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org.dinky.shaded.paimon.metrics.DescriptiveStatisticsHistogramStatistics Maven / Gradle / Ivy
/*
* 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.dinky.shaded.paimon.metrics;
import org.dinky.shaded.paimon.annotation.VisibleForTesting;
import org.apache.commons.math3.exception.MathIllegalArgumentException;
import org.apache.commons.math3.stat.descriptive.DescriptiveStatistics;
import org.apache.commons.math3.stat.descriptive.UnivariateStatistic;
import org.apache.commons.math3.stat.descriptive.moment.SecondMoment;
import org.apache.commons.math3.stat.descriptive.moment.StandardDeviation;
import org.apache.commons.math3.stat.descriptive.rank.Percentile;
import org.apache.commons.math3.stat.ranking.NaNStrategy;
import java.io.Serializable;
import java.util.Arrays;
/**
* DescriptiveStatistics histogram statistics implementation returned by {@link
* DescriptiveStatisticsHistogram}.
*
* The statistics takes a point-in-time snapshot of a {@link DescriptiveStatistics} instance and
* allows optimised metrics retrieval from this.
*/
public class DescriptiveStatisticsHistogramStatistics extends HistogramStatistics
implements Serializable {
private static final long serialVersionUID = 1L;
private final CommonMetricsSnapshot statisticsSummary = new CommonMetricsSnapshot();
public DescriptiveStatisticsHistogramStatistics(
DescriptiveStatisticsHistogram.CircularDoubleArray histogramValues) {
this(histogramValues.toUnsortedArray());
}
public DescriptiveStatisticsHistogramStatistics(final double[] values) {
statisticsSummary.evaluate(values);
}
@Override
public double getQuantile(double quantile) {
return statisticsSummary.getPercentile(quantile * 100);
}
@Override
public long[] getValues() {
return Arrays.stream(statisticsSummary.getValues()).mapToLong(i -> (long) i).toArray();
}
@Override
public int size() {
return (int) statisticsSummary.getCount();
}
@Override
public double getMean() {
return statisticsSummary.getMean();
}
@Override
public double getStdDev() {
return statisticsSummary.getStandardDeviation();
}
@Override
public long getMax() {
return (long) statisticsSummary.getMax();
}
@Override
public long getMin() {
return (long) statisticsSummary.getMin();
}
/**
* Function to extract several commonly used metrics in an optimised way, i.e. with as few runs
* over the data / calculations as possible.
*
*
Note that calls to {@link #evaluate(double[])} or {@link #evaluate(double[], int, int)}
* will not return a value but instead populate this class so that further values can be
* retrieved from it.
*/
@VisibleForTesting
static class CommonMetricsSnapshot implements UnivariateStatistic, Serializable {
private static final long serialVersionUID = 2L;
private double[] data;
private double min = Double.NaN;
private double max = Double.NaN;
private double mean = Double.NaN;
private double stddev = Double.NaN;
private transient Percentile percentilesImpl;
@Override
public double evaluate(final double[] values) throws MathIllegalArgumentException {
return evaluate(values, 0, values.length);
}
@Override
public double evaluate(double[] values, int begin, int length)
throws MathIllegalArgumentException {
this.data = values;
SimpleStats secondMoment = new SimpleStats();
secondMoment.evaluate(values, begin, length);
this.mean = secondMoment.getMean();
this.min = secondMoment.getMin();
this.max = secondMoment.getMax();
this.stddev = new StandardDeviation(secondMoment).getResult();
return Double.NaN;
}
@Override
public CommonMetricsSnapshot copy() {
CommonMetricsSnapshot result = new CommonMetricsSnapshot();
result.data = Arrays.copyOf(data, data.length);
result.min = min;
result.max = max;
result.mean = mean;
result.stddev = stddev;
return result;
}
long getCount() {
return data.length;
}
double getMin() {
return min;
}
double getMax() {
return max;
}
double getMean() {
return mean;
}
double getStandardDeviation() {
return stddev;
}
double getPercentile(double p) {
maybeInitPercentile();
return percentilesImpl.evaluate(p);
}
double[] getValues() {
maybeInitPercentile();
return percentilesImpl.getData();
}
private void maybeInitPercentile() {
if (percentilesImpl == null) {
percentilesImpl = new Percentile().withNaNStrategy(NaNStrategy.FIXED);
}
if (data != null) {
percentilesImpl.setData(data);
}
}
}
/**
* Calculates min, max, mean (first moment), as well as the second moment in one go over the
* value array.
*/
private static class SimpleStats extends SecondMoment {
private static final long serialVersionUID = 1L;
private double min = Double.NaN;
private double max = Double.NaN;
@Override
public void increment(double d) {
if (d < min || Double.isNaN(min)) {
min = d;
}
if (d > max || Double.isNaN(max)) {
max = d;
}
super.increment(d);
}
@Override
public SecondMoment copy() {
SimpleStats result = new SimpleStats();
SecondMoment.copy(this, result);
result.min = min;
result.max = max;
return result;
}
public double getMin() {
return min;
}
public double getMax() {
return max;
}
public double getMean() {
return m1;
}
}
}