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/*
* DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS HEADER.
*
* Copyright (c) [2018-2023] Payara Foundation and/or its affiliates. All rights reserved.
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* and Distribution License("CDDL") (collectively, the "License"). You
* may not use this file except in compliance with the License. You can
* obtain a copy of the License at
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* exception as provided by the Payara Foundation in the GPL Version 2 section of the License
* file that accompanied this code.
*
* Modifications:
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* *****************************************************************************
* Copyright 2010-2013 Coda Hale and Yammer, Inc.
*
* 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
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package fish.payara.microprofile.metrics.impl;
import java.io.OutputStream;
import java.io.OutputStreamWriter;
import java.io.PrintWriter;
import static java.nio.charset.StandardCharsets.UTF_8;
import java.util.Arrays;
import java.util.Collection;
import java.util.Comparator;
import org.eclipse.microprofile.metrics.Snapshot;
/**
* A statistical snapshot of a {@link WeightedSnapshot}.
*/
public class WeightedSnapshot extends Snapshot {
private final long[] values;
private final double[] normWeights;
private final double[] quantiles;
private ConfigurationProperties configurationProperties;
/**
* Create a new {@link Snapshot} with the given values.
*
* @param values an unordered set of values in the reservoir
*/
public WeightedSnapshot(Collection values, ConfigurationProperties configurationProperties) {
this(values);
this.configurationProperties = configurationProperties;
}
public WeightedSnapshot(Collection values) {
final WeightedSample[] copy = values.toArray(new WeightedSample[]{});
Arrays.sort(copy, Comparator.comparing(w -> w.value));
this.values = new long[copy.length];
this.normWeights = new double[copy.length];
this.quantiles = new double[copy.length];
double sumWeight = 0;
for (WeightedSample sample : copy) {
sumWeight += sample.weight;
}
for (int i = 0; i < copy.length; i++) {
this.values[i] = copy[i].value;
this.normWeights[i] = sumWeight == 0d ? 0d : copy[i].weight / sumWeight;
}
for (int i = 1; i < copy.length; i++) {
this.quantiles[i] = this.quantiles[i - 1] + this.normWeights[i - 1];
}
}
/**
* Returns the number of values in the snapshot.
*
* @return the number of values
*/
@Override
public long size() {
return values.length;
}
/**
* Returns the highest value in the snapshot.
*
* @return the highest value
*/
@Override
public double getMax() {
if (values.length == 0) {
return 0;
}
return values[values.length - 1];
}
/**
* Returns the weighted arithmetic mean of the values in the snapshot.
*
* @return the weighted arithmetic mean
*/
@Override
public double getMean() {
if (values.length == 0) {
return 0;
}
double sum = 0;
for (int i = 0; i < values.length; i++) {
sum += values[i] * normWeights[i];
}
return sum;
}
@Override
public PercentileValue[] percentileValues() {
PercentileValue[] percentileValues = null;
if (configurationProperties != null) {
Double[] percentiles = configurationProperties.percentileValues();
percentileValues = new PercentileValue[percentiles.length];
for (int i = 0; i < percentiles.length; i++) {
percentileValues[i] = new PercentileValue(percentiles[i], getValue(percentiles[i]));
}
} else {
double[] percentiles = {0.5, 0.75, 0.95, 0.98, 0.99, 0.999};
if (values.length > 0 && quantiles.length > 0 && values.length == quantiles.length) {
percentileValues = new PercentileValue[percentiles.length];
for (int i = 0; i < percentiles.length; i++) {
percentileValues[i] = new PercentileValue(percentiles[i], getValue(percentiles[i]));
}
} else {
percentileValues = new PercentileValue[percentiles.length];
for (int i = 0; i < percentiles.length; i++) {
percentileValues[i] = new PercentileValue(percentiles[i], 0);
}
}
}
return percentileValues;
}
@Override
public HistogramBucket[] bucketValues() {
Double[] buckets = configurationProperties.bucketValues();
Arrays.sort(buckets);
HistogramBucket[] histogramBuckets = new HistogramBucket[buckets.length];
for (int i = 0; i < buckets.length; i++) {
histogramBuckets[i] = new HistogramBucket(buckets[i], 0);
}
return histogramBuckets;
}
private double getValue(double quantile) {
if (quantile < 0.0 || quantile > 1.0 || Double.isNaN(quantile)) {
throw new IllegalArgumentException(quantile + " is not in [0..1]");
}
if (values.length == 0) {
return 0.0;
}
int posx = Arrays.binarySearch(quantiles, quantile);
if (posx < 0) {
posx = ((-posx) - 1) - 1;
}
if (posx < 1) {
return values[0];
}
if (posx >= values.length) {
return values[values.length - 1];
}
return values[posx];
}
public long[] getValues() {
return values;
}
/**
* Writes the values of the snapshot to the given stream.
*
* @param output an output stream
*/
@Override
public void dump(OutputStream output) {
try (PrintWriter out = new PrintWriter(new OutputStreamWriter(output, UTF_8))) {
for (long value : values) {
out.printf("%d%n", value);
}
}
}
public ConfigurationProperties getConfigAdapter() {
return this.configurationProperties;
}
@Override
public String toString() {
return "Snapshot[" + size() + "]";
}
/**
* A single sample item with value and its weights for
* {@link WeightedSnapshot}.
*/
public static class WeightedSample {
public final long value;
public final double weight;
public WeightedSample(long value, double weight) {
this.value = value;
this.weight = weight;
}
}
}