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Why Does Go's Garbage Collector Delay Memory Release, and How Can I Optimize Memory Usage?

Susan Sarandon

Jan 04, 2025 am 06:40 AM

Why Does Go's Garbage Collector Delay Memory Release, and How Can I Optimize Memory Usage?

Go 1.3 Garbage Collector: Memory Release Delay

In this scenario, a simple TCP server exhibits a problem where significant memory allocated by connections is not immediately released back to the system. This raises concerns about memory scalability and resource utilization.

The Go runtime uses a garbage collector (GC) to manage memory, and it releases memory after objects become unreachable. However, in this case, the GC seems to have a delay in reclaiming memory, resulting in the observed behavior.

According to the experts, Go does not always shrink its memory space. It releases heap memory, but not all the virtual address space used by the process. Additionally, on Unix-based systems (such as Ubuntu 12.04.4 LTS), Go can reclaim unused heap memory by performing a system call, but this facility is not available on Windows.

Furthermore, the memory release process involves both the GC sweep and a subsequent OS return sweep. In the worst case, this could take up to 7 minutes to complete. Alternatively, calling runtime.FreeOSMemory can force memory release, but only after the GC has run.

It's worth noting that memory allocated by Goroutine stacks is never released. This means that if there are many long-lived Goroutines, memory consumption may not decrease as expected.

As a partial solution, it is possible to force garbage collection using runtime.GC(). However, this should be used with caution to avoid excessive garbage collection. Also, note that not all allocated system memory is actually "real" memory. The runtime may allocate memory that is already available to the OS, resulting in an overestimation of memory usage.

In summary, while Go's garbage collector generally releases memory, it may not always do so immediately or release memory allocated by Goroutine stacks. Forcing garbage collection and understanding the nature of allocated memory can help in optimizing memory management in such scenarios.

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