DOCSP-43826: v5.2 release

config/redirects

@@ -1,6 +1,6 @@
 define: prefix docs/drivers/java/sync
 define: base https://www.mongodb.com/${prefix}
-define: versions v4.3 v4.4 v4.5 v4.6 v4.7 v4.8 v4.9 v4.10 v4.11 v5.0 v5.1 master
+define: versions v4.3 v4.4 v4.5 v4.6 v4.7 v4.8 v4.9 v4.10 v4.11 v5.0 v5.1 v5.2 master
 
 raw: ${prefix}/ -> ${base}/current/
 raw: ${prefix}/master -> ${base}/upcoming/

snooty.toml

@@ -20,8 +20,8 @@ sharedinclude_root = "https://raw.githubusercontent.com/10gen/docs-shared/main/"
 driver = "java"
 driver-long = "MongoDB Java Driver"
 driver-short = "Java driver"
-version = "5.1"
-full-version = "{+version+}.4"
+version = "5.2"
+full-version = "{+version+}.0"
 mdb-server = "MongoDB Server"
 package-name-org = "mongodb-org"
 api = "https://mongodb.github.io/mongo-java-driver/{+version+}"

source/fundamentals/builders/aggregates.txt

@@ -992,15 +992,17 @@ Atlas Vector Search
    :atlas:`Limitations </atlas-vector-search/vector-search-stage/#limitations>`
    in the MongoDB Atlas documentation.
 
-Use the ``vectorSearch()`` method to create a :atlas:`$vectorSearch </atlas-vector-search/vector-search-stage/>`
+Use the ``vectorSearch()`` method to create a :atlas:`$vectorSearch
+</atlas-vector-search/vector-search-stage/>`
 pipeline stage that specifies a **semantic search**. A semantic search is
 a type of search which locates information that is similar in meaning.
 
 To use this feature, you must set up a vector search index and index your
 vector embeddings. To learn about how to programmatically create a
 vector search index, see the :ref:`java-search-indexes` section in the Indexes guide. To
 learn more about vector embeddings, see
-:atlas:`How to Index Vector Embeddings for Vector Search </atlas-search/field-types/knn-vector/>`.
+:atlas:`How to Index Vector Embeddings for Vector Search
+</atlas-search/field-types/knn-vector/>`.
 
 The following example shows how to build an aggregation pipeline that uses the
 ``vectorSearch()`` and ``project()`` methods to compute a vector search score:
@@ -1020,5 +1022,7 @@ preceding aggregation pipeline:
    :language: java
    :dedent:
 
-Learn more about this helper from the
-`vectorSearch() <{+api+}//apidocs/mongodb-driver-core/com/mongodb/client/model/Aggregates.html#vectorSearch(com.mongodb.client.model.search.FieldSearchPath,java.lang.Iterable,java.lang.String,long,long)>`__ API documentation.
+Learn more about this helper in the
+`vectorSearch()
+<{+api+}/apidocs/mongodb-driver-core/com/mongodb/client/model/Aggregates.html#vectorSearch(com.mongodb.client.model.search.FieldSearchPath,java.lang.Iterable,java.lang.String,long,com.mongodb.client.model.search.VectorSearchOptions)>`__
+API documentation.

source/fundamentals/indexes.txt

@@ -257,6 +257,11 @@ The following code example shows how to create an Atlas Search index:
    :start-after: start create-search-index
    :end-before: end create-search-index
 
+To create multiple Search or Vector Search indexes, you must create a
+`SearchIndexModel
+<{+api+}/apidocs/mongodb-driver-core/com/mongodb/client/model/SearchIndexModel.html>`__
+instance for each index.
+
 The following code example shows how to create Search and
 Vector Search indexes in one call:
 

source/includes/fundamentals/code-snippets/SearchIndexMethods.java

@@ -2,6 +2,7 @@
 
 import com.mongodb.client.*;
 import com.mongodb.client.model.SearchIndexModel;
+import com.mongodb.client.model.SearchIndexType;
 import org.bson.Document;
 
 import java.util.Arrays;

source/includes/fundamentals/code-snippets/builders/AggBuilders.java

@@ -7,7 +7,7 @@
 import static com.mongodb.client.model.Sorts.*;
 import static com.mongodb.client.model.Accumulators.*;
 import static com.mongodb.client.model.search.SearchPath.fieldPath;
-import static com.mongodb.client.model.search.VectorSearchOptions.vectorSearchOptions;
+import static com.mongodb.client.model.search.VectorSearchOptions.exactVectorSearchOptions;
 import static java.util.Arrays.asList;
 // end static import
 
@@ -317,16 +317,14 @@ private void vectorSearchPipeline() {
         List<Double> queryVector = (asList(-0.0072121937, -0.030757688, -0.012945653));
         String indexName = "mflix_movies_embedding_index";
         FieldSearchPath fieldSearchPath = fieldPath("plot_embedding");
-        int numCandidates = 2;
         int limit = 1;
-        VectorSearchOptions options = vectorSearchOptions().filter(gte("year", 2016));
+        VectorSearchOptions options = exactVectorSearchOptions().filter(gte("year", 2016));
 
         List<Bson> pipeline = asList(
                 vectorSearch(
                         fieldSearchPath,
                         queryVector,
                         indexName,
-                        numCandidates,
                         limit,
                         options),
                 project(

source/includes/language-compatibility-table-java.rst

@@ -12,7 +12,7 @@
      - Java 6
      - Java 5
 
-   * - 5.1
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@@ -21,70 +21,7 @@
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 .. [#virtual-threads-note] This driver version is not compatible with virtual threads.