ExecutorService – Waiting for Threads to Finish

Last updated: May 11, 2024

Written by: baeldung

Reviewed by: Michal Aibin

Java Concurrency

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1. Overview

The ExecutorService framework makes it easy to process tasks in multiple threads. We’re going to exemplify some scenarios in which we wait for threads to finish their execution.

Also, we’ll show how to gracefully shutdown an ExecutorService and wait for already running threads to finish their execution.

**2. After Executor’s Shutdown**

When using an Executor, we can shut it down by calling the shutdown() or shutdownNow() methods. Although, it won’t wait until all threads stop executing.

Waiting for existing threads to complete their execution can be achieved by using the awaitTermination() method.

This blocks the thread until all tasks complete their execution or the specified timeout is reached:

public void awaitTerminationAfterShutdown(ExecutorService threadPool) {
    threadPool.shutdown();
    try {
        if (!threadPool.awaitTermination(60, TimeUnit.SECONDS)) {
            threadPool.shutdownNow();
        }
    } catch (InterruptedException ex) {
        threadPool.shutdownNow();
        Thread.currentThread().interrupt();
    }
}

3. Using CountDownLatch

Next, let’s look at another approach to solving this problem – using a CountDownLatch to signal the completion of a task.

We can initialize it with a value that represents the number of times it can be decremented before all threads, that have called the await() method, are notified.

For example, if we need the current thread to wait for another N threads to finish their execution, we can initialize the latch using N:

ExecutorService WORKER_THREAD_POOL 
  = Executors.newFixedThreadPool(10);
CountDownLatch latch = new CountDownLatch(2);
for (int i = 0; i < 2; i++) {
    WORKER_THREAD_POOL.submit(() -> {
        try {
            // ...
            latch.countDown();
        } catch (InterruptedException e) {
            Thread.currentThread().interrupt();
        }
    });
}

// wait for the latch to be decremented by the two remaining threads
latch.await();

4. Using invokeAll()

The first approach that we can use to run threads is the invokeAll() method. The method returns a list of Future objects after all tasks finish or the timeout expires.

Also, we must note that the order of the returned Future objects is the same as the list of the provided Callable objects:

ExecutorService WORKER_THREAD_POOL = Executors.newFixedThreadPool(10);

List<Callable<String>> callables = Arrays.asList(
  new DelayedCallable("fast thread", 100), 
  new DelayedCallable("slow thread", 3000));

long startProcessingTime = System.currentTimeMillis();
List<Future<String>> futures = WORKER_THREAD_POOL.invokeAll(callables);

awaitTerminationAfterShutdown(WORKER_THREAD_POOL);

long totalProcessingTime = System.currentTimeMillis() - startProcessingTime;
 
assertTrue(totalProcessingTime >= 3000);

String firstThreadResponse = futures.get(0).get();
 
assertTrue("fast thread".equals(firstThreadResponse));

String secondThreadResponse = futures.get(1).get();
assertTrue("slow thread".equals(secondThreadResponse));

5. Using ExecutorCompletionService

Another approach to running multiple threads is by using ExecutorCompletionService. It uses a supplied ExecutorService to execute tasks.

One difference over invokeAll() is the order in which the Futures, representing the executed tasks are returned. ExecutorCompletionService uses a queue to store the results in the order they are finished, while invokeAll() returns a list having the same sequential order as produced by the iterator for the given task list:

CompletionService<String> service
  = new ExecutorCompletionService<>(WORKER_THREAD_POOL);

List<Callable<String>> callables = Arrays.asList(
  new DelayedCallable("fast thread", 100), 
  new DelayedCallable("slow thread", 3000));

for (Callable<String> callable : callables) {
    service.submit(callable);
}

The results can be accessed using the take() method:

long startProcessingTime = System.currentTimeMillis();

Future<String> future = service.take();
String firstThreadResponse = future.get();
long totalProcessingTime
  = System.currentTimeMillis() - startProcessingTime;

assertTrue("First response should be from the fast thread", 
  "fast thread".equals(firstThreadResponse));
assertTrue(totalProcessingTime >= 100
  && totalProcessingTime < 1000);
LOG.debug("Thread finished after: " + totalProcessingTime
  + " milliseconds");

future = service.take();
String secondThreadResponse = future.get();
totalProcessingTime
  = System.currentTimeMillis() - startProcessingTime;

assertTrue(
  "Last response should be from the slow thread", 
  "slow thread".equals(secondThreadResponse));
assertTrue(
  totalProcessingTime >= 3000
  && totalProcessingTime < 4000);
LOG.debug("Thread finished after: " + totalProcessingTime
  + " milliseconds");

awaitTerminationAfterShutdown(WORKER_THREAD_POOL);

6. Conclusion

Depending on the use case, we have various options to wait for threads to finish their execution.

A CountDownLatch is useful when we need a mechanism to notify one or more threads that a set of operations performed by other threads has finished.

ExecutorCompletionService is useful when we need to access the task result as soon as possible and other approaches when we want to wait for all of the running tasks to finish.

The code backing this article is available on GitHub. Once you're logged in as a Baeldung Pro Member, start learning and coding on the project.

Of course, Azure Container Apps has really solid support for our ecosystem, from a number of build options, managed Java components, native metrics, dynamic logger, and quite a bit more.

To learn more about Java features on Azure Container Apps, visit the documentation page.

You can also ask questions and leave feedback on the Azure Container Apps GitHub page.

Orkes is the leading workflow orchestration platform built to enable teams to transform the way they develop, connect, and deploy applications, microservices, AI agents, and more.

Try a 14-Day Free Trial of Orkes Conductor today.

Orkes is the leading workflow orchestration platform built to enable teams to transform the way they develop, connect, and deploy applications, microservices, AI agents, and more.

Try a 14-Day Free Trial of Orkes Conductor today.