epotyom commented on code in PR #14204: URL: https://github.com/apache/lucene/pull/14204#discussion_r1959444929
########## lucene/sandbox/src/java/org/apache/lucene/sandbox/facet/plain/histograms/HistogramCollector.java: ########## @@ -0,0 +1,274 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF 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.apache.lucene.sandbox.facet.plain.histograms; + +import java.io.IOException; +import org.apache.lucene.index.DocValues; +import org.apache.lucene.index.DocValuesSkipper; +import org.apache.lucene.index.DocValuesType; +import org.apache.lucene.index.FieldInfo; +import org.apache.lucene.index.LeafReaderContext; +import org.apache.lucene.index.NumericDocValues; +import org.apache.lucene.index.SortedNumericDocValues; +import org.apache.lucene.internal.hppc.LongIntHashMap; +import org.apache.lucene.search.CollectionTerminatedException; +import org.apache.lucene.search.Collector; +import org.apache.lucene.search.LeafCollector; +import org.apache.lucene.search.Scorable; +import org.apache.lucene.search.ScoreMode; + +final class HistogramCollector implements Collector { + + private final String field; + private final long bucketWidth; + private final int maxBuckets; + private final LongIntHashMap counts; + + HistogramCollector(String field, long bucketWidth, int maxBuckets) { + this.field = field; + this.bucketWidth = bucketWidth; + this.maxBuckets = maxBuckets; + this.counts = new LongIntHashMap(); + } + + @Override + public LeafCollector getLeafCollector(LeafReaderContext context) throws IOException { + FieldInfo fi = context.reader().getFieldInfos().fieldInfo(field); + if (fi == null) { + // The segment has no values, nothing to do. + throw new CollectionTerminatedException(); + } + if (fi.getDocValuesType() != DocValuesType.NUMERIC + && fi.getDocValuesType() != DocValuesType.SORTED_NUMERIC) { + throw new IllegalStateException( + "Expected numeric field, but got doc-value type: " + fi.getDocValuesType()); + } + SortedNumericDocValues values = DocValues.getSortedNumeric(context.reader(), field); + NumericDocValues singleton = DocValues.unwrapSingleton(values); + if (singleton == null) { + return new HistogramNaiveLeafCollector(values, bucketWidth, maxBuckets, counts); + } else { + DocValuesSkipper skipper = context.reader().getDocValuesSkipper(field); + if (skipper != null) { + long leafMinBucket = Math.floorDiv(skipper.minValue(), bucketWidth); + long leafMaxBucket = Math.floorDiv(skipper.maxValue(), bucketWidth); + if (leafMaxBucket - leafMinBucket <= 1024) { + // Only use the optimized implementation if there is a small number of unique buckets, + // so that we can count them using a dense array instead of a hash table. This helps save + // the overhead of hashing and collision resolution. + return new HistogramLeafCollector(singleton, skipper, bucketWidth, maxBuckets, counts); + } + } + return new HistogramNaiveSingleValuedLeafCollector( + singleton, bucketWidth, maxBuckets, counts); + } + } + + @Override + public ScoreMode scoreMode() { + return ScoreMode.COMPLETE_NO_SCORES; + } + + LongIntHashMap getCounts() { + return counts; + } + + /** + * Naive implementation of a histogram {@link LeafCollector}, which iterates all maches and looks + * up the value to determine the corresponding bucket. + */ + private static class HistogramNaiveLeafCollector implements LeafCollector { + + private final SortedNumericDocValues values; + private final long bucketWidth; + private final int maxBuckets; + private final LongIntHashMap counts; + + HistogramNaiveLeafCollector( + SortedNumericDocValues values, long bucketWidth, int maxBuckets, LongIntHashMap counts) { + this.values = values; + this.bucketWidth = bucketWidth; + this.maxBuckets = maxBuckets; + this.counts = counts; + } + + @Override + public void setScorer(Scorable scorer) throws IOException {} + + @Override + public void collect(int doc) throws IOException { + if (values.advanceExact(doc)) { + int valueCount = values.docValueCount(); + long prevBucket = Long.MIN_VALUE; + for (int i = 0; i < valueCount; ++i) { + final long value = values.nextValue(); + final long bucket = Math.floorDiv(value, bucketWidth); + // We must not double-count values that map to the same bucket since this returns doc + // counts as opposed to value counts. + if (bucket != prevBucket) { + counts.addTo(bucket, 1); + checkMaxBuckets(counts.size(), maxBuckets); + prevBucket = bucket; + } + } + } + } + } + + /** + * Naive implementation of a histogram {@link LeafCollector}, which iterates all maches and looks + * up the value to determine the corresponding bucket. + */ + private static class HistogramNaiveSingleValuedLeafCollector implements LeafCollector { + + private final NumericDocValues values; + private final long bucketWidth; + private final int maxBuckets; + private final LongIntHashMap counts; + + HistogramNaiveSingleValuedLeafCollector( + NumericDocValues values, long bucketWidth, int maxBuckets, LongIntHashMap counts) { + this.values = values; + this.bucketWidth = bucketWidth; + this.maxBuckets = maxBuckets; + this.counts = counts; + } + + @Override + public void setScorer(Scorable scorer) throws IOException {} + + @Override + public void collect(int doc) throws IOException { + if (values.advanceExact(doc)) { + final long value = values.longValue(); + final long bucket = Math.floorDiv(value, bucketWidth); + counts.addTo(bucket, 1); + checkMaxBuckets(counts.size(), maxBuckets); + } + } + } + + /** + * Optimized histogram {@link LeafCollector}, that takes advantage of the doc-values index to + * speed up collection. + */ + private static class HistogramLeafCollector implements LeafCollector { + + private final NumericDocValues values; + private final DocValuesSkipper skipper; + private final long bucketWidth; + private final int maxBuckets; + private final int[] counts; + private final long leafMinBucket; + private final LongIntHashMap collectorCounts; + + /** Max doc ID (inclusive) up to which all docs values may map to the same bucket. */ + private int upToInclusive = -1; + + /** Whether all docs up to {@link #upToInclusive} values map to the same bucket. */ + private boolean upToSameBucket; + + /** Index in {@link #counts} for docs up to {@link #upToInclusive}. */ + private int upToBucketIndex; + + HistogramLeafCollector( + NumericDocValues values, + DocValuesSkipper skipper, + long bucketWidth, + int maxBuckets, + LongIntHashMap collectorCounts) { + this.values = values; + this.skipper = skipper; + this.bucketWidth = bucketWidth; + this.maxBuckets = maxBuckets; + this.collectorCounts = collectorCounts; + + leafMinBucket = Math.floorDiv(skipper.minValue(), bucketWidth); + long leafMaxBucket = Math.floorDiv(skipper.maxValue(), bucketWidth); + counts = new int[Math.toIntExact(leafMaxBucket - leafMinBucket + 1)]; Review Comment: Maybe fallback to `HistogramNaiveLeafCollector` instead of throwing `ArithmeticException` when array size overflows an int, to avoid this hidden limitation? -- This is an automated message from the Apache Git Service. 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