按比例控制流量的一种实现
网关做灰度的时候,要控制流量的比例,比如 3:7 的分发流量到两个不同版本的服务上去。刚开始的想法是每次流量过来生成 100 以内的随机数,随机数落在那个区间就转到那个版本的服务上去,但是发现这样无法较精准的保证 3:7 的比例,因为有可能某段时间内生成的随机数大范围的落在某个区间内,比如请求了 100 次,每次生成的随机数都是大于 30 的,这样 70% 比例的服务就承受了 100% 的流量。
接下来想到了第二种解决方案,能够保证 10(基数) 倍的流量比例正好是 3:7,思路如下:
1、生成 0 - 99 的数组(集合) 2、打乱数组(集合)的顺序,为了防止出现某比例的流量集中出现 3、全局的计数器,要考虑原子性 4、从数组(集合)中取出计数器和 100 取余后位置的值 5、判断取到的值落在那个区间
以下是 Java 的简单实现:
package io.github.ehlxr.rate;
import java.util.Collections;
import java.util.List;
import java.util.concurrent.atomic.AtomicInteger;
/**
 * 按比例控制流量
 *
 * @author ehlxr
 * @since 2019-07-19.
 */
public class RateBarrier {
    private AtomicInteger op = new AtomicInteger(0);
    private List<Integer> source;
    private int base;
    private int rate;
    public boolean allow() {
        return source.get(op.incrementAndGet() % base) < rate;
    }
    private RateBarrier() {
    }
    public RateBarrier(int base, int rate) {
        this.base = base;
        this.rate = rate;
        source = new ArrayList<>(base);
        for (int i = 0; i < base; i++) {
            source.add(i);
        }
        // 打乱集合顺序
        Collections.shuffle(source);
    }
}
以下是 3:7 流量控制的测试:
package io.github.ehlxr.rate;
/**
 * @author ehlxr
 * @since 2019-07-19.
 */
public class Main {
    public static void main(String[] args) {
        RateBarrier rateBarrier = new RateBarrier(10, 3);
        final Thread[] threads = new Thread[20];
        for (int i = 0; i < threads.length; i++) {
            threads[i] = new Thread(() -> {
                if (rateBarrier.allow()) {
                    System.out.println("this is on 3");
                } else {
                    System.out.println("this is on 7");
                }
            });
            threads[i].start();
        }
        for (Thread t : threads) {
            try {
                t.join();
            } catch (InterruptedException e) {
                e.printStackTrace();
            }
        }
    }
}
// Output:
/*
this is on 7
this is on 7
this is on 7
this is on 7
this is on 3
this is on 7
this is on 3
this is on 7
this is on 7
this is on 3
this is on 7
this is on 7
this is on 7
this is on 7
this is on 3
this is on 7
this is on 3
this is on 7
this is on 7
this is on 3
*/
以下是 Golang 版本 2:3:5 比例分流的简单实现:
package main
import (
	"fmt"
	"math/rand"
	"sync"
	"sync/atomic"
)
type RateBarrier struct {
	source []int
	op     uint64
	base   int
}
func NewRateBarrier(base int) *RateBarrier {
	source := make([]int, base, base)
	for i := 0; i < base; i++ {
		source[i] = i
	}
	// 随机排序
	rand.Shuffle(base, func(i, j int) {
		source[i], source[j] = source[j], source[i]
	})
	return &RateBarrier{
		source: source,
		base:   base,
	}
}
func (b *RateBarrier) Rate() int {
	return b.source[int(atomic.AddUint64(&b.op, 1))%b.base]
}
func main() {
	var wg sync.WaitGroup
	wg.Add(20)
	// 2:3:5
	b := NewRateBarrier(10)
	for i := 0; i < 20; i++ {
		go func() {
			rate := b.Rate()
			switch {
			case rate < 2:
				fmt.Println("this is on 20%")
			case rate >= 2 && rate < 5:
				fmt.Println("this is on 30%")
			case rate >= 5:
				fmt.Println("this is on 50%")
			}
			wg.Done()
		}()
	}
	wg.Wait()
}
// Output:
/*
this is on 30%
this is on 50%
this is on 30%
this is on 20%
this is on 50%
this is on 50%
this is on 50%
this is on 20%
this is on 30%
this is on 20%
this is on 50%
this is on 30%
this is on 30%
this is on 50%
this is on 50%
this is on 50%
this is on 20%
this is on 50%
this is on 50%
this is on 30%
*/