DOCSP-33664: fix explain agg code + other fixes (#503)

* DOCSP-33664: fix explain agg code + other fixes

* small fixes

(cherry picked from commit b34c2d6)
(cherry picked from commit 7522203)

Author: rustagir

source/compatibility.txt

@@ -21,6 +21,8 @@ Compatibility
    :depth: 2
    :class: singlecol
 
+Connect to a Compatible MongoDB Deployment
+------------------------------------------
 
 You can use the {+driver-short+} to connect to deployments hosted in the
 following environments:

source/fundamentals/aggregation.txt

@@ -1,7 +1,16 @@
+.. _java-aggregation:
+
 ===========
 Aggregation
 ===========
 
+.. facet::
+   :name: genre
+   :values: reference
+ 
+.. meta::
+   :keywords: code example, transform, computed
+
 .. contents:: On this page
    :local:
    :backlinks: none
@@ -11,37 +20,41 @@ Aggregation
 Overview
 --------
 
-.. _java-aggregation:
-
-In this guide, you can learn how to use **aggregation operations** in the MongoDB Java driver.
+In this guide, you can learn how to use the {+driver-short+} to perform
+**aggregation operations**.
 
-Aggregation operations process data in your MongoDB collections and return computed results. MongoDB's Aggregation
-pipeline, part of the Query API, is modeled on the concept of data processing pipelines. Documents enter a multi-staged pipeline that
-transforms the documents into an aggregated result.
+Aggregation operations process data in your MongoDB collections and
+return computed results. The MongoDB Aggregation framework, which is
+part of the Query API, is modeled on the concept of data processing
+pipelines. Documents enter a pipeline comprised of one or more stages,
+and this pipeline transforms the documents into an aggregated result.
 
-Another way to think of aggregation is like a car factory. Within the car factory is an assembly line, along which
-are assembly stations with specialized tools to do a specific job, like drills and welders. Raw parts enter the factory,
-which are then transformed and assembled into a finished product.
+An aggregation operation is similar to a car factory. A car factory has
+an assembly line, which contains assembly stations with specialized
+tools to do specific jobs, like drills and welders. Raw parts enter the
+factory, and then the assembly line transforms and assembles them into a
+finished product.
 
-The **aggregation pipeline** is the assembly line, **aggregation stages** are the assembly stations, and
-**operator expressions** are the specialized tools.
+The **aggregation pipeline** is the assembly line, **aggregation
+stages** are the assembly stations, and **operator expressions** are the
+specialized tools.
 
-Aggregation and Find Operations Compared
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+Compare Aggregation and Find Operations
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
-Using ``find`` operations, you can:
+You can use find operations to perform the following actions:
 
-- select *what* documents to return
-- select *what* fields to return
-- sort the results
+- Select *what* documents to return
+- Select *what* fields to return
+- Sort the results
 
-Using ``aggregation`` operations, you can:
+You can use aggregation operations to perform the following actions:
 
-- perform all ``find`` operations
-- rename fields
-- calculate fields
-- summarize data
-- group values
+- Perform find operations
+- Rename fields
+- Calculate fields
+- Summarize data
+- Group values
 
 Aggregation operations have some :manual:`limitations </core/aggregation-pipeline-limits/>` you must keep in mind:
 
@@ -68,8 +81,8 @@ Useful References
 Runnable Examples
 -----------------
 
-Base Setup
-~~~~~~~~~~
+Import Classes
+~~~~~~~~~~~~~~
 
 Create a new Java file called ``AggTour.java`` and include the following import statements:
 
@@ -79,7 +92,6 @@ Create a new Java file called ``AggTour.java`` and include the following import
    :start-after: begin imports
    :end-before: end imports
 
-
 Connect to a MongoDB Deployment
 +++++++++++++++++++++++++++++++
 
@@ -89,22 +101,23 @@ Connect to a MongoDB Deployment
 
        public static void main(String[] args) {
            // Replace the uri string with your MongoDB deployment's connection string
-           String uri = "<connection string uri>";
+           String uri = "<connection string>";
 
            MongoClient mongoClient = MongoClients.create(uri);
            MongoDatabase database = mongoClient.getDatabase("aggregation");
            MongoCollection<Document> collection = database.getCollection("restaurants");
 
-           // aggregation here
+           // Paste the aggregation code here
        }
    }
 
-.. seealso::
+.. tip::
 
-   For information on connecting to MongoDB, see the :ref:`Connection Guide <mongoclient>`
+   To learn more about connecting to MongoDB, see the :ref:`Connection
+   Guide <connect-to-mongodb>`.
 
-Insert the Data
-+++++++++++++++
+Insert Sample Data
+++++++++++++++++++
 
 .. literalinclude:: /includes/fundamentals/code-snippets/AggTour.java
    :language: java
@@ -131,15 +144,15 @@ In the following example, the aggregation pipeline:
 - Uses a :manual:`$group </reference/operator/aggregation/group/>` stage to group the matching documents by the ``stars``
   field, accumulating a count of documents for each distinct value of ``stars``.
 
-.. seealso::
+.. note::
 
    You can build the expressions used in this example using the :ref:`aggregation builders <aggregates-builders>`.
 
 .. literalinclude:: /includes/fundamentals/code-snippets/AggTour.java
    :language: java
    :dedent:
-   :start-after: begin aggregation one
-   :end-before: end aggregation one
+   :start-after: begin aggregation basic
+   :end-before: end aggregation basic
 
 The preceding aggregation should produce the following results:
 
@@ -162,32 +175,45 @@ To view information about how MongoDB executes your operation, use the
 ``explain()`` method of the ``AggregateIterable`` class. The ``explain()``
 method returns **execution plans** and performance statistics. An execution
 plan is a potential way MongoDB can complete an operation.
-The ``explain()`` method provides both the winning plan (the plan MongoDB
-executed) and rejected plans.
+The ``explain()`` method provides both the winning plan, which is the plan MongoDB
+executed, and any rejected plans.
+
+.. tip::
+   
+   To learn more about query plans and execution statistics, see
+   :manual:`Explain Results </reference/explain-results/>` in the Server manual.
 
 .. include:: /includes/fundamentals/explain-verbosity.rst
 
-In the following example, we print the JSON representation of the
-winning plans for aggregation stages that produce execution plans:
+The following example prints the JSON representation of the
+winning plans for any aggregation stages that produce execution plans:
 
 .. literalinclude:: /includes/fundamentals/code-snippets/AggTour.java
    :language: java
    :dedent:
-   :start-after: begin aggregation three
-   :end-before: end aggregation three
+   :start-after: begin aggregation explain
+   :end-before: end aggregation explain
 
-The preceding code snippet should produce the following output:
+The example produces the following output as the ``$group`` stage
+is the only stage that produces an execution plan:
 
 .. code-block:: none
    :copyable: false
 
-   { "stage": "PROJECTION_SIMPLE",
-     "transformBy": {"stars": 1, "_id": 0},
+   {
+     "stage": "GROUP",
+     "planNodeId": 2,
      "inputStage": {
-      "stage": "COLLSCAN",
-      "filter": {
-         "categories": {"$eq":"bakery"}},
-     "direction": "forward"}}
+       "stage": "COLLSCAN",
+       "planNodeId": 1,
+       "filter": {
+         "categories": {
+           "$eq": "Bakery"
+         }
+       },
+       "direction": "forward"
+     }
+   }
 
 For more information about the topics mentioned in this section, see the
 following resources:
@@ -201,7 +227,7 @@ following resources:
 Aggregation Expression Example
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
-The Java driver provides builders for accumulator expressions for use with
+The {+driver-short+} provides builders for accumulator expressions for use with
 ``$group``. You must declare all other expressions in JSON format or
 compatible document format.
 
@@ -211,7 +237,7 @@ compatible document format.
    expression.
 
    The ``$`` in front of "categories" tells MongoDB that this is a :manual:`field path </meta/aggregation-quick-reference/#expressions>`,
-   using the "categories" field from the input document.
+   using the ``categories`` field from the input document.
 
    .. code-block:: java
       :copyable: false
@@ -223,6 +249,10 @@ compatible document format.
 
       Document.parse("{ $arrayElemAt: ['$categories', 0] }")
 
+   Alternatively, you can construct expressions by using the Aggregation
+   Expression Operations API. To learn more, see
+   :ref:`java-aggregation-expression-operations`.
+
 In the following example, the aggregation pipeline uses a
 ``$project`` stage and various ``Projections`` to return the ``name``
 field and the calculated field ``firstCategory`` whose value is the
@@ -231,8 +261,8 @@ first element in the ``categories`` field.
 .. literalinclude:: /includes/fundamentals/code-snippets/AggTour.java
    :language: java
    :dedent:
-   :start-after: begin aggregation two
-   :end-before: end aggregation two
+   :start-after: begin aggregation expression
+   :end-before: end aggregation expression
 
 The preceding aggregation should produce the following results:
 

source/includes/fact-environments.rst

@@ -1,7 +1,7 @@
 - `MongoDB Atlas
-  <https://www.mongodb.com/docs/atlas>`__: The fully
+  <https://www.mongodb.com/docs/atlas>`__: the fully
   managed service for MongoDB deployments in the cloud
-- :ref:`MongoDB Enterprise <install-mdb-enterprise>`: The
+- :ref:`MongoDB Enterprise <install-mdb-enterprise>`: the
   subscription-based, self-managed version of MongoDB
-- :ref:`MongoDB Community <install-mdb-community-edition>`: The
-  source-available, free-to-use, and self-managed version of MongoDB
+- :ref:`MongoDB Community <install-mdb-community-edition>`: the
+  source-available, free-to-use, and self-managed version of MongoDB

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

@@ -1,7 +1,6 @@
 package docs.aggregation;
 
 // begin imports
-
 import com.mongodb.client.MongoClient;
 import com.mongodb.client.MongoClients;
 import com.mongodb.client.MongoCollection;
@@ -12,18 +11,18 @@
 import com.mongodb.client.model.Filters;
 import com.mongodb.client.model.Projections;
 import org.bson.Document;
+import org.bson.json.JsonWriterSettings;
 
 import java.util.Arrays;
 import java.util.List;
-
 // end imports
 
 // begin class intro
 // begin connection
 public class AggTour {
     public static void main(String[] args) {
         // Replace the uri string with your MongoDB deployment's connection string
-        final String uri = "<connection string uri>";
+        final String uri = "<connection string>";
 
         MongoClient mongoClient = MongoClients.create(uri);
         MongoDatabase database = mongoClient.getDatabase("aggregation");
@@ -49,37 +48,36 @@ public static void main(String[] args) {
         // end insert
 
         // Creates an aggregation pipeline that matches documents, groups them by the "stars" field, and tallies them by distinct values
-        // begin aggregation one
+        // begin aggregation basic
         collection.aggregate(
             Arrays.asList(
                 Aggregates.match(Filters.eq("categories", "Bakery")),
                 Aggregates.group("$stars", Accumulators.sum("count", 1))
             )
         // Prints the result of the aggregation operation as JSON
         ).forEach(doc -> System.out.println(doc.toJson()));
-        // end aggregation one
+        // end aggregation basic
 
-        // begin aggregation three
+        // begin aggregation explain
         Document explanation = collection.aggregate(
-            Arrays.asList(
-                    Aggregates.match(Filters.eq("categories", "Bakery")),
-                    Aggregates.group("$stars", Accumulators.sum("count", 1))
-            )
+                Arrays.asList(
+                        Aggregates.match(Filters.eq("categories", "Bakery")),
+                        Aggregates.group("$stars", Accumulators.sum("count", 1))
+                )
         ).explain(ExplainVerbosity.EXECUTION_STATS);
 
-        List<Document> stages = explanation.get("stages", List.class);
-        List<String> keys = Arrays.asList("queryPlanner", "winningPlan");
+        String winningPlans = explanation
+            .getEmbedded(
+                Arrays.asList("queryPlanner", "winningPlan", "queryPlan"),
+                Document.class
+            )
+            .toJson(JsonWriterSettings.builder().indent(true).build());
+
+        System.out.println(winningPlans);
+        // end aggregation explain
 
-        // Prints the JSON representation of the winning execution plans
-        for (Document stage : stages) {
-            Document cursorStage = stage.get("$cursor", Document.class);
-            if (cursorStage != null) {
-                System.out.println(cursorStage.getEmbedded(keys, Document.class).toJson());
-            }
-        }
-        // end aggregation three
         // Prints the restaurant name and the first value in the "categories" array as a field named "firstCategory"
-        // begin aggregation two
+        // begin aggregation expression
         collection.aggregate(
             Arrays.asList(
                 Aggregates.project(
@@ -88,12 +86,15 @@ public static void main(String[] args) {
                         Projections.include("name"),
                         Projections.computed(
                             "firstCategory",
-                            new Document("$arrayElemAt", Arrays.asList("$categories", 0))
+                            new Document(
+                                "$arrayElemAt", 
+                                Arrays.asList("$categories", 0)
+                            )
                         )
                     )
                 )
             )
         ).forEach(doc -> System.out.println(doc.toJson()));
-        // end aggregation two
+        // end aggregation expression
     }
 }

source/index.txt

@@ -45,11 +45,11 @@ If your Java application requires asynchronous stream processing, use the
 :driver:`Reactive Streams Driver </reactive-streams/>` which uses Reactive
 Streams to make non-blocking calls to MongoDB.
 
-Compatibility
--------------
+Connect to a Compatible MongoDB Deployment
+------------------------------------------
 
-You can use the {+driver-short+} to connect to deployments hosted in the
-following environments:
+You can use the {+driver-short+} to connect to MongoDB
+deployments running on one of the following hosted services or editions:
 
 .. include:: /includes/fact-environments.rst