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/*
* 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.
*/
package org.elasticsearch.search.aggregations.matrix.stats;
import org.apache.lucene.index.LeafReaderContext;
import org.elasticsearch.common.lease.Releasables;
import org.elasticsearch.common.util.BigArrays;
import org.elasticsearch.common.util.ObjectArray;
import org.elasticsearch.index.fielddata.NumericDoubleValues;
import org.elasticsearch.search.MultiValueMode;
import org.elasticsearch.search.aggregations.Aggregator;
import org.elasticsearch.search.aggregations.InternalAggregation;
import org.elasticsearch.search.aggregations.LeafBucketCollector;
import org.elasticsearch.search.aggregations.LeafBucketCollectorBase;
import org.elasticsearch.search.aggregations.metrics.MetricsAggregator;
import org.elasticsearch.search.aggregations.pipeline.PipelineAggregator;
import org.elasticsearch.search.aggregations.support.MultiValuesSource.NumericMultiValuesSource;
import org.elasticsearch.search.aggregations.support.ValuesSource;
import org.elasticsearch.search.internal.SearchContext;
import java.io.IOException;
import java.util.List;
import java.util.Map;
/**
* Metric Aggregation for computing the pearson product correlation coefficient between multiple fields
**/
public class MatrixStatsAggregator extends MetricsAggregator {
/** Multiple ValuesSource with field names */
final NumericMultiValuesSource valuesSources;
/** array of descriptive stats, per shard, needed to compute the correlation */
ObjectArray<RunningStats> stats;
public MatrixStatsAggregator(String name, Map<String, ValuesSource.Numeric> valuesSources, SearchContext context,
Aggregator parent, MultiValueMode multiValueMode, List<PipelineAggregator> pipelineAggregators,
Map<String,Object> metaData) throws IOException {
super(name, context, parent, pipelineAggregators, metaData);
if (valuesSources != null && !valuesSources.isEmpty()) {
this.valuesSources = new NumericMultiValuesSource(valuesSources, multiValueMode);
stats = context.bigArrays().newObjectArray(1);
} else {
this.valuesSources = null;
}
}
@Override
public boolean needsScores() {
return (valuesSources == null) ? false : valuesSources.needsScores();
}
@Override
public LeafBucketCollector getLeafCollector(LeafReaderContext ctx,
final LeafBucketCollector sub) throws IOException {
if (valuesSources == null) {
return LeafBucketCollector.NO_OP_COLLECTOR;
}
final BigArrays bigArrays = context.bigArrays();
final NumericDoubleValues[] values = new NumericDoubleValues[valuesSources.fieldNames().length];
for (int i = 0; i < values.length; ++i) {
values[i] = valuesSources.getField(i, ctx);
}
return new LeafBucketCollectorBase(sub, values) {
final String[] fieldNames = valuesSources.fieldNames();
final double[] fieldVals = new double[fieldNames.length];
@Override
public void collect(int doc, long bucket) throws IOException {
// get fields
if (includeDocument(doc) == true) {
stats = bigArrays.grow(stats, bucket + 1);
RunningStats stat = stats.get(bucket);
// add document fields to correlation stats
if (stat == null) {
stat = new RunningStats(fieldNames, fieldVals);
stats.set(bucket, stat);
} else {
stat.add(fieldNames, fieldVals);
}
}
}
/**
* return a map of field names and data
*/
private boolean includeDocument(int doc) throws IOException {
// loop over fields
for (int i = 0; i < fieldVals.length; ++i) {
final NumericDoubleValues doubleValues = values[i];
if (doubleValues.advanceExact(doc)) {
final double value = doubleValues.doubleValue();
if (value == Double.NEGATIVE_INFINITY) {
// TODO: Fix matrix stats to treat neg inf as any other value
return false;
}
fieldVals[i] = value;
} else {
return false;
}
}
return true;
}
};
}
@Override
public InternalAggregation buildAggregation(long bucket) {
if (valuesSources == null || bucket >= stats.size()) {
return buildEmptyAggregation();
}
return new InternalMatrixStats(name, stats.size(), stats.get(bucket), null, pipelineAggregators(), metaData());
}
@Override
public InternalAggregation buildEmptyAggregation() {
return new InternalMatrixStats(name, 0, null, null, pipelineAggregators(), metaData());
}
@Override
public void doClose() {
Releasables.close(stats);
}
}
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