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Signed-off-by: Jay Deng <[email protected]> (cherry picked from commit 8005bbf) Co-authored-by: Jay Deng <[email protected]>
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106 changes: 106 additions & 0 deletions
106
src/main/java/org/opensearch/knn/index/codec/KNN9120Codec/KNN9120BinaryVectorScorer.java
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/* | ||
* Copyright OpenSearch Contributors | ||
* SPDX-License-Identifier: Apache-2.0 | ||
*/ | ||
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package org.opensearch.knn.index.codec.KNN9120Codec; | ||
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import org.apache.lucene.codecs.hnsw.FlatVectorsScorer; | ||
import org.apache.lucene.index.VectorSimilarityFunction; | ||
import org.apache.lucene.util.Bits; | ||
import org.apache.lucene.util.hnsw.RandomAccessVectorValues; | ||
import org.apache.lucene.util.hnsw.RandomVectorScorer; | ||
import org.apache.lucene.util.hnsw.RandomVectorScorerSupplier; | ||
import org.opensearch.knn.index.KNNVectorSimilarityFunction; | ||
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import java.io.IOException; | ||
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/** | ||
* A FlatVectorsScorer to be used for scoring binary vectors. Meant to be used with {@link KNN9120BinaryVectorScorer} | ||
*/ | ||
public class KNN9120BinaryVectorScorer implements FlatVectorsScorer { | ||
@Override | ||
public RandomVectorScorerSupplier getRandomVectorScorerSupplier( | ||
VectorSimilarityFunction vectorSimilarityFunction, | ||
RandomAccessVectorValues randomAccessVectorValues | ||
) throws IOException { | ||
if (randomAccessVectorValues instanceof RandomAccessVectorValues.Bytes) { | ||
return new BinaryRandomVectorScorerSupplier((RandomAccessVectorValues.Bytes) randomAccessVectorValues); | ||
} | ||
throw new IllegalArgumentException("vectorValues must be an instance of RandomAccessVectorValues.Bytes"); | ||
} | ||
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@Override | ||
public RandomVectorScorer getRandomVectorScorer( | ||
VectorSimilarityFunction vectorSimilarityFunction, | ||
RandomAccessVectorValues randomAccessVectorValues, | ||
float[] queryVector | ||
) throws IOException { | ||
throw new IllegalArgumentException("binary vectors do not support float[] targets"); | ||
} | ||
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@Override | ||
public RandomVectorScorer getRandomVectorScorer( | ||
VectorSimilarityFunction vectorSimilarityFunction, | ||
RandomAccessVectorValues randomAccessVectorValues, | ||
byte[] queryVector | ||
) throws IOException { | ||
if (randomAccessVectorValues instanceof RandomAccessVectorValues.Bytes) { | ||
return new BinaryRandomVectorScorer((RandomAccessVectorValues.Bytes) randomAccessVectorValues, queryVector); | ||
} | ||
throw new IllegalArgumentException("vectorValues must be an instance of RandomAccessVectorValues.Bytes"); | ||
} | ||
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static class BinaryRandomVectorScorer implements RandomVectorScorer { | ||
private final RandomAccessVectorValues.Bytes vectorValues; | ||
private final byte[] queryVector; | ||
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BinaryRandomVectorScorer(RandomAccessVectorValues.Bytes vectorValues, byte[] query) { | ||
this.queryVector = query; | ||
this.vectorValues = vectorValues; | ||
} | ||
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@Override | ||
public float score(int node) throws IOException { | ||
return KNNVectorSimilarityFunction.HAMMING.compare(queryVector, vectorValues.vectorValue(node)); | ||
} | ||
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@Override | ||
public int maxOrd() { | ||
return vectorValues.size(); | ||
} | ||
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@Override | ||
public int ordToDoc(int ord) { | ||
return vectorValues.ordToDoc(ord); | ||
} | ||
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@Override | ||
public Bits getAcceptOrds(Bits acceptDocs) { | ||
return vectorValues.getAcceptOrds(acceptDocs); | ||
} | ||
} | ||
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static class BinaryRandomVectorScorerSupplier implements RandomVectorScorerSupplier { | ||
protected final RandomAccessVectorValues.Bytes vectorValues; | ||
protected final RandomAccessVectorValues.Bytes vectorValues1; | ||
protected final RandomAccessVectorValues.Bytes vectorValues2; | ||
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public BinaryRandomVectorScorerSupplier(RandomAccessVectorValues.Bytes vectorValues) throws IOException { | ||
this.vectorValues = vectorValues; | ||
this.vectorValues1 = vectorValues.copy(); | ||
this.vectorValues2 = vectorValues.copy(); | ||
} | ||
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@Override | ||
public RandomVectorScorer scorer(int ord) throws IOException { | ||
byte[] queryVector = vectorValues1.vectorValue(ord); | ||
return new BinaryRandomVectorScorer(vectorValues2, queryVector); | ||
} | ||
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@Override | ||
public RandomVectorScorerSupplier copy() throws IOException { | ||
return new BinaryRandomVectorScorerSupplier(vectorValues.copy()); | ||
} | ||
} | ||
} |
119 changes: 119 additions & 0 deletions
119
...main/java/org/opensearch/knn/index/codec/KNN9120Codec/KNN9120HnswBinaryVectorsFormat.java
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/* | ||
* Copyright OpenSearch Contributors | ||
* SPDX-License-Identifier: Apache-2.0 | ||
*/ | ||
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package org.opensearch.knn.index.codec.KNN9120Codec; | ||
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import org.apache.lucene.codecs.KnnVectorsFormat; | ||
import org.apache.lucene.codecs.KnnVectorsReader; | ||
import org.apache.lucene.codecs.KnnVectorsWriter; | ||
import org.apache.lucene.codecs.hnsw.FlatVectorsFormat; | ||
import org.apache.lucene.codecs.lucene99.Lucene99FlatVectorsFormat; | ||
import org.apache.lucene.codecs.lucene99.Lucene99HnswVectorsReader; | ||
import org.apache.lucene.codecs.lucene99.Lucene99HnswVectorsWriter; | ||
import org.apache.lucene.index.SegmentReadState; | ||
import org.apache.lucene.index.SegmentWriteState; | ||
import org.apache.lucene.search.TaskExecutor; | ||
import org.opensearch.knn.index.engine.KNNEngine; | ||
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import java.io.IOException; | ||
import java.util.concurrent.ExecutorService; | ||
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import static org.apache.lucene.codecs.lucene99.Lucene99HnswVectorsFormat.DEFAULT_BEAM_WIDTH; | ||
import static org.apache.lucene.codecs.lucene99.Lucene99HnswVectorsFormat.DEFAULT_MAX_CONN; | ||
import static org.apache.lucene.codecs.lucene99.Lucene99HnswVectorsFormat.DEFAULT_NUM_MERGE_WORKER; | ||
import static org.apache.lucene.codecs.lucene99.Lucene99HnswVectorsFormat.MAXIMUM_BEAM_WIDTH; | ||
import static org.apache.lucene.codecs.lucene99.Lucene99HnswVectorsFormat.MAXIMUM_MAX_CONN; | ||
import static org.opensearch.knn.index.engine.KNNEngine.getMaxDimensionByEngine; | ||
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/** | ||
* Custom KnnVectorsFormat implementation to support binary vectors. This class is mostly identical to | ||
* {@link org.apache.lucene.codecs.lucene99.Lucene99HnswVectorsFormat}, however we use the custom {@link KNN9120BinaryVectorScorer} | ||
* to perform hamming bit scoring. | ||
*/ | ||
public final class KNN9120HnswBinaryVectorsFormat extends KnnVectorsFormat { | ||
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private final int maxConn; | ||
private final int beamWidth; | ||
private static final FlatVectorsFormat flatVectorsFormat = new Lucene99FlatVectorsFormat(new KNN9120BinaryVectorScorer()); | ||
private final int numMergeWorkers; | ||
private final TaskExecutor mergeExec; | ||
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private static final String NAME = "KNN990HnswBinaryVectorsFormat"; | ||
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/** | ||
* Constructor logic is identical to {@link org.apache.lucene.codecs.lucene99.Lucene99HnswVectorsFormat#Lucene99HnswVectorsFormat()} | ||
*/ | ||
public KNN9120HnswBinaryVectorsFormat() { | ||
this(DEFAULT_MAX_CONN, DEFAULT_BEAM_WIDTH, DEFAULT_NUM_MERGE_WORKER, null); | ||
} | ||
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/** | ||
* Constructor logic is identical to {@link org.apache.lucene.codecs.lucene99.Lucene99HnswVectorsFormat#Lucene99HnswVectorsFormat(int, int)} | ||
*/ | ||
public KNN9120HnswBinaryVectorsFormat(int maxConn, int beamWidth) { | ||
this(maxConn, beamWidth, 1, null); | ||
} | ||
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/** | ||
* Constructor logic is identical to {@link org.apache.lucene.codecs.lucene99.Lucene99HnswVectorsFormat#Lucene99HnswVectorsFormat(int, int, int, java.util.concurrent.ExecutorService)} | ||
*/ | ||
public KNN9120HnswBinaryVectorsFormat(int maxConn, int beamWidth, int numMergeWorkers, ExecutorService mergeExec) { | ||
super(NAME); | ||
if (maxConn <= 0 || maxConn > MAXIMUM_MAX_CONN) { | ||
throw new IllegalArgumentException( | ||
"maxConn must be positive and less than or equal to " + MAXIMUM_MAX_CONN + "; maxConn=" + maxConn | ||
); | ||
} | ||
if (beamWidth <= 0 || beamWidth > MAXIMUM_BEAM_WIDTH) { | ||
throw new IllegalArgumentException( | ||
"beamWidth must be positive and less than or equal to " + MAXIMUM_BEAM_WIDTH + "; beamWidth=" + beamWidth | ||
); | ||
} | ||
this.maxConn = maxConn; | ||
this.beamWidth = beamWidth; | ||
if (numMergeWorkers == 1 && mergeExec != null) { | ||
throw new IllegalArgumentException("No executor service is needed as we'll use single thread to merge"); | ||
} | ||
this.numMergeWorkers = numMergeWorkers; | ||
if (mergeExec != null) { | ||
this.mergeExec = new TaskExecutor(mergeExec); | ||
} else { | ||
this.mergeExec = null; | ||
} | ||
} | ||
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@Override | ||
public KnnVectorsWriter fieldsWriter(SegmentWriteState state) throws IOException { | ||
return new Lucene99HnswVectorsWriter( | ||
state, | ||
this.maxConn, | ||
this.beamWidth, | ||
flatVectorsFormat.fieldsWriter(state), | ||
this.numMergeWorkers, | ||
this.mergeExec | ||
); | ||
} | ||
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@Override | ||
public KnnVectorsReader fieldsReader(SegmentReadState state) throws IOException { | ||
return new Lucene99HnswVectorsReader(state, flatVectorsFormat.fieldsReader(state)); | ||
} | ||
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@Override | ||
public int getMaxDimensions(String fieldName) { | ||
return getMaxDimensionByEngine(KNNEngine.LUCENE); | ||
} | ||
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@Override | ||
public String toString() { | ||
return "KNN990HnswBinaryVectorsFormat(name=KNN990HnswBinaryVectorsFormat, maxConn=" | ||
+ this.maxConn | ||
+ ", beamWidth=" | ||
+ this.beamWidth | ||
+ ", flatVectorFormat=" | ||
+ flatVectorsFormat | ||
+ ")"; | ||
} | ||
} |
63 changes: 63 additions & 0 deletions
63
...ain/java/org/opensearch/knn/index/codec/KNN9120Codec/KNN9120PerFieldKnnVectorsFormat.java
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/* | ||
* Copyright OpenSearch Contributors | ||
* SPDX-License-Identifier: Apache-2.0 | ||
*/ | ||
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package org.opensearch.knn.index.codec.KNN9120Codec; | ||
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import org.apache.lucene.codecs.lucene99.Lucene99HnswScalarQuantizedVectorsFormat; | ||
import org.apache.lucene.codecs.lucene99.Lucene99HnswVectorsFormat; | ||
import org.opensearch.index.mapper.MapperService; | ||
import org.opensearch.knn.index.SpaceType; | ||
import org.opensearch.knn.index.codec.BasePerFieldKnnVectorsFormat; | ||
import org.opensearch.knn.index.engine.KNNEngine; | ||
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import java.util.Optional; | ||
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/** | ||
* Class provides per field format implementation for Lucene Knn vector type | ||
*/ | ||
public class KNN9120PerFieldKnnVectorsFormat extends BasePerFieldKnnVectorsFormat { | ||
private static final int NUM_MERGE_WORKERS = 1; | ||
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public KNN9120PerFieldKnnVectorsFormat(final Optional<MapperService> mapperService) { | ||
super( | ||
mapperService, | ||
Lucene99HnswVectorsFormat.DEFAULT_MAX_CONN, | ||
Lucene99HnswVectorsFormat.DEFAULT_BEAM_WIDTH, | ||
Lucene99HnswVectorsFormat::new, | ||
knnVectorsFormatParams -> { | ||
// There is an assumption here that hamming space will only be used for binary vectors. This will need to be fixed if that | ||
// changes in the future. | ||
if (knnVectorsFormatParams.getSpaceType() == SpaceType.HAMMING) { | ||
return new KNN9120HnswBinaryVectorsFormat( | ||
knnVectorsFormatParams.getMaxConnections(), | ||
knnVectorsFormatParams.getBeamWidth() | ||
); | ||
} else { | ||
return new Lucene99HnswVectorsFormat(knnVectorsFormatParams.getMaxConnections(), knnVectorsFormatParams.getBeamWidth()); | ||
} | ||
}, | ||
knnScalarQuantizedVectorsFormatParams -> new Lucene99HnswScalarQuantizedVectorsFormat( | ||
knnScalarQuantizedVectorsFormatParams.getMaxConnections(), | ||
knnScalarQuantizedVectorsFormatParams.getBeamWidth(), | ||
NUM_MERGE_WORKERS, | ||
knnScalarQuantizedVectorsFormatParams.getBits(), | ||
knnScalarQuantizedVectorsFormatParams.isCompressFlag(), | ||
knnScalarQuantizedVectorsFormatParams.getConfidenceInterval(), | ||
null | ||
) | ||
); | ||
} | ||
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@Override | ||
/** | ||
* This method returns the maximum dimension allowed from KNNEngine for Lucene codec | ||
* | ||
* @param fieldName Name of the field, ignored | ||
* @return Maximum constant dimension set by KNNEngine | ||
*/ | ||
public int getMaxDimensions(String fieldName) { | ||
return KNNEngine.getMaxDimensionByEngine(KNNEngine.LUCENE); | ||
} | ||
} |
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