Structured concurrency and scoped values in Java

Robert Pudlik

07 Sep 2023.4 minutes read

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The work on JEP-428 resulted in the introduction of structured concurrency in Java 19. In this article, we will delve into the concept of structured concurrency, compare it with the current API, and explore the problems it solves.

Find out what Java Experts say about the newest Java release: Java21

What is structured concurrency

Structured concurrency is a paradigm that facilitates and simplifies concurrent programming, allowing you to take a structured approach to multithreaded code. This enhances resource management and error-handling predictability, reducing common pitfalls associated with uncontrolled spawning and termination of threads or tasks, like thread leaks, leading to more maintainable, reliable, and efficient concurrent code.

In addition, the Java implementation uses virtual threads from the Loom project, making it less costly for us to create new threads.


To illustrate well what problems we can encounter in the current API, we will use the example of an invoice. We can do it on one thread, download data about the invoice issuer, customer, and purchased items one by one. However, we want to download this data in parallel to speed up the process. In the first example, we'll use ExecutorService and see what happens.

(Un)structured concurrency

Invoice generateInvoice() throws ExecutionException, InterruptedException {
    try (ExecutorService executorService = Executors.newFixedThreadPool(3)) {
        Future<Issuer> issuer = executorService.submit(this::findIssuer);
        Future<Customer> customer = executorService.submit(this::findCustomer);
        Future<List<Item>> items = executorService.submit(this::findItems);

        return new Invoice(issuer.get(), customer.get(), items.get());

This approach brings with it a couple of problems:

  • When findCustomer takes longer to execute than findItems, and findItems throws an exception, code will be blocked at customer.get(), till the thread executing findCustomer ends. As a result, we will waste resources waiting for the subtask to finish.
  • If the thread calling generateInvoice() is interrupted, the subtasks in the executor are not interrupted and get leaked. They can even operate indefinitely without control.

Structured concurrency

Invoice generateInvoice() throws ExecutionException, InterruptedException {
    try (var scope = new StructuredTaskScope.ShutdownOnFailure()) { // [1]
        Supplier<Issuer> issuer = scope.fork(this::findIssuer);
        Supplier<Customer> customer = scope.fork(this::findCustomer);
        Supplier<List<Item>> items = scope.fork(this::findItems);

        scope.join().throwIfFailed(); // [2]

        return new Invoice(issuer.get(), customer.get(), items.get());
  • [1]: We create a new StructuredTaskScope with the policy ShutdownOnFailure. If an exception is thrown by findIssuer, findCustomer, or findItems, each thread will be stopped and an error will be returned.
  • [2]: Waits for all subtasks in scope to be finished and throws ExecutionException on any failure

The code below is free of the problems mentioned above:

  • When findCustomer takes longer to execute than findItems, but findItems throws exception, findItems will be terminated
  • If the thread calling generateInvoice() is interrupted, cancellation is propagated to subtasks
  • All subtasks will be completed before leaving the scope

At first glance, we can see that not much has changed, the structure of the code is very similar. Instead of using ExecutorService, we use StructuredTaskScope, both implement AutoClosable, so we're able to use try-with-resources. But they differ in a couple of things, one of the biggest is that most implementations of ExecutorService use regular threads, and StructuredTaskScope uses the new lightweight threads from the Loom project. We can see in the code that ExecutorService returns objects wrapped in Future<T>, and in the other case, it is Supplier<T>.

They have a different purpose and lifecycle, more precisely, ExecutorService does not have it clearly defined, it can exist throughout the application lifecycle and act as a simplified interface for thread pools. The tasks themselves in ExecutorService may or may not be related to each other.

The StructuredTaskScope for this is to help manage subtasks that need to be completed before the main task and are related to each other in some way. In addition, the new API for structured concurrency has mechanisms to define the relationship between these subtasks, they are called Policy and are explained in the next section.

Structured concurrency policies

A policy is a set of rules for how a StructuredTaskScope should behave in the event of success or failure of one or more subtasks. So far in the article. we have not mentioned other policies, we have focused on ShutdownOnFailure, this is one of the two basic implementations that is in the language standard.


If any subtask fails, the rest of the subtasks are interrupted. Think of the example with invoicing - getting it right depends on having all the necessary information, such as customer details, issuer details, and items. If any of this information is missing, we are unable to generate the invoice correctly.


It stops the remaining threads once any subtasks have been finished successfully, or throws an exception when all subtasks fail. This is useful when receiving identical information from multiple sources simultaneously, with execution speed being prioritized over specific sources.

Other Policies

Although we only have 2 standard policies, we can create our own policy implementation based on our requirements. To do this, we need to create our own class by extending StructuredTaskScope<T> .


Structured concurrency is a very good addition to the standard Java API that will simplify writing concurrent code. This is another new feature that takes advantage of the promising Loom Project, which could change the approach to asynchronicity and multithreading in Java in the near future.

If you would like to know more about the Loom project, read our blog posts.

Reviewed by: Rafał Maciak, Łukasz Rola, Dariusz Broda

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