jtibshirani commented on code in PR #11756:
URL: https://github.com/apache/lucene/pull/11756#discussion_r965154356
##########
lucene/core/src/java/org/apache/lucene/search/KnnVectorQuery.java:
##########
@@ -175,9 +176,42 @@ private TopDocs approximateSearch(LeafReaderContext
context, Bits acceptDocs, in
}
// We allow this to be overridden so that tests can check what search
strategy is used
- protected TopDocs exactSearch(LeafReaderContext context, DocIdSetIterator
acceptDocs)
+ protected TopDocs exactSearch(LeafReaderContext context, DocIdSetIterator
acceptIterator)
throws IOException {
- return context.reader().searchNearestVectorsExhaustively(field, target, k,
acceptDocs);
+ FieldInfo fi = context.reader().getFieldInfos().fieldInfo(field);
+ if (fi == null || fi.getVectorDimension() == 0) {
+ // The field does not exist or does not index vectors
+ return NO_RESULTS;
+ }
+
+ VectorScorer vectorScorer = VectorScorer.create(context, fi, target);
+ HitQueue queue = new HitQueue(k, true);
+ ScoreDoc topDoc = queue.top();
+ int doc;
+ while ((doc = acceptIterator.nextDoc()) != DocIdSetIterator.NO_MORE_DOCS) {
+ boolean advanced = vectorScorer.advanceExact(doc);
+ assert advanced;
+
+ float score = vectorScorer.score();
+ if (score >= topDoc.score) {
Review Comment:
That seems right, I updated this and pushed a test covering the tie-breaking
case. As a note, we don't guarantee we'll always return the lowest matching doc
IDs (since approximate HNSW search can't do this efficiently).
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