How to reduce memory footprint in Golang API?
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.
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) }
The above is the detailed content of How to reduce memory footprint in Golang API?. For more information, please follow other related articles on the PHP Chinese website!

Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Hot Topics



There is no function named "sum" in the C language standard library. "sum" is usually defined by programmers or provided in specific libraries, and its functionality depends on the specific implementation. Common scenarios are summing for arrays, and can also be used in other data structures, such as linked lists. In addition, "sum" is also used in fields such as image processing and statistical analysis. An excellent "sum" function should have good readability, robustness and efficiency.

Multithreading in the language can greatly improve program efficiency. There are four main ways to implement multithreading in C language: Create independent processes: Create multiple independently running processes, each process has its own memory space. Pseudo-multithreading: Create multiple execution streams in a process that share the same memory space and execute alternately. Multi-threaded library: Use multi-threaded libraries such as pthreads to create and manage threads, providing rich thread operation functions. Coroutine: A lightweight multi-threaded implementation that divides tasks into small subtasks and executes them in turn.

std::unique removes adjacent duplicate elements in the container and moves them to the end, returning an iterator pointing to the first duplicate element. std::distance calculates the distance between two iterators, that is, the number of elements they point to. These two functions are useful for optimizing code and improving efficiency, but there are also some pitfalls to be paid attention to, such as: std::unique only deals with adjacent duplicate elements. std::distance is less efficient when dealing with non-random access iterators. By mastering these features and best practices, you can fully utilize the power of these two functions.

Which libraries in Go are developed by large companies or well-known open source projects? When programming in Go, developers often encounter some common needs, ...

Efficiently handle concurrency security issues in multi-process log writing. Multiple processes write the same log file at the same time. How to ensure concurrency is safe and efficient? This is a...

Automatic deletion of Golang generic function type constraints in VSCode Users may encounter a strange problem when writing Golang code using VSCode. when...

Algorithms are the set of instructions to solve problems, and their execution speed and memory usage vary. In programming, many algorithms are based on data search and sorting. This article will introduce several data retrieval and sorting algorithms. Linear search assumes that there is an array [20,500,10,5,100,1,50] and needs to find the number 50. The linear search algorithm checks each element in the array one by one until the target value is found or the complete array is traversed. The algorithm flowchart is as follows: The pseudo-code for linear search is as follows: Check each element: If the target value is found: Return true Return false C language implementation: #include#includeintmain(void){i

Go language performs well in building efficient and scalable systems. Its advantages include: 1. High performance: compiled into machine code, fast running speed; 2. Concurrent programming: simplify multitasking through goroutines and channels; 3. Simplicity: concise syntax, reducing learning and maintenance costs; 4. Cross-platform: supports cross-platform compilation, easy deployment.
