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 * 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,
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package org.elasticsearch.search.aggregations.bucket.histogram;

import org.apache.lucene.index.AtomicReaderContext;
import org.apache.lucene.index.SortedNumericDocValues;
import org.apache.lucene.util.CollectionUtil;
import org.elasticsearch.common.inject.internal.Nullable;
import org.elasticsearch.common.lease.Releasables;
import org.elasticsearch.common.rounding.Rounding;
import org.elasticsearch.common.util.LongHash;
import org.elasticsearch.search.aggregations.Aggregator;
import org.elasticsearch.search.aggregations.AggregatorFactories;
import org.elasticsearch.search.aggregations.InternalAggregation;
import org.elasticsearch.search.aggregations.bucket.BucketsAggregator;
import org.elasticsearch.search.aggregations.support.AggregationContext;
import org.elasticsearch.search.aggregations.support.ValuesSource;
import org.elasticsearch.search.aggregations.support.ValuesSourceAggregatorFactory;
import org.elasticsearch.search.aggregations.support.ValuesSourceConfig;
import org.elasticsearch.search.aggregations.support.format.ValueFormatter;

import java.io.IOException;
import java.util.ArrayList;
import java.util.Collections;
import java.util.List;

public class HistogramAggregator extends BucketsAggregator {

    private final ValuesSource.Numeric valuesSource;
    private final @Nullable ValueFormatter formatter;
    private final Rounding rounding;
    private final InternalOrder order;
    private final boolean keyed;

    private final long minDocCount;
    private final ExtendedBounds extendedBounds;
    private final InternalHistogram.Factory histogramFactory;

    private final LongHash bucketOrds;
    private SortedNumericDocValues values;

    public HistogramAggregator(String name, AggregatorFactories factories, Rounding rounding, InternalOrder order,
                               boolean keyed, long minDocCount, @Nullable ExtendedBounds extendedBounds,
                               @Nullable ValuesSource.Numeric valuesSource, @Nullable ValueFormatter formatter,
                               long initialCapacity, InternalHistogram.Factory histogramFactory,
                               AggregationContext aggregationContext, Aggregator parent) {

        super(name, BucketAggregationMode.PER_BUCKET, factories, initialCapacity, aggregationContext, parent);
        this.rounding = rounding;
        this.order = order;
        this.keyed = keyed;
        this.minDocCount = minDocCount;
        this.extendedBounds = extendedBounds;
        this.valuesSource = valuesSource;
        this.formatter = formatter;
        this.histogramFactory = histogramFactory;

        bucketOrds = new LongHash(initialCapacity, aggregationContext.bigArrays());
    }

    @Override
    public boolean shouldCollect() {
        return valuesSource != null;
    }

    @Override
    public void setNextReader(AtomicReaderContext reader) {
        values = valuesSource.longValues();
    }

    @Override
    public void collect(int doc, long owningBucketOrdinal) throws IOException {
        assert owningBucketOrdinal == 0;
        values.setDocument(doc);
        final int valuesCount = values.count();

        long previousKey = Long.MIN_VALUE;
        for (int i = 0; i < valuesCount; ++i) {
            long value = values.valueAt(i);
            long key = rounding.roundKey(value);
            assert key >= previousKey;
            if (key == previousKey) {
                continue;
            }
            long bucketOrd = bucketOrds.add(key);
            if (bucketOrd < 0) { // already seen
                bucketOrd = -1 - bucketOrd;
                collectExistingBucket(doc, bucketOrd);
            } else {
                collectBucket(doc, bucketOrd);
            }
            previousKey = key;
        }
    }

    @Override
    public InternalAggregation buildAggregation(long owningBucketOrdinal) {
        assert owningBucketOrdinal == 0;
        List buckets = new ArrayList<>((int) bucketOrds.size());
        for (long i = 0; i < bucketOrds.size(); i++) {
            buckets.add(histogramFactory.createBucket(rounding.valueForKey(bucketOrds.get(i)), bucketDocCount(i), bucketAggregations(i), formatter));
        }

        CollectionUtil.introSort(buckets, order.comparator());

        // value source will be null for unmapped fields
        InternalHistogram.EmptyBucketInfo emptyBucketInfo = minDocCount == 0 ? new InternalHistogram.EmptyBucketInfo(rounding, buildEmptySubAggregations(), extendedBounds) : null;
        return histogramFactory.create(name, buckets, order, minDocCount, emptyBucketInfo, formatter, keyed);
    }

    @Override
    public InternalAggregation buildEmptyAggregation() {
        InternalHistogram.EmptyBucketInfo emptyBucketInfo = minDocCount == 0 ? new InternalHistogram.EmptyBucketInfo(rounding, buildEmptySubAggregations(), extendedBounds) : null;
        return histogramFactory.create(name, Collections.emptyList(), order, minDocCount, emptyBucketInfo, formatter, keyed);
    }

    @Override
    public void doClose() {
        Releasables.close(bucketOrds);
    }

    public static class Factory extends ValuesSourceAggregatorFactory {

        private final Rounding rounding;
        private final InternalOrder order;
        private final boolean keyed;
        private final long minDocCount;
        private final ExtendedBounds extendedBounds;
        private final InternalHistogram.Factory histogramFactory;

        public Factory(String name, ValuesSourceConfig config,
                       Rounding rounding, InternalOrder order, boolean keyed, long minDocCount,
                       ExtendedBounds extendedBounds, InternalHistogram.Factory histogramFactory) {

            super(name, histogramFactory.type(), config);
            this.rounding = rounding;
            this.order = order;
            this.keyed = keyed;
            this.minDocCount = minDocCount;
            this.extendedBounds = extendedBounds;
            this.histogramFactory = histogramFactory;
        }

        @Override
        protected Aggregator createUnmapped(AggregationContext aggregationContext, Aggregator parent) {
            return new HistogramAggregator(name, factories, rounding, order, keyed, minDocCount, null, null, config.formatter(), 0, histogramFactory, aggregationContext, parent);
        }

        @Override
        protected Aggregator create(ValuesSource.Numeric valuesSource, long expectedBucketsCount, AggregationContext aggregationContext, Aggregator parent) {
            // todo if we'll keep track of min/max values in IndexFieldData, we could use the max here to come up with a better estimation for the buckets count
            long estimatedBucketCount = 50;
            if (hasParentBucketAggregator(parent)) {
                estimatedBucketCount = 8;
            }

            // we need to round the bounds given by the user and we have to do it for every aggregator we crate
            // as the rounding is not necessarily an idempotent operation.
            // todo we need to think of a better structure to the factory/agtor code so we won't need to do that
            ExtendedBounds roundedBounds = null;
            if (extendedBounds != null) {
                // we need to process & validate here using the parser
                extendedBounds.processAndValidate(name, aggregationContext.searchContext(), config.parser());
                roundedBounds = extendedBounds.round(rounding);
            }
            return new HistogramAggregator(name, factories, rounding, order, keyed, minDocCount, roundedBounds, valuesSource, config.formatter(), estimatedBucketCount, histogramFactory, aggregationContext, parent);
        }

    }
}




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