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LUCENE-9614: add KnnVectorQuery implementation
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lucene/core/src/java/org/apache/lucene/search/KnnVectorQuery.java
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/* | ||
* 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; | ||
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import static org.apache.lucene.search.DocIdSetIterator.NO_MORE_DOCS; | ||
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import java.io.IOException; | ||
import java.util.Arrays; | ||
import java.util.Comparator; | ||
import java.util.Objects; | ||
import org.apache.lucene.codecs.KnnVectorsReader; | ||
import org.apache.lucene.document.KnnVectorField; | ||
import org.apache.lucene.index.IndexReader; | ||
import org.apache.lucene.index.LeafReaderContext; | ||
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/** Uses {@link KnnVectorsReader#search} to perform nearest Neighbour search. */ | ||
public class KnnVectorQuery extends Query { | ||
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private static final TopDocs NO_RESULTS = | ||
new TopDocs(new TotalHits(0, TotalHits.Relation.EQUAL_TO), new ScoreDoc[0]); | ||
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private final String field; | ||
private final float[] target; | ||
private final int k; | ||
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/** | ||
* Find the <code>k</code> nearest documents to the target vector according to the vectors in the | ||
* given field. <code>target</code> vector. | ||
* | ||
* @param field a field that has been indexed as a {@link KnnVectorField}. | ||
* @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 KnnVectorQuery(String field, float[] target, int k) { | ||
this.field = field; | ||
this.target = target; | ||
this.k = k; | ||
if (k < 1) { | ||
throw new IllegalArgumentException("k must be at least 1, got: " + k); | ||
} | ||
} | ||
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@Override | ||
public Query rewrite(IndexReader reader) throws IOException { | ||
TopDocs[] perLeafResults = new TopDocs[reader.leaves().size()]; | ||
for (LeafReaderContext ctx : reader.leaves()) { | ||
perLeafResults[ctx.ord] = searchLeaf(ctx, Math.min(k, reader.numDocs())); | ||
} | ||
// Merge sort the results | ||
TopDocs topK = TopDocs.merge(k, perLeafResults); | ||
if (topK.scoreDocs.length == 0) { | ||
return new MatchNoDocsQuery(); | ||
} | ||
return createRewrittenQuery(reader, topK); | ||
} | ||
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private TopDocs searchLeaf(LeafReaderContext ctx, int kPerLeaf) throws IOException { | ||
TopDocs results = ctx.reader().searchNearestVectors(field, target, kPerLeaf); | ||
if (results == null) { | ||
return NO_RESULTS; | ||
} | ||
if (ctx.docBase > 0) { | ||
for (ScoreDoc scoreDoc : results.scoreDocs) { | ||
scoreDoc.doc += ctx.docBase; | ||
} | ||
} | ||
return results; | ||
} | ||
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private Query createRewrittenQuery(IndexReader reader, TopDocs topK) { | ||
int len = topK.scoreDocs.length; | ||
Arrays.sort(topK.scoreDocs, Comparator.comparingInt(a -> a.doc)); | ||
int[] docs = new int[len]; | ||
float[] scores = new float[len]; | ||
for (int i = 0; i < len; i++) { | ||
docs[i] = topK.scoreDocs[i].doc; | ||
scores[i] = topK.scoreDocs[i].score; | ||
} | ||
int[] segmentStarts = findSegmentStarts(reader, docs); | ||
return new DocAndScoreQuery(k, docs, scores, segmentStarts, reader.hashCode()); | ||
} | ||
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private int[] findSegmentStarts(IndexReader reader, int[] docs) { | ||
int[] starts = new int[reader.leaves().size() + 1]; | ||
starts[starts.length - 1] = docs.length; | ||
if (starts.length == 2) { | ||
return starts; | ||
} | ||
int resultIndex = 0; | ||
for (int i = 1; i < starts.length - 1; i++) { | ||
int upper = reader.leaves().get(i).docBase; | ||
resultIndex = Arrays.binarySearch(docs, resultIndex, docs.length, upper); | ||
if (resultIndex < 0) { | ||
resultIndex = -1 - resultIndex; | ||
} | ||
starts[i] = resultIndex; | ||
} | ||
return starts; | ||
} | ||
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@Override | ||
public String toString(String field) { | ||
return "<vector:" + this.field + "[" + target[0] + ",...][" + k + "]>"; | ||
} | ||
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@Override | ||
public void visit(QueryVisitor visitor) { | ||
if (visitor.acceptField(field)) { | ||
visitor.visitLeaf(this); | ||
} | ||
} | ||
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@Override | ||
public boolean equals(Object obj) { | ||
return obj instanceof KnnVectorQuery | ||
&& ((KnnVectorQuery) obj).k == k | ||
&& ((KnnVectorQuery) obj).field.equals(field) | ||
&& Arrays.equals(((KnnVectorQuery) obj).target, target); | ||
} | ||
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@Override | ||
public int hashCode() { | ||
return Objects.hash(field, k, Arrays.hashCode(target)); | ||
} | ||
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/** Caches the results of a KnnVector search: a list of docs and their scores */ | ||
static class DocAndScoreQuery extends Query { | ||
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private final int k; | ||
private final int[] docs; | ||
private final float[] scores; | ||
private final int[] segmentStarts; | ||
private final int readerHash; | ||
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/** | ||
* Constructor | ||
* | ||
* @param k the number of documents requested | ||
* @param docs the global docids of documents that match, in ascending order | ||
* @param scores the scores of the matching documents | ||
* @param segmentStarts the indexes in docs and scores corresponding to the first matching | ||
* document in each segment. If a segment has no matching documents, it should be assigned | ||
* the index of the next segment that does. There should be a final entry that is always | ||
* docs.length-1. | ||
* @param readerHash a hash code identifying the IndexReader used to create this query | ||
*/ | ||
DocAndScoreQuery(int k, int[] docs, float[] scores, int[] segmentStarts, int readerHash) { | ||
this.k = k; | ||
this.docs = docs; | ||
this.scores = scores; | ||
this.segmentStarts = segmentStarts; | ||
this.readerHash = readerHash; | ||
} | ||
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@Override | ||
public Weight createWeight(IndexSearcher searcher, ScoreMode scoreMode, float boost) | ||
throws IOException { | ||
if (searcher.getIndexReader().hashCode() != readerHash) { | ||
throw new IllegalStateException("This DocAndScore query was created by a different reader"); | ||
} | ||
return new Weight(this) { | ||
@Override | ||
public Explanation explain(LeafReaderContext context, int doc) { | ||
int found = Arrays.binarySearch(docs, doc); | ||
if (found < 0) { | ||
return Explanation.noMatch("not in top " + k); | ||
} | ||
return Explanation.match(scores[found], "within top " + k); | ||
} | ||
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@Override | ||
public Scorer scorer(LeafReaderContext context) { | ||
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return new Scorer(this) { | ||
final int lower = segmentStarts[context.ord]; | ||
final int upper = segmentStarts[context.ord + 1]; | ||
int upTo = -1; | ||
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@Override | ||
public DocIdSetIterator iterator() { | ||
return new DocIdSetIterator() { | ||
@Override | ||
public int docID() { | ||
return docIdNoShadow(); | ||
} | ||
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@Override | ||
public int nextDoc() { | ||
if (upTo == -1) { | ||
upTo = lower; | ||
} else { | ||
++upTo; | ||
} | ||
return docIdNoShadow(); | ||
} | ||
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@Override | ||
public int advance(int target) throws IOException { | ||
return slowAdvance(target); | ||
} | ||
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@Override | ||
public long cost() { | ||
return upper - lower; | ||
} | ||
}; | ||
} | ||
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@Override | ||
public float getMaxScore(int docid) { | ||
docid += context.docBase; | ||
float maxScore = 0; | ||
for (int idx = Math.max(0, upTo); idx < upper && docs[idx] <= docid; idx++) { | ||
maxScore = Math.max(maxScore, scores[idx]); | ||
} | ||
return maxScore; | ||
} | ||
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@Override | ||
public float score() { | ||
return scores[upTo]; | ||
} | ||
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@Override | ||
public int advanceShallow(int docid) { | ||
int start = Math.max(upTo, lower); | ||
int docidIndex = Arrays.binarySearch(docs, start, upper, docid + context.docBase); | ||
if (docidIndex < 0) { | ||
docidIndex = -1 - docidIndex; | ||
} | ||
if (docidIndex >= upper) { | ||
return NO_MORE_DOCS; | ||
} | ||
return docs[docidIndex]; | ||
} | ||
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/** | ||
* move the implementation of docID() into a differently-named method so we can call it | ||
* from DocIDSetIterator.docID() even though this class is anonymous | ||
* | ||
* @return the current docid | ||
*/ | ||
private int docIdNoShadow() { | ||
if (upTo == -1) { | ||
return -1; | ||
} | ||
if (upTo >= upper) { | ||
return NO_MORE_DOCS; | ||
} | ||
return docs[upTo] - context.docBase; | ||
} | ||
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@Override | ||
public int docID() { | ||
return docIdNoShadow(); | ||
} | ||
}; | ||
} | ||
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@Override | ||
public boolean isCacheable(LeafReaderContext ctx) { | ||
return true; | ||
} | ||
}; | ||
} | ||
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@Override | ||
public String toString(String field) { | ||
return "DocAndScore[" + k + "]"; | ||
} | ||
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@Override | ||
public void visit(QueryVisitor visitor) { | ||
visitor.visitLeaf(this); | ||
} | ||
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@Override | ||
public boolean equals(Object obj) { | ||
if (obj instanceof DocAndScoreQuery == false) { | ||
return false; | ||
} | ||
return Arrays.equals(docs, ((DocAndScoreQuery) obj).docs) | ||
&& Arrays.equals(scores, ((DocAndScoreQuery) obj).scores); | ||
} | ||
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@Override | ||
public int hashCode() { | ||
return Objects.hash( | ||
DocAndScoreQuery.class.hashCode(), Arrays.hashCode(docs), Arrays.hashCode(scores)); | ||
} | ||
} | ||
} |
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