Application of Golang functions in caching mechanism
Go functions can implement efficient caching mechanisms: 1. Use functions as cache keys: refine cache granularity; 2. Use functions to calculate cache values: avoid repeated calculations; 3. Practical cases: implement memory cache, use Go functions as keys and calculation functions.
Use Go language functions to implement efficient caching mechanism
In high-performance applications, caching plays a vital role. Can greatly reduce request latency and improve throughput. The Go language provides powerful functional programming features that can be used to create efficient caching mechanisms.
Using Go functions as cache keys
We can use Go functions as cache keys to provide finer cache granularity. For example, for a user shopping cart, we could use the user ID as the primary key and use functions to create subkeys for different states (e.g., added to cart, purchased).
import "context" type User struct { ID int } type ShoppingCartCacheEntry struct { Products []string } func getUserShoppingCartCacheKey(ctx context.Context, user User) string { return fmt.Sprintf("shopping-cart:%d", user.ID) } func getUserShoppingCartStatusCacheKey(ctx context.Context, user User, status string) string { return getUserShoppingCartCacheKey(ctx, user) + ":" + status }
Using Go functions to calculate cache values
By putting expensive calculations into functions, we can avoid performing these calculations repeatedly on every request. For example, we can use a function to calculate the total price of products in a shopping cart.
func calculateShoppingCartTotal(ctx context.Context, cart ShoppingCartCacheEntry) float64 { var total float64 for _, product := range cart.Products { price, err := getProductPrice(ctx, product) if err != nil { return 0 } total += price } return total }
Practical case: Implementing memory cache
Let us create a memory cache and use Go functions as cache key and cache value calculation functions.
package main import ( "context" "errors" "fmt" "time" "github.com/patrickmn/go-cache" ) type User struct { ID int } type ShoppingCartCacheEntry struct { Products []string } var ( cache *cache.Cache ErrCacheMiss = errors.New("cache miss") ) func init() { // 创建一个新的内存缓存,过期时间为 10 分钟 cache = cache.New(10 * time.Minute, 5 * time.Minute) } func getUserShoppingCartCacheKey(ctx context.Context, user User) string { return fmt.Sprintf("shopping-cart:%d", user.ID) } func getUserShoppingCartStatusCacheKey(ctx context.Context, user User, status string) string { return getUserShoppingCartCacheKey(ctx, user) + ":" + status } func calculateShoppingCartTotal(ctx context.Context, cart ShoppingCartCacheEntry) float64 { // 省略了实际的产品价格获取逻辑 return 100.0 } func main() { ctx := context.Background() user := User{ID: 1} key := getUserShoppingCartCacheKey(ctx, user) if v, ok := cache.Get(key); ok { fmt.Println("Cache hit") cart := v.(ShoppingCartCacheEntry) total := calculateShoppingCartTotal(ctx, cart) fmt.Println("Total:", total) } else { fmt.Println("Cache miss") // 计算实际值,并将其放入缓存中 cart := ShoppingCartCacheEntry{Products: []string{"A", "B"}} total := calculateShoppingCartTotal(ctx, cart) cache.Set(key, cart, cache.DefaultExpiration) fmt.Println("Total:", total) } }
By leveraging the functional programming features of the Go language, we can create efficient caching mechanisms that provide finer caching granularity and avoid expensive computations.
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