vigyasharma commented on code in PR #14009: URL: https://github.com/apache/lucene/pull/14009#discussion_r2098815198
########## lucene/core/src/java/org/apache/lucene/search/RerankKnnFloatVectorQuery.java: ########## @@ -0,0 +1,117 @@ +/* + * 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.search; + +import static org.apache.lucene.search.AbstractKnnVectorQuery.createRewrittenQuery; + +import java.io.IOException; +import java.util.Arrays; +import java.util.Objects; +import org.apache.lucene.index.FieldInfo; +import org.apache.lucene.index.FloatVectorValues; +import org.apache.lucene.index.IndexReader; +import org.apache.lucene.index.VectorSimilarityFunction; + +/** + * A wrapper of KnnFloatVectorQuery which does full-precision reranking. + * + * @lucene.experimental + */ +public class RerankKnnFloatVectorQuery extends Query { + + private final int k; + private final float[] target; + private final KnnFloatVectorQuery query; + + /** + * Execute the KnnFloatVectorQuery and re-rank using full-precision vectors + * + * @param query the KNN query to execute as initial phase + * @param target the target of the search + * @param k the number of documents to find + * @throws IllegalArgumentException if <code>k</code> is less than 1 + */ + public RerankKnnFloatVectorQuery(KnnFloatVectorQuery query, float[] target, int k) { + this.query = query; + this.target = target; + this.k = k; + } + + @Override + public Query rewrite(IndexSearcher indexSearcher) throws IOException { Review Comment: Can we implement `Weight` and `Scorer` classes for this query instead of running it in `rewrite` ? I know `AbstractKnnVectorQuery` uses rewrite and my guess is because it needs to decide b/w exact and approximate search. But we hopefully don't have such requirements here? ########## lucene/core/src/java/org/apache/lucene/search/RerankKnnFloatVectorQuery.java: ########## @@ -0,0 +1,117 @@ +/* + * 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.search; + +import static org.apache.lucene.search.AbstractKnnVectorQuery.createRewrittenQuery; + +import java.io.IOException; +import java.util.Arrays; +import java.util.Objects; +import org.apache.lucene.index.FieldInfo; +import org.apache.lucene.index.FloatVectorValues; +import org.apache.lucene.index.IndexReader; +import org.apache.lucene.index.VectorSimilarityFunction; + +/** + * A wrapper of KnnFloatVectorQuery which does full-precision reranking. + * + * @lucene.experimental + */ +public class RerankKnnFloatVectorQuery extends Query { + + private final int k; + private final float[] target; + private final KnnFloatVectorQuery query; + + /** + * Execute the KnnFloatVectorQuery and re-rank using full-precision vectors + * + * @param query the KNN query to execute as initial phase + * @param target the target of the search + * @param k the number of documents to find + * @throws IllegalArgumentException if <code>k</code> is less than 1 + */ + public RerankKnnFloatVectorQuery(KnnFloatVectorQuery query, float[] target, int k) { Review Comment: I wonder if we could generalize it to rerank any query with full precision vector similarity, instead of only `KnnFloatVectorQuery`s. ########## lucene/core/src/java/org/apache/lucene/search/RerankKnnFloatVectorQuery.java: ########## @@ -0,0 +1,117 @@ +/* + * 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.search; + +import static org.apache.lucene.search.AbstractKnnVectorQuery.createRewrittenQuery; + +import java.io.IOException; +import java.util.Arrays; +import java.util.Objects; +import org.apache.lucene.index.FieldInfo; +import org.apache.lucene.index.FloatVectorValues; +import org.apache.lucene.index.IndexReader; +import org.apache.lucene.index.VectorSimilarityFunction; + +/** + * A wrapper of KnnFloatVectorQuery which does full-precision reranking. + * + * @lucene.experimental + */ +public class RerankKnnFloatVectorQuery extends Query { + + private final int k; + private final float[] target; + private final KnnFloatVectorQuery query; + + /** + * Execute the KnnFloatVectorQuery and re-rank using full-precision vectors + * + * @param query the KNN query to execute as initial phase + * @param target the target of the search + * @param k the number of documents to find + * @throws IllegalArgumentException if <code>k</code> is less than 1 + */ + public RerankKnnFloatVectorQuery(KnnFloatVectorQuery query, float[] target, int k) { + this.query = query; + this.target = target; + this.k = k; + } + + @Override + public Query rewrite(IndexSearcher indexSearcher) throws IOException { + IndexReader reader = indexSearcher.getIndexReader(); + Query rewritten = indexSearcher.rewrite(query); + // short-circuit: don't re-rank if we already got all possible results + if (query.getK() <= k) { + return rewritten; + } + Weight weight = indexSearcher.createWeight(rewritten, ScoreMode.COMPLETE_NO_SCORES, 1.0f); + HitQueue queue = new HitQueue(k, false); + for (var leaf : reader.leaves()) { + Scorer scorer = weight.scorer(leaf); + if (scorer == null) { + continue; + } + FloatVectorValues floatVectorValues = leaf.reader().getFloatVectorValues(query.getField()); + if (floatVectorValues == null) { + continue; + } + FieldInfo fi = leaf.reader().getFieldInfos().fieldInfo(query.getField()); + if (fi == null) { + continue; + } + VectorSimilarityFunction comparer = fi.getVectorSimilarityFunction(); + DocIdSetIterator iterator = scorer.iterator(); + while (iterator.nextDoc() != DocIdSetIterator.NO_MORE_DOCS) { + int docId = iterator.docID(); + float[] vectorValue = floatVectorValues.vectorValue(docId); + float score = comparer.compare(vectorValue, target); + queue.insertWithOverflow(new ScoreDoc(leaf.docBase + docId, score)); + } + } + int i = 0; + ScoreDoc[] scoreDocs = new ScoreDoc[queue.size()]; + for (ScoreDoc topDoc : queue) { + scoreDocs[i++] = topDoc; + } + return createRewrittenQuery(reader, scoreDocs); Review Comment: nit: should we use `AbstractKnnVectorQuery.createRewrittenQuery()` instead of a static import, for readability? -- This is an automated message from the Apache Git Service. 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