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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.index.SortedSetDocValues; import org.apache.lucene.util.BytesRef; import org.elasticsearch.common.lease.Releasables; import org.elasticsearch.common.util.LongHash; 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.GlobalOrdinalsStringTermsAggregator; import org.elasticsearch.search.aggregations.bucket.terms.support.IncludeExclude; 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; /** * An global ordinal based implementation of significant terms, based on {@link SignificantStringTermsAggregator}. */ public class GlobalOrdinalsSignificantTermsAggregator extends GlobalOrdinalsStringTermsAggregator { protected long numCollectedDocs; protected final SignificantTermsAggregatorFactory termsAggFactory; private final SignificanceHeuristic significanceHeuristic; public GlobalOrdinalsSignificantTermsAggregator(String name, AggregatorFactories factories, ValuesSource.Bytes.WithOrdinals.FieldData valuesSource, DocValueFormat format, BucketCountThresholds bucketCountThresholds, IncludeExclude.OrdinalsFilter includeExclude, SearchContext context, Aggregator parent, SignificanceHeuristic significanceHeuristic, SignificantTermsAggregatorFactory termsAggFactory, List<PipelineAggregator> pipelineAggregators, Map<String, Object> metaData) throws IOException { super(name, factories, valuesSource, null, format, bucketCountThresholds, includeExclude, context, parent, SubAggCollectionMode.DEPTH_FIRST, false, pipelineAggregators, metaData); this.significanceHeuristic = significanceHeuristic; 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.getSupersetNumDocs(); long subsetSize = numCollectedDocs; BucketSignificancePriorityQueue<SignificantStringTerms.Bucket> 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, format); } 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(significanceHeuristic); spare = ordered.insertWithOverflow(spare); } final SignificantStringTerms.Bucket[] list = new SignificantStringTerms.Bucket[ordered.size()]; for (int i = ordered.size() - 1; i >= 0; i--) { final SignificantStringTerms.Bucket 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(name, bucketCountThresholds.getRequiredSize(), bucketCountThresholds.getMinDocCount(), pipelineAggregators(), metaData(), format, subsetSize, supersetSize, significanceHeuristic, Arrays.asList(list)); } @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.searcher(); IndexReader topReader = searcher.getIndexReader(); int supersetSize = topReader.numDocs(); return new SignificantStringTerms(name, bucketCountThresholds.getRequiredSize(), bucketCountThresholds.getMinDocCount(), pipelineAggregators(), metaData(), format, 0, supersetSize, significanceHeuristic, emptyList()); } @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, DocValueFormat format, BucketCountThresholds bucketCountThresholds, IncludeExclude.OrdinalsFilter includeExclude, SearchContext context, Aggregator parent, SignificanceHeuristic significanceHeuristic, SignificantTermsAggregatorFactory termsAggFactory, List<PipelineAggregator> pipelineAggregators, Map<String, Object> metaData) throws IOException { super(name, factories, valuesSource, format, bucketCountThresholds, includeExclude, context, parent, significanceHeuristic, termsAggFactory, pipelineAggregators, metaData); bucketOrds = new LongHash(1, context.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++; if (globalOrds.advanceExact(doc)) { for (long globalOrd = globalOrds.nextOrd(); globalOrd != SortedSetDocValues.NO_MORE_ORDS; globalOrd = globalOrds.nextOrd()) { 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); } } }