/* * 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 weighted avg agg * * @opensearch.internal */ public class InternalWeightedAvg extends InternalNumericMetricsAggregation.SingleValue implements WeightedAvg { private final double sum; private final double weight; InternalWeightedAvg(String name, double sum, double weight, DocValueFormat format, Map metadata) { super(name, metadata); this.sum = sum; this.weight = weight; this.format = format; } /** * Read from a stream. */ public InternalWeightedAvg(StreamInput in) throws IOException { super(in); format = in.readNamedWriteable(DocValueFormat.class); sum = in.readDouble(); weight = in.readDouble(); } @Override protected void doWriteTo(StreamOutput out) throws IOException { out.writeNamedWriteable(format); out.writeDouble(sum); out.writeDouble(weight); } @Override public double value() { return getValue(); } @Override public double getValue() { return sum / weight; } double getSum() { return sum; } double getWeight() { return weight; } DocValueFormat getFormatter() { return format; } @Override public String getWriteableName() { return WeightedAvgAggregationBuilder.NAME; } @Override public InternalWeightedAvg reduce(List aggregations, ReduceContext reduceContext) { CompensatedSum sumCompensation = new CompensatedSum(0, 0); CompensatedSum weightCompensation = new CompensatedSum(0, 0); // Compute the sum of double values with Kahan summation algorithm which is more // accurate than naive summation. for (InternalAggregation aggregation : aggregations) { InternalWeightedAvg avg = (InternalWeightedAvg) aggregation; weightCompensation.add(avg.weight); sumCompensation.add(avg.sum); } return new InternalWeightedAvg(getName(), sumCompensation.value(), weightCompensation.value(), format, getMetadata()); } @Override public XContentBuilder doXContentBody(XContentBuilder builder, Params params) throws IOException { builder.field(CommonFields.VALUE.getPreferredName(), weight != 0 ? getValue() : null); if (weight != 0 && format != DocValueFormat.RAW) { builder.field(CommonFields.VALUE_AS_STRING.getPreferredName(), format.format(getValue())); } return builder; } @Override public int hashCode() { return Objects.hash(super.hashCode(), sum, weight, format.getWriteableName()); } @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; InternalWeightedAvg other = (InternalWeightedAvg) obj; return Objects.equals(sum, other.sum) && Objects.equals(weight, other.weight) && Objects.equals(format.getWriteableName(), other.format.getWriteableName()); } }