content: /*
   * Licensed to the Apache Software Foundation (ASF) under one
   * or more contributor license agreements.  See the NOTICE file
   * distributed with this work for additional information
   * regarding copyright ownership.  The ASF licenses this file
   * to you under the Apache License, Version 2.0 (the
   * "License"); you may not use this file except in compliance
   * with the License.  You may obtain a copy of the License at
   *
   *     http://www.apache.org/licenses/LICENSE-2.0
   *
   * Unless required by applicable law or agreed to in writing, software
   * distributed under the License is distributed on an "AS IS" BASIS,
   * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
   * See the License for the specific language governing permissions and
   * limitations under the License.
   */
  
  package org.apache.cassandra.utils;
  
  import com.google.common.util.concurrent.AtomicDouble;
  
  /**
   * Sample-based exponential moving average. On every update a fraction of the current average is replaced by the new
   * sample. New values have greater representation in the average, and older samples' effect exponentially decays with
   * new data.
   */
  public class ExpMovingAverage implements MovingAverage
  {
      /** The ratio of decay, between 0 and 1, where smaller alpha means values are averaged over more samples */
      private final double alpha;
  
      /** The long term average with exponential decay */
      private final AtomicDouble average = new AtomicDouble(Double.NaN);
  
      /**
       * Create a {@link ExpMovingAverage} where older values have less than 1% effect after 1000 samples.
       */
      public static MovingAverage decayBy1000()
      {
          return new ExpMovingAverage(0.0046);
      }
  
      /**
       * Create a {@link ExpMovingAverage} where older values have less than 1% effect after 100 samples.
       */
      public static ExpMovingAverage decayBy100()
      {
          return new ExpMovingAverage(0.045);
      }
  
      /**
       * Create a {@link ExpMovingAverage} where older values have less than 1% effect after 10 samples.
       */
      public static ExpMovingAverage decayBy10()
      {
          return new ExpMovingAverage(0.37);
      }
  
      /**
       * Create a {@link ExpMovingAverage} where older values have less effect than the given ratio after the given
       * number of samples.
       */
      public static ExpMovingAverage withDecay(double ratio, int samples)
      {
          assert ratio > 0.0 && ratio < 1.0;
          assert samples > 0;
          return new ExpMovingAverage(1 - Math.pow(ratio, 1.0 / samples));
      }
  
      ExpMovingAverage(double alpha)
      {
          assert alpha > 0.0 && alpha <= 1.0;
          this.alpha = alpha;
      }
  
      @Override
      public MovingAverage update(double val)
      {
          double current, update;
          do
          {
              current = average.get();
  
              if (!Double.isNaN(current))
                  update = current + alpha * (val - current);
              else
                  update = val;   // Not initialized yet. Incidentally, passing NaN will cause reinitialization on the
                                  // next update.
          }
          while (!average.compareAndSet(current, update));
  
          return this;
      }
  
      @Override
      public double get()
      {
          return average.get();
      }
  
      @Override
      public String toString()
      {
          return String.format("%.2f", get());
      }
  }
  