Java Project Loom: Understand the new Java concurrency model

From an OS perspective, you are spawning only a few threads but in terms of the programming language or JVM, you are using many threads. Asynchronous calls will overcome most of the problems of synchronous calls like scaling which is an important factor of any application in the current world. But it has its disadvantages like it is difficult to write and debug it.

Reasons for Using Java Project Loom

Where you can get away with barely any allocations is a much smaller niche even for microservices. And Java’s GC is in an entirely other generation of GCs compared to Go’s. The others don’t matter as we’re talking about GC performance under load.

But this pattern limits the throughput of the server because the number of concurrent requests becomes directly proportional to the server’s hardware performance. So, the number of available threads has to be limited even in multi-core processors. The entire point of virtual threads is to keep the “real” thread, the platform host-OS thread, busy. With Loom, now you have M green threads mapped to N kernel threads. These green threads are way cheaper to spawn, so you could have thousands (millions even?) of green threads.

An Introduction To Inline Classes In Java

StructuredTaskScope also ensures the following behavior automatically. Imagine that updateInventory() is an expensive long-running operation and updateOrder() throws an error. The handleOrder() task will be blocked on inventory.get() even though updateOrder() threw an error. Ideally, we would like the handleOrder() task to cancel updateInventory() when a failure occurs in updateOrder() so that we are not wasting time.

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. Note that after using the virtual threads, our application may be able to handle millions of threads, but other systems or platforms handle only a few requests at a time.

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You can still use a fixed thread pool with a custom task scheduler if you like, but probably not exactly what you are after. If everyone was clamoring for Java and settled on Go only because of goroutines, then sure, but I think Go was liked for a lot of reasons aside from that. I also don’t often see people complain about wanting more control over the scheduler for Go . That doesn’t solve the problem in parallel contexts, only for concurrent ones.

Using Java’s Project Loom to build more reliable distributed systems

I’ve found Jepsen and FoundationDB to apply two similar in idea but different in implementation testing methodologies in an extremely interesting way. Java’s Project Loom makes fine grained control over execution easier than ever before, enabling a hybridized approach to be cheaply project loom java invested in. Historically this approach was viable, but a gamble, since it led to large compromises elsewhere in the stack. I think that there’s room for a library to be built that provides standard Java primitives in a way that can admits straightforward simulation .

Loom is going to leapfrog it and remove pretty much all downsides. I tried getting into it with Quarkus (Vert.x) and it was a nightmare. Kept running into not being able to block on certain threads. There are a few different patterns and approaches to learn, but a lot of those are way easier to grasp and visualize over callback wiring.

Reasons for Using Java Project Loom

The project is currently in the final stages of development and is planned to be released as a preview feature with JDK19. Project Loom is certainly a game-changing feature from Java so far. 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. https://globalcloudteam.com/ With virtual thread, a program can handle millions of threads with a small amount of physical memory and computing resources, otherwise not possible with traditional platform threads. It will also lead to better-written programs when combined with structured concurrency. Apart from the number of threads, latency is also a big concern.

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CompletableFuture and RxJava are quite commonly used APIs, to name a few. These APIs do not block the thread in case of a delay. Instead, it gives the application a concurrency construct over the Java threads to manage their work.

  • But this pattern limits the throughput of the server because the number of concurrent requests becomes directly proportional to the server’s hardware performance.
  • It’s usual for adding and removing nodes to Cassandra to take hours or even days, although for small databases it might be possible in minutes, probably not much less than.
  • So I do not expect to see the Java team retrofitting virtual threads onto existing features of Java generally.
  • For example, if you want to serialize one task after another, we would use an executor service backed by a single thread.
  • They help said customers to migrate to the new Thread API, some help might be in the form of paid consulting.
  • Project Loom goes down that road again, providing lightweight threads to the programmer.

Virtual threads are produced over the heavyweight kernel thread. It means that from one kernel thread we can produce many virtual threads. The number of threads created by the Executor is unbounded. We can use the Thread.Builder reference to create and start multiple threads. Executer service can be created with virtual thread factory as well, just putting thread factory with it constructor argument.

Moving the goal post to benchmarks that don’t involve putting the GC under load aren’t relevant to the conversation. But frankly I’m afraid of how these changes affect garbage collection since more and more vthread stacks are going to be in the heap . I wouldn’t reach for Kotlin for backend projects at all tbeh, since the ecosystem on that side is immature and doesn’t always play well with standard Java tools such as JPA. Non-standard tools are half-baked, inconsistently maintained and not ready for primetime. But for apps, like in mobile, the ecosystem is rich and I would prefer it over Java, especially with advances such as KMM and KotlinJS.

Project loom: what makes the performance better when using virtual threads?

Getting a good virtual thread API GA will be paramount in the decisions around scheduling and continuations in the future. Monitors record their owners as the OS thread, which makes the VM not know whether the carrier or the virtual thread owns a monitor, as they both share the same OS thread. I don’t know that I’d say Scala gets immutability right in that it still provides you equal access to the mutable collections , but I cede the point it’s way better than either Go or Java here. I readily admit Golang gets this wrong, just, -slightly- better than Java. I’m coming from an Erlang background, and that’s the main influence I’m looking at concurrency from; the JVM as a whole gives me a sad when it comes to helping me write correctly behaving code. Async/await in c# is 80% there – it still invades your whole codebase and you have to be really careful about not blocking, but at least it does not look like ass.

Such a large number of instances can put enough burden on the physical memory and it should be avoided. In particular, in most cases a Java programmer uses the Executors utility class to produce an ExecutorService. That executor service is backed by various kinds of thread factories or thread pools. So, even though there is no way to set priorities on virtual threads, it comes as a small drawback since you can spawn an unlimited number of those light threads.

Structured concurrency

With loom, there isn’t a need to chain multiple CompletableFuture’s . And with each blocking operation encountered (ReentrantLock, i/o, JDBC calls), the virtual-thread gets parked. And because these are light-weight threads, the context switch is way-cheaper, distinguishing itself from kernel-threads.

Reasons for Using Java Project Loom

So if you have many long-running IO tasks, they aren’t going to waste a kernel thread and have it sit around idle waiting on IO. This is similar to async libraries, but without the mental overhead. You should be able to just code synchronously and the JVM will take care of the rest. The executor services referred to in the blog are for the order of execution of tasks on the virtual thread pool. For a “virtualThreadExecutor” service, every task will get a virtual thread and scheduling will happen internally.

1. Classic Threads or Platform Threads

This places a hard limit on the scalability of concurrent Java apps. Not only does it imply a one-to-one relationship between app threads and operating system threads, but there is no mechanism for organizing threads for optimal arrangement. 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.

In some ways this is similar to SQLite’s approach to CPU optimization. More broad usage of the model can easily become unwieldy2. 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. Java has had good multi-threading and concurrency capabilities from early on in its evolution and can effectively utilize multi-threaded and multi-core CPUs.

Implement the ability to insert delays, errors in the results as necessary. One could implement a simulation of core I/O primitives like Socket, or a much higher level primitive like a gRPC unary RPC4. Suppose that we either have a large server farm or a large amount of time and have detected the bug somewhere in our stack of at least tens of thousands of lines of code. If there is some kind of smoking gun in the bug report or a sufficiently small set of potential causes, this might just be the start of an odyssey. As a white box tool for bug detection, Jepsen is fantastic.

Traditional Java threads have served very well for a long time. With the growing demand of scalability and high throughput in the world of microservices, virtual threads will prove a milestone feature in Java history. In the following example, we are submitting 10,000 tasks and waiting for all of them to complete.

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