How to implement memory caching using Golang?

Golang memory cache implementation: Use the sync.Map type, which is a concurrently safe key-value store that can implement thread-safe memory cache. Other approaches include third-party libraries such as go-cache and doubly linked lists in the standard library (used to implement LRU caching). Common use cases: Caching database query results in web applications to improve response times and reduce database stress.

How to use Golang to implement memory cache

The memory cache is a temporary storage that stores frequently accessed data, which can significantly Improve application performance. Golang provides multiple methods to implement memory caching, the most commonly used of which is to use the sync.Map type.

sync.Map

sync.Map is a concurrency-safe mapping type that can store key-value pairs. Unlike regular maps, sync.Map can be accessed concurrently from multiple coroutines at the same time without explicit locking.

Example

The following example shows how to use sync.Map to implement memory caching:

package main

import (
    "sync"
)

// 创建一个内存缓存
var cache = sync.Map{}

func main() {
    // 设置一个值
    cache.Store("user-1", "John Doe")

    // 读取一个值
    username, ok := cache.Load("user-1")
    if ok {
        fmt.Printf("用户名为 %s\n", username)
    }

    // 删除一个值
    cache.Delete("user-1")
}

Other methods

In addition to sync.Map, there are other Golang methods for implementing memory caching, such as:

• github.com/patrickmn/go-cache: A third party Cache library with rich features such as invalidation strategies and parallelism.
• container/list: A doubly linked list in the Golang standard library, which can be used to implement LRU (least recently used) cache.

Practical Case

A common caching use case is caching the results of frequently accessed database queries in a web application. For example, we could store the key-value pairs of all usernames into an in-memory cache for quick retrieval when needed, without having to hit the database. This can greatly improve application response time, especially if there are a large number of queries.

Note:

• Release expired data: Make sure to release expired data regularly to prevent memory leaks.
• Size limit: Where possible, limit the size of the cache to prevent out of memory.

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