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本文主要研究一下rsocket load balancer的Ewma
Moving Average
SMA
SMA(Simple Moving Average)，即简单移动平均，其公式如下：
SMAt = (Pt + Pt-1 + Pt-2 + Pt-3 + ... + Pt-n+1) / n
这里的Pt到为Pt-n+1为最近的n个数据
WMA
WMA(Weighted Moving Average)，即加权移动平均，其公式如下：
WMAt = (Pt * Wt) + (Pt-1 * Wt-1) + ... + (Pt-n+1 * Wt-n+1)
WMA会给最近的n个数据加上权重，其中这些权重加起来和为1，一般是较近的数据权重比较大
EMA或EWMA
EMA(Exponentially Moving Average)指数移动平均或EWMA(Exponentially Weighted Moving Average)指数加权移动平均，其公式如下：
EMAt = (Pt * S) + (1- S) * EMAt-1
它有一个S参数为平滑指数，一般是取2/(N+1)
Ewma
rsocket-load-balancer-0.12.1-sources.jar!/io/rsocket/stat/Ewma.java
public class Ewma { private final long tau; private volatile long stamp; private volatile double ewma; public Ewma(long halfLife, TimeUnit unit, double initialValue) { this.tau = Clock.unit().convert((long) (halfLife / Math.log(2)), unit); stamp = 0L; ewma = initialValue; } public synchronized void insert(double x) { long now = Clock.now(); double elapsed = Math.max(0, now - stamp); stamp = now; double w = Math.exp(-elapsed / tau); ewma = w * ewma + (1.0 - w) * x; } public synchronized void reset(double value) { stamp = 0L; ewma = value; } public double value() { return ewma; } @Override public String toString() { return "Ewma(value=" + ewma + ", age=" + (Clock.now() - stamp) + ")"; }} - Ewma的构造器需要指定halfLife、timeunit、initialValue(
ewma初始值)参数；ewma = w * ewma + (1.0 - w) * x，其中x为当前值，w为权重 - 权重w = Math.exp(-elapsed / tau)，即e的-elapsed / tau次方；elapsed为距离上次计算的时间长度；tau(
希腊字母)为EWMA的时间常量 - 这里的tau = halfLife / Math.log(2)根据timeunit转换后的值；其中halfLife参数，代表speed of convergence，即收敛的速度
RSocketSupplier
rsocket-load-balancer-0.12.1-sources.jar!/io/rsocket/client/filter/RSocketSupplier.java
public class RSocketSupplier implements Availability, Supplier>, Closeable { private static final double EPSILON = 1e-4; private Supplier > rSocketSupplier; private final MonoProcessor onClose; private final long tau; private long stamp; private final Ewma errorPercentage; public RSocketSupplier(Supplier > rSocketSupplier, long halfLife, TimeUnit unit) { this.rSocketSupplier = rSocketSupplier; this.tau = Clock.unit().convert((long) (halfLife / Math.log(2)), unit); this.stamp = Clock.now(); this.errorPercentage = new Ewma(halfLife, unit, 1.0); this.onClose = MonoProcessor.create(); } public RSocketSupplier(Supplier > rSocketSupplier) { this(rSocketSupplier, 5, TimeUnit.SECONDS); } @Override public double availability() { double e = errorPercentage.value(); if (Clock.now() - stamp > tau) { // If the window is expired artificially increase the availability double a = Math.min(1.0, e + 0.5); errorPercentage.reset(a); } if (e < EPSILON) { e = 0.0; } else if (1.0 - EPSILON < e) { e = 1.0; } return e; } private synchronized void updateErrorPercentage(double value) { errorPercentage.insert(value); stamp = Clock.now(); } @Override public Mono get() { return rSocketSupplier .get() .doOnNext(o -> updateErrorPercentage(1.0)) .doOnError(t -> updateErrorPercentage(0.0)) .map(AvailabilityAwareRSocketProxy::new); } @Override public void dispose() { onClose.onComplete(); } @Override public boolean isDisposed() { return onClose.isDisposed(); } @Override public Mono onClose() { return onClose; } private class AvailabilityAwareRSocketProxy extends RSocketProxy { public AvailabilityAwareRSocketProxy(RSocket source) { super(source); onClose.doFinally(signalType -> source.dispose()).subscribe(); } @Override public Mono fireAndForget(Payload payload) { return source .fireAndForget(payload) .doOnError(t -> errorPercentage.insert(0.0)) .doOnSuccess(v -> updateErrorPercentage(1.0)); } @Override public Mono requestResponse(Payload payload) { return source .requestResponse(payload) .doOnError(t -> errorPercentage.insert(0.0)) .doOnSuccess(p -> updateErrorPercentage(1.0)); } @Override public Flux requestStream(Payload payload) { return source .requestStream(payload) .doOnError(th -> errorPercentage.insert(0.0)) .doOnComplete(() -> updateErrorPercentage(1.0)); } @Override public Flux requestChannel(Publisher payloads) { return source .requestChannel(payloads) .doOnError(th -> errorPercentage.insert(0.0)) .doOnComplete(() -> updateErrorPercentage(1.0)); } @Override public Mono metadataPush(Payload payload) { return source .metadataPush(payload) .doOnError(t -> errorPercentage.insert(0.0)) .doOnSuccess(v -> updateErrorPercentage(1.0)); } @Override public double availability() { // If the window is expired set success and failure to zero and return // the child availability if (Clock.now() - stamp > tau) { updateErrorPercentage(1.0); } return source.availability() * errorPercentage.value(); } }}
- RSocketSupplier实现了Availability、Supplier、Closeable接口，其中它定义了errorPercentage变量，其类型为Ewma；如果没有指定halfLife值，则RSocketSupplier默认halfLife为5秒，ewma的初始值为1.0
- RSocketSupplier定义了一个常量EPSILON = 1e-4，其availability方法会先计算availability，然后在距离上次计算时间stamp超过tau值时会重置errorPercentage；之后当availability小于EPSILON时返回0，当availability + EPSILON大于1时返回1.0
- updateErrorPercentage方法用于往ewma插入新值，同时更新stamp；get方法的doOnNext方法updateErrorPercentage值为1.0，doOnError方法updateErrorPercentage值为0.0；map会将RSocket转换为AvailabilityAwareRSocketProxy；AvailabilityAwareRSocketProxy对目标RSocket进行代理，对相关方法的doOnError及doOnSuccess都织入errorPercentage的统计
小结
- Moving Average有好几种算法，包括SMA(
Simple Moving Average)、WMA(Weighted Moving Average)、EMA(Exponentially Moving Average)或EWMA(Exponentially Weighted Moving Average) - Ewma的构造器需要指定halfLife、timeunit、initialValue(
ewma初始值)参数；ewma = w * ewma + (1.0 - w) * x，其中x为当前值，w为权重；权重w = Math.exp(-elapsed / tau)，即e的-elapsed / tau次方；elapsed为距离上次计算的时间长度；tau(希腊字母)为EWMA的时间常量；这里的tau = halfLife / Math.log(2)根据timeunit转换后的值；其中halfLife参数，代表speed of convergence，即收敛的速度 - rsocket load balancer使用了Ewma了统计服务的availability；其中RSocketSupplier实现了Availability、Supplier、Closeable接口，其中它定义了errorPercentage变量，其类型为Ewma；如果没有指定halfLife值，则RSocketSupplier默认halfLife为5秒，ewma的初始值为1.0；RSocketSupplier的get方法会将RSocket转换为AvailabilityAwareRSocketProxy，而AvailabilityAwareRSocketProxy则会对目标RSocket进行代理，对相关方法的doOnError及doOnSuccess都织入errorPercentage的统计