How to implement cache elimination strategy in Golang?

Golang is a programming language that has become very popular in recent years. One of its characteristics is its high efficiency and strong concurrency. When using Golang to develop web applications, we often involve the use of cache. Caching can improve application performance and response speed, but if we do not handle cache eviction properly, it will cause the cache to occupy too much memory and affect the stability of the system. This article will introduce how to implement cache elimination strategy in Golang.

What is cache elimination?

Simply put, cache elimination means that when the cache space is not enough, some cache data needs to be eliminated to make room for new cache data. The cache data elimination strategy is often related to the actual needs of the application.

Cache elimination in Golang

In Golang, we can use the container package in the standard library to implement the cache elimination strategy. This package provides two data structures, List and Heap, both of which can be used to implement cache eviction.

List

List is a doubly linked list in the Golang standard library. We can add cached data to the List according to certain rules and update the data usage in real time. When the cache space is insufficient, we can delete some no longer used cache data from the end of the linked list according to a certain elimination strategy.

The following is a simple sample code to implement the LRU (Least Recently Used) elimination strategy:

type Cache struct {
    maxBytes  int64                    // 允许使用的最大内存
    usedBytes int64                    // 当前已使用的内存
    lruList   *list.List               // 双向链表
    cache     map[string]*list.Element // map 作为缓存数据的索引
    onEvicted func(key string, value []byte)
}

type entry struct {
    key   string
    value []byte
}

// Add 新增一个缓存
func (c *Cache) Add(key string, value []byte) {
    if ele, ok := c.cache[key]; ok {
        c.lruList.MoveToFront(ele)
        kv := ele.Value.(*entry)
        c.usedBytes += int64(len(value) - len(kv.value))
        kv.value = value
        return
    }
    ele := c.lruList.PushFront(&entry{key, value})
    c.cache[key] = ele
    c.usedBytes += int64(len(key) + len(value))
    if c.maxBytes > 0 && c.usedBytes > c.maxBytes {
        c.RemoveOldest()
    }
}

// Get 获取一个缓存
func (c *Cache) Get(key string) ([]byte, bool) {
    if ele, ok := c.cache[key]; ok {
        c.lruList.MoveToFront(ele)
        kv := ele.Value.(*entry)
        return kv.value, true
    }
    return nil, false
}

// RemoveOldest 删除最久未使用的缓存
func (c *Cache) RemoveOldest() { 
    ele := c.lruList.Back()
    if ele != nil {
        c.lruList.Remove(ele)
        kv := ele.Value.(*entry)
        delete(c.cache, kv.key)
        c.usedBytes -= int64(len(kv.key) + len(kv.value))
        if c.onEvicted != nil {
            c.onEvicted(kv.key, kv.value)
        }
    }
}

In the above code, we use List to save cache data and cache map as Index to find a cache quickly and easily. When the cache storage space exceeds the limit, we delete the cache that has not been used for the longest time starting from the end of the list (ie, LRU policy) to make room. At the same time, we also support some other features, such as setting the maximum memory required for each cache and supporting some specific operations when cache data is deleted.

Heap

Heap is the heap in the Golang standard library. It manages a set of data according to a certain priority rule (such as the access time of cached data, the size of the data, etc.) and based on Rules automatically implement data insertion, deletion and query. Similarly, when the cache space is insufficient, we can use Heap to automatically eliminate some data.

The following is a simple sample code to implement the LFU (Least Frequently Used) elimination strategy:

type Item struct {
    Value  []byte
    Priority int // 优先级，即缓存访问次数
    Index  int    // 在 heap 中的索引
}

type PriorityQueue []*Item

// 实现 heap.Interface 接口的 Push 方法
func (pq *PriorityQueue) Push(x interface{}) {
    n := len(*pq)
    item := x.(*Item)
    item.Index = n
    *pq = append(*pq, item)
}

// 实现 heap.Interface 接口的 Pop 方法
func (pq *PriorityQueue) Pop() interface{} {
    old := *pq
    n := len(old)
    item := old[n-1]
    item.Index = -1 // 为了安全起见
    *pq = old[0 : n-1]
    return item
}

// 实现 heap.Interface 接口的 Len 方法
func (pq PriorityQueue) Len() int {
    return len(pq)
}

// 实现 heap.Interface 接口的 Less 方法
func (pq PriorityQueue) Less(i, j int) bool {
    return pq[i].Priority < pq[j].Priority
}

// 实现 heap.Interface 接口的 Swap 方法
func (pq PriorityQueue) Swap(i, j int) {
    pq[i], pq[j] = pq[j], pq[i]
    pq[i].Index = i
    pq[j].Index = j
}

type Cache struct {
    maxBytes  int64
    usedBytes int64
    cache     map[string]*Item
    queue     PriorityQueue
    onEvicted func(key string, value []byte)
}

// Add 新增一个缓存
func (c *Cache) Add(key string, value []byte) {
    if item, ok := c.cache[key]; ok {
        item.Priority++
        item.Value = value
        heap.Fix(&c.queue, item.Index)
    } else {
        item = &Item{Value: value, Priority: 1}
        c.cache[key] = item
        heap.Push(&c.queue, item)
    }
    c.usedBytes += int64(len(key) + len(value))
    if c.maxBytes > 0 && c.usedBytes > c.maxBytes {
        c.RemoveOldest()
    }
}

// Get 获取一个缓存
func (c *Cache) Get(key string) ([]byte, bool) {
    if item, ok := c.cache[key]; ok {
        item.Priority++
        heap.Fix(&c.queue, item.Index)
        return item.Value, true
    }
    return nil, false
}

// RemoveOldest 删除访问次数最少的缓存
func (c *Cache) RemoveOldest() {
    item := heap.Pop(&c.queue).(*Item)
    delete(c.cache, item.Value)
    c.usedBytes -= int64(len(item.Value) + item.Priority)
    if c.onEvicted != nil {
        c.onEvicted(item.Value, item.Value)
    }
}

In the above code, we use Heap to save cache data and use cache map as an index. Different from List, in heap, we automatically manage the priority of cached data and operations such as insertion and deletion. When the cache storage space exceeds the limit, the heap will automatically delete some cache data that is accessed less frequently.

Summary

When using Golang to write web applications, the use of cache is often inevitable. But to prevent cached data from taking up too much memory, we must handle cache eviction correctly. By using the List and Heap data structures in the Golang standard library, we can easily implement commonly used cache elimination strategies and ensure the stable operation of the application.

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