/* * SPDX-License-Identifier: Apache-2.0 * * The OpenSearch Contributors require contributions made to * this file be licensed under the Apache-2.0 license or a * compatible open source license. */ /* * Licensed to Elasticsearch under one or more contributor * license agreements. See the NOTICE file distributed with * this work for additional information regarding copyright * ownership. Elasticsearch 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. */ /* * Modifications Copyright OpenSearch Contributors. See * GitHub history for details. */ package org.opensearch.search.aggregations.metrics; import org.opensearch.core.common.io.stream.StreamInput; import org.opensearch.core.common.io.stream.StreamOutput; import org.opensearch.core.xcontent.XContentBuilder; import org.opensearch.search.DocValueFormat; import org.opensearch.search.aggregations.InternalAggregation; import java.io.IOException; import java.util.List; import java.util.Map; import java.util.Objects; /** * Implementation of stats agg * * @opensearch.internal */ public class InternalStats extends InternalNumericMetricsAggregation.MultiValue implements Stats { /** * The metrics for the internal stats * * @opensearch.internal */ enum Metrics { count, sum, min, max, avg; public static Metrics resolve(String name) { return Metrics.valueOf(name); } } protected final long count; protected final double min; protected final double max; protected final double sum; public InternalStats( String name, long count, double sum, double min, double max, DocValueFormat formatter, Map metadata ) { super(name, metadata); this.count = count; this.sum = sum; this.min = min; this.max = max; this.format = formatter; } /** * Read from a stream. */ public InternalStats(StreamInput in) throws IOException { super(in); format = in.readNamedWriteable(DocValueFormat.class); count = in.readVLong(); min = in.readDouble(); max = in.readDouble(); sum = in.readDouble(); } @Override protected final void doWriteTo(StreamOutput out) throws IOException { out.writeNamedWriteable(format); out.writeVLong(count); out.writeDouble(min); out.writeDouble(max); out.writeDouble(sum); writeOtherStatsTo(out); } protected void writeOtherStatsTo(StreamOutput out) throws IOException {} @Override public String getWriteableName() { return StatsAggregationBuilder.NAME; } @Override public long getCount() { return count; } @Override public double getMin() { return min; } @Override public double getMax() { return max; } @Override public double getAvg() { return sum / count; } @Override public double getSum() { return sum; } @Override public String getMinAsString() { return valueAsString(Metrics.min.name()); } @Override public String getMaxAsString() { return valueAsString(Metrics.max.name()); } @Override public String getAvgAsString() { return valueAsString(Metrics.avg.name()); } @Override public String getSumAsString() { return valueAsString(Metrics.sum.name()); } @Override public double value(String name) { Metrics metrics = Metrics.valueOf(name); switch (metrics) { case min: return this.min; case max: return this.max; case avg: return this.getAvg(); case count: return this.count; case sum: return this.sum; default: throw new IllegalArgumentException("Unknown value [" + name + "] in common stats aggregation"); } } @Override public InternalStats reduce(List aggregations, ReduceContext reduceContext) { long count = 0; double min = Double.POSITIVE_INFINITY; double max = Double.NEGATIVE_INFINITY; CompensatedSum kahanSummation = new CompensatedSum(0, 0); for (InternalAggregation aggregation : aggregations) { InternalStats stats = (InternalStats) aggregation; count += stats.getCount(); min = Math.min(min, stats.getMin()); max = Math.max(max, stats.getMax()); // Compute the sum of double values with Kahan summation algorithm which is more // accurate than naive summation. kahanSummation.add(stats.getSum()); } return new InternalStats(name, count, kahanSummation.value(), min, max, format, getMetadata()); } /** * Fields for stats agg * * @opensearch.internal */ static class Fields { public static final String COUNT = "count"; public static final String MIN = "min"; public static final String MIN_AS_STRING = "min_as_string"; public static final String MAX = "max"; public static final String MAX_AS_STRING = "max_as_string"; public static final String AVG = "avg"; public static final String AVG_AS_STRING = "avg_as_string"; public static final String SUM = "sum"; public static final String SUM_AS_STRING = "sum_as_string"; } @Override public XContentBuilder doXContentBody(XContentBuilder builder, Params params) throws IOException { builder.field(Fields.COUNT, count); if (count != 0) { builder.field(Fields.MIN, min); builder.field(Fields.MAX, max); builder.field(Fields.AVG, getAvg()); builder.field(Fields.SUM, sum); if (format != DocValueFormat.RAW) { builder.field(Fields.MIN_AS_STRING, format.format(min)); builder.field(Fields.MAX_AS_STRING, format.format(max)); builder.field(Fields.AVG_AS_STRING, format.format(getAvg())); builder.field(Fields.SUM_AS_STRING, format.format(sum)); } } else { builder.nullField(Fields.MIN); builder.nullField(Fields.MAX); builder.nullField(Fields.AVG); builder.field(Fields.SUM, 0.0d); } otherStatsToXContent(builder, params); return builder; } protected XContentBuilder otherStatsToXContent(XContentBuilder builder, Params params) throws IOException { return builder; } @Override public int hashCode() { return Objects.hash(super.hashCode(), count, min, max, sum); } @Override public boolean equals(Object obj) { if (this == obj) return true; if (obj == null || getClass() != obj.getClass()) return false; if (super.equals(obj) == false) return false; InternalStats other = (InternalStats) obj; return count == other.count && Double.compare(min, other.min) == 0 && Double.compare(max, other.max) == 0 && Double.compare(sum, other.sum) == 0; } }