benwtrent commented on code in PR #13910:
URL: https://github.com/apache/lucene/pull/13910#discussion_r1803132931
##########
lucene/test-framework/src/java/org/apache/lucene/tests/index/BaseKnnVectorsFormatTestCase.java:
##########
@@ -1906,4 +1916,122 @@ public void testMismatchedFields() throws Exception {
IOUtils.close(reader, w2, dir1, dir2);
}
+
+ /**
+ * Test that the query is a viable approximation to exact search. This test
is designed to uncover
+ * gross failures only, not to represent the true expected recall.
+ */
+ public void testRecall() throws IOException {
+ VectorSimilarityFunction vectorSimilarityFunction =
VectorSimilarityFunction.EUCLIDEAN;
+ int dim = 16;
+ try (Directory indexStore = getKnownIndexStore("field", dim,
vectorSimilarityFunction);
+ IndexReader reader = DirectoryReader.open(indexStore)) {
+ IndexSearcher searcher = newSearcher(reader);
+ float[] queryEmbedding = new float[dim];
+ String queryString = "Apache License";
+ computeLineEmbedding(queryString, queryEmbedding);
+ // computeLineEmbedding(" END OF TERMS AND CONDITIONS",
queryEmbedding);
+ // pass match-all "filter" to force full traversal, bypassing graph
+ KnnFloatVectorQuery exactQuery =
+ new KnnFloatVectorQuery("field", queryEmbedding, 1000, new
MatchAllDocsQuery());
Review Comment:
Also, I think for more consistent runs, we may want to have multiple query
embeddings that we test with and gather `min` `max` and `avg` recalls. But this
can be a further refinement on this work.
I just think having a single query might be very flaky in the long run.
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