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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.apache.lucene.util.BytesRef;
import org.elasticsearch.common.lease.Releasables;
import org.elasticsearch.common.util.LongHash;
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.terms.GlobalOrdinalsStringTermsAggregator;
import org.elasticsearch.search.aggregations.bucket.terms.support.IncludeExclude;
import org.elasticsearch.search.aggregations.pipeline.PipelineAggregator;
import org.elasticsearch.search.aggregations.support.AggregationContext;
import org.elasticsearch.search.aggregations.support.ValuesSource;
import org.elasticsearch.search.internal.ContextIndexSearcher;
import java.io.IOException;
import java.util.Arrays;
import java.util.Collections;
import java.util.List;
import java.util.Map;
/**
* An global ordinal based implementation of significant terms, based on {@link SignificantStringTermsAggregator}.
*/
public class GlobalOrdinalsSignificantTermsAggregator extends GlobalOrdinalsStringTermsAggregator {
protected long numCollectedDocs;
protected final SignificantTermsAggregatorFactory termsAggFactory;
public GlobalOrdinalsSignificantTermsAggregator(String name, AggregatorFactories factories,
ValuesSource.Bytes.WithOrdinals.FieldData valuesSource, BucketCountThresholds bucketCountThresholds,
IncludeExclude.OrdinalsFilter includeExclude, AggregationContext aggregationContext, Aggregator parent,
SignificantTermsAggregatorFactory termsAggFactory, List pipelineAggregators, Map metaData)
throws IOException {
super(name, factories, valuesSource, null, bucketCountThresholds, includeExclude, aggregationContext, parent,
SubAggCollectionMode.DEPTH_FIRST, false, pipelineAggregators, metaData);
this.termsAggFactory = termsAggFactory;
}
@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 SignificantStringTerms buildAggregation(long owningBucketOrdinal) throws IOException {
assert owningBucketOrdinal == 0;
if (globalOrds == null) { // no context in this reader
return buildEmptyAggregation();
}
final int size;
if (bucketCountThresholds.getMinDocCount() == 0) {
// if minDocCount == 0 then we can end up with more buckets then maxBucketOrd() returns
size = (int) Math.min(globalOrds.getValueCount(), bucketCountThresholds.getShardSize());
} else {
size = (int) Math.min(maxBucketOrd(), bucketCountThresholds.getShardSize());
}
long supersetSize = termsAggFactory.prepareBackground(context);
long subsetSize = numCollectedDocs;
BucketSignificancePriorityQueue ordered = new BucketSignificancePriorityQueue(size);
SignificantStringTerms.Bucket spare = null;
for (long globalTermOrd = 0; globalTermOrd < globalOrds.getValueCount(); ++globalTermOrd) {
if (includeExclude != null && !acceptedGlobalOrdinals.get(globalTermOrd)) {
continue;
}
final long bucketOrd = getBucketOrd(globalTermOrd);
final int bucketDocCount = bucketOrd < 0 ? 0 : bucketDocCount(bucketOrd);
if (bucketCountThresholds.getMinDocCount() > 0 && bucketDocCount == 0) {
continue;
}
if (bucketDocCount < bucketCountThresholds.getShardMinDocCount()) {
continue;
}
if (spare == null) {
spare = new SignificantStringTerms.Bucket(new BytesRef(), 0, 0, 0, 0, null);
}
spare.bucketOrd = bucketOrd;
copy(globalOrds.lookupOrd(globalTermOrd), spare.termBytes);
spare.subsetDf = bucketDocCount;
spare.subsetSize = subsetSize;
spare.supersetDf = termsAggFactory.getBackgroundFrequency(spare.termBytes);
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(termsAggFactory.getSignificanceHeuristic());
spare = (SignificantStringTerms.Bucket) ordered.insertWithOverflow(spare);
}
final InternalSignificantTerms.Bucket[] list = new InternalSignificantTerms.Bucket[ordered.size()];
for (int i = ordered.size() - 1; i >= 0; i--) {
final SignificantStringTerms.Bucket bucket = (SignificantStringTerms.Bucket) ordered.pop();
// the terms are owned by the BytesRefHash, we need to pull a copy since the BytesRef hash data may be recycled at some point
bucket.termBytes = BytesRef.deepCopyOf(bucket.termBytes);
bucket.aggregations = bucketAggregations(bucket.bucketOrd);
list[i] = bucket;
}
return new SignificantStringTerms(subsetSize, supersetSize, name, bucketCountThresholds.getRequiredSize(),
bucketCountThresholds.getMinDocCount(), termsAggFactory.getSignificanceHeuristic(), Arrays.asList(list), pipelineAggregators(),
metaData());
}
@Override
public SignificantStringTerms buildEmptyAggregation() {
// We need to account for the significance of a miss in our global stats - provide corpus size as context
ContextIndexSearcher searcher = context.searchContext().searcher();
IndexReader topReader = searcher.getIndexReader();
int supersetSize = topReader.numDocs();
return new SignificantStringTerms(0, supersetSize, name, bucketCountThresholds.getRequiredSize(),
bucketCountThresholds.getMinDocCount(), termsAggFactory.getSignificanceHeuristic(),
Collections. emptyList(), pipelineAggregators(), metaData());
}
@Override
protected void doClose() {
Releasables.close(termsAggFactory);
}
public static class WithHash extends GlobalOrdinalsSignificantTermsAggregator {
private final LongHash bucketOrds;
public WithHash(String name, AggregatorFactories factories, ValuesSource.Bytes.WithOrdinals.FieldData valuesSource,
BucketCountThresholds bucketCountThresholds, IncludeExclude.OrdinalsFilter includeExclude,
AggregationContext aggregationContext, Aggregator parent, SignificantTermsAggregatorFactory termsAggFactory,
List pipelineAggregators, Map metaData) throws IOException {
super(name, factories, valuesSource, bucketCountThresholds, includeExclude, aggregationContext, parent, termsAggFactory,
pipelineAggregators, metaData);
bucketOrds = new LongHash(1, aggregationContext.bigArrays());
}
@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 {
assert bucket == 0;
numCollectedDocs++;
globalOrds.setDocument(doc);
final int numOrds = globalOrds.cardinality();
for (int i = 0; i < numOrds; i++) {
final long globalOrd = globalOrds.ordAt(i);
long bucketOrd = bucketOrds.add(globalOrd);
if (bucketOrd < 0) {
bucketOrd = -1 - bucketOrd;
collectExistingBucket(sub, doc, bucketOrd);
} else {
collectBucket(sub, doc, bucketOrd);
}
}
}
};
}
@Override
protected long getBucketOrd(long termOrd) {
return bucketOrds.find(termOrd);
}
@Override
protected void doClose() {
Releasables.close(termsAggFactory, bucketOrds);
}
}
}