Add radial search feature to main branch

CHANGELOG.md

@@ -14,6 +14,7 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
 
 ## [Unreleased 2.x](https://github.com/opensearch-project/k-NN/compare/2.13...2.x)
 ### Features
+* Support radial search in k-NN plugin [#1617](https://github.com/opensearch-project/k-NN/pull/1617)
 ### Enhancements
 * Make the HitQueue size more appropriate for exact search [#1549](https://github.com/opensearch-project/k-NN/pull/1549)
 * Support script score when doc value is disabled [#1573](https://github.com/opensearch-project/k-NN/pull/1573)

jni/include/faiss_wrapper.h

@@ -73,6 +73,18 @@ namespace knn_jni {
         // Return the serialized representation
         jbyteArray TrainIndex(knn_jni::JNIUtilInterface * jniUtil, JNIEnv * env, jobject parametersJ, jint dimension,
                               jlong trainVectorsPointerJ);
+
+        /*
+         * Perform a range search against the index located in memory at indexPointerJ.
+         *
+         * @param indexPointerJ - pointer to the index
+         * @param queryVectorJ - the query vector
+         * @param radiusJ - the radius for the range search
+         * @param maxResultsWindowJ - the maximum number of results to return
+         * @return an array of RangeQueryResults
+         */
+        jobjectArray RangeSearch(knn_jni::JNIUtilInterface *jniUtil, JNIEnv *env, jlong indexPointerJ, jfloatArray queryVectorJ,
+                    jfloat radiusJ, jint maxResultsWindowJ);
     }
 }
 

jni/include/org_opensearch_knn_jni_FaissService.h

@@ -122,6 +122,14 @@ JNIEXPORT jbyteArray JNICALL Java_org_opensearch_knn_jni_FaissService_trainIndex
 JNIEXPORT jlong JNICALL Java_org_opensearch_knn_jni_FaissService_transferVectors
   (JNIEnv *, jclass, jlong, jobjectArray);
 
+/*
+* Class:     org_opensearch_knn_jni_FaissService
+* Method:    rangeSearchIndex
+* Signature: (J[F[F)J
+*/
+JNIEXPORT jobjectArray JNICALL Java_org_opensearch_knn_jni_FaissService_rangeSearchIndex
+  (JNIEnv *, jclass, jlong, jfloatArray, jfloat, jint);
+
 #ifdef __cplusplus
 }
 #endif

jni/src/faiss_wrapper.cpp

@@ -587,3 +587,47 @@ faiss::IndexIVFPQ * extractIVFPQIndex(faiss::Index * index) {
 
     throw std::runtime_error("Unable to extract IVFPQ index. IVFPQ index not present.");
 }
+
+jobjectArray knn_jni::faiss_wrapper::RangeSearch(knn_jni::JNIUtilInterface *jniUtil, JNIEnv *env, jlong indexPointerJ,
+                                                 jfloatArray queryVectorJ, jfloat radiusJ, jint maxResultWindowJ) {
+    if (queryVectorJ == nullptr) {
+        throw std::runtime_error("Query Vector cannot be null");
+    }
+
+    auto *indexReader = reinterpret_cast<faiss::IndexIDMap *>(indexPointerJ);
+
+    if (indexReader == nullptr) {
+        throw std::runtime_error("Invalid pointer to indexReader");
+    }
+
+    float *rawQueryVector = jniUtil->GetFloatArrayElements(env, queryVectorJ, nullptr);
+
+    // The res will be freed by ~RangeSearchResult() in FAISS
+    // The second parameter is always true, as lims is allocated by FAISS
+    faiss::RangeSearchResult res(1, true);
+    indexReader->range_search(1, rawQueryVector, radiusJ, &res);
+
+    // lims is structured to support batched queries, it has a length of nq + 1 (where nq is the number of queries),
+    // lims[i] - lims[i-1] gives the number of results for the i-th query. With a single query we used in k-NN,
+    // res.lims[0] is always 0, and res.lims[1] gives the total number of matching entries found.
+    int resultSize = res.lims[1];
+
+    // Limit the result size to maxResultWindowJ so that we don't return more than the max result window
+    // TODO: In the future, we should prevent this via FAISS's ResultHandler.
+    if (resultSize > maxResultWindowJ) {
+        resultSize = maxResultWindowJ;
+    }
+
+    jclass resultClass = jniUtil->FindClass(env,"org/opensearch/knn/index/query/KNNQueryResult");
+    jmethodID allArgs = jniUtil->FindMethod(env, "org/opensearch/knn/index/query/KNNQueryResult", "<init>");
+
+    jobjectArray results = jniUtil->NewObjectArray(env, resultSize, resultClass, nullptr);
+
+    jobject result;
+    for(int i = 0; i < resultSize; ++i) {
+        result = jniUtil->NewObject(env, resultClass, allArgs, res.labels[i], res.distances[i]);
+        jniUtil->SetObjectArrayElement(env, results, i, result);
+    }
+
+    return results;
+}

jni/src/org_opensearch_knn_jni_FaissService.cpp

@@ -190,3 +190,17 @@ JNIEXPORT jlong JNICALL Java_org_opensearch_knn_jni_FaissService_transferVectors
 
     return (jlong) vect;
 }
+
+JNIEXPORT jobjectArray JNICALL Java_org_opensearch_knn_jni_FaissService_rangeSearchIndex(JNIEnv * env, jclass cls,
+                                                                                   jlong indexPointerJ,
+                                                                                   jfloatArray queryVectorJ,
+                                                                                   jfloat radiusJ, jint maxResultWindowJ)
+{
+    try {
+        return knn_jni::faiss_wrapper::RangeSearch(&jniUtil, env, indexPointerJ, queryVectorJ, radiusJ, maxResultWindowJ);
+
+    } catch (...) {
+        jniUtil.CatchCppExceptionAndThrowJava(env);
+    }
+    return nullptr;
+}

jni/tests/faiss_wrapper_test.cpp

@@ -615,3 +615,116 @@ TEST(FaissInitAndSetSharedIndexState, BasicAssertions) {
     ASSERT_EQ(1, ivfpqIndex->use_precomputed_table);
     knn_jni::faiss_wrapper::FreeSharedIndexState(sharedModelAddress);
 }
+
+TEST(FaissRangeSearchQueryIndexTest, BasicAssertions) {
+    // Define the index data
+    faiss::idx_t numIds = 200;
+    int dim = 2;
+    std::vector<faiss::idx_t> ids = test_util::Range(numIds);
+    std::vector<float> vectors = test_util::RandomVectors(dim, numIds, randomDataMin, randomDataMax);
+
+    faiss::MetricType metricType = faiss::METRIC_L2;
+    std::string method = "HNSW32,Flat";
+
+    // Define query data
+    float radius = 100000.0;
+    int numQueries = 2;
+    std::vector<std::vector<float>> queries;
+
+    for (int i = 0; i < numQueries; i++) {
+        std::vector<float> query;
+        query.reserve(dim);
+        for (int j = 0; j < dim; j++) {
+            query.push_back(test_util::RandomFloat(randomDataMin, randomDataMax));
+        }
+        queries.push_back(query);
+    }
+
+    // Create the index
+    std::unique_ptr<faiss::Index> createdIndex(
+            test_util::FaissCreateIndex(dim, method, metricType));
+    auto createdIndexWithData =
+            test_util::FaissAddData(createdIndex.get(), ids, vectors);
+
+    // Setup jni
+    JNIEnv *jniEnv = nullptr;
+    NiceMock<test_util::MockJNIUtil> mockJNIUtil;
+
+    int maxResultWindow = 20000;
+
+    for (auto query : queries) {
+        std::unique_ptr<std::vector<std::pair<int, float> *>> results(
+                reinterpret_cast<std::vector<std::pair<int, float> *> *>(
+
+                        knn_jni::faiss_wrapper::RangeSearch(
+                                &mockJNIUtil, jniEnv,
+                                reinterpret_cast<jlong>(&createdIndexWithData),
+                                reinterpret_cast<jfloatArray>(&query), radius, maxResultWindow)));
+
+        // assert result size is not 0
+        ASSERT_NE(0, results->size());
+
+
+        // Need to free up each result
+        for (auto it : *results) {
+            delete it;
+        }
+    }
+}
+
+TEST(FaissRangeSearchQueryIndexTest_WhenHitMaxWindowResult, BasicAssertions){
+    // Define the index data
+    faiss::idx_t numIds = 200;
+    int dim = 2;
+    std::vector<faiss::idx_t> ids = test_util::Range(numIds);
+    std::vector<float> vectors = test_util::RandomVectors(dim, numIds, randomDataMin, randomDataMax);
+
+    faiss::MetricType metricType = faiss::METRIC_L2;
+    std::string method = "HNSW32,Flat";
+
+    // Define query data
+    float radius = 100000.0;
+    int numQueries = 2;
+    std::vector<std::vector<float>> queries;
+
+    for (int i = 0; i < numQueries; i++) {
+        std::vector<float> query;
+        query.reserve(dim);
+        for (int j = 0; j < dim; j++) {
+            query.push_back(test_util::RandomFloat(randomDataMin, randomDataMax));
+        }
+        queries.push_back(query);
+    }
+
+    // Create the index
+    std::unique_ptr<faiss::Index> createdIndex(
+            test_util::FaissCreateIndex(dim, method, metricType));
+    auto createdIndexWithData =
+            test_util::FaissAddData(createdIndex.get(), ids, vectors);
+
+    // Setup jni
+    JNIEnv *jniEnv = nullptr;
+    NiceMock<test_util::MockJNIUtil> mockJNIUtil;
+
+    int maxResultWindow = 10;
+
+    for (auto query : queries) {
+        std::unique_ptr<std::vector<std::pair<int, float> *>> results(
+                reinterpret_cast<std::vector<std::pair<int, float> *> *>(
+
+                        knn_jni::faiss_wrapper::RangeSearch(
+                                &mockJNIUtil, jniEnv,
+                                reinterpret_cast<jlong>(&createdIndexWithData),
+                                reinterpret_cast<jfloatArray>(&query), radius, maxResultWindow)));
+
+        // assert result size is not 0
+        ASSERT_NE(0, results->size());
+        // assert result size is equal to maxResultWindow
+        ASSERT_EQ(maxResultWindow, results->size());
+
+        // Need to free up each result
+        for (auto it : *results) {
+            delete it;
+        }
+    }
+}

src/main/java/org/opensearch/knn/common/KNNConstants.java

@@ -67,6 +67,8 @@ public class KNNConstants {
     public static final String VECTOR_DATA_TYPE_FIELD = "data_type";
     public static final VectorDataType DEFAULT_VECTOR_DATA_TYPE_FIELD = VectorDataType.FLOAT;
 
+    public static final String RADIAL_SEARCH_KEY = "radial_search";
+
     // Lucene specific constants
     public static final String LUCENE_NAME = "lucene";
 

src/main/java/org/opensearch/knn/index/IndexUtil.java

@@ -43,11 +43,13 @@ public class IndexUtil {
     private static final Version MINIMAL_SUPPORTED_VERSION_FOR_IGNORE_UNMAPPED = Version.V_2_11_0;
     private static final Version MINIMAL_SUPPORTED_VERSION_FOR_MODEL_NODE_ASSIGNMENT = Version.V_2_12_0;
     private static final Version MINIMAL_SUPPORTED_VERSION_FOR_MODEL_METHOD_COMPONENT_CONTEXT = Version.V_2_13_0;
+    private static final Version MINIMAL_SUPPORTED_VERSION_FOR_RADIAL_SEARCH = Version.V_2_14_0;
     private static final Map<String, Version> minimalRequiredVersionMap = new HashMap<String, Version>() {
         {
             put("ignore_unmapped", MINIMAL_SUPPORTED_VERSION_FOR_IGNORE_UNMAPPED);
             put(MODEL_NODE_ASSIGNMENT_KEY, MINIMAL_SUPPORTED_VERSION_FOR_MODEL_NODE_ASSIGNMENT);
             put(MODEL_METHOD_COMPONENT_CONTEXT_KEY, MINIMAL_SUPPORTED_VERSION_FOR_MODEL_METHOD_COMPONENT_CONTEXT);
+            put(KNNConstants.RADIAL_SEARCH_KEY, MINIMAL_SUPPORTED_VERSION_FOR_RADIAL_SEARCH);
         }
     };
 

src/main/java/org/opensearch/knn/index/SpaceType.java

@@ -36,6 +36,14 @@ public float scoreTranslation(float rawScore) {
         public VectorSimilarityFunction getVectorSimilarityFunction() {
             return VectorSimilarityFunction.EUCLIDEAN;
         }
+
+        @Override
+        public float scoreToDistanceTranslation(float score) {
+            if (score == 0) {
+                throw new IllegalArgumentException(String.format(Locale.ROOT, "score cannot be 0 when space type is [%s]", getValue()));
+            }
+            return 1 / score - 1;
+        }
     },
     COSINESIMIL("cosinesimil") {
         @Override
@@ -170,4 +178,14 @@ public static SpaceType getSpace(String spaceTypeName) {
         }
         throw new IllegalArgumentException("Unable to find space: " + spaceTypeName);
     }
+
+    /**
+     * Translate a score to a distance for this space type
+     *
+     * @param score score to translate
+     * @return translated distance
+     */
+    public float scoreToDistanceTranslation(float score) {
+        throw new UnsupportedOperationException(String.format("Space [%s] does not have a score to distance translation", getValue()));
+    }
 }

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

@@ -0,0 +1,95 @@
+/*
+ * Copyright OpenSearch Contributors
+ * SPDX-License-Identifier: Apache-2.0
+ */
+
+package org.opensearch.knn.index.query;
+
+import lombok.AllArgsConstructor;
+import lombok.Builder;
+import lombok.Getter;
+import lombok.NonNull;
+import lombok.extern.log4j.Log4j2;
+import org.apache.lucene.search.Query;
+import org.apache.lucene.search.join.BitSetProducer;
+import org.apache.lucene.search.join.ToChildBlockJoinQuery;
+import org.opensearch.index.query.QueryBuilder;
+import org.opensearch.index.query.QueryShardContext;
+import org.opensearch.index.search.NestedHelper;
+import org.opensearch.knn.index.VectorDataType;
+import org.opensearch.knn.index.util.KNNEngine;
+
+import java.io.IOException;
+import java.util.Optional;
+
+/**
+* Base class for creating vector search queries.
+*/
+@Log4j2
+public abstract class BaseQueryFactory {
+    /**
+     * DTO object to hold data required to create a Query instance.
+     */
+    @AllArgsConstructor
+    @Builder
+    @Getter
+    public static class CreateQueryRequest {
+        @NonNull
+        private KNNEngine knnEngine;
+        @NonNull
+        private String indexName;
+        private String fieldName;
+        private float[] vector;
+        private byte[] byteVector;
+        private VectorDataType vectorDataType;
+        private Integer k;
+        private Float radius;
+        private QueryBuilder filter;
+        private QueryShardContext context;
+
+        public Optional<QueryBuilder> getFilter() {
+            return Optional.ofNullable(filter);
+        }
+
+        public Optional<QueryShardContext> getContext() {
+            return Optional.ofNullable(context);
+        }
+    }
+
+    /**
+     * Creates a query filter.
+     *
+     * @param createQueryRequest request object that has all required fields to construct the query
+     * @return Lucene Query
+     */
+    protected static Query getFilterQuery(BaseQueryFactory.CreateQueryRequest createQueryRequest) {
+        if (!createQueryRequest.getFilter().isPresent()) {
+            return null;
+        }
+
+        final QueryShardContext queryShardContext = createQueryRequest.getContext()
+            .orElseThrow(() -> new RuntimeException("Shard context cannot be null"));
+        log.debug(
+            String.format(
+                "Creating query with filter for index [%s], field [%s]",
+                createQueryRequest.getIndexName(),
+                createQueryRequest.getFieldName()
+            )
+        );
+        final Query filterQuery;
+        try {
+            filterQuery = createQueryRequest.getFilter().get().toQuery(queryShardContext);
+        } catch (IOException e) {
+            throw new RuntimeException("Cannot create query with filter", e);
+        }
+        BitSetProducer parentFilter = queryShardContext.getParentFilter();
+        if (parentFilter != null) {
+            boolean mightMatch = new NestedHelper(queryShardContext.getMapperService()).mightMatchNestedDocs(filterQuery);
+            if (mightMatch) {
+                return filterQuery;
+            }
+            return new ToChildBlockJoinQuery(filterQuery, parentFilter);
+        }
+        return filterQuery;
+    }
+}