parallel data processing and performance

Java provides built-in support for parallel data processing to help applications make better use of multi-core processors. Parallel streams allow stream operations to be executed concurrently, automatically dividing work across multiple threads while preserving the declarative style of the Stream API. Under the hood, parallel streams rely on the ForkJoinPool, a framework designed for fine-grained parallelism and efficient work-stealing. Understanding how the ForkJoinPool works, how tasks are split and scheduled, and when parallel execution actually improves performance is critical to using parallel streams effectively. The articles in this section explain parallel streams and the ForkJoinPool from both a conceptual and practical perspective, helping you decide when parallel processing is beneficial—and when a sequential approach is the better choice.