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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.bucket.significant;
import org.apache.lucene.index.IndexReader;
import org.apache.lucene.index.LeafReaderContext;
import org.elasticsearch.common.lease.Releasables;
import org.elasticsearch.search.DocValueFormat;
import org.elasticsearch.search.aggregations.Aggregator;
import org.elasticsearch.search.aggregations.AggregatorFactories;
import org.elasticsearch.search.aggregations.LeafBucketCollector;
import org.elasticsearch.search.aggregations.LeafBucketCollectorBase;
import org.elasticsearch.search.aggregations.bucket.significant.heuristics.SignificanceHeuristic;
import org.elasticsearch.search.aggregations.bucket.terms.IncludeExclude;
import org.elasticsearch.search.aggregations.bucket.terms.LongTermsAggregator;
import org.elasticsearch.search.aggregations.pipeline.PipelineAggregator;
import org.elasticsearch.search.aggregations.support.ValuesSource;
import org.elasticsearch.search.internal.ContextIndexSearcher;
import org.elasticsearch.search.internal.SearchContext;
import java.io.IOException;
import java.util.Arrays;
import java.util.List;
import java.util.Map;
import static java.util.Collections.emptyList;
public class SignificantLongTermsAggregator extends LongTermsAggregator {
public SignificantLongTermsAggregator(String name, AggregatorFactories factories, ValuesSource.Numeric valuesSource,
DocValueFormat format, BucketCountThresholds bucketCountThresholds, SearchContext context, Aggregator parent,
SignificanceHeuristic significanceHeuristic, SignificantTermsAggregatorFactory termsAggFactory,
IncludeExclude.LongFilter includeExclude,
List pipelineAggregators, Map metaData) throws IOException {
super(name, factories, valuesSource, format, null, bucketCountThresholds, context, parent,
SubAggCollectionMode.DEPTH_FIRST, false, includeExclude, pipelineAggregators, metaData);
this.significanceHeuristic = significanceHeuristic;
this.termsAggFactory = termsAggFactory;
}
protected long numCollectedDocs;
private final SignificantTermsAggregatorFactory termsAggFactory;
private final SignificanceHeuristic significanceHeuristic;
@Override
public LeafBucketCollector getLeafCollector(LeafReaderContext ctx,
final LeafBucketCollector sub) throws IOException {
return new LeafBucketCollectorBase(super.getLeafCollector(ctx, sub), null) {
@Override
public void collect(int doc, long bucket) throws IOException {
super.collect(doc, bucket);
numCollectedDocs++;
}
};
}
@Override
public SignificantLongTerms buildAggregation(long owningBucketOrdinal) throws IOException {
assert owningBucketOrdinal == 0;
final int size = (int) Math.min(bucketOrds.size(), bucketCountThresholds.getShardSize());
long supersetSize = termsAggFactory.getSupersetNumDocs();
long subsetSize = numCollectedDocs;
BucketSignificancePriorityQueue ordered = new BucketSignificancePriorityQueue<>(size);
SignificantLongTerms.Bucket spare = null;
for (long i = 0; i < bucketOrds.size(); i++) {
final int docCount = bucketDocCount(i);
if (docCount < bucketCountThresholds.getShardMinDocCount()) {
continue;
}
if (spare == null) {
spare = new SignificantLongTerms.Bucket(0, 0, 0, 0, 0, null, format);
}
spare.term = bucketOrds.get(i);
spare.subsetDf = docCount;
spare.subsetSize = subsetSize;
spare.supersetDf = termsAggFactory.getBackgroundFrequency(spare.term);
spare.supersetSize = supersetSize;
// During shard-local down-selection we use subset/superset stats that are for this shard only
// Back at the central reducer these properties will be updated with global stats
spare.updateScore(significanceHeuristic);
spare.bucketOrd = i;
spare = ordered.insertWithOverflow(spare);
if (spare == null) {
consumeBucketsAndMaybeBreak(1);
}
}
final SignificantLongTerms.Bucket[] list = new SignificantLongTerms.Bucket[ordered.size()];
for (int i = ordered.size() - 1; i >= 0; i--) {
final SignificantLongTerms.Bucket bucket = ordered.pop();
bucket.aggregations = bucketAggregations(bucket.bucketOrd);
list[i] = bucket;
}
return new SignificantLongTerms(name, bucketCountThresholds.getRequiredSize(), bucketCountThresholds.getMinDocCount(),
pipelineAggregators(), metaData(), format, subsetSize, supersetSize, significanceHeuristic, Arrays.asList(list));
}
@Override
public SignificantLongTerms buildEmptyAggregation() {
// We need to account for the significance of a miss in our global stats - provide corpus size as context
ContextIndexSearcher searcher = context.searcher();
IndexReader topReader = searcher.getIndexReader();
int supersetSize = topReader.numDocs();
return new SignificantLongTerms(name, bucketCountThresholds.getRequiredSize(), bucketCountThresholds.getMinDocCount(),
pipelineAggregators(), metaData(), format, 0, supersetSize, significanceHeuristic, emptyList());
}
@Override
public void doClose() {
Releasables.close(bucketOrds, termsAggFactory);
}
}