Table of Contents:
Java v25: Choosing the Right Multithreading for Any Task
Introduction
The Java world is rapidly evolving, and with each version, new tools are emerging for effectively working with multithreading, collections, and asynchrony. Java 25 brings powerful features to developers: Virtual Threads, Structured Concurrency, Record Patterns, and improved memory and native library APIs.
"Multithreading in modern applications isn't just about speedup; it's about safe scalability without unnecessary resource overhead."
In this article, we'll discuss which tool is best for I/O-heavy and CPU-heavy tasks, as well as when ForkJoin and Virtual Threads are the optimal choice.
Comparison of Multithreading Approaches
| Approach | Strengths | Weaknesses | Automation (%) | Optimal for |
|---|---|---|---|---|
| ForkJoinPool | Excellent for CPU-heavy tasks, can divide work recursively | Inefficient for I/O-heavy tasks, harder to collect results asynchronously | 70 | Heavy calculations, large data sets |
| FixedThreadPool + CompletableFuture | Controllable number of threads, predictable CPU load | Limited by the number of threads, does not scale to millions of I/O tasks | 60 | Moderate I/O and CPU tasks |
| Virtual Threads (Loom) | Scalable to millions of threads, ideal for I/O-heavy tasks | Doesn't speed up CPU-bound tasks, still consumes resources even with large volumes | 95 | Network services, asynchronous I/O, databases |
Code Examples
ForkJoinPool for CPU-heavy tasks
ForkJoinPool pool = new ForkJoinPool(24);
long result = pool.submit(() ->
LongStream.range(0, 1_000_000_000)
.parallel()
.map(i -> i * i)
.sum()
).get();
CompletableFuture with FixedThreadPool
ExecutorService pool = Executors.newFixedThreadPool(100);
List<CompletableFuture<Void>> futures = new ArrayList<>();
for (int i = 0; i < 1000; i++) {
futures.add(CompletableFuture.runAsync(() -> doIoTask(), pool));
}
CompletableFuture.allOf(futures.toArray(new CompletableFuture[0])).join();
Virtual Threads (Loom) for I/O-heavy tasks
ExecutorService loomExecutor = Executors.newVirtualThreadPerTaskExecutor();
for (int i = 0; i < 1_000_000; i++) {
loomExecutor.submit(() -> doIoTask());
}
loomExecutor.shutdown();
Conclusion
The choice of multithreading approach depends on the type of workload. For high-computing tasks, ForkJoinPool remains indispensable. Virtual Threads are ideal for millions of asynchronous operations. FixedThreadPool with CompletableFuture is good for predictable mixed tasks.
"With Virtual Threads, Java 25 makes multithreading safe and scalable, opening the door to millions of concurrent tasks without the usual chaos of legacy threads."
| Task Type | Recommended Tool | Why / Strengths | When Not to Use / Weaknesses |
|---|---|---|---|
| I/O-heavy (network, database, files) | Virtual Threads + Structured Concurrency | You can create thousands/millions of threads with almost no memory usage. The code is clean and easy to scale. | Doesn't accelerate heavy computations (CPU-bound); extra CPU tasks can block others. |
| CPU-heavy (math, data processing) | ForkJoinPool / Parallel Streams | Maximum load on all CPU cores, automatic division of tasks into subtasks. | Many I/O threads will be inefficient, requiring fine-tuning of the pool. |
| Mixed tasks (CPU + I/O) | Structured Concurrency + Loom for I/O + ForkJoin for CPU | This combination allows for safe scaling without blocking threads on I/O, while still utilizing the CPU. | More complex to write code for than just Virtual Threads or ForkJoin separately. |
| Simple async tasks / one-off calls | CompletableFuture | Convenient for small async tasks; easy to handle async chains. | Not suitable for thousands of concurrently waiting I/O — Loom is better. |
| Microservices / network servers | Virtual Threads + Structured Concurrency | Thousands of connections without No performance degradation, clean code, simple thread lifecycle management. | Doesn't speed up CPU-heavy tasks; requires JVM 21+ for stable virtual threads. |
Test - Multithreading in Java v25
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