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聊聊apache gossip的FailureDetector

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本文主要研究一下apache gossip的FailureDetector

FailureDetector

incubator-retired-gossip/gossip-base/src/main/java/org/apache/gossip/accrual/FailureDetector.java

public class FailureDetector {

  public static final Logger LOGGER = Logger.getLogger(FailureDetector.class);
  private final DescriptiveStatistics descriptiveStatistics;
  private final long minimumSamples;
  private volatile long latestHeartbeatMs = -1;
  private final String distribution;

  public FailureDetector(long minimumSamples, int windowSize, String distribution) {
    descriptiveStatistics = new DescriptiveStatistics(windowSize);
    this.minimumSamples = minimumSamples;
    this.distribution = distribution;
  }

  /**
   * Updates the statistics based on the delta between the last
   * heartbeat and supplied time
   *
   * @param now the time of the heartbeat in milliseconds
   */
  public synchronized void recordHeartbeat(long now) {
    if (now <= latestHeartbeatMs) {
      return;
    }
    if (latestHeartbeatMs != -1) {
      descriptiveStatistics.addValue(now - latestHeartbeatMs);
    }
    latestHeartbeatMs = now;
  }

  public synchronized Double computePhiMeasure(long now) {
    if (latestHeartbeatMs == -1 || descriptiveStatistics.getN() < minimumSamples) {
      return null;
    }
    long delta = now - latestHeartbeatMs;
    try {
      double probability;
      if (distribution.equals("normal")) {
        double standardDeviation = descriptiveStatistics.getStandardDeviation();
        standardDeviation = standardDeviation < 0.1 ? 0.1 : standardDeviation;
        probability = new NormalDistributionImpl(descriptiveStatistics.getMean(), standardDeviation).cumulativeProbability(delta);
      } else {
        probability = new ExponentialDistributionImpl(descriptiveStatistics.getMean()).cumulativeProbability(delta);
      }
      final double eps = 1e-12;
      if (1 - probability < eps) {
        probability = 1.0;
      }
      return -1.0d * Math.log10(1.0d - probability);
    } catch (MathException | IllegalArgumentException e) {
      LOGGER.debug(e);
      return null;
    }
  }
}

FailureDetector的构造器接收三个参数，分别是minimumSamples, windowSize, distribution
其中minimumSamples表示最少需要多少统计值的时候才真正计算phi值，windowSize表示统计窗口的大小，distribution表示使用哪种分布，normal表示NormalDistribution，其他表示ExponentialDistribution
FailureDetector使用了apache commons math的DescriptiveStatistics来作为Heartbeat Interval的时间窗口统计；使用了NormalDistribution、ExponentialDistribution来完成正态分布、指数分布的累积分布probability，最后使用公式-1.0d * Math.log10(1.0d - probability)来计算phi值

小结

The Phi Accrual Failure Detector by Hayashibara et al 论文提出了基于phi值的Accrual Failure Detector方法
业界关于Failure Detector的实现大致有两种，一种是以akka为代表的按照论文基于NormalDistribution来计算；一种是以cassandra为代表的基于ExponentialDistribution来计算
apache gossip的FailureDetector则集大成地同时支持了NormalDistribution及ExponentialDistribution两种实现方式

doc

The Phi Accrual Failure Detector by Hayashibara et al
PhiAccrualFailureDetector.scala
聊聊hazelcast的PhiAccrualFailureDetector
聊聊Cassandra的FailureDetector
inconsistent implementation of 'cumulative distribution function' for Exponential Distribution

原文 https://segmentfault.com/a/1190000019060028

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