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This is one of a series of CLs adding a new metric type, EventMetric, which is used for tracking numerical distributions. ------------- Created by MOE: https://github.com/google/moe MOE_MIGRATED_REVID=132103552
111 lines
3.7 KiB
Java
111 lines
3.7 KiB
Java
// Copyright 2016 The Domain Registry Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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package google.registry.monitoring.metrics;
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import static com.google.common.base.Preconditions.checkArgument;
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import static com.google.common.base.Preconditions.checkNotNull;
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import static google.registry.monitoring.metrics.MetricsUtils.checkDouble;
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import com.google.common.collect.ImmutableRangeMap;
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import com.google.common.collect.ImmutableSortedSet;
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import com.google.common.collect.Ordering;
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import com.google.common.collect.Range;
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import com.google.common.collect.TreeRangeMap;
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import com.google.common.primitives.Doubles;
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import java.util.Map;
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import javax.annotation.concurrent.NotThreadSafe;
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/**
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* A mutable {@link Distribution}. Instances of this class <b>should not</b> be used to construct
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* {@link MetricPoint} instances as {@link MetricPoint} instances are supposed to represent
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* immutable values.
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*
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* @see ImmutableDistribution
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*/
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@NotThreadSafe
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public final class MutableDistribution implements Distribution {
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private final TreeRangeMap<Double, Long> intervalCounts;
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private final DistributionFitter distributionFitter;
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private double sumOfSquaredDeviation = 0.0;
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private double mean = 0.0;
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private int count = 0;
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/** Constructs an empty Distribution with the specified {@link DistributionFitter}. */
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public MutableDistribution(DistributionFitter distributionFitter) {
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this.distributionFitter = checkNotNull(distributionFitter);
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ImmutableSortedSet<Double> boundaries = distributionFitter.boundaries();
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checkArgument(boundaries.size() > 0);
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checkArgument(Ordering.natural().isOrdered(boundaries));
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this.intervalCounts = TreeRangeMap.create();
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double[] boundariesArray = Doubles.toArray(distributionFitter.boundaries());
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// Add underflow and overflow intervals
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this.intervalCounts.put(Range.lessThan(boundariesArray[0]), 0L);
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this.intervalCounts.put(Range.atLeast(boundariesArray[boundariesArray.length - 1]), 0L);
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// Add finite intervals
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for (int i = 1; i < boundariesArray.length; i++) {
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this.intervalCounts.put(Range.closedOpen(boundariesArray[i - 1], boundariesArray[i]), 0L);
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}
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}
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public void add(double value) {
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add(value, 1L);
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}
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public void add(double value, long numSamples) {
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checkArgument(numSamples > 0, "numSamples must be greater than 0");
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checkDouble(value);
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Map.Entry<Range<Double>, Long> entry = intervalCounts.getEntry(value);
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intervalCounts.put(entry.getKey(), entry.getValue() + numSamples);
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this.count += numSamples;
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// Update mean and sumOfSquaredDeviation using Welford's method
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// See Knuth, "The Art of Computer Programming", Vol. 2, page 232, 3rd edition
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double delta = value - mean;
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mean += delta * numSamples / count;
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sumOfSquaredDeviation += delta * (value - mean) * numSamples;
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}
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@Override
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public double mean() {
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return mean;
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}
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@Override
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public double sumOfSquaredDeviation() {
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return sumOfSquaredDeviation;
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}
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@Override
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public long count() {
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return count;
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}
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@Override
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public ImmutableRangeMap<Double, Long> intervalCounts() {
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return ImmutableRangeMap.copyOf(intervalCounts);
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}
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@Override
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public DistributionFitter distributionFitter() {
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return distributionFitter;
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}
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}
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