服务限流-令牌桶java实现

此文非常不错，抄自：

https://www.cnblogs.com/googlemeoften/p/6020718.html

其他实现

https://www.cnblogs.com/LBSer/p/4083131.html

a. 按特定的速率向令牌桶投放令牌

b. 根据预设的匹配规则先对报文进行分类，不符合匹配规则的报文不需要经过令牌桶的处理，直接发送；

c. 符合匹配规则的报文，则需要令牌桶进行处理。当桶中有足够的令牌则报文可以被继续发送下去，同时令牌桶中的令牌 量按报文的长度做相应的减少；

d. 当令牌桶中的令牌不足时，报文将不能被发送，只有等到桶中生成了新的令牌，报文才可以发送。这就可以限制报文的流量只能是小于等于令牌生成的速度，达到限制流量的目的。

保留学习

import java.io.BufferedWriter;
import java.io.FileOutputStream;
import java.io.IOException;
import java.io.OutputStreamWriter;
import java.util.Random;
import java.util.concurrent.ArrayBlockingQueue;
import java.util.concurrent.Executors;
import java.util.concurrent.ScheduledExecutorService;
import java.util.concurrent.TimeUnit;
import java.util.concurrent.locks.ReentrantLock;

/**
 * <pre>
 * Created by inter12 on 15-3-18.
 * </pre>
 */
public class TokenBucket {

    // 默认桶大小个数 即最大瞬间流量是64M
    private static final int DEFAULT_BUCKET_SIZE = 1024 * 1024 * 64;

    // 一个桶的单位是1字节
    private int everyTokenSize = 1;

    // 瞬间最大流量
    private int maxFlowRate;

    // 平均流量
    private int avgFlowRate;

    // 队列来缓存桶数量：最大的流量峰值就是 = everyTokenSize*DEFAULT_BUCKET_SIZE 64M = 1 * 1024 * 1024
    // * 64
    private ArrayBlockingQueue<Byte> tokenQueue = new ArrayBlockingQueue<Byte>(DEFAULT_BUCKET_SIZE);

    private ScheduledExecutorService scheduledExecutorService = Executors.newSingleThreadScheduledExecutor();

    private volatile boolean isStart = false;

    private ReentrantLock lock = new ReentrantLock(true);

    private static final byte A_CHAR = 'a';

    public TokenBucket() {
    }

    public TokenBucket(int maxFlowRate, int avgFlowRate) {
        this.maxFlowRate = maxFlowRate;
        this.avgFlowRate = avgFlowRate;
    }

    public TokenBucket(int everyTokenSize, int maxFlowRate, int avgFlowRate) {
        this.everyTokenSize = everyTokenSize;
        this.maxFlowRate = maxFlowRate;
        this.avgFlowRate = avgFlowRate;
    }

    public void addTokens(Integer tokenNum) {
        // 若是桶已经满了，就不再加入新的令牌
        for (int i = 0; i < tokenNum; i++) {
            tokenQueue.offer(Byte.valueOf(A_CHAR));
        }
    }

    public TokenBucket build() {
        start();
        return this;
    }

    /**
     * 获取足够的令牌个数
     * 
     * @return
     */
    public boolean getTokens(byte[] dataSize) {
//        Preconditions.checkNotNull(dataSize);
//        Preconditions.checkArgument(isStart,
//                "please invoke start method first !");
        int needTokenNum = dataSize.length / everyTokenSize + 1;// 传输内容大小对应的桶个数

        final ReentrantLock lock = this.lock;
        lock.lock();
        try {
            boolean result = needTokenNum <= tokenQueue.size(); // 是否存在足够的桶数量
            if (!result) {
                return false;
            }

            int tokenCount = 0;
            for (int i = 0; i < needTokenNum; i++) {
                Byte poll = tokenQueue.poll();
                if (poll != null) {
                    tokenCount++;
                }
            }
            return tokenCount == needTokenNum;
        } finally {
            lock.unlock();
        }
    }

    public void start() {
        // 初始化桶队列大小
        if (maxFlowRate != 0) {
            tokenQueue = new ArrayBlockingQueue<Byte>(maxFlowRate);
        }

        // 初始化令牌生产者
        TokenProducer tokenProducer = new TokenProducer(avgFlowRate, this);
        scheduledExecutorService.scheduleAtFixedRate(tokenProducer, 0, 1, TimeUnit.SECONDS);
        isStart = true;
    }

    public void stop() {
        isStart = false;
        scheduledExecutorService.shutdown();
    }

    public boolean isStarted() {
        return isStart;
    }

    class TokenProducer implements Runnable {
        private int avgFlowRate;
        private TokenBucket tokenBucket;
        public TokenProducer(int avgFlowRate, TokenBucket tokenBucket) {
            this.avgFlowRate = avgFlowRate;
            this.tokenBucket = tokenBucket;
        }

        @Override
        public void run() {
            tokenBucket.addTokens(avgFlowRate);
        }
    }

    public static TokenBucket newBuilder() {
        return new TokenBucket();
    }

    public TokenBucket everyTokenSize(int everyTokenSize) {
        this.everyTokenSize = everyTokenSize;
        return this;
    }

    public TokenBucket maxFlowRate(int maxFlowRate) {
        this.maxFlowRate = maxFlowRate;
        return this;
    }

    public TokenBucket avgFlowRate(int avgFlowRate) {
        this.avgFlowRate = avgFlowRate;
        return this;
    }

    private String stringCopy(String data, int copyNum) {
        StringBuilder sbuilder = new StringBuilder(data.length() * copyNum);
        for (int i = 0; i < copyNum; i++) {
            sbuilder.append(data);
        }
        return sbuilder.toString();
    }

    public static void main(String[] args) throws IOException, InterruptedException {
        TokenBucket tokenBucket = TokenBucket.newBuilder().avgFlowRate(512).maxFlowRate(1024).build();
        BufferedWriter bufferedWriter = new BufferedWriter(new OutputStreamWriter(new FileOutputStream("D:/ds_test")));
        String data = "xxxx";// 四个字节
        for (int i = 1; i <= 1000; i++) {
            Random random = new Random();
            int i1 = random.nextInt(100);
            boolean tokens = tokenBucket.getTokens(tokenBucket.stringCopy(data, i1).getBytes());
            TimeUnit.MILLISECONDS.sleep(100);
            if (tokens) {
                bufferedWriter.write("token pass --- index:" + i1);
                System.out.println("token pass --- index:" + i1);
            } else {
                bufferedWriter.write("token rejuect --- index" + i1);
                System.out.println("token rejuect --- index" + i1);
            }
            bufferedWriter.newLine();
            bufferedWriter.flush();
        }
        bufferedWriter.close();
    }
}