Networking i o with virtual threads under the hood

This gets unpleasant quickly, as the callbacks nest ever more deeply. When Java 1.0 was released in 1995, its API had about a hundred classes, among them java.lang.Thread. Java was the first mainstream programming language that directly supported concurrent programming. Gavin Bierman, consulting member of technical staff at Oracle, has published the first draft of the specification document for review by the Java community.

For example, if we scale a million virtual threads in the application, there will be a million ThreadLocal instances along with the data they refer to. Such a large number of instances can put enough burden on the physical memory and it should be avoided. 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. Thread locals can be a problem when migrating to virtual threads. There will likely be far more virtual threads than threads in a thread pool, and now you have many more thread-local instances.

Structured concurrency (Preview)

The similarity is by design and makes refactoring existing applications and servers relatively easy. This compatibility also means that existing tools for monitoring and observing threads in the JVM will work with virtual threads. In this architecture, the application instantiates virtual threads and the JVM assigns the compute resources to handle them. Contrast this to conventional threads, which are mapped directly onto operating system (OS) processes.

• To increase the throughput of the system, we have to continuously increase the number of threads, but the threads of the machine are expensive and the number of available threads is limited.
• If the virtual thread makes a blocking network call from inside
  a synchronized block, the virtual thread may also remain pinned to the platform thread.
• This will execute all the tasks in virtual threads instead of platform threads.
• The threads are yielding control to each other, state preserved and then resumed, a true CoRoutine.
• As mentioned above, a virtual thread remains mounted to a platform thread until the virtual thread makes a blocking network call in which case the virtual thread is unmounted from the platform thread.

When a virtual thread executes a blocking operation, it is supposed to be unmounted from its its carrier thread, which can then execute a different virtual thread. However, there are situations where this unmounting is not possible. In some situations, the virtual thread scheduler will compensate by starting another carrier thread.

More developer resources

With a virtual thread, the request can be issued asynchronously and park the virtual thread and schedule another virtual thread. Once the response is received, the virtual thread is rescheduled and this is done completely transparently. The programming model is much more intuitive than using classic threads and callbacks. This is a cumbersome programming model, often with significant duplication, and would require the new construct to be introduced into every layer of libraries, frameworks, and tooling in order to get a seamless result. Why would we implement yet another unit of concurrency — one that is only syntax-deep — which does not align with the threads we already have? This might be more attractive in another language, where language-runtime co-evolution was not an option, but fortunately we didnt have to make that choice.

It creates an ExecutorService that runs each task in a new virtual thread, submits two tasks to it, and waits for the results. ExecutorService has been retrofitted to implement AutoCloseable, so it can be used with try-with-resources, and the close method shuts down the executor and waits for tasks to complete. Virtual threads are so-named because they share characteristics with virtual memory. With virtual memory, applications have the illusion that they have access to the entire memory address space, not limited by the available physical memory. Similarly, virtual threads are cheap and plentiful, and share the scarce and expensive platform threads as needed, and inactive virtual thread stacks are «paged» out to the heap. As we said, the blocking sleep operation is inside the synchronized useTheToilet method, so the virtual thread is not unmounted.

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Furthermore, the lifetime of the subtasks should not be more than the parent itself. Imagine a task operation that would compose results of multiple fast-running I/O operations concurrently if each operation is executed in a thread. The structured concurrency model brings thread programming closer to the ease of single-threaded code style by leveraging the virtual threads API and the StructuredTaskScope. These frameworks also make us give up a number of the runtime features that make developing in Java easier. This programming style is at odds with the Java Platform because the frameworks unit of concurrency — a stage of an asynchronous pipeline — is not the same as the platforms unit of concurrency. Virtual threads, on the other hand, allow us to gain the same throughput benefit without giving up key language and runtime features.

For this reason, Java 20 will introduce scoped values, which enable the sharing of immutable data within and across threads. As we can see, the IO operation, the sleep() method, is after the infinite loop. We also defined an alwaysTrue() function, which returns true and allows us to write an infinite loop without using the while (true) construct that is not permitted by the compiler. As a best practice, if a method is used very frequently and it uses a synchronized block then consider replacing it with the ReentrantLock mechanism. Note that the following syntax is part of structured concurrency, another new feature proposed in Project Loom. As an example, on my personal web site, I provide demo services for producing random items.

1. Classic Threads or Platform Threads

The virtual thread scheduler mounts virtual threads onto carrier threads. By default, there are as many carrier threads as there are CPU cores. You can tune that count with the jdk.virtualThreadScheduler.parallelism VM option. When a result is not immediately available, you simply block in a virtual thread.

We see Virtual Threads complementing reactive programming models in removing barriers of blocking I/O while processing infinite streams using Virtual Threads purely remains a challenge. ReactiveX is the right approach for concurrent scenarios in which declarative concurrency (such as scatter-gather) matters. The underlying Reactive Streams specification defines a protocol for demand, back pressure, and cancellation of data pipelines without limiting itself to non-blocking API or specific Thread usage. This makes lightweight Virtual Threads an exciting approach for application developers and the Spring Framework. Past years indicated a trend towards applications that communicate over the network with each other. Many applications make use of data stores, message brokers, and remote services.

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This brings many interesting and exciting prospects, one of which is to simplify code that interacts with the network. Servers today can handle far larger numbers of open socket connections than the number of threads they can support, which creates both opportunities and challenges. This java virtual thread is very easy to write, understand and debug, but what if the client requests something that performs a blocking call? Blocking calls are operations that wait for a third-party call to finish, for example, SQL query, request to a different service, or simply IO operation to the OS.

Enter virtual threads, which solve this problem by mapping Java threads to carrier threads that manage (i.e., mount/unmount) thread operations to a carrier thread. It is an abstraction that gives more flexibility and control for developers. A function can return a promise, for example, the result of an HTTP request, and then caller functions can chain their logic to it. Java also has promised, but they are called Futures, however, only the CompletableFuture has the complete feature list of a Promise.

Best practices for virtual threads

But there are actually quite a few things we need to unlearn in order to use them effectively. The workingHard virtual thread is never unmounted from the carrier thread, and the takeABreak virtual thread is never scheduled. Therefore, the initial memory footprint of a virtual thread tends to be very small, a few hundred bytes instead of megabytes.