Remove unnecessary knn param boxing and simplyfing somethings

server/src/main/java/org/elasticsearch/search/vectors/ESDiversifyingChildrenByteKnnVectorQuery.java

@@ -17,14 +17,14 @@
 import org.elasticsearch.search.profile.query.QueryProfiler;
 
 public class ESDiversifyingChildrenByteKnnVectorQuery extends DiversifyingChildrenByteKnnVectorQuery implements QueryProfilerProvider {
-    private final Integer kParam;
+    private final int kParam;
     private long vectorOpsCount;
 
     public ESDiversifyingChildrenByteKnnVectorQuery(
         String field,
         byte[] query,
         Query childFilter,
-        Integer k,
+        int k,
         int numCands,
         BitSetProducer parentsFilter,
         KnnSearchStrategy strategy
@@ -35,7 +35,7 @@ public ESDiversifyingChildrenByteKnnVectorQuery(
 
     @Override
     protected TopDocs mergeLeafResults(TopDocs[] perLeafResults) {
-        TopDocs topK = kParam == null ? super.mergeLeafResults(perLeafResults) : TopDocs.merge(kParam, perLeafResults);
+        TopDocs topK = TopDocs.merge(kParam, perLeafResults);
         vectorOpsCount = topK.totalHits.value();
         return topK;
     }

server/src/main/java/org/elasticsearch/search/vectors/ESDiversifyingChildrenFloatKnnVectorQuery.java

@@ -17,14 +17,14 @@
 import org.elasticsearch.search.profile.query.QueryProfiler;
 
 public class ESDiversifyingChildrenFloatKnnVectorQuery extends DiversifyingChildrenFloatKnnVectorQuery implements QueryProfilerProvider {
-    private final Integer kParam;
+    private final int kParam;
     private long vectorOpsCount;
 
     public ESDiversifyingChildrenFloatKnnVectorQuery(
         String field,
         float[] query,
         Query childFilter,
-        Integer k,
+        int k,
         int numCands,
         BitSetProducer parentsFilter,
         KnnSearchStrategy strategy
@@ -35,7 +35,7 @@ public ESDiversifyingChildrenFloatKnnVectorQuery(
 
     @Override
     protected TopDocs mergeLeafResults(TopDocs[] perLeafResults) {
-        TopDocs topK = kParam == null ? super.mergeLeafResults(perLeafResults) : TopDocs.merge(kParam, perLeafResults);
+        TopDocs topK = TopDocs.merge(kParam, perLeafResults);
         vectorOpsCount = topK.totalHits.value();
         return topK;
     }

server/src/main/java/org/elasticsearch/search/vectors/ESKnnByteVectorQuery.java

@@ -16,18 +16,18 @@
 import org.elasticsearch.search.profile.query.QueryProfiler;
 
 public class ESKnnByteVectorQuery extends KnnByteVectorQuery implements QueryProfilerProvider {
-    private final Integer kParam;
+    private final int kParam;
     private long vectorOpsCount;
 
-    public ESKnnByteVectorQuery(String field, byte[] target, Integer k, int numCands, Query filter, KnnSearchStrategy strategy) {
+    public ESKnnByteVectorQuery(String field, byte[] target, int k, int numCands, Query filter, KnnSearchStrategy strategy) {
         super(field, target, numCands, filter, strategy);
         this.kParam = k;
     }
 
     @Override
     protected TopDocs mergeLeafResults(TopDocs[] perLeafResults) {
         // if k param is set, we get only top k results from each shard
-        TopDocs topK = kParam == null ? super.mergeLeafResults(perLeafResults) : TopDocs.merge(kParam, perLeafResults);
+        TopDocs topK = TopDocs.merge(kParam, perLeafResults);
         vectorOpsCount = topK.totalHits.value();
         return topK;
     }

server/src/main/java/org/elasticsearch/search/vectors/ESKnnFloatVectorQuery.java

@@ -16,18 +16,18 @@
 import org.elasticsearch.search.profile.query.QueryProfiler;
 
 public class ESKnnFloatVectorQuery extends KnnFloatVectorQuery implements QueryProfilerProvider {
-    private final Integer kParam;
+    private final int kParam;
     private long vectorOpsCount;
 
-    public ESKnnFloatVectorQuery(String field, float[] target, Integer k, int numCands, Query filter, KnnSearchStrategy strategy) {
+    public ESKnnFloatVectorQuery(String field, float[] target, int k, int numCands, Query filter, KnnSearchStrategy strategy) {
         super(field, target, numCands, filter, strategy);
         this.kParam = k;
     }
 
     @Override
     protected TopDocs mergeLeafResults(TopDocs[] perLeafResults) {
         // if k param is set, we get only top k results from each shard
-        TopDocs topK = kParam == null ? super.mergeLeafResults(perLeafResults) : TopDocs.merge(kParam, perLeafResults);
+        TopDocs topK = TopDocs.merge(kParam, perLeafResults);
         vectorOpsCount = topK.totalHits.value();
         return topK;
     }
@@ -37,7 +37,7 @@ public void profile(QueryProfiler queryProfiler) {
         queryProfiler.addVectorOpsCount(vectorOpsCount);
     }
 
-    public Integer kParam() {
+    public int kParam() {
         return kParam;
     }
 

server/src/test/java/org/elasticsearch/index/mapper/vectors/DenseVectorFieldTypeTests.java

@@ -712,7 +712,7 @@ private static void checkRescoreQueryParameters(
         int k,
         int candidates,
         float oversample,
-        Integer expectedK,
+        int expectedK,
         int expectedCandidates,
         int expectedResults
     ) {

server/src/test/java/org/elasticsearch/search/vectors/AbstractKnnVectorQueryBuilderTestCase.java

@@ -187,14 +187,16 @@ protected void doAssertLuceneQuery(KnnVectorQueryBuilder queryBuilder, Query que
             assertThat(((VectorSimilarityQuery) query).getSimilarity(), equalTo(queryBuilder.getVectorSimilarity()));
             query = ((VectorSimilarityQuery) query).getInnerKnnQuery();
         }
-        Integer k = queryBuilder.k();
-        if (k == null) {
+        int k;
+        if (queryBuilder.k() == null) {
             k = context.requestSize() == null || context.requestSize() < 0 ? DEFAULT_SIZE : context.requestSize();
+        } else {
+            k = queryBuilder.k();
         }
         if (queryBuilder.rescoreVectorBuilder() != null && isQuantizedElementType()) {
             if (queryBuilder.rescoreVectorBuilder().oversample() > 0) {
                 RescoreKnnVectorQuery rescoreQuery = (RescoreKnnVectorQuery) query;
-                assertEquals(k.intValue(), (rescoreQuery.k()));
+                assertEquals(k, (rescoreQuery.k()));
                 query = rescoreQuery.innerQuery();
             } else {
                 assertFalse(query instanceof RescoreKnnVectorQuery);
@@ -213,7 +215,7 @@ protected void doAssertLuceneQuery(KnnVectorQueryBuilder queryBuilder, Query que
         Query filterQuery = booleanQuery.clauses().isEmpty() ? null : booleanQuery;
         Integer numCands = queryBuilder.numCands();
         if (queryBuilder.rescoreVectorBuilder() != null && isQuantizedElementType()) {
-            Float oversample = queryBuilder.rescoreVectorBuilder().oversample();
+            float oversample = queryBuilder.rescoreVectorBuilder().oversample();
             k = Math.min(OVERSAMPLE_LIMIT, (int) Math.ceil(k * oversample));
             numCands = Math.max(numCands, k);
         }

server/src/test/java/org/elasticsearch/search/vectors/KnnSearchBuilderTests.java

@@ -110,93 +110,94 @@ protected KnnSearchBuilder createTestInstance() {
 
     @Override
     protected KnnSearchBuilder mutateInstance(KnnSearchBuilder instance) {
-        switch (random().nextInt(8)) {
-            case 0:
+        return switch (random().nextInt(8)) {
+            case 0 -> {
                 String newField = randomValueOtherThan(instance.field, () -> randomAlphaOfLength(5));
-                return new KnnSearchBuilder(
+                yield new KnnSearchBuilder(
                     newField,
                     instance.queryVector,
                     instance.k,
                     instance.numCands,
                     instance.getRescoreVectorBuilder(),
                     instance.similarity
                 ).boost(instance.boost);
-            case 1:
+            }
+            case 1 -> {
                 float[] newVector = randomValueOtherThan(instance.queryVector.asFloatVector(), () -> randomVector(5));
-                return new KnnSearchBuilder(
+                yield new KnnSearchBuilder(
                     instance.field,
                     newVector,
                     instance.k,
                     instance.numCands,
                     instance.getRescoreVectorBuilder(),
                     instance.similarity
                 ).boost(instance.boost);
-            case 2:
+            }
+            case 2 -> {
                 // given how the test instance is created, we have a 20-value gap between `k` and `numCands` so we SHOULD be safe
                 Integer newK = randomValueOtherThan(instance.k, () -> instance.k + ESTestCase.randomInt(10));
-                return new KnnSearchBuilder(
+                yield new KnnSearchBuilder(
                     instance.field,
                     instance.queryVector,
                     newK,
                     instance.numCands,
                     instance.getRescoreVectorBuilder(),
                     instance.similarity
                 ).boost(instance.boost);
-            case 3:
+            }
+            case 3 -> {
                 Integer newNumCands = randomValueOtherThan(instance.numCands, () -> instance.numCands + ESTestCase.randomInt(100));
-                return new KnnSearchBuilder(
+                yield new KnnSearchBuilder(
                     instance.field,
                     instance.queryVector,
                     instance.k,
                     newNumCands,
                     instance.getRescoreVectorBuilder(),
                     instance.similarity
                 ).boost(instance.boost);
-            case 4:
-                return new KnnSearchBuilder(
-                    instance.field,
-                    instance.queryVector,
-                    instance.k,
-                    instance.numCands,
-                    instance.getRescoreVectorBuilder(),
-                    instance.similarity
-                ).addFilterQueries(instance.filterQueries)
-                    .addFilterQuery(QueryBuilders.termQuery("new_field", "new-value"))
-                    .boost(instance.boost);
-            case 5:
+            }
+            case 4 -> new KnnSearchBuilder(
+                instance.field,
+                instance.queryVector,
+                instance.k,
+                instance.numCands,
+                instance.getRescoreVectorBuilder(),
+                instance.similarity
+            ).addFilterQueries(instance.filterQueries)
+                .addFilterQuery(QueryBuilders.termQuery("new_field", "new-value"))
+                .boost(instance.boost);
+            case 5 -> {
                 float newBoost = randomValueOtherThan(instance.boost, ESTestCase::randomFloat);
-                return new KnnSearchBuilder(
+                yield new KnnSearchBuilder(
                     instance.field,
                     instance.queryVector,
                     instance.k,
                     instance.numCands,
                     instance.getRescoreVectorBuilder(),
                     instance.similarity
                 ).addFilterQueries(instance.filterQueries).boost(newBoost);
-            case 6:
-                return new KnnSearchBuilder(
-                    instance.field,
-                    instance.queryVector,
-                    instance.k,
-                    instance.numCands,
+            }
+            case 6 -> new KnnSearchBuilder(
+                instance.field,
+                instance.queryVector,
+                instance.k,
+                instance.numCands,
+                instance.getRescoreVectorBuilder(),
+                randomValueOtherThan(instance.similarity, ESTestCase::randomFloat)
+            ).addFilterQueries(instance.filterQueries).boost(instance.boost);
+            case 7 -> new KnnSearchBuilder(
+                instance.field,
+                instance.queryVector,
+                instance.k,
+                instance.numCands,
+                randomValueOtherThan(
                     instance.getRescoreVectorBuilder(),
-                    randomValueOtherThan(instance.similarity, ESTestCase::randomFloat)
-                ).addFilterQueries(instance.filterQueries).boost(instance.boost);
-            case 7:
-                return new KnnSearchBuilder(
-                    instance.field,
-                    instance.queryVector,
-                    instance.k,
-                    instance.numCands,
-                    randomValueOtherThan(
-                        instance.getRescoreVectorBuilder(),
-                        () -> new RescoreVectorBuilder(randomFloatBetween(1.0f, 10.0f, false))
-                    ),
-                    instance.similarity
-                ).addFilterQueries(instance.filterQueries).boost(instance.boost);
-            default:
-                throw new IllegalStateException();
-        }
+                    () -> new RescoreVectorBuilder(randomFloatBetween(1.0f, 10.0f, false))
+                ),
+                instance.similarity
+            ).addFilterQueries(instance.filterQueries).boost(instance.boost);
+            default -> throw new IllegalStateException();
+        };
     }
 
     public void testToQueryBuilder() {

server/src/test/java/org/elasticsearch/search/vectors/TestQueryVectorBuilderPlugin.java

@@ -45,7 +45,7 @@ public static class TestQueryVectorBuilder implements QueryVectorBuilder {
             PARSER.declareFloatArray(ConstructingObjectParser.constructorArg(), QUERY_VECTOR);
         }
 
-        private List<Float> vectorToBuild;
+        private final List<Float> vectorToBuild;
 
         public TestQueryVectorBuilder(List<Float> vectorToBuild) {
             this.vectorToBuild = vectorToBuild;