This way, multiple threads are involved in handling a single async request. Virtual threads typically employ a small set of platform threads that are used as carrier threads. Code executing in a virtual thread will usually not be aware of the underlying carrier thread. Locking and I/O operations are scheduling points where a carrier thread is re-scheduled from one virtual thread to another.
They require a few thousand CPU instructions to start, and they consume a few megabytes of memory. Server applications can serve so many concurrent requests that it becomes infeasible to have each of them execute on a separate platform thread. In a typical server application, these requests spend much of their time blocking, waiting for a result from a database or another service. Virtual threads are user-mode threads scheduled by the Java virtual machine rather than the operating system.
Embracing Virtual Threads
If we try running this program with a cached thread pool instead, depending on how much memory is available, it may well crash with OutOfMemoryError before all the tasks are submitted. And if we ran it with a fixed-sized thread pool with 1000 threads, it wont crash, but Littles Law accurately predicts it will take 100 seconds to complete. Therefore, their allocation doesn’t require a system call, and they’re free of the operating system’s context switch. Furthermore, virtual threads run on the carrier thread, which is the actual kernel thread used under-the-hood. As a result, since we’re free of the system’s context switch, we could spawn many more such virtual threads. First an ExecutorService is created using the Executors newFixedThreadPool()
This works, we can now handle as many requests as we like if we pay enough to our cloud vendor, but with cloud technologies, one of the main driving factors is reducing the cost of operation. Sometimes we can’t afford the extra spending and we end up with a slow and barely usable system. With regular threads, it is difficult to reach high levels of concurrency with blocking calls due to context switch overhead. Requests can be issued asynchronously in some cases (e.g. NIO + Epoll or Netty io_uring binding), but then you need to deal with callbacks and callback hell. Virtual threads are wrapped upon platform threads, so you may consider them an illusion that JVM provides, the whole idea is to make lifecycle of threads to CPU bound operations.
We will not write ugly asynchronous code anymore. Maybe.
In that case, the Kotlin compiler generates continuation from the coroutine code. Kotlin’s coroutines have no direct support in the JVM, so they are supported using code generation by the compiler. As we can see, each thread stores a different value in the ThreadLocal, which is not accessible to other threads.
To overcome the problems of callbacks, reactive programming, and async/await strategies were introduced. We used virtual.threads.playground, mariadb developers but we can use any name we want. The important thing is that we need to use the requires directive to enable the incubator module.
Creating a Java Virtual Thread
Platform Threads are instances of java.lang.Thread and are a wrapper for the OS threads provided by the platform. This indicates that when the blocking call was made the thread was waiting and after 2 seconds resumed. To support this they pretty much-implemented coroutines into the language. They are essentially suspendable tasks managed by the runtime, they form a tree-like structure of chain calls.
- The invokeAll() method invokes all of the Callable objects you pass to
it in the collection passed as parameter.
- For CPU-bound workloads, we already have tools to get to optimal CPU utilization, such as the fork-join framework and parallel streams.
- The readAllBytes method is a bulk synchronous read operation that reads all of the response bytes.
- An API for simulating loops or conditionals will never be as flexible or familiar as the constructs built into the language.
- 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.
They were very much a product of their time, when systems were single-core and OSes didnt have thread support at all. Virtual threads are useful when the number of concurrent tasks is large, and the tasks mostly block on network I/O. For such tasks, consider parallel streams or recursive fork-join tasks. When Java 1.0 was released in 1995, its API had about a hundred classes, among them java.lang.Thread.
More about executor methods
As per the above-described thread’s life cycle, only during step #3 and step #5 virtual thread will be assigned to the platform thread(which in turn uses OS thread) for execution. In all other steps, virtual thread will be residing as objects in the Java heap memory region just like any of your application objects. With more virtual threads running you can do more blocking IO in parallel than with fewer platform threads. This is useful if your application needs to make many parallel network calls to external services such
as REST APIs, or open many connections to external databases (via JDBC)
Libraries may also need to adjust their use of ThreadLocal in light of virtual threads. But the calculus changes dramatically with a few million threads that each only perform a single task, because there are potentially many more instances allocated and there is much less chance of each being reused. In order to efficiently use underlying operating system threads, virtual threads have been introduced in JDK 19. In this new architecture, a virtual thread will be assigned to a platform thread (aka carrier thread) only when it executes real work.
How to create virtual threads?
Virtual threads are not just syntactic sugar for an asynchronous framework, but an overhaul to the JDK libraries to be more “blocking-aware”. Without that, an errant call to a synchronous blocking method from an async task will still tie up a platform thread for the duration of the call. Merely making it syntactically easier to manage asynchronous operations does not offer any scalability benefit unless you find every blocking operation in your system and turn it into an async method.
Currently, we have no way of stopping a thread that no longer needs to run since its result became obsolete. We can only send the interrupt signal which eventually will be consumed and the thread stops. If function A calls function B and that is the last thing that A does then we can say that B is a continuation of A. It saves you the tedious boilerplate you have to write for chaining, subscribing, and managing the promises. Usually, you can mark a function as async and its result is internally wrapped in a promise. Unfortunately, because they were implemented as a separate class, it was very hard to migrate your whole codebase to it, and eventually, they disappeared and never got merged into the language.
Capturing Task Results
Instead of passing the context from one method to another, the task code simply reads the thread-local variable whenever it needs to access the database. Now, calling factory.newThread(myRunnable) creates a new (unstarted) virtual thread. The name method configures the builder to set thread names request-1, request-2, and so on. The classic remedy for increasing throughput is a non-blocking API. Instead of waiting for a result, the programmer indicates which method should be called when the result has become available, and perhaps another method that is called in case of failure. This gets unpleasant quickly, as the callbacks nest ever more deeply.
The program spawns 50 thousand iterations of whichever thread type you choose. Then, it does some simple math with random numbers and tracks how long the execution takes. One of the most far-reaching Java 19 updates is the introduction of virtual threads. Virtual threads are part of Project Loom, and are available in Java 19 as a preview. Virtual threads are so lightweight that it is perfectly OK to create a virtual thread even for short-lived tasks, and counterproductive to try to reuse or recycle them.
Note that the following syntax is part of structured concurrency, another new feature proposed in Project Loom. To demo it, we have a very simple task that waits for 1 second before printing a message in the console. We are creating this task to keep the example simple so we can focus on the concept. Let us understand the difference between both kinds of threads when they are submitted with the same executable code. We’ve already seen how Kotlin coroutines implement continuations (Kotlin Coroutines – A Comprehensive Introduction – Suspending Functions).