends and practices. After plenty of trial and error, I arrived at the following set of Linux kernel parameter changes to support the target socket scale. The loon balloons would levitate around the globe needing maintenance stations across the world even in remote areas which would be very difficult to achieve. The project Loon has certain limitations as it needs the balloons to be refilled every few weeks with helium.

When you’re creating a new thread, it shares the same memory with the parent thread. It’s just a matter of a single bit when choosing between them. From the operating system’s perspective, every time you create a Java thread, you are creating a kernel thread, which is, in some sense you’re actually creating a new process. This may actually give you some overview like how heavyweight Java threads actually are. As a result, it prevents the expensive context switch between kernel threads. The only difference in asynchronous mode is that the current working threads steal the task from the head of another deque.

A few more critical or skeptic points of view, mainly around the fact that Project Loom won’t really change that much. It’s especially for the people who believe that we will no longer need reactive programming because we will all just write our code using plain Project Loom. Also, my personal opinion, that’s not going to be the case, we will still need some higher level abstraction. Loom and Java in general are prominently devoted to building web applications. Obviously, Java is used in many other areas, and the ideas introduced by Loom may well be useful in these applications.

Kernel threads are created and managed by the kernel. In the very prehistoric days, in the very beginning of the Java platform, there used to be this mechanism called the many-to-one model. The JVM was actually creating user threads, so every time you set newthread.start, a JVM was creating a new user thread. However, these threads, all of them were actually mapped to a single kernel thread, meaning that the JVM was only utilizing a single thread in your operating system. It was doing all the scheduling, so making sure your user threads are effectively using the CPU. The JVM from the outside was only using a single kernel thread, which means only a single CPU.

Java’s Concurrency Model

It proposes that developers could be allowed to use virtual threads using traditional blocking I/O. If a virtual thread is blocked due to a delay by an I/O task, it still won’t block the thread as the virtual threads can be managed by the application instead of the operating system. This could easily eliminate scalability issues due to blocking I/O. 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.

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. Consider an application in which all the threads are waiting for a database to respond.

What is Project Loon’s launch date?

It’s a normal platform thread because it uses carrier thread underneath. As far as JVM is concerned, they do not exist, because they are suspended. With Project Loom, we simply start java project loom 10,000 threads, each thread per each image. Using the structured concurrency, it’s actually fairly simple. Once we reach the last line, it will wait for all images to download.

However, you will still be probably using multiple threads to handle a single request. In some cases, it will be easier but it’s not like an entirely better experience. On the other hand, you now have 10 times or 100 times more threads, which are all doing something. With Project Loom, you no longer consume the so-called stack space. The virtual threads that are not running at the moment, which is technically called pinned, so they are not pinned to a carrier thread, but they are suspended.

Fibers: Virtual threads in Java

He co-leads JHipster and created the JDL Studio and KDash. He’s a Senior Developer Advocate for DevOps at Okta. He is also an international speaker and published author. Error handling with short-circuiting — If either the updateInventory() or updateOrder() fails, the other is canceled unless its already completed. This is managed by the cancellation policy implemented by ShutdownOnFailure(); other policies are possible. For these situations, we would have to carefully write workarounds and failsafe, putting all the burden on the developer.

Under the hood, asynchronous acrobatics are under way. Why go to this trouble, instead of just adopting something like ReactiveX at the language level? The answer is both to make it easier for developers to understand, and to make it easier to move the universe of existing code. For example, data store drivers can be more easily transitioned to the new model. Building responsiveness applications is a never-ending task.

• After all, it’s just a different way of creating 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.
• Vert.x is one such library that helps Java developers write code in a reactive manner.
• And thus, there is a need for a lightweight concurrency construct that is independent of kernel threads.
• The downside is that Java threads are mapped directly to the threads in the OS.
• For instance, threads that are closely related may wind up sharing different processes, when they could benefit from sharing the heap on the same process.
• The new virtual threads in Java 19 will be pretty easy to use.

The ss command reflects that both client and server had 5,000,000+ sockets open. I stopped the experiment after about 40 minutes of continuous operation. The client launched with the same server target port range and a connections-per-port count of 50,000, for a total of 5,000,000 target connections. The project consists of two simple components, EchoServer and EchoClient.

Project Loom – Goal

First, let’s see how many platform threads vs. virtual threads we can create on a machine. My machine is Intel Core i H with 8 cores, 16 threads, and 64GB RAM running Fedora 36. Another common use case is parallel processing or multi-threading, where you might split a task into subtasks across multiple threads. Here you have to write solutions to avoid data corruption and data races.

a. Pluggable user-mode scheduler

Internally, it was doing all this back and forth switching between threads, also known as context switching, it was doing it for ourselves. One downside of this solution is that these APIs are complex, and their integration with legacy APIs is https://globalcloudteam.com/ also a pretty complex process. Most concurrent applications developed in Java require some level of synchronization between threads for every request to work properly. It is required due to the high frequency of threads working concurrently.

Java fibers in action

If you suspend such a virtual thread, you do have to keep that memory that holds all these stack lines somewhere. The cost of the virtual thread will actually approach the cost of the platform thread. Because after all, you do have to store the stack trace somewhere. Most of the time it’s going to be less expensive, you will use less memory, but it doesn’t mean that you can create millions of very complex threads that are doing a lot of work. I will not go into the API too much because it’s subject to change.

Project Loon: Internet From a Balloon

With the rise of powerful and multicore CPUs, more raw power is available for applications to consume. In Java, threads are used to make the application work on multiple tasks concurrently. A developer starts a Java thread in the program, and tasks are assigned to this thread to get processed.

The job is broken down into multiple smaller tasks, executed simultaneously to complete it more quickly. 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.