How to limit flow in golang? Detailed explanation of algorithm

With the continuous development of Internet technology, the demand for high concurrency and large traffic is becoming more and more common, which makes the importance of current limiting technology more and more important. As a fast and efficient language, golang cannot ignore its application in current limiting. So, let’s look specifically at how golang limits current flow.

1. Funnel algorithm

The funnel algorithm is a commonly used current limiting algorithm. Its core idea is to maintain a funnel with a fixed capacity, and then add water to the funnel at a certain rate. If When the funnel reaches its maximum capacity, the water behind it will overflow. For requests entering the funnel, the water in the funnel needs to be consumed. If there is insufficient water in the funnel, it means that the request cannot be processed at this time.

In golang, you can use the "rate" package to implement the funnel algorithm for current limiting, such as the following code:

import (
     "golang.org/x/time/rate"
     "net/http"
)

// 创建一个每秒钟只允许1个请求的漏斗
r := rate.NewLimiter(1, 1)
http.HandleFunc("/", func(w http.ResponseWriter, r *http.Request) {
     if r.Method != "GET" {
          http.Error(w, "Method Not Allowed", http.StatusMethodNotAllowed)
          return
     }
     if !r.Limiter.CanAllow() {
          http.Error(w, "Too Many Requests", http.StatusTooManyRequests)
          return
     }
     // 处理业务逻辑
})

2. Token Bucket Algorithm

Token Bucket The algorithm is also a common current limiting algorithm. Its core idea is to maintain a fixed-capacity bucket and continuously put tokens into the bucket at a certain rate. For requests entering the bucket, tokens in the bucket need to be consumed. If there are insufficient tokens in the bucket, the request cannot be processed at this time.

In golang, you can use the "golang.org/x/time/rate" package to implement the token bucket algorithm for current limiting, such as the following code:

import (
     "golang.org/x/time/rate"
     "net/http"
)

// 创建一个每秒钟只允许1个请求的令牌桶
r := rate.NewLimiter(1, 1)
http.HandleFunc("/", func(w http.ResponseWriter, r *http.Request) {
     if r.Method != "GET" {
          http.Error(w, "Method Not Allowed", http.StatusMethodNotAllowed)
          return
     }
     if !r.Wait(r.Context()) {
          http.Error(w, "Too Many Requests", http.StatusTooManyRequests)
          return
     }
     // 处理业务逻辑
})

3. Sliding window algorithm

The sliding window algorithm is also a commonly used current limiting algorithm. Its core idea is to divide each second into multiple fixed-size time periods, and maintain a fixed-size time period in each time period. Counter, whenever a request is entered, the counter of the corresponding time period is incremented by one. If the number of requests entering the counter reaches the upper limit, the request cannot be processed.

In golang, you can use the "github.com/uber-go/ratelimit" package to implement the sliding window algorithm for current limiting, such as the following code:

import (
     "github.com/uber-go/ratelimit"
     "net/http"
)

// 创建一个每秒最多只允许1个请求的滑动窗口
rl := ratelimit.New(10) // 表示在一个时间段内最多允许处理10个请求
http.HandleFunc("/", func(w http.ResponseWriter, r *http.Request) {
     if r.Method != "GET" {
          http.Error(w, "Method Not Allowed", http.StatusMethodNotAllowed)
          return
     }
     if !rl.TakeAvailable(1) { // 表示当前请求需要消耗1个计数
          http.Error(w, "Too Many Requests", http.StatusTooManyRequests)
          return
     }
     // 处理业务逻辑
})

4. Token bucket and Comparison of Leaky Bucket Algorithms

Although both token bucket and funnel algorithms can be used for current limiting, they are still different in terms of application scenarios, algorithm complexity, implementation difficulty, and effects. Specifically:

• Application scenario: The token bucket algorithm is more suitable for limiting the average traffic and processing requests at a stable speed; while the funnel algorithm is more suitable for limiting the peak traffic to prevent the system from being overwhelmed by requests in an instant. collapse.
• Algorithm complexity: The funnel algorithm has low complexity and only needs to maintain an int type counter and a timestamp; while the token bucket algorithm needs to maintain the capacity of the token bucket and place tokens speed and more parameters.
• Implementation difficulty: The implementation of the funnel algorithm is relatively simple. You can use a for loop to simulate the process of adding water and consuming water; while the token bucket algorithm needs to consider multi-thread security, token expiration and other details. .

In general, different current limiting algorithms have their specific application scenarios, advantages and disadvantages, and you can choose the appropriate algorithm for current limiting according to actual needs.

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