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/*
* 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());
}
}