Use min_candidates

Author: carlosdelest

x-pack/plugin/esql/src/main/java/org/elasticsearch/xpack/esql/expression/function/vector/Knn.java

@@ -79,8 +79,10 @@ public class Knn extends FullTextFunction implements OptionalArgument, VectorFun
     // Expressions to be used as prefilters in knn query
     private final List<Expression> filterExpressions;
 
+    public static final String MIN_CANDIDATES_OPTION = "min_candidates";
+
     public static final Map<String, DataType> ALLOWED_OPTIONS = Map.ofEntries(
-        entry(NUM_CANDS_FIELD.getPreferredName(), INTEGER),
+        entry(MIN_CANDIDATES_OPTION, INTEGER),
         entry(VECTOR_SIMILARITY_FIELD.getPreferredName(), FLOAT),
         entry(BOOST_FIELD.getPreferredName(), FLOAT),
         entry(KnnQuery.RESCORE_OVERSAMPLE_FIELD, FLOAT)

x-pack/plugin/esql/src/main/java/org/elasticsearch/xpack/esql/querydsl/query/KnnQuery.java

@@ -12,6 +12,7 @@
 import org.elasticsearch.search.vectors.RescoreVectorBuilder;
 import org.elasticsearch.xpack.esql.core.querydsl.query.Query;
 import org.elasticsearch.xpack.esql.core.tree.Source;
+import org.elasticsearch.xpack.esql.expression.function.vector.Knn;
 
 import java.util.ArrayList;
 import java.util.Arrays;
@@ -20,8 +21,6 @@
 import java.util.Objects;
 
 import static org.elasticsearch.index.query.AbstractQueryBuilder.BOOST_FIELD;
-import static org.elasticsearch.search.vectors.KnnVectorQueryBuilder.K_FIELD;
-import static org.elasticsearch.search.vectors.KnnVectorQueryBuilder.NUM_CANDS_FIELD;
 import static org.elasticsearch.search.vectors.KnnVectorQueryBuilder.VECTOR_SIMILARITY_FIELD;
 
 public class KnnQuery extends Query {
@@ -36,6 +35,7 @@ public class KnnQuery extends Query {
 
     public KnnQuery(Source source, String field, float[] query, Integer k, Map<String, Object> options, List<QueryBuilder> filterQueries) {
         super(source);
+        assert k != null && k > 0 : "k must be a positive integer, but was: " + k;
         this.k = k;
         assert options != null;
         this.field = field;
@@ -46,15 +46,23 @@ public KnnQuery(Source source, String field, float[] query, Integer k, Map<Strin
 
     @Override
     protected QueryBuilder asBuilder() {
-        Integer numCands = (Integer) options.get(NUM_CANDS_FIELD.getPreferredName());
         RescoreVectorBuilder rescoreVectorBuilder = null;
         Float oversample = (Float) options.get(RESCORE_OVERSAMPLE_FIELD);
         if (oversample != null) {
             rescoreVectorBuilder = new RescoreVectorBuilder(oversample);
         }
         Float vectorSimilarity = (Float) options.get(VECTOR_SIMILARITY_FIELD.getPreferredName());
-
-        KnnVectorQueryBuilder queryBuilder = new KnnVectorQueryBuilder(field, query, k, numCands, rescoreVectorBuilder, vectorSimilarity);
+        Integer minCandidates = (Integer) options.get(Knn.MIN_CANDIDATES_OPTION);
+        int adjustedK = Math.max(k, minCandidates == null ? 0 : minCandidates);
+
+        KnnVectorQueryBuilder queryBuilder = new KnnVectorQueryBuilder(
+            field,
+            query,
+            adjustedK,
+            minCandidates,
+            rescoreVectorBuilder,
+            vectorSimilarity
+        );
         for (QueryBuilder filter : filterQueries) {
             queryBuilder.addFilterQuery(filter);
         }