How to build a simple caching system in Golang

Caching is a common performance optimization technique. In modern computer systems, we often store frequently used data in memory for faster access. In web applications, the caching mechanism can reduce the pressure on the database and improve the response speed of the application.

Golang provides excellent concurrency mechanisms and memory management models, so it is very suitable for implementing high-performance caching systems. In this article, we will learn how to build a simple caching system using Golang.

1. Basic Concept

The simplest caching system stores data in a map. Map is one of the most important built-in data structures in Golang, which provides fast query operations. We can think of a map as a collection of key-value pairs, where the key is unique and corresponds to each value.

We can use the following code to create a map:

cache := make(map[string]string)

Next, we can add data to the map:

cache["key"] = "value"

Then we can query the value according to the key:

val, ok := cache["key"]
if ok {
    fmt.Println(val)
}

We can use map to implement a simple caching system to store data retrieved from the database. Since querying the database takes a certain amount of time, we can avoid repeatedly querying the database by storing the data in a map. In this way, we can use caching to improve the performance of our application.

2. Basic method

We can use map and mutex to implement a basic caching system. Using mutex to implement concurrency control can avoid the problem of multiple goroutines accessing the map at the same time. The specific implementation is as follows:

type Cache struct {
    items map[string]string
    sync.Mutex
}

func (c *Cache) Set(key, val string) {
    c.Lock()
    defer c.Unlock()
    c.items[key] = val
}

func (c *Cache) Get(key string) (string, bool) {
    c.Lock()
    defer c.Unlock()
    val, ok := c.items[key]
    return val, ok
}

In this cache system, we define a structure Cache to save all cache items. items is a map used to store data items. We also define two methods, Set and Get, to set and get cache items respectively. Both methods use mutex to ensure thread safety.

3. Expiration Policy

In actual applications, we usually need to define an expiration policy. Without using an expiration policy, we cannot periodically delete expired data items in the cache. Therefore, the performance of the caching system is negatively affected. In Golang, we can use the Time type in the time package to calculate the expiration time of cache items.

First, in the Cache structure, we need to add an expires field to specify the expiration time of each cache item:

type cacheItem struct {
    value    string
    expireAt time.Time
}

type Cache struct {
    items map[string]cacheItem
    sync.Mutex
}

Then, in the Get method, we need to check the cache item Has it expired? If it expires, we will delete it and return false:

func (c *Cache) Get(key string) (string, bool) {
    c.Lock()
    defer c.Unlock()
    item, ok := c.items[key]
    if !ok {
        return "", false
    }
    if item.expireAt.Before(time.Now()) {
        delete(c.items, key)
        return "", false
    }
    return item.value, true
}

At the same time, we also need to add a method to regularly clean expired cache items:

func (c *Cache) cleanUp() {
    for {
        time.Sleep(time.Minute)
        c.Lock()
        for key, item := range c.items {
            if item.expireAt.Before(time.Now()) {
                delete(c.items, key)
            }
        }
        c.Unlock()
    }
}

This method uses Sleep to periodically Check whether cache items have expired and delete expired cache items.

4. Summary

In this article, we learned how to build a simple caching system using Golang. We use map and mutex to implement data storage and concurrency control, and use the Time type in the time package to specify the expiration time. By implementing regular cleaning of expired cache items in the Get method, we avoid the problem of cache system performance degradation. This simple caching system can be extended to improve application performance and scalability.

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