event_engine/iomgr_engine/time_averaged_stats.h

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/*
 *
 * Copyright 2015 gRPC authors.
 *
 * Licensed 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.
 *
 */
 
#ifndef GRPC_CORE_LIB_EVENT_ENGINE_IOMGR_ENGINE_TIME_AVERAGED_STATS_H
#define GRPC_CORE_LIB_EVENT_ENGINE_IOMGR_ENGINE_TIME_AVERAGED_STATS_H
 
namespace grpc_event_engine {
namespace iomgr_engine {
 
/* This tracks a time-decaying weighted average.  It works by collecting
   batches of samples and then mixing their average into a time-decaying
   weighted mean.  It is designed for batch operations where we do many adds
   before updating the average. */
 
class TimeAveragedStats {
 public:
  TimeAveragedStats(double init_avg, double regress_weight,
                    double persistence_factor);
 
  /* Add a sample to the current batch. */
  void AddSample(double value);
  /* Complete a batch and compute the new estimate of the average sample
     value. */
  double UpdateAverage();
 
  double aggregate_weighted_avg() const { return aggregate_weighted_avg_; }
  double aggregate_total_weight() const { return aggregate_total_weight_; }
 
 private:
  /* The initial average value.  This is the reported average until the first
     grpc_time_averaged_stats_update_average call.  If a positive regress_weight
     is used, we also regress towards this value on each update. */
  const double init_avg_;
  /* The sample weight of "init_avg" that is mixed in with each call to
     grpc_time_averaged_stats_update_average.  If the calls to
     grpc_time_averaged_stats_add_sample stop, this will cause the average to
     regress back to the mean.  This should be non-negative.  Set it to 0 to
     disable the bias.  A value of 1 has the effect of adding in 1 bonus sample
     with value init_avg to each sample period. */
  const double regress_weight_;
  /* This determines the rate of decay of the time-averaging from one period
     to the next by scaling the aggregate_total_weight of samples from prior
     periods when combining with the latest period.  It should be in the range
     [0,1].  A higher value adapts more slowly.  With a value of 0.5, if the
     batches each have k samples, the samples_in_avg_ will grow to 2 k, so the
     weighting of the time average will eventually be 1/3 new batch and 2/3
     old average. */
  const double persistence_factor_;
 
  /* The total value of samples since the last UpdateAverage(). */
  double batch_total_value_ = 0;
  /* The number of samples since the last UpdateAverage(). */
  double batch_num_samples_ = 0;
  /* The time-decayed sum of batch_num_samples_ over previous batches.  This is
     the "weight" of the old aggregate_weighted_avg_ when updating the
     average. */
  double aggregate_total_weight_ = 0;
  /* A time-decayed average of the (batch_total_value_ / batch_num_samples_),
     computed by decaying the samples_in_avg_ weight in the weighted average. */
  double aggregate_weighted_avg_ = init_avg_;
};
 
}  // namespace iomgr_engine
}  // namespace grpc_event_engine
 
#endif /* GRPC_CORE_LIB_EVENT_ENGINE_IOMGR_ENGINE_TIME_AVERAGED_STATS_H */