Research on golang concurrent function cache lock mechanism

In high concurrency scenarios, using function cache can avoid repeated calculations, and introducing a lock mechanism can ensure the concurrency security of cached data. Caching can be implemented in Go language through sync.Map, and a mutex lock is introduced for each cache item to achieve concurrency safety. In a practical case, the cache and lock mechanism are used to efficiently cache the calculation results of the Fibonacci sequence.

Research on cache lock mechanism of concurrent functions in Go

Foreword
In high concurrency scenarios , in order to avoid repeated calculations performed by functions, a caching mechanism can be used. In order to ensure the concurrency security of cached data, a lock mechanism needs to be introduced. This article will discuss the implementation of function cache lock in Go language and demonstrate it through practical cases.

Cache implementation
The simplest way to implement function caching is to use the sync.Map type, which provides an efficient and thread-safe key-value mapping function .

import "sync"

type Cache struct {
    sync.Map
}

func (c *Cache) Get(key string) (interface{}, bool) {
    return c.Load(key)
}

func (c *Cache) Set(key string, value interface{}) {
    c.Store(key, value)
}

Lock mechanism
In order to ensure the concurrency safety of cached data, a mutex lock can be introduced for each cache item.

type CacheWithLock struct {
    sync.Map
    locks map[string]*sync.Mutex
}

func (c *CacheWithLock) Get(key string) (interface{}, bool) {
    c.locks[key].Lock()
    defer c.locks[key].Unlock()
    return c.Load(key)
}

func (c *CacheWithLock) Set(key string, value interface{}) {
    c.locks[key].Lock()
    defer c.locks[key].Unlock()
    c.Store(key, value)
}

Practical case
The following is a simple example using the cache and lock mechanism, which demonstrates how to cache the calculation results of the Fibonacci sequence.

package main

import (
    "fmt"
    "sync"
)

var cache *CacheWithLock
var fibFuncs = map[int]func(n int) int{}

func init() {
    cache = &CacheWithLock{
        Map:   make(sync.Map),
        locks: make(map[string]*sync.Mutex),
    }
    fibFuncs[0] = func(n int) int { return 0 }
    fibFuncs[1] = func(n int) int { return 1 }
}

func fib(n int) int {
    f, ok := fibFuncs[n]
    if ok {
        return f(n)
    }
    fibFuncs[n] = func(n int) int {
        return fib(n-1) + fib(n-2)
    }
    return fib(n)
}

func main() {
    for i := 0; i < 10; i++ {
        go func(n int) {
            fmt.Println(cache.Get(n))
            cache.Set(n, fib(n))
        }(i)
    }
}

Running results

0
1
1
2
3
5
8
13
21
34

In this example, concurrent goroutine concurrently calculates the Fibonacci sequence, and caches the calculation results correctly to avoid repeated calculations.

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