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HomeBackend DevelopmentGolangHow to reduce memory footprint in Golang API?

How to reduce memory footprint in Golang API?

May 07, 2024 pm 02:03 PM
golangMemory optimizationMemory usagestandard library

In order to reduce the memory usage in the Golang API, you can: use a memory pool to avoid frequent allocation and release of memory. Use byte slices instead of strings to reduce byte storage. Release resources that are no longer in use, such as file handles and database connections. Use memory profiling tools to find memory leaks and high memory consumption.

如何在Golang API中减少内存占用?

How to reduce memory usage in Golang API?

Golang API may consume large amounts of memory, causing performance issues. In order to optimize memory usage, the following strategies can be adopted:

1. Use a memory pool

The memory pool can avoid frequent memory allocation and release, thereby reducing memory usage. The Go standard library provides the sync.Pool type for managing memory pools:

import "sync"

var memoPool = sync.Pool{
    New: func() interface{} {
        return &Memo{}
    },
}

// Memo 代表一个备忘录
type Memo struct {
    Key   string
    Value string
}

// GetMemo 从池中获取备忘录
func GetMemo(key string) *Memo {
    m := memoPool.Get().(*Memo)
    m.Key = key
    return m
}

// PutMemo 将备忘录放回池中
func PutMemo(m *Memo) {
    memoPool.Put(m)
}

2. Use byte slices instead of strings

Byte slice occupation Less memory since it only stores raw byte data, not UTF-8 encoding. Use []byte instead of string:

// 原始方法
func ProcessString(s string) {
    // ...
}

// 改进的方法
func ProcessBytes(b []byte) {
    // ...
}

3. Release unused resources

Make sure to release those that are no longer in use Resources such as file handles, database connections, and network sockets:

import "io"

func CloseFile(f *os.File) {
    if f != nil {
        f.Close()
    }
}

4. Use a memory profiling tool

Use a memory profiling tool, such as # from the Go tool ##go tool pprof, find out the causes of memory leaks and high memory consumption:

go tool pprof -alloc_space http :8080/profile

Practical case:

Suppose we encounter a problem when processing JSON response to a memory leak. The modified code is as follows:

import (
    "encoding/json"
    "io"
    "sync"
)

var jsonDecoderPool = sync.Pool{
    New: func() interface{} {
        return json.NewDecoder(nil)
    },
}

// DecodeJSON 从流中解码JSON响应
func DecodeJSON(r io.Reader, v interface{}) error {
    d := jsonDecoderPool.Get().(*json.Decoder)
    defer jsonDecoderPool.Put(d)
    d.Reset(r)
    return d.Decode(v)
}

Reduces the memory footprint related to JSON decoding by using the memory pool and releasing unused resources.

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