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eBook – Java Streams – NPI EA (cat=Java Streams)
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Since its introduction in Java 8, the Stream API has become a staple of Java development. The basic operations like iterating, filtering, mapping sequences of elements are deceptively simple to use.

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Distributed systems often come with complex challenges such as service-to-service communication, state management, asynchronous messaging, security, and more.

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eBook – Java Concurrency – NPI (cat=Java Concurrency)
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1. Overview

ExecutorService is a JDK API that simplifies running tasks in asynchronous mode. Generally speaking, ExecutorService automatically provides a pool of threads and an API for assigning tasks to it.

Further reading:

Guide to the Fork/Join Framework in Java

An intro to the fork/join framework presented in Java 7 and the tools to help speed up parallel processing by attempting to use all available processor cores.

Overview of the java.util.concurrent

Discover the content of the java.util.concurrent package.

Guide to java.util.concurrent.Locks

In this article, we explore various implementations of the Lock interface and the newly introduced in Java 9 StampedLock class.

2. Instantiating ExecutorService

2.1. Factory Methods of the Executors Class

The easiest way to create ExecutorService is to use one of the factory methods of the Executors class.

For example, the following line of code will create a thread pool with 10 threads:

ExecutorService executor = Executors.newFixedThreadPool(10);

There are several other factory methods to create a predefined ExecutorService that meets specific use cases. To find the best method for your needs, consult Oracle’s official documentation.

2.2. Directly Create an ExecutorService

Because ExecutorService is an interface, an instance of any its implementations can be used. There are several implementations to choose from in the java.util.concurrent package, or you can create your own.

For example, the ThreadPoolExecutor class has a few constructors that we can use to configure an executor service and its internal pool:

ExecutorService executorService = 
  new ThreadPoolExecutor(1, 1, 0L, TimeUnit.MILLISECONDS,   
  new LinkedBlockingQueue<Runnable>());

You may notice that the code above is very similar to the source code of the factory method newSingleThreadExecutor(). For most cases, a detailed manual configuration isn’t necessary.

3. Assigning Tasks to the ExecutorService

ExecutorService can execute Runnable and Callable tasks. To keep things simple in this article, two primitive tasks will be used. Notice that we use lambda expressions here instead of anonymous inner classes:

Runnable runnableTask = () -> {
    try {
        TimeUnit.MILLISECONDS.sleep(300);
    } catch (InterruptedException e) {
        e.printStackTrace();
    }
};

Callable<String> callableTask = () -> {
    TimeUnit.MILLISECONDS.sleep(300);
    return "Task's execution";
};

List<Callable<String>> callableTasks = new ArrayList<>();
callableTasks.add(callableTask);
callableTasks.add(callableTask);
callableTasks.add(callableTask);

We can assign tasks to the ExecutorService using several methods including execute(), which is inherited from the Executor interface, and also submit(), invokeAny() and invokeAll().

The execute() method is void and doesn’t give any possibility to get the result of a task’s execution or to check the task’s status (is it running):

executorService.execute(runnableTask);

submit() submits a Callable or a Runnable task to an ExecutorService and returns a result of type Future:

Future<String> future = 
  executorService.submit(callableTask);

invokeAny() assigns a collection of tasks to an ExecutorService, causing each to run, and returns the result of a successful execution of one task (if there was a successful execution):

String result = executorService.invokeAny(callableTasks);

invokeAll() assigns a collection of tasks to an ExecutorService, causing each to run, and returns the result of all task executions in the form of a list of objects of type Future:

List<Future<String>> futures = executorService.invokeAll(callableTasks);

Before going further, we need to discuss two more items: shutting down an ExecutorService and dealing with Future return types.

4. Shutting Down an ExecutorService

In general, the ExecutorService will not be automatically destroyed when there is no task to process. It will stay alive and wait for new work to do.

In some cases this is very helpful, such as when an app needs to process tasks that appear on an irregular basis or the task quantity is not known at compile time.

On the other hand, an app could reach its end but not be stopped because a waiting ExecutorService will cause the JVM to keep running.

To properly shut down an ExecutorService, we have the shutdown() and shutdownNow() APIs.

The shutdown() method doesn’t cause immediate destruction of the ExecutorService. It will make the ExecutorService stop accepting new tasks and shut down after all running threads finish their current work:

executorService.shutdown();

The shutdownNow() method tries to destroy the ExecutorService immediately, but it doesn’t guarantee that all the running threads will be stopped at the same time:

List<Runnable> notExecutedTasks = executorService.shutdownNow();

This method returns a list of tasks that are waiting to be processed. It is up to the developer to decide what to do with these tasks.

One good way to shut down the ExecutorService (which is also recommended by Oracle) is to use both of these methods combined with the awaitTermination() method:

executorService.shutdown();
try {
    if (!executorService.awaitTermination(800, TimeUnit.MILLISECONDS)) {
        executorService.shutdownNow();
    } 
} catch (InterruptedException e) {
    executorService.shutdownNow();
}

With this approach, the ExecutorService will first stop taking new tasks and then wait up to a specified period of time for all tasks to be completed. If that time expires, the execution is stopped immediately.

5. The Future Interface

The submit() and invokeAll() methods return an object or a collection of objects of type Future, which allows us to get the result of a task’s execution or to check the task’s status (is it running).

The Future interface provides a special blocking method get(), which returns an actual result of the Callable task’s execution or null in the case of a Runnable task:

Future<String> future = executorService.submit(callableTask);
String result = null;
try {
    result = future.get();
} catch (InterruptedException | ExecutionException e) {
    e.printStackTrace();
}

Calling the get() method while the task is still running will cause execution to block until the task properly executes and the result is available.

With very long blocking caused by the get() method, an application’s performance can degrade. If the resulting data is not crucial, it is possible to avoid such a problem by using timeouts:

String result = future.get(200, TimeUnit.MILLISECONDS);

If the execution period is longer than specified (in this case, 200 milliseconds), a TimeoutException will be thrown.

We can use the isDone() method to check if the assigned task already processed or not.

The Future interface also provides for canceling task execution with the cancel() method and checking the cancellation with the isCancelled() method:

boolean canceled = future.cancel(true);
boolean isCancelled = future.isCancelled();

6. The ScheduledExecutorService Interface

The ScheduledExecutorService runs tasks after some predefined delay and/or periodically.

Once again, the best way to instantiate a ScheduledExecutorService is to use the factory methods of the Executors class.

For this section, we use a ScheduledExecutorService with one thread:

ScheduledExecutorService executorService = Executors
  .newSingleThreadScheduledExecutor();

To schedule a single task’s execution after a fixed delay, use the scheduled() method of the ScheduledExecutorService.

Two scheduled() methods allow you to execute Runnable or Callable tasks:

Future<String> resultFuture = 
  executorService.schedule(callableTask, 1, TimeUnit.SECONDS);

The scheduleAtFixedRate() method lets us run a task periodically after a fixed delay. The code above delays for one second before executing callableTask.

The following block of code will run a task after an initial delay of 100 milliseconds. And after that, it will run the same task every 450 milliseconds:

executorService.scheduleAtFixedRate(runnableTask, 100, 450, TimeUnit.MILLISECONDS);

If the processor needs more time to run an assigned task than the period parameter of the scheduleAtFixedRate() method, the ScheduledExecutorService will wait until the current task is completed before starting the next.

If it is necessary to have a fixed length delay between iterations of the task, scheduleWithFixedDelay() should be used.

For example, the following code will guarantee a 150-millisecond pause between the end of the current execution and the start of another one:

executorService.scheduleWithFixedDelay(task, 100, 150, TimeUnit.MILLISECONDS);

According to the scheduleAtFixedRate() and scheduleWithFixedDelay() method contracts, period execution of the task will end at the termination of the ExecutorService or if an exception is thrown during task execution.

7. ExecutorService vs Fork/Join

After the release of Java 7, many developers decided to replace the ExecutorService framework with the fork/join framework.

This is not always the right decision, however. Despite the simplicity and frequent performance gains associated with fork/join, it reduces developer control over concurrent execution.

ExecutorService gives the developer the ability to control the number of generated threads and the granularity of tasks that should be run by separate threads. The best use case for ExecutorService is the processing of independent tasks, such as transactions or requests according to the scheme “one thread for one task.”

In contrast, according to Oracle’s documentation, fork/join was designed to speed up work that can be broken into smaller pieces recursively.

8. Conclusion

Despite the relative simplicity of ExecutorService, there are a few common pitfalls.

Let’s summarize them:

Keeping an unused ExecutorService alive: See the detailed explanation in Section 4 on how to shut down an ExecutorService.

Wrong thread-pool capacity while using fixed length thread pool: It is very important to determine how many threads the application will need to run tasks efficiently. A too-large thread pool will cause unnecessary overhead just to create threads that will mostly be in the waiting mode. Too few can make an application seem unresponsive because of long waiting periods for tasks in the queue.

Calling a Future‘s get() method after task cancellation: Attempting to get the result of an already canceled task triggers a CancellationException.

Unexpectedly long blocking with Future‘s get() method: We should use timeouts to avoid unexpected waits.

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.
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eBook – HTTP Client – NPI EA (cat=HTTP Client-Side)
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eBook – Java Concurrency – NPI EA (cat=Java Concurrency)
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eBook – Java Streams – NPI EA (cat=Java Streams)
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Since its introduction in Java 8, the Stream API has become a staple of Java development. The basic operations like iterating, filtering, mapping sequences of elements are deceptively simple to use.

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Partner – Moderne – NPI EA (tag=Refactoring)
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Modern Java teams move fast — but codebases don’t always keep up. Frameworks change, dependencies drift, and tech debt builds until it starts to drag on delivery. OpenRewrite was built to fix that: an open-source refactoring engine that automates repetitive code changes while keeping developer intent intact.

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eBook – Java Concurrency – NPI (cat=Java Concurrency)
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