Groovy, like many programming languages, supports concurrency and parallelism to enable more efficient and effective use of computing resources.
Concurrency refers to the ability of a program to perform multiple tasks or operations concurrently. In other words, it allows different parts of a program to execute independently, without waiting for each other. Groovy provides several ways to achieve concurrency:
1. Threads: Groovy supports multi-threading, which enables a program to perform multiple tasks concurrently by creating and managing multiple threads of execution.
2. Asynchronous programming: Groovy supports asynchronous programming using the `CompletableFuture` class, which enables a program to perform non-blocking I/O operations and other tasks concurrently.
Parallelism, on the other hand, refers to the ability of a program to perform multiple tasks or operations simultaneously, by distributing them among multiple processors or cores. Groovy provides several ways to achieve parallelism:
1. Parallel collections: Groovy provides the `parallel()` method on collections, which enables a program to process the elements of a collection in parallel.
2. GPars: GPars is a library for concurrency and parallelism in Groovy. It provides several abstractions for parallel programming, including actors, dataflow concurrency, and parallel collections.
Overall, Groovy provides a variety of tools and libraries for concurrency and parallelism, which enable developers to write efficient and scalable programs.