Concurrent Access to Maps in Go: Exploring Solutions to 'Concurrent Map Read and Map Write' Error
In the realm of Go programming, concurrency is an integral aspect, particularly when handling multiple connections. However, mishandling concurrent access to shared resources, such as maps, can lead to catastrophic errors like "concurrent map read and map write."
In your case, your Go server, handling 2000 connections, throws this error. The underlying cause is the simultaneous read and write operations on your map structure. To resolve this, you have several options to employ:
1. Employing sync.RWMutex:
Utilize sync.RWMutex, a versatile synchronization primitive that allows for controlled access to your map. This option is suitable for scenarios involving single reads and writes, not iterations over the entire map.
Here's an example demonstrating the use of sync.RWMutex to access someMap:
var ( someMap = map[string]string{} someMapMutex = sync.RWMutex{} ) go func() { someMapMutex.Lock() someMap["key"] = "value" someMapMutex.Unlock() }() someMapMutex.RLock() v, ok := someMap["key"] someMapMutex.RUnlock() if !ok { fmt.Println("key missing") return } fmt.Println(v)
2. Utilizing syncmap.Map:
Consider using syncmap.Map, a synchronization-safe map implementation. This approach simplifies concurrency concerns but may incur performance implications depending on usage. This option excels in scenarios involving for loops.
An example showcasing the use of syncmap.Map:
var ( someMap = syncmap.Map{} ) go func() { someMap.Store("key", "value") }() v, ok := someMap.Load("key") if !ok { fmt.Println("key missing") return } fmt.Println(v) someMap.Range(func(key, value interface{}) bool { // cast value to correct format val, ok := value.(string) if !ok { // this will break iteration return false } // do something with key/value fmt.Println(key, val) // this will continue iterating return true })
General Recommendations:
go run -race server.go
By leveraging these techniques, you can effectively manage concurrent access to maps in your Go server, ensuring stability even under heavy loads.
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