Beginner's Guide: Comprehensive analysis of caching technology in Golang.

Golang is a very popular programming language in recent years. It is very popular because of its powerful concurrency performance and concise syntax. In Golang, caching technology is a very important component. Caching can help us shorten response time and improve system performance. This article will provide a comprehensive analysis of caching technology in Golang to help beginners better understand and apply caching technology.

1. What is cache?

Cache is an auxiliary data storage method used to speed up access to data and improve system performance. The essence of caching is to balance access speed and storage space. Some commonly used data can be stored in the cache to speed up access. In web applications, the computing speed of the server is generally much faster than the reading speed of the hard disk. Storing data in memory can greatly improve the response speed.

2. Caching in Golang

In Golang, there are two common caching methods: memory cache and distributed cache. Each will be introduced in detail below.

1. Memory cache

Memory cache stores data in computer memory to speed up data access. In Golang, memory caching is generally implemented using map or slice.

Use map to implement memory caching:

package main

import (
    "fmt"
    "time"
)

func main() {
    cache := make(map[string]string)
    cache["key1"] = "value1"
    cache["key2"] = "value2"
    
    // 读缓存
    cacheValue, ok := cache["key1"]
    if ok {
        fmt.Println("cache hit:", cacheValue)
    } else {
        fmt.Println("cache miss")
    }
    
    // 延迟1秒后写入新的缓存
    time.Sleep(1 * time.Second)
    cache["key3"] = "value3"
}

In the above code, we use the make function to create a string type map type variablecache and added two key-value pairs to it. When reading the cache, we first obtain whether the cache value exists through the ok variable, and if it exists, print out the cache content. Finally, after simulating a 1-second delay through the time.Sleep function, we added a new key-value pair to the cache.

Use slice to implement memory cache:

package main

import (
    "fmt"
    "time"
)

type CacheItem struct {
    Key string
    Value string
}

func main() {
    cache := []CacheItem{
        {Key: "key1", Value: "value1"},
        {Key: "key2", Value: "value2"},
    }
    
    // 读缓存
    cacheValue, ok := findCacheItemByKey(cache, "key1")
    if ok {
        fmt.Println("cache hit:", cacheValue.Value)
    } else {
        fmt.Println("cache miss")
    }
    
    // 延迟1秒后写入新的缓存
    time.Sleep(1 * time.Second)
    cache = append(cache, CacheItem{Key: "key3", Value: "value3"})
}

func findCacheItemByKey(cache []CacheItem, key string) (CacheItem, bool) {
    for _, item := range cache {
        if item.Key == key {
            return item, true
        }
    }
    return CacheItem{}, false
}

In the above code, we create a CacheItem structure to represent each element in the cache, and then use slice to store Multiple CacheItem structures. When reading the cache, we call the findCacheItemByKey function to find the element in the cache. Finally, after simulating a 1-second delay through the time.Sleep function, we added a new CacheItem element to the cache.

In the memory cache, we need to pay attention to the cache capacity and cache expiration time. If the cache capacity is too small, it will easily cause cache failure and increase the number of database accesses. If the cache expiration time is set improperly, it will also cause the cache hit rate to decrease, thereby affecting system performance.

2. Distributed cache

Distributed cache stores data in the memory of multiple computers to speed up data reading. In Golang, common distributed caches include Memcached and Redis.

Use Memcached as a distributed cache:

package main

import (
    "fmt"
    "time"

    "github.com/bradfitz/gomemcache/memcache"
)

func main() {
    mc := memcache.New("127.0.0.1:11211")
    mc.Set(&memcache.Item{Key: "key1", Value: []byte("value1")})
    mc.Set(&memcache.Item{Key: "key2", Value: []byte("value2")})

    // 读缓存
    cacheValue, err := mc.Get("key1")
    if err == nil {
        fmt.Println("cache hit:", string(cacheValue.Value))
    } else {
        fmt.Println("cache miss")
    }

    // 延迟1秒后写入新的缓存
    time.Sleep(1 * time.Second)
    mc.Set(&memcache.Item{Key: "key3", Value: []byte("value3")})
}

In the above code, we first instantiate a Memcached client through the gomemcache/memcache package and add it to it Two key-value pairs. When reading the cache, we called the Get function to get the cache value. Finally, after simulating a 1-second delay through the time.Sleep function, we added a new key-value pair to the cache.

Use Redis as a distributed cache:

package main

import (
    "fmt"
    "time"

    "github.com/go-redis/redis"
)

func main() {
    rdb := redis.NewClient(&redis.Options{
        Addr:     "localhost:6379",
        Password: "",
        DB:       0,
    })
    defer rdb.Close()

    rdb.Set("key1", "value1", 0)
    rdb.Set("key2", "value2", 0)

    // 读缓存
    cacheValue, err := rdb.Get("key1").Result()
    if err == nil {
        fmt.Println("cache hit:", cacheValue)
    } else {
        fmt.Println("cache miss")
    }

    // 延迟1秒后写入新的缓存
    time.Sleep(1 * time.Second)
    rdb.Set("key3", "value3", 0)
}

In the above code, we first instantiate a Redis client through the go-redis/redis package and add it to it Two key-value pairs have been added. When reading the cache, we called the Get function to get the cache value. Finally, after simulating a 1-second delay through the time.Sleep function, we added a new key-value pair to the cache.

3. Caching application scenarios

Common caching application scenarios include:

1. Database query cache. If there are a large number of identical query requests in the system, the query results can be cached to improve database access speed.
2. Network request cache. If there are a large number of identical network requests in the system, the request results can be cached to improve network access speed.
3. Page caching. If there are a large number of requests for the same page in the system, the page can be cached to improve page response speed.
4. Static resource cache. If there are a large number of requests for static resources in the system, such as pictures, CSS files, etc., these resources can be cached to improve website access speed.

4. Summary

This article provides a comprehensive analysis of caching technology in Golang, introduces two common caching forms, memory cache and distributed cache, and illustrates how to Use both caches in Golang. In addition, this article also introduces the application scenarios of caching in detail, hoping to help beginners better understand and apply caching technology and improve system performance.

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