Minor performance improvments in KNNQueryBuilder (#2528) (#2531)

Signed-off-by: Tejas Shah <shatejas@amazon.com>
(cherry picked from commit 45ecb5b)

Co-authored-by: Tejas Shah <shatejas@amazon.com>

Author: opensearch-trigger-bot[bot]

src/main/java/org/opensearch/knn/index/query/KNNQueryBuilder.java

@@ -9,7 +9,6 @@
 import lombok.AllArgsConstructor;
 import lombok.Getter;
 import lombok.extern.log4j.Log4j2;
-import org.apache.commons.lang.StringUtils;
 import org.apache.lucene.search.MatchNoDocsQuery;
 import org.apache.lucene.search.Query;
 import org.opensearch.common.ValidationException;
@@ -24,6 +23,7 @@
 import org.opensearch.index.query.QueryRewriteContext;
 import org.opensearch.index.query.QueryShardContext;
 import org.opensearch.knn.index.engine.KNNMethodConfigContext;
+import org.opensearch.knn.index.engine.KNNMethodContext;
 import org.opensearch.knn.index.engine.model.QueryContext;
 import org.opensearch.knn.index.engine.qframe.QuantizationConfig;
 import org.opensearch.knn.index.mapper.KNNMappingConfig;
@@ -47,7 +47,6 @@
 import java.util.Locale;
 import java.util.Map;
 import java.util.Objects;
-import java.util.concurrent.atomic.AtomicReference;
 
 import static org.opensearch.knn.common.KNNConstants.EXPAND_NESTED;
 import static org.opensearch.knn.common.KNNConstants.MAX_DISTANCE;
@@ -393,40 +392,12 @@ protected Query doToQuery(QueryShardContext context) {
         }
         KNNVectorFieldType knnVectorFieldType = (KNNVectorFieldType) mappedFieldType;
         KNNMappingConfig knnMappingConfig = knnVectorFieldType.getKnnMappingConfig();
-        final AtomicReference<QueryConfigFromMapping> queryConfigFromMapping = new AtomicReference<>();
-        int fieldDimension = knnMappingConfig.getDimension();
-        knnMappingConfig.getKnnMethodContext()
-            .ifPresentOrElse(
-                knnMethodContext -> queryConfigFromMapping.set(
-                    new QueryConfigFromMapping(
-                        knnMethodContext.getKnnEngine(),
-                        knnMethodContext.getMethodComponentContext(),
-                        knnMethodContext.getSpaceType(),
-                        knnVectorFieldType.getVectorDataType()
-                    )
-                ),
-                () -> knnMappingConfig.getModelId().ifPresentOrElse(modelId -> {
-                    ModelMetadata modelMetadata = getModelMetadataForField(modelId);
-                    queryConfigFromMapping.set(
-                        new QueryConfigFromMapping(
-                            modelMetadata.getKnnEngine(),
-                            modelMetadata.getMethodComponentContext(),
-                            modelMetadata.getSpaceType(),
-                            modelMetadata.getVectorDataType()
-                        )
-                    );
-                },
-                    () -> {
-                        throw new IllegalArgumentException(
-                            String.format(Locale.ROOT, "Field '%s' is not built for ANN search.", this.fieldName)
-                        );
-                    }
-                )
-            );
-        KNNEngine knnEngine = queryConfigFromMapping.get().getKnnEngine();
-        MethodComponentContext methodComponentContext = queryConfigFromMapping.get().getMethodComponentContext();
-        SpaceType spaceType = queryConfigFromMapping.get().getSpaceType();
-        VectorDataType vectorDataType = queryConfigFromMapping.get().getVectorDataType();
+        QueryConfigFromMapping queryConfigFromMapping = getQueryConfig(knnMappingConfig, knnVectorFieldType);
+
+        KNNEngine knnEngine = queryConfigFromMapping.getKnnEngine();
+        MethodComponentContext methodComponentContext = queryConfigFromMapping.getMethodComponentContext();
+        SpaceType spaceType = queryConfigFromMapping.getSpaceType();
+        VectorDataType vectorDataType = queryConfigFromMapping.getVectorDataType();
         RescoreContext processedRescoreContext = knnVectorFieldType.resolveRescoreContext(rescoreContext);
         knnVectorFieldType.transformQueryVector(vector);
 
@@ -435,7 +406,7 @@ protected Query doToQuery(QueryShardContext context) {
 
         // This could be null in the case of when a model did not have serialized methodComponent information
         final String method = methodComponentContext != null ? methodComponentContext.getName() : null;
-        if (StringUtils.isNotBlank(method)) {
+        if (method != null && !method.isBlank()) {
             final KNNLibrarySearchContext engineSpecificMethodContext = knnEngine.getKNNLibrarySearchContext(method);
             QueryContext queryContext = new QueryContext(vectorQueryType);
             ValidationException validationException = validateParameters(
@@ -494,9 +465,13 @@ protected Query doToQuery(QueryShardContext context) {
         }
 
         int vectorLength = VectorDataType.BINARY == vectorDataType ? vector.length * Byte.SIZE : vector.length;
-        if (fieldDimension != vectorLength) {
+        if (knnMappingConfig.getDimension() != vectorLength) {
             throw new IllegalArgumentException(
-                String.format("Query vector has invalid dimension: %d. Dimension should be: %d", vectorLength, fieldDimension)
+                String.format(
+                    "Query vector has invalid dimension: %d. Dimension should be: %d",
+                    vectorLength,
+                    knnMappingConfig.getDimension()
+                )
             );
         }
 
@@ -572,6 +547,31 @@ protected Query doToQuery(QueryShardContext context) {
         throw new IllegalArgumentException(String.format(Locale.ROOT, "[%s] requires k or distance or score to be set", NAME));
     }
 
+    private QueryConfigFromMapping getQueryConfig(final KNNMappingConfig knnMappingConfig, final KNNVectorFieldType knnVectorFieldType) {
+
+        if (knnMappingConfig.getKnnMethodContext().isPresent()) {
+            KNNMethodContext knnMethodContext = knnMappingConfig.getKnnMethodContext().get();
+            return new QueryConfigFromMapping(
+                knnMethodContext.getKnnEngine(),
+                knnMethodContext.getMethodComponentContext(),
+                knnMethodContext.getSpaceType(),
+                knnVectorFieldType.getVectorDataType()
+            );
+        }
+
+        if (knnMappingConfig.getModelId().isPresent()) {
+            ModelMetadata modelMetadata = getModelMetadataForField(knnMappingConfig.getModelId().get());
+            return new QueryConfigFromMapping(
+                modelMetadata.getKnnEngine(),
+                modelMetadata.getMethodComponentContext(),
+                modelMetadata.getSpaceType(),
+                modelMetadata.getVectorDataType()
+            );
+        }
+
+        throw new IllegalArgumentException(String.format(Locale.ROOT, "Field '%s' is not built for ANN search.", this.fieldName));
+    }
+
     private ModelMetadata getModelMetadataForField(String modelId) {
         ModelMetadata modelMetadata = modelDao.getMetadata(modelId);
         if (!ModelUtil.isModelCreated(modelMetadata)) {

src/main/java/org/opensearch/knn/index/query/KNNQueryFactory.java

@@ -121,7 +121,7 @@ public static Query create(CreateQueryRequest createQueryRequest) {
             requestEfSearch = (Integer) methodParameters.get(METHOD_PARAMETER_EF_SEARCH);
         }
         int luceneK = requestEfSearch == null ? k : Math.max(k, requestEfSearch);
-        log.debug(String.format("Creating Lucene k-NN query for index: %s \"\", field: %s \"\", k: %d", indexName, fieldName, k));
+        log.debug("Creating Lucene k-NN query for index: {}, field:{}, k: {}", indexName, fieldName, k);
         switch (vectorDataType) {
             case BYTE:
             case BINARY: