Golang function library performance optimization manual

Go function library performance optimization allocates memory in advance: use make() or new() to pre-allocate memory to avoid allocation overhead. Concurrency safety: Use the sync package to implement concurrency-safe data structures. Reduce the number of function calls: Encapsulate reused operations within functions to avoid unnecessary calls. Practical case: Optimizing hash table search: Use pre-allocated arrays instead of linked lists to improve search efficiency. Optimize the cache mechanism: Use concurrent mapping to improve the performance of concurrent reads and writes to the cache.

Go Function Library Performance Optimization Manual

In Go, function libraries are the key to code reusability and modularity. Optimizing function libraries can improve the overall performance and scalability of your application. This manual provides practical techniques and real-world examples for improving the performance of Go libraries.

Technology

• Allocate memory in advance: Use make() or new () Pre-allocate memory to avoid allocating memory during the call.

  // 正确的做法
  func InitMap(size int) map[string]string {
    return make(map[string]string, size)
  }
  
  // 错误的做法
  func InitMap(size int) map[string]string {
    m := map[string]string{}
    for i := 0; i < size; i++ {
        m[strconv.Itoa(i)] = ""
    }
    return m
  }

• Concurrency safety: Use the locks and channels provided by the sync package to implement concurrency-safe data structures.

  // 并发安全的计数器示例
  type Counter struct {
    sync.Mutex
    value int
  }

• Reduce the number of function calls: Encapsulate reusable operations within functions and call them once in the appropriate context.

  // 将重复的字符串连接操作封装在函数内
  func JoinStrings(s1, s2 string) string {
    return s1 + s2
  }
  
  // 使用封装函数来减少函数调用次数
  func PrintJoinedStrings(a, b string) {
    fmt.Println(JoinStrings(a, b))
  }

Practical case

Case 1: Optimizing hash table lookup

By using pre- Using an allocated array instead of a linked list to implement the map structure can significantly improve the performance of hash table lookups.

// 预分配数组的哈希表实现
type HashTable struct {
    buckets []*[]KeyValuePair
}

// 使用预分配数组查找元素
func (h *HashTable) Get(key string) (value string, ok bool) {
    hash := hashFunc(key)
    bucket := h.buckets[hash]
    for _, pair := range *bucket {
        if pair.Key == key {
            return pair.Value, true
        }
    }
    return "", false
}

Case 2: Optimizing the cache mechanism

Using concurrent mapping with concurrency safety to implement the cache mechanism can improve the performance of concurrent reads and writes to the cache.

// 使用并发映射的缓存机制示例
type Cache struct {
    sync.Mutex
    m map[string]interface{}
}

// 使用并发映射从缓存中获取元素
func (c *Cache) Get(key string) (value interface{}, ok bool) {
    c.Lock()
    defer c.Unlock()
    value, ok := c.m[key]
    return
}

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