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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.
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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.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.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,
                                                    boolean forceRemapGlobalOrds,
                                                    SignificanceHeuristic significanceHeuristic,
                                                    SignificantTermsAggregatorFactory termsAggFactory,
                                                    List<PipelineAggregator> pipelineAggregators,
                                                    Map<String, Object> metaData) throws IOException {
        super(name, factories, valuesSource, null, format, bucketCountThresholds, includeExclude, context, parent,
            forceRemapGlobalOrds, SubAggCollectionMode.DEPTH_FIRST, false, pipelineAggregators, metaData);
        this.significanceHeuristic = significanceHeuristic;
        this.termsAggFactory = termsAggFactory;
        this.numCollectedDocs = 0;
    }

    @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 (valueCount == 0) { // 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(valueCount, 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;
        final boolean needsFullScan = bucketOrds == null || bucketCountThresholds.getMinDocCount() == 0;
        final long maxId = needsFullScan ? valueCount : bucketOrds.size();
        for (long ord = 0; ord < maxId; ord++) {
            final long globalOrd;
            final long bucketOrd;
            if (needsFullScan) {
                bucketOrd = bucketOrds == null ? ord : bucketOrds.find(ord);
                globalOrd = ord;
            } else {
                assert bucketOrds != null;
                bucketOrd = ord;
                globalOrd = bucketOrds.get(ord);
            }
            if (includeExclude != null && !acceptedGlobalOrdinals.get(globalOrd)) {
                continue;
            }
            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(lookupGlobalOrd.apply(globalOrd), 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);
            if (spare == null) {
                consumeBucketsAndMaybeBreak(1);
            }
        }

        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, numCollectedDocs, supersetSize, significanceHeuristic, emptyList());
    }

    @Override
    protected void doClose() {
        super.doClose();
        Releasables.close(termsAggFactory);
    }
}

