Add test coverage for knn options

Author: carlosdelest

x-pack/plugin/esql/qa/testFixtures/src/main/resources/mapping-all-types.json

@@ -63,6 +63,9 @@
         "semantic_text": {
             "type": "semantic_text",
             "inference_id": "foo_inference_id"
+        },
+        "dense_vector": {
+            "type": "dense_vector"
         }
     }
 }

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

@@ -63,7 +63,7 @@ public class Knn extends FullTextFunction implements OptionalArgument, VectorFun
         entry(NUM_CANDS_FIELD.getPreferredName(), INTEGER),
         entry(VECTOR_SIMILARITY_FIELD.getPreferredName(), FLOAT),
         entry(BOOST_FIELD.getPreferredName(), FLOAT),
-        entry(OVERSAMPLE_FIELD.getPreferredName(), FLOAT)
+        entry(KnnQuery.RESCORE_OVERSAMPLE_FIELD, FLOAT)
     );
 
     @FunctionInfo(returnType = "boolean", preview = true, description = """

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

@@ -27,6 +27,8 @@ public class KnnQuery extends Query {
     private final float[] query;
     private final Map<String, Object> options;
 
+    public static final String RESCORE_OVERSAMPLE_FIELD = "rescore_oversample";
+
     public KnnQuery(Source source, String field, float[] query, Map<String, Object> options) {
         super(source);
         assert options != null;
@@ -40,7 +42,7 @@ protected QueryBuilder asBuilder() {
         Integer k = (Integer) options.get(K_FIELD.getPreferredName());
         Integer numCands = (Integer) options.get(NUM_CANDS_FIELD.getPreferredName());
         RescoreVectorBuilder rescoreVectorBuilder = null;
-        Float oversample = (Float) options.get(RescoreVectorBuilder.OVERSAMPLE_FIELD.getPreferredName());
+        Float oversample = (Float) options.get(RESCORE_OVERSAMPLE_FIELD);
         if (oversample != null) {
             rescoreVectorBuilder = new RescoreVectorBuilder(oversample);
         }

x-pack/plugin/esql/src/test/java/org/elasticsearch/xpack/esql/optimizer/LocalPhysicalPlanOptimizerTests.java

@@ -30,6 +30,8 @@
 import org.elasticsearch.index.query.RangeQueryBuilder;
 import org.elasticsearch.index.query.SearchExecutionContext;
 import org.elasticsearch.license.XPackLicenseState;
+import org.elasticsearch.search.vectors.KnnVectorQueryBuilder;
+import org.elasticsearch.search.vectors.RescoreVectorBuilder;
 import org.elasticsearch.test.VersionUtils;
 import org.elasticsearch.xpack.core.enrich.EnrichPolicy;
 import org.elasticsearch.xpack.esql.EsqlTestUtils;
@@ -1904,6 +1906,28 @@ public void testMultiMatchOptionsPushDown() {
         assertThat(expectedQuery.toString(), is(planStr.get()));
     }
 
+    public void testKnnOptionsPushDown() {
+        String query = """
+            from test
+            | where KNN(dense_vector, [0.1, 0.2, 0.3], { "k": 5, "similarity": 0.001, "num_candidates": 10, "rescore_oversample": 7 })
+            """;
+        var analyzer = makeAnalyzer("mapping-all-types.json");
+        var plan = plannerOptimizer.plan(query, IS_SV_STATS, analyzer);
+
+        AtomicReference<String> planStr = new AtomicReference<>();
+        plan.forEachDown(EsQueryExec.class, result -> planStr.set(result.query().toString()));
+
+        var expectedQuery = new KnnVectorQueryBuilder(
+            "dense_vector",
+            new float[] { 0.1f, 0.2f, 0.3f },
+            5,
+            10,
+            new RescoreVectorBuilder(7),
+            0.001f
+        );
+        assertThat(expectedQuery.toString(), is(planStr.get()));
+    }
+
     /**
      * Expecting
      * LimitExec[1000[INTEGER]]