vigyasharma commented on code in PR #15613: URL: https://github.com/apache/lucene/pull/15613#discussion_r2728750810
########## lucene/core/src/java/org/apache/lucene/codecs/spann/Lucene99SpannVectorsReader.java: ########## @@ -0,0 +1,470 @@ +/* + * 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.spann; + +import java.io.IOException; +import java.util.HashMap; +import java.util.Map; +import org.apache.lucene.codecs.CodecUtil; +import org.apache.lucene.codecs.KnnVectorsFormat; +import org.apache.lucene.codecs.KnnVectorsReader; +import org.apache.lucene.index.ByteVectorValues; +import org.apache.lucene.index.FieldInfo; +import org.apache.lucene.index.FloatVectorValues; +import org.apache.lucene.index.IndexFileNames; +import org.apache.lucene.index.SegmentReadState; +import org.apache.lucene.index.VectorEncoding; +import org.apache.lucene.search.AcceptDocs; +import org.apache.lucene.search.DocIdSetIterator; +import org.apache.lucene.search.KnnCollector; +import org.apache.lucene.search.ScoreDoc; +import org.apache.lucene.search.TopDocs; +import org.apache.lucene.search.TopKnnCollector; +import org.apache.lucene.search.VectorScorer; +import org.apache.lucene.store.IndexInput; +import org.apache.lucene.util.Bits; +import org.apache.lucene.util.IOUtils; + +/** + * Reader for SPANN (HNSW-IVF) vectors. + * + * @lucene.experimental + */ +public class Lucene99SpannVectorsReader extends KnnVectorsReader { + + private final KnnVectorsReader centroidDelegate; + private final Map<String, SpannFieldEntry> fields = new HashMap<>(); + private final int nprobe; + + public Lucene99SpannVectorsReader( + SegmentReadState state, KnnVectorsFormat centroidFormat, int nprobe) throws IOException { + this.nprobe = nprobe; + this.centroidDelegate = centroidFormat.fieldsReader(state); + + for (FieldInfo fieldInfo : state.fieldInfos) { + if (fieldInfo.hasVectorValues()) { + String metaFileName = + IndexFileNames.segmentFileName( + state.segmentInfo.name, state.segmentSuffix, fieldInfo.name + ".spam"); + String dataFileName = + IndexFileNames.segmentFileName( + state.segmentInfo.name, state.segmentSuffix, fieldInfo.name + ".spad"); + + IndexInput metaIn = null; + IndexInput dataIn = null; + boolean success = false; + + try { + // Probe for the "spam" (Meta) file. + // If it's missing, this field is likely managed by another codec (e.g., HNSW). + // We must catch this to allow mixed-codec segments. + metaIn = state.directory.openInput(metaFileName, state.context); + } catch (java.nio.file.NoSuchFileException | java.io.FileNotFoundException _) { + continue; + } + + try { + // If we found the meta file, we assume this IS a SPANN field. + // Any subsequent missing files (like .spad) or corruption MUST throw an + // exception. + CodecUtil.checkIndexHeader( + metaIn, "Lucene99SpannMeta", 0, 0, state.segmentInfo.getId(), state.segmentSuffix); + + int totalSize = metaIn.readVInt(); + Map<Integer, Long> offsets = new HashMap<>(); + Map<Integer, Long> lengths = new HashMap<>(); + + while (metaIn.getFilePointer() < metaIn.length() - CodecUtil.footerLength()) { + int partitionId = metaIn.readVInt(); + long offset = metaIn.readVLong(); + long length = metaIn.readVLong(); + offsets.put(partitionId, offset); + lengths.put(partitionId, length); + } + + dataIn = state.directory.openInput(dataFileName, state.context); + CodecUtil.checkIndexHeader( + dataIn, "Lucene99SpannData", 0, 0, state.segmentInfo.getId(), state.segmentSuffix); + + // Build ordinal map for random access vectorValue(ord) + int[] ordToDocId = new int[totalSize]; + long[] ordToOffset = new long[totalSize]; + int currentOrd = 0; + IndexInput dataInClone = dataIn.clone(); + int vectorByteWidth = + fieldInfo.getVectorEncoding() == VectorEncoding.BYTE + ? fieldInfo.getVectorDimension() + : fieldInfo.getVectorDimension() * Float.BYTES; + + for (Integer pId : offsets.keySet()) { + long start = offsets.get(pId); + long len = lengths.get(pId); + dataInClone.seek(start); + long end = start + len; + while (dataInClone.getFilePointer() < end) { + ordToDocId[currentOrd] = dataInClone.readInt(); + ordToOffset[currentOrd] = dataInClone.getFilePointer(); + currentOrd++; + dataInClone.skipBytes(vectorByteWidth); + } + } + + fields.put( + fieldInfo.name, + new SpannFieldEntry( + offsets, lengths, dataIn, fieldInfo, totalSize, ordToDocId, ordToOffset)); + success = true; + } finally { + if (!success) { + IOUtils.closeWhileHandlingException(metaIn, dataIn); + } else { + IOUtils.closeWhileHandlingException(metaIn); + } + } + } + } + } + + @Override + public void checkIntegrity() throws IOException { + centroidDelegate.checkIntegrity(); + + for (SpannFieldEntry entry : fields.values()) { + // Meta check is done on open + CodecUtil.checksumEntireFile(entry.dataIn); + } + } + + @Override + public FloatVectorValues getFloatVectorValues(String field) throws IOException { + SpannFieldEntry entry = fields.get(field); + if (entry == null) { + return centroidDelegate.getFloatVectorValues(field); + } + if (entry.fieldInfo.getVectorEncoding() != VectorEncoding.FLOAT32) { + return null; + } + return new SpannFloatVectorValues(entry); + } + + @Override + public ByteVectorValues getByteVectorValues(String field) throws IOException { + SpannFieldEntry entry = fields.get(field); + if (entry == null) { + return centroidDelegate.getByteVectorValues(field); + } + if (entry.fieldInfo.getVectorEncoding() != VectorEncoding.BYTE) { + return null; + } + return new SpannByteVectorValues(entry); + } + + @Override + public void search(String field, float[] target, KnnCollector knnCollector, AcceptDocs acceptDocs) + throws IOException { + SpannFieldEntry entry = fields.get(field); + if (entry == null) { + centroidDelegate.search(field, target, knnCollector, acceptDocs); + return; + } + + TopDocs topCentroids; + if (entry.fieldInfo.getVectorEncoding() == VectorEncoding.BYTE) { + byte[] byteTarget = new byte[target.length]; Review Comment: I'm confused on the need for handling these cases - float target with byte vectors. Are you always storing the postings in byte format? (but I see a vice versa conversion as well). From what I know, the only place we have this currently is when vectors are explicitly stored as bytes, e.g. with scalar quantized vectors. In which case, the target is converted to bytes when it is quantized. ########## lucene/core/src/java/org/apache/lucene/codecs/spann/Lucene99SpannVectorsReader.java: ########## @@ -0,0 +1,470 @@ +/* + * 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.spann; + +import java.io.IOException; +import java.util.HashMap; +import java.util.Map; +import org.apache.lucene.codecs.CodecUtil; +import org.apache.lucene.codecs.KnnVectorsFormat; +import org.apache.lucene.codecs.KnnVectorsReader; +import org.apache.lucene.index.ByteVectorValues; +import org.apache.lucene.index.FieldInfo; +import org.apache.lucene.index.FloatVectorValues; +import org.apache.lucene.index.IndexFileNames; +import org.apache.lucene.index.SegmentReadState; +import org.apache.lucene.index.VectorEncoding; +import org.apache.lucene.search.AcceptDocs; +import org.apache.lucene.search.DocIdSetIterator; +import org.apache.lucene.search.KnnCollector; +import org.apache.lucene.search.ScoreDoc; +import org.apache.lucene.search.TopDocs; +import org.apache.lucene.search.TopKnnCollector; +import org.apache.lucene.search.VectorScorer; +import org.apache.lucene.store.IndexInput; +import org.apache.lucene.util.Bits; +import org.apache.lucene.util.IOUtils; + +/** + * Reader for SPANN (HNSW-IVF) vectors. + * + * @lucene.experimental + */ +public class Lucene99SpannVectorsReader extends KnnVectorsReader { + + private final KnnVectorsReader centroidDelegate; + private final Map<String, SpannFieldEntry> fields = new HashMap<>(); + private final int nprobe; + + public Lucene99SpannVectorsReader( + SegmentReadState state, KnnVectorsFormat centroidFormat, int nprobe) throws IOException { + this.nprobe = nprobe; + this.centroidDelegate = centroidFormat.fieldsReader(state); + + for (FieldInfo fieldInfo : state.fieldInfos) { + if (fieldInfo.hasVectorValues()) { + String metaFileName = + IndexFileNames.segmentFileName( + state.segmentInfo.name, state.segmentSuffix, fieldInfo.name + ".spam"); + String dataFileName = + IndexFileNames.segmentFileName( + state.segmentInfo.name, state.segmentSuffix, fieldInfo.name + ".spad"); + + IndexInput metaIn = null; + IndexInput dataIn = null; + boolean success = false; + + try { + // Probe for the "spam" (Meta) file. + // If it's missing, this field is likely managed by another codec (e.g., HNSW). + // We must catch this to allow mixed-codec segments. + metaIn = state.directory.openInput(metaFileName, state.context); + } catch (java.nio.file.NoSuchFileException | java.io.FileNotFoundException _) { + continue; + } + + try { + // If we found the meta file, we assume this IS a SPANN field. + // Any subsequent missing files (like .spad) or corruption MUST throw an + // exception. + CodecUtil.checkIndexHeader( + metaIn, "Lucene99SpannMeta", 0, 0, state.segmentInfo.getId(), state.segmentSuffix); + + int totalSize = metaIn.readVInt(); + Map<Integer, Long> offsets = new HashMap<>(); + Map<Integer, Long> lengths = new HashMap<>(); + + while (metaIn.getFilePointer() < metaIn.length() - CodecUtil.footerLength()) { + int partitionId = metaIn.readVInt(); + long offset = metaIn.readVLong(); + long length = metaIn.readVLong(); + offsets.put(partitionId, offset); + lengths.put(partitionId, length); + } + + dataIn = state.directory.openInput(dataFileName, state.context); + CodecUtil.checkIndexHeader( + dataIn, "Lucene99SpannData", 0, 0, state.segmentInfo.getId(), state.segmentSuffix); + + // Build ordinal map for random access vectorValue(ord) + int[] ordToDocId = new int[totalSize]; + long[] ordToOffset = new long[totalSize]; + int currentOrd = 0; + IndexInput dataInClone = dataIn.clone(); + int vectorByteWidth = + fieldInfo.getVectorEncoding() == VectorEncoding.BYTE + ? fieldInfo.getVectorDimension() + : fieldInfo.getVectorDimension() * Float.BYTES; + + for (Integer pId : offsets.keySet()) { + long start = offsets.get(pId); + long len = lengths.get(pId); + dataInClone.seek(start); + long end = start + len; + while (dataInClone.getFilePointer() < end) { + ordToDocId[currentOrd] = dataInClone.readInt(); + ordToOffset[currentOrd] = dataInClone.getFilePointer(); + currentOrd++; + dataInClone.skipBytes(vectorByteWidth); + } + } + + fields.put( + fieldInfo.name, + new SpannFieldEntry( + offsets, lengths, dataIn, fieldInfo, totalSize, ordToDocId, ordToOffset)); + success = true; + } finally { + if (!success) { + IOUtils.closeWhileHandlingException(metaIn, dataIn); + } else { + IOUtils.closeWhileHandlingException(metaIn); + } + } + } + } + } + + @Override + public void checkIntegrity() throws IOException { + centroidDelegate.checkIntegrity(); + + for (SpannFieldEntry entry : fields.values()) { + // Meta check is done on open + CodecUtil.checksumEntireFile(entry.dataIn); + } + } + + @Override + public FloatVectorValues getFloatVectorValues(String field) throws IOException { + SpannFieldEntry entry = fields.get(field); + if (entry == null) { + return centroidDelegate.getFloatVectorValues(field); + } + if (entry.fieldInfo.getVectorEncoding() != VectorEncoding.FLOAT32) { + return null; + } + return new SpannFloatVectorValues(entry); + } + + @Override + public ByteVectorValues getByteVectorValues(String field) throws IOException { + SpannFieldEntry entry = fields.get(field); + if (entry == null) { + return centroidDelegate.getByteVectorValues(field); + } + if (entry.fieldInfo.getVectorEncoding() != VectorEncoding.BYTE) { + return null; + } + return new SpannByteVectorValues(entry); + } + + @Override + public void search(String field, float[] target, KnnCollector knnCollector, AcceptDocs acceptDocs) + throws IOException { + SpannFieldEntry entry = fields.get(field); + if (entry == null) { + centroidDelegate.search(field, target, knnCollector, acceptDocs); + return; + } + + TopDocs topCentroids; + if (entry.fieldInfo.getVectorEncoding() == VectorEncoding.BYTE) { + byte[] byteTarget = new byte[target.length]; + for (int i = 0; i < target.length; i++) { + byteTarget[i] = (byte) target[i]; + } + topCentroids = searchCentroids(field, byteTarget, acceptDocs); + } else { + topCentroids = searchCentroids(field, target, acceptDocs); + } + + searchFine(entry, target, topCentroids, knnCollector, acceptDocs); + } + + @Override + public void search(String field, byte[] target, KnnCollector knnCollector, AcceptDocs acceptDocs) + throws IOException { + SpannFieldEntry entry = fields.get(field); + if (entry == null) { + centroidDelegate.search(field, target, knnCollector, acceptDocs); + return; + } + + TopDocs topCentroids; + float[] floatTarget = new float[target.length]; + for (int i = 0; i < target.length; i++) { + floatTarget[i] = (float) target[i]; + } Review Comment: Do we need an `i+=4` i.e. jump by 4 bytes when converting it to floats. I've seen us use ByteBuffers in Lucene for these things. ########## lucene/core/src/java/org/apache/lucene/codecs/spann/Lucene99SpannVectorsWriter.java: ########## @@ -0,0 +1,246 @@ +/* + * 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.spann; + +import java.io.IOException; +import java.util.ArrayList; +import java.util.HashMap; +import java.util.List; +import java.util.Map; +import org.apache.lucene.codecs.CodecUtil; +import org.apache.lucene.codecs.KnnFieldVectorsWriter; +import org.apache.lucene.codecs.KnnVectorsFormat; +import org.apache.lucene.codecs.KnnVectorsWriter; +import org.apache.lucene.index.FieldInfo; +import org.apache.lucene.index.IndexFileNames; +import org.apache.lucene.index.SegmentWriteState; +import org.apache.lucene.index.Sorter; +import org.apache.lucene.index.VectorEncoding; +import org.apache.lucene.index.VectorSimilarityFunction; +import org.apache.lucene.store.IndexOutput; +import org.apache.lucene.util.IOUtils; + +/** + * Writes vectors in the SPANN (HNSW-IVF) format. + * + * <p>Centroids are computed via K-Means and indexed into an HNSW-based coarse quantizer. Vector + * data is assigned to the nearest centroid and written sequentially in a clustered format. + */ +public class Lucene99SpannVectorsWriter extends KnnVectorsWriter { + + private static final int KMEANS_MAX_ITERS = 20; + + private final SegmentWriteState state; + private final KnnVectorsWriter centroidDelegate; + private final Map<String, SpannFieldVectorsWriter> fieldWriters = new HashMap<>(); + private final int maxPartitions; + private final int clusteringSampleSize; + + public Lucene99SpannVectorsWriter( + SegmentWriteState state, + KnnVectorsFormat centroidFormat, + int maxPartitions, + int clusteringSampleSize) + throws IOException { + this.state = state; + this.centroidDelegate = centroidFormat.fieldsWriter(state); + this.maxPartitions = maxPartitions; + this.clusteringSampleSize = clusteringSampleSize; + } + + @Override + public KnnFieldVectorsWriter<?> addField(FieldInfo fieldInfo) throws IOException { + SpannFieldVectorsWriter writer = new SpannFieldVectorsWriter(fieldInfo); + fieldWriters.put(fieldInfo.name, writer); + + if (fieldInfo.getVectorEncoding() == VectorEncoding.BYTE) { + return new KnnFieldVectorsWriter<byte[]>() { + @Override + public void addValue(int docID, byte[] vectorValue) throws IOException { + float[] floats = new float[vectorValue.length]; + for (int i = 0; i < vectorValue.length; i++) { + floats[i] = (float) vectorValue[i]; + } + writer.addValue(docID, floats); + } + + @Override + public byte[] copyValue(byte[] vectorValue) { + return vectorValue.clone(); + } + + @Override + public long ramBytesUsed() { + return 0; // The delegate writer tracks usage + } + }; + } + + return writer; + } + + @Override + public void flush(int maxDoc, Sorter.DocMap sortMap) throws IOException { + + for (Map.Entry<String, SpannFieldVectorsWriter> entry : fieldWriters.entrySet()) { + String fieldName = entry.getKey(); + SpannFieldVectorsWriter writer = entry.getValue(); + FieldInfo fieldInfo = writer.getFieldInfo(); + + if (writer.getVectors().isEmpty()) { + continue; + } + + float[][] vectorArray = writer.getVectors().toArray(new float[0][]); + + // Cap the number of partitions at configured limit (default 100) + int numPartitions = Math.min(vectorArray.length, maxPartitions); + + // Downsample to keep flush time constant Review Comment: Minor: Let's treat this downsampling as a "clustering impl" detail and move it into the clustering class? ########## lucene/core/src/java/org/apache/lucene/codecs/spann/Lucene99SpannVectorsWriter.java: ########## @@ -0,0 +1,246 @@ +/* + * 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.spann; + +import java.io.IOException; +import java.util.ArrayList; +import java.util.HashMap; +import java.util.List; +import java.util.Map; +import org.apache.lucene.codecs.CodecUtil; +import org.apache.lucene.codecs.KnnFieldVectorsWriter; +import org.apache.lucene.codecs.KnnVectorsFormat; +import org.apache.lucene.codecs.KnnVectorsWriter; +import org.apache.lucene.index.FieldInfo; +import org.apache.lucene.index.IndexFileNames; +import org.apache.lucene.index.SegmentWriteState; +import org.apache.lucene.index.Sorter; +import org.apache.lucene.index.VectorEncoding; +import org.apache.lucene.index.VectorSimilarityFunction; +import org.apache.lucene.store.IndexOutput; +import org.apache.lucene.util.IOUtils; + +/** + * Writes vectors in the SPANN (HNSW-IVF) format. + * + * <p>Centroids are computed via K-Means and indexed into an HNSW-based coarse quantizer. Vector + * data is assigned to the nearest centroid and written sequentially in a clustered format. + */ +public class Lucene99SpannVectorsWriter extends KnnVectorsWriter { + + private static final int KMEANS_MAX_ITERS = 20; + + private final SegmentWriteState state; + private final KnnVectorsWriter centroidDelegate; + private final Map<String, SpannFieldVectorsWriter> fieldWriters = new HashMap<>(); + private final int maxPartitions; + private final int clusteringSampleSize; + + public Lucene99SpannVectorsWriter( + SegmentWriteState state, + KnnVectorsFormat centroidFormat, + int maxPartitions, + int clusteringSampleSize) + throws IOException { + this.state = state; + this.centroidDelegate = centroidFormat.fieldsWriter(state); + this.maxPartitions = maxPartitions; + this.clusteringSampleSize = clusteringSampleSize; + } + + @Override + public KnnFieldVectorsWriter<?> addField(FieldInfo fieldInfo) throws IOException { + SpannFieldVectorsWriter writer = new SpannFieldVectorsWriter(fieldInfo); + fieldWriters.put(fieldInfo.name, writer); + + if (fieldInfo.getVectorEncoding() == VectorEncoding.BYTE) { + return new KnnFieldVectorsWriter<byte[]>() { + @Override + public void addValue(int docID, byte[] vectorValue) throws IOException { + float[] floats = new float[vectorValue.length]; + for (int i = 0; i < vectorValue.length; i++) { + floats[i] = (float) vectorValue[i]; + } + writer.addValue(docID, floats); + } + + @Override + public byte[] copyValue(byte[] vectorValue) { + return vectorValue.clone(); + } + + @Override + public long ramBytesUsed() { + return 0; // The delegate writer tracks usage + } + }; + } + + return writer; + } + + @Override + public void flush(int maxDoc, Sorter.DocMap sortMap) throws IOException { + + for (Map.Entry<String, SpannFieldVectorsWriter> entry : fieldWriters.entrySet()) { + String fieldName = entry.getKey(); + SpannFieldVectorsWriter writer = entry.getValue(); + FieldInfo fieldInfo = writer.getFieldInfo(); + + if (writer.getVectors().isEmpty()) { + continue; + } + + float[][] vectorArray = writer.getVectors().toArray(new float[0][]); + + // Cap the number of partitions at configured limit (default 100) + int numPartitions = Math.min(vectorArray.length, maxPartitions); + + // Downsample to keep flush time constant + // Cap at max(clusteringSampleSize, 256 * numPartitions) + float[][] trainingVectors = vectorArray; + if (vectorArray.length > clusteringSampleSize) { + int step = vectorArray.length / clusteringSampleSize; + trainingVectors = new float[clusteringSampleSize][]; + for (int i = 0; i < clusteringSampleSize; i++) { + trainingVectors[i] = vectorArray[i * step]; + } + } + + float[][] centroids = + SpannKMeans.cluster( + trainingVectors, + numPartitions, + fieldInfo.getVectorSimilarityFunction(), + KMEANS_MAX_ITERS); + + if (fieldInfo.getVectorEncoding() == VectorEncoding.BYTE) { + @SuppressWarnings("unchecked") + KnnFieldVectorsWriter<byte[]> byteCentroidWriter = + (KnnFieldVectorsWriter<byte[]>) centroidDelegate.addField(fieldInfo); + for (int partitionId = 0; partitionId < centroids.length; partitionId++) { + byte[] byteCentroid = new byte[centroids[partitionId].length]; + for (int k = 0; k < centroids[partitionId].length; k++) { + byteCentroid[k] = (byte) centroids[partitionId][k]; + } + byteCentroidWriter.addValue(partitionId, byteCentroid); + } + } else { + @SuppressWarnings("unchecked") + KnnFieldVectorsWriter<float[]> floatCentroidWriter = + (KnnFieldVectorsWriter<float[]>) centroidDelegate.addField(fieldInfo); + for (int partitionId = 0; partitionId < centroids.length; partitionId++) { + floatCentroidWriter.addValue(partitionId, centroids[partitionId]); + } + } + + List<List<Integer>> partitionDocIds = new ArrayList<>(centroids.length); + List<List<float[]>> partitions = new ArrayList<>(centroids.length); + for (int i = 0; i < centroids.length; i++) { + partitions.add(new ArrayList<>()); + partitionDocIds.add(new ArrayList<>()); + } + + VectorSimilarityFunction simFunc = fieldInfo.getVectorSimilarityFunction(); + List<float[]> vectors = writer.getVectors(); + List<Integer> docIds = writer.getDocIds(); + for (int i = 0; i < vectors.size(); i++) { + float[] vector = vectors.get(i); + int docId = docIds.get(i); + int bestCentroid = 0; + float bestScore = Float.NEGATIVE_INFINITY; + + for (int c = 0; c < centroids.length; c++) { + float score = simFunc.compare(vector, centroids[c]); Review Comment: k-means clustering would've done assigned some vectors to partitions already. Do we need to compare every vector against every centroid? ########## lucene/core/src/java/org/apache/lucene/codecs/spann/SpannFieldVectorsWriter.java: ########## @@ -0,0 +1,73 @@ +/* + * 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.spann; + +import java.io.IOException; +import java.util.ArrayList; +import java.util.List; +import org.apache.lucene.codecs.KnnFieldVectorsWriter; +import org.apache.lucene.index.FieldInfo; +import org.apache.lucene.util.RamUsageEstimator; + +/** + * Buffers vectors in memory until flush. + * + * <p>Future improvements could include off-heap or disk-backed buffering (e.g. ByteBlockPool) to Review Comment: Minor: How do you feel about keeping these ideas in github issues instead of code comments? IMO it's okay to call out a performance bottleneck TODO in comments, but naming specific techniques leaves future readers wondering whether and where they were implemented. ########## lucene/core/src/java/org/apache/lucene/codecs/spann/Lucene99SpannVectorsReader.java: ########## @@ -0,0 +1,470 @@ +/* + * 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.spann; + +import java.io.IOException; +import java.util.HashMap; +import java.util.Map; +import org.apache.lucene.codecs.CodecUtil; +import org.apache.lucene.codecs.KnnVectorsFormat; +import org.apache.lucene.codecs.KnnVectorsReader; +import org.apache.lucene.index.ByteVectorValues; +import org.apache.lucene.index.FieldInfo; +import org.apache.lucene.index.FloatVectorValues; +import org.apache.lucene.index.IndexFileNames; +import org.apache.lucene.index.SegmentReadState; +import org.apache.lucene.index.VectorEncoding; +import org.apache.lucene.search.AcceptDocs; +import org.apache.lucene.search.DocIdSetIterator; +import org.apache.lucene.search.KnnCollector; +import org.apache.lucene.search.ScoreDoc; +import org.apache.lucene.search.TopDocs; +import org.apache.lucene.search.TopKnnCollector; +import org.apache.lucene.search.VectorScorer; +import org.apache.lucene.store.IndexInput; +import org.apache.lucene.util.Bits; +import org.apache.lucene.util.IOUtils; + +/** + * Reader for SPANN (HNSW-IVF) vectors. + * + * @lucene.experimental + */ +public class Lucene99SpannVectorsReader extends KnnVectorsReader { + + private final KnnVectorsReader centroidDelegate; + private final Map<String, SpannFieldEntry> fields = new HashMap<>(); + private final int nprobe; + + public Lucene99SpannVectorsReader( + SegmentReadState state, KnnVectorsFormat centroidFormat, int nprobe) throws IOException { + this.nprobe = nprobe; + this.centroidDelegate = centroidFormat.fieldsReader(state); + + for (FieldInfo fieldInfo : state.fieldInfos) { + if (fieldInfo.hasVectorValues()) { + String metaFileName = + IndexFileNames.segmentFileName( + state.segmentInfo.name, state.segmentSuffix, fieldInfo.name + ".spam"); + String dataFileName = + IndexFileNames.segmentFileName( + state.segmentInfo.name, state.segmentSuffix, fieldInfo.name + ".spad"); + + IndexInput metaIn = null; + IndexInput dataIn = null; + boolean success = false; + + try { + // Probe for the "spam" (Meta) file. + // If it's missing, this field is likely managed by another codec (e.g., HNSW). + // We must catch this to allow mixed-codec segments. + metaIn = state.directory.openInput(metaFileName, state.context); + } catch (java.nio.file.NoSuchFileException | java.io.FileNotFoundException _) { + continue; + } + + try { + // If we found the meta file, we assume this IS a SPANN field. + // Any subsequent missing files (like .spad) or corruption MUST throw an + // exception. + CodecUtil.checkIndexHeader( + metaIn, "Lucene99SpannMeta", 0, 0, state.segmentInfo.getId(), state.segmentSuffix); + + int totalSize = metaIn.readVInt(); + Map<Integer, Long> offsets = new HashMap<>(); + Map<Integer, Long> lengths = new HashMap<>(); + + while (metaIn.getFilePointer() < metaIn.length() - CodecUtil.footerLength()) { + int partitionId = metaIn.readVInt(); + long offset = metaIn.readVLong(); + long length = metaIn.readVLong(); + offsets.put(partitionId, offset); + lengths.put(partitionId, length); + } + + dataIn = state.directory.openInput(dataFileName, state.context); + CodecUtil.checkIndexHeader( + dataIn, "Lucene99SpannData", 0, 0, state.segmentInfo.getId(), state.segmentSuffix); + + // Build ordinal map for random access vectorValue(ord) + int[] ordToDocId = new int[totalSize]; + long[] ordToOffset = new long[totalSize]; + int currentOrd = 0; + IndexInput dataInClone = dataIn.clone(); + int vectorByteWidth = + fieldInfo.getVectorEncoding() == VectorEncoding.BYTE + ? fieldInfo.getVectorDimension() + : fieldInfo.getVectorDimension() * Float.BYTES; + + for (Integer pId : offsets.keySet()) { + long start = offsets.get(pId); + long len = lengths.get(pId); + dataInClone.seek(start); + long end = start + len; + while (dataInClone.getFilePointer() < end) { + ordToDocId[currentOrd] = dataInClone.readInt(); + ordToOffset[currentOrd] = dataInClone.getFilePointer(); + currentOrd++; + dataInClone.skipBytes(vectorByteWidth); + } + } + + fields.put( + fieldInfo.name, + new SpannFieldEntry( + offsets, lengths, dataIn, fieldInfo, totalSize, ordToDocId, ordToOffset)); + success = true; + } finally { + if (!success) { + IOUtils.closeWhileHandlingException(metaIn, dataIn); + } else { + IOUtils.closeWhileHandlingException(metaIn); + } + } + } + } + } + + @Override + public void checkIntegrity() throws IOException { + centroidDelegate.checkIntegrity(); + + for (SpannFieldEntry entry : fields.values()) { + // Meta check is done on open + CodecUtil.checksumEntireFile(entry.dataIn); + } + } + + @Override + public FloatVectorValues getFloatVectorValues(String field) throws IOException { + SpannFieldEntry entry = fields.get(field); + if (entry == null) { + return centroidDelegate.getFloatVectorValues(field); + } + if (entry.fieldInfo.getVectorEncoding() != VectorEncoding.FLOAT32) { + return null; + } + return new SpannFloatVectorValues(entry); + } + + @Override + public ByteVectorValues getByteVectorValues(String field) throws IOException { + SpannFieldEntry entry = fields.get(field); + if (entry == null) { + return centroidDelegate.getByteVectorValues(field); + } + if (entry.fieldInfo.getVectorEncoding() != VectorEncoding.BYTE) { + return null; + } + return new SpannByteVectorValues(entry); + } + + @Override + public void search(String field, float[] target, KnnCollector knnCollector, AcceptDocs acceptDocs) + throws IOException { + SpannFieldEntry entry = fields.get(field); + if (entry == null) { + centroidDelegate.search(field, target, knnCollector, acceptDocs); + return; + } + + TopDocs topCentroids; + if (entry.fieldInfo.getVectorEncoding() == VectorEncoding.BYTE) { + byte[] byteTarget = new byte[target.length]; + for (int i = 0; i < target.length; i++) { + byteTarget[i] = (byte) target[i]; + } + topCentroids = searchCentroids(field, byteTarget, acceptDocs); + } else { + topCentroids = searchCentroids(field, target, acceptDocs); + } + + searchFine(entry, target, topCentroids, knnCollector, acceptDocs); + } + + @Override + public void search(String field, byte[] target, KnnCollector knnCollector, AcceptDocs acceptDocs) + throws IOException { + SpannFieldEntry entry = fields.get(field); + if (entry == null) { + centroidDelegate.search(field, target, knnCollector, acceptDocs); + return; + } + + TopDocs topCentroids; + float[] floatTarget = new float[target.length]; + for (int i = 0; i < target.length; i++) { + floatTarget[i] = (float) target[i]; + } + + if (entry.fieldInfo.getVectorEncoding() == VectorEncoding.BYTE) { + topCentroids = searchCentroids(field, target, acceptDocs); + } else { + topCentroids = searchCentroids(field, floatTarget, acceptDocs); + } + + searchFine(entry, floatTarget, topCentroids, knnCollector, acceptDocs); + } + + private TopDocs searchCentroids(String field, float[] target, AcceptDocs acceptDocs) + throws IOException { + TopKnnCollector coarseCollector = new TopKnnCollector(nprobe, Integer.MAX_VALUE); + centroidDelegate.search(field, target, coarseCollector, acceptDocs); + return coarseCollector.topDocs(); + } + + private TopDocs searchCentroids(String field, byte[] target, AcceptDocs acceptDocs) + throws IOException { + TopKnnCollector coarseCollector = new TopKnnCollector(nprobe, Integer.MAX_VALUE); + centroidDelegate.search(field, target, coarseCollector, acceptDocs); + return coarseCollector.topDocs(); + } + + private void searchFine( + SpannFieldEntry entry, + float[] target, + TopDocs topCentroids, + KnnCollector knnCollector, + AcceptDocs acceptDocs) + throws IOException { + IndexInput dataIn = entry.dataIn.clone(); + for (ScoreDoc centroidDoc : topCentroids.scoreDocs) { Review Comment: Can we avoid looking at all the topK centroid postings, and short-circuit if `dist(centroid, target) > nearest_centroid_distance + small_threshold` ? 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