mccullocht commented on code in PR #15169: URL: https://github.com/apache/lucene/pull/15169#discussion_r2350130404
########## lucene/core/src/java/org/apache/lucene/codecs/lucene104/Lucene104ScalarQuantizedVectorsFormat.java: ########## @@ -0,0 +1,206 @@ +/* + * 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.codecs.lucene104; + +import java.io.IOException; +import java.util.Optional; +import org.apache.lucene.codecs.hnsw.FlatVectorScorerUtil; +import org.apache.lucene.codecs.hnsw.FlatVectorsFormat; +import org.apache.lucene.codecs.hnsw.FlatVectorsReader; +import org.apache.lucene.codecs.hnsw.FlatVectorsWriter; +import org.apache.lucene.codecs.lucene99.Lucene99FlatVectorsFormat; +import org.apache.lucene.index.SegmentReadState; +import org.apache.lucene.index.SegmentWriteState; + +/** + * The quantization format used here is a per-vector optimized scalar quantization. These ideas are + * evolutions of LVQ proposed in <a href="https://arxiv.org/abs/2304.04759";>Similarity search in the + * blink of an eye with compressed indices</a> by Cecilia Aguerrebere et al., the previous work on + * globally optimized scalar quantization in Apache Lucene, and <a + * href="https://arxiv.org/abs/1908.10396";>Accelerating Large-Scale Inference with Anisotropic + * Vector Quantization </a> by Ruiqi Guo et. al. Also see {@link + * org.apache.lucene.util.quantization.OptimizedScalarQuantizer}. Some of key features are: + * + * <ul> + * <li>Estimating the distance between two vectors using their centroid centered distance. This + * requires some additional corrective factors, but allows for centroid centering to occur. + * <li>Optimized scalar quantization to single bit level of centroid centered vectors. + * <li>Asymmetric quantization of vectors, where query vectors are quantized to half-byte (4 bits) + * precision (normalized to the centroid) and then compared directly against the single bit + * quantized vectors in the index. + * <li>Transforming the half-byte quantized query vectors in such a way that the comparison with + * single bit vectors can be done with bit arithmetic. + * </ul> + * + * A previous work related to improvements over regular LVQ is <a + * href="https://arxiv.org/abs/2409.09913";>Practical and Asymptotically Optimal Quantization of + * High-Dimensional Vectors in Euclidean Space for Approximate Nearest Neighbor Search </a> by + * Jianyang Gao, et. al. + * + * <p>The format is stored within two files: + * + * <h2>.veq (vector data) file</h2> + * + * <p>Stores the quantized vectors in a flat format. Additionally, it stores each vector's + * corrective factors. At the end of the file, additional information is stored for vector ordinal + * to centroid ordinal mapping and sparse vector information. + * + * <ul> + * <li>For each vector: + * <ul> + * <li><b>[byte]</b> the quantized values. Each dimension may be up to 8 bits, and multiple + * dimensions may be packed into a single byte. + * <li><b>[float]</b> the optimized quantiles and an additional similarity dependent + * corrective factor. + * <li><b>[int]</b> the sum of the quantized components + * </ul> + * <li>After the vectors, sparse vector information keeping track of monotonic blocks. + * </ul> + * + * <h2>.vemq (vector metadata) file</h2> + * + * <p>Stores the metadata for the vectors. This includes the number of vectors, the number of + * dimensions, and file offset information. + * + * <ul> + * <li><b>int</b> the field number + * <li><b>int</b> the vector encoding ordinal + * <li><b>int</b> the vector similarity ordinal + * <li><b>vint</b> the vector dimensions + * <li><b>vlong</b> the offset to the vector data in the .veq file + * <li><b>vlong</b> the length of the vector data in the .veq file + * <li><b>vint</b> the number of vectors + * <li><b>vint</b> the wire number for ScalarEncoding + * <li><b>[float]</b> the centroid + * <li><b>float</b> the centroid square magnitude + * <li>The sparse vector information, if required, mapping vector ordinal to doc ID + * </ul> + */ +public class Lucene104ScalarQuantizedVectorsFormat extends FlatVectorsFormat { + public static final String QUANTIZED_VECTOR_COMPONENT = "QVEC"; + public static final String NAME = "Lucene104ScalarQuantizedVectorsFormat"; + + static final int VERSION_START = 0; + static final int VERSION_CURRENT = VERSION_START; + static final String META_CODEC_NAME = "Lucene104ScalarQuantizedVectorsFormatMeta"; + static final String VECTOR_DATA_CODEC_NAME = "Lucene104ScalarQuantizedVectorsFormatData"; + static final String META_EXTENSION = "vemq"; + static final String VECTOR_DATA_EXTENSION = "veq"; + static final int DIRECT_MONOTONIC_BLOCK_SHIFT = 16; + + private static final FlatVectorsFormat rawVectorFormat = + new Lucene99FlatVectorsFormat(FlatVectorScorerUtil.getLucene99FlatVectorsScorer()); + + private static final Lucene104ScalarQuantizedVectorScorer scorer = + new Lucene104ScalarQuantizedVectorScorer(FlatVectorScorerUtil.getLucene99FlatVectorsScorer()); + + private final ScalarEncoding encoding; + + /** + * Allowed encodings for scalar quantization. + * + * <p>This specifies how many bits are used per dimension and also dictates packing of dimensions + * into a byte stream. + */ + public enum ScalarEncoding { + /** Each dimension is quantized to 8 bits and treated as an unsigned value. */ + UNSIGNED_BYTE(0, (byte) 8), Review Comment: Added a SEVEN_BITS enum, but documented that 8 bits is preferred. -- This is an automated message from the Apache Git Service. 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