What are goroutines in Go, and how do they differ from threads?
What are goroutines?In Go, a goroutine is the basic unit for concurrency. It is a lightweight thread managed by the Go runtime. Developers can create tens of thousands of goroutines, which run efficiently on a small number of operating system threads. Using goroutines simplifies and clarifies concurrent programming.Differences between goroutines and threadsResource Consumption:Threads: Traditional threads are directly managed by the operating system, and each thread typically has a relatively large fixed stack (usually a few MBs), meaning creating many threads consumes significant memory resources.Goroutines: In contrast, goroutines are managed by the Go runtime, with an initial stack size of only a few KB, and can dynamically scale as needed. Therefore, more goroutines can be created under the same memory conditions.Scheduling:Threads: Thread scheduling is handled by the operating system, which involves switching from user mode to kernel mode, resulting in higher scheduling overhead.Goroutines: Goroutine scheduling is performed by the Go runtime, using M:N scheduling (multiple goroutines mapped to multiple OS threads). This approach reduces interaction with the kernel, thereby lowering scheduling overhead.Creation and Switching Speed:Threads: Creating threads and context switching between threads are typically time-consuming.Goroutines: Due to being managed by the Go runtime, the creation and switching speed are very fast.Practical Application ExampleIn a network service, handling a large number of concurrent requests is necessary. Using a traditional thread model, if each request is assigned a thread, system resources will be exhausted quickly, leading to performance degradation.By using Go's goroutines, we can assign a goroutine to each network request. For example:In this example, is a function that creates a new goroutine for each HTTP request received. This efficiently utilizes system resources while maintaining high throughput and low latency, making it ideal for scenarios requiring handling a large number of concurrent requests.