How to solve the problem of concurrent cache access in Go language?

How to solve the problem of concurrent cache access in Go language?

In concurrent programming, caching is a commonly used optimization strategy. By caching data, frequent access to underlying storage can be reduced and system performance improved. However, in multiple concurrent access scenarios, concurrent cache access problems are often encountered, such as cache competition, cache penetration, etc. This article will introduce how to solve the problem of concurrent cache access in Go language and provide specific code examples.

1. Using mutex locks
   Mutex locks are one of the most commonly used methods to solve concurrent cache access problems. By locking before and after read and write operations, it can be ensured that only one thread can modify the cache at the same time. The following is a sample code that uses a mutex lock to solve the problem of concurrent cache access:

package main

import (
    "fmt"
    "sync"
)

var cache map[string]string
var mutex sync.Mutex

func main() {
    cache = make(map[string]string)

    var wg sync.WaitGroup
    for i := 0; i < 10; i++ {
        wg.Add(1)
        go func(index int) {
            defer wg.Done()

            key := fmt.Sprintf("key-%d", index)
            value, ok := getFromCache(key)
            if ok {
                fmt.Printf("Read from cache: %s -> %s
", key, value)
            } else {
                value = expensiveCalculation(key)
                setToCache(key, value)
                fmt.Printf("Write to cache: %s -> %s
", key, value)
            }
        }(i)
    }

    wg.Wait()
}

func getFromCache(key string) (string, bool) {
    mutex.Lock()
    defer mutex.Unlock()

    value, ok := cache[key]
    return value, ok
}

func setToCache(key string, value string) {
    mutex.Lock()
    defer mutex.Unlock()

    cache[key] = value
}

func expensiveCalculation(key string) string {
    // 模拟耗时操作
    return fmt.Sprintf("value-%s", key)
}

In the above code, we are before and after the getFromCache and setToCache operations The addition of a mutex lock ensures that only one thread can read and write to the cache at the same time, thus solving the problem of concurrent cache access.

2. Using read-write locks
   The disadvantage of the mutex lock is that it blocks both read operations and write operations, resulting in poor concurrency performance. Using read-write locks allows multiple threads to read the cache at the same time, but only one thread can perform write operations, improving concurrency performance. The following is a sample code that uses read-write locks to solve concurrent cache access problems:

package main

import (
    "fmt"
    "sync"
)

var cache map[string]string
var rwmutex sync.RWMutex

func main() {
    cache = make(map[string]string)

    var wg sync.WaitGroup
    for i := 0; i < 10; i++ {
        wg.Add(1)
        go func(index int) {
            defer wg.Done()

            key := fmt.Sprintf("key-%d", index)
            value, ok := getFromCache(key)
            if ok {
                fmt.Printf("Read from cache: %s -> %s
", key, value)
            } else {
                value = expensiveCalculation(key)
                setToCache(key, value)
                fmt.Printf("Write to cache: %s -> %s
", key, value)
            }
        }(i)
    }

    wg.Wait()
}

func getFromCache(key string) (string, bool) {
    rwmutex.RLock()
    defer rwmutex.RUnlock()

    value, ok := cache[key]
    return value, ok
}

func setToCache(key string, value string) {
    rwmutex.Lock()
    defer rwmutex.Unlock()

    cache[key] = value
}

func expensiveCalculation(key string) string {
    // 模拟耗时操作
    return fmt.Sprintf("value-%s", key)
}

In the above code, we use read-write locks sync.RWMutex, before and after the read operation A read lock RLock is added, and a write lock Lock is added before and after the write operation, so that we can allow multiple threads to read the cache at the same time, but only one thread can perform write operations. This improves concurrency performance.

By using mutex locks or read-write locks, we can effectively solve the concurrent cache access problem in Go language. In actual applications, the appropriate lock mechanism can be selected according to specific needs to ensure the security and performance of concurrent access.

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