In Go, how to build efficient key-value pair memory?

This article discusses the best practices for building efficient key-value pair memory in Go language. Although map are simple and easy to use, threads are not safe in concurrent environments, limiting their performance and reliability. So, how to build an efficient, thread-safe key-value pair memory similar to Redis?

First of all, sync.Map is a commonly used choice. Although some people question its performance, its read-write separation design usually provides good performance in high concurrency scenarios by internally maintaining two map (one for reading and one for writing). It should be added that specific performance test data or reliable evidence is lacking to support the view that sync.Map is poorly performed.

Secondly, simulating Redis's single-threaded model, using channels ( chan ) to communicate between coroutines, and storing data with map , can also ensure thread safety. However, this method can easily cause the request queue to be too long and become a bottleneck under high concurrency. Although Redis's single-threaded model is efficient in memory read and write, this is not always the best solution in the Go locale.

Finally, concurrentMap mentioned in the article is not part of the Go standard library, usually comes from third-party libraries or sample code. If there are extremely high requirements for memory performance and face extremely high concurrency scenarios, you need to study these non-standard libraries in-depth solutions.

In short, choosing the right Go key-value pair memory requires a trade-off of thread safety, performance, and application scenarios. sync.Map is usually a good starting point, but the final solution needs to be adjusted and optimized according to actual conditions.

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