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Aggregation

Aggregation Examples

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Overview

This page demonstrates how to use aggregation pipelines.

Import Classes

Create a new Java file called AggTour.java and include the following import statements:

import com.mongodb.client.MongoClient;
import com.mongodb.client.MongoClients;
import com.mongodb.client.MongoCollection;
import com.mongodb.client.MongoDatabase;
import com.mongodb.ExplainVerbosity;
import com.mongodb.client.model.Accumulators;
import com.mongodb.client.model.Aggregates;
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;

Connect to a MongoDB Deployment

public class AggTour {
    public static void main(String[] args) {
        // Replace the uri string with your MongoDB deployment's connection string
        String uri = "<connection string>";
        MongoClient mongoClient = MongoClients.create(uri);
        MongoDatabase database = mongoClient.getDatabase("aggregation");
        MongoCollection<Document> collection = database.getCollection("restaurants");
        // Paste the aggregation code here
    }
}

Tip

To learn more about connecting to MongoDB, see the Connection Guide.

Insert Sample Data

collection.insertMany(Arrays.asList(
    new Document("name", "Sun Bakery Trattoria").append("contact", new Document().append("phone", "386-555-0189").append("email", "SunBakeryTrattoria@example.org").append("location", Arrays.asList(-74.0056649, 40.7452371))).append("stars", 4).append("categories", Arrays.asList("Pizza", "Pasta", "Italian", "Coffee", "Sandwiches")),
    new Document("name", "Blue Bagels Grill").append("contact", new Document().append("phone", "786-555-0102").append("email", "BlueBagelsGrill@example.com").append("location", Arrays.asList(-73.92506, 40.8275556))).append("stars", 3).append("categories", Arrays.asList("Bagels", "Cookies", "Sandwiches")),
    new Document("name", "XYZ Bagels Restaurant").append("contact", new Document().append("phone", "435-555-0190").append("email", "XYZBagelsRestaurant@example.net").append("location", Arrays.asList(-74.0707363, 40.59321569999999))).append("stars", 4).append("categories", Arrays.asList("Bagels", "Sandwiches", "Coffee")),
    new Document("name", "Hot Bakery Cafe").append("contact", new Document().append("phone", "264-555-0171").append("email", "HotBakeryCafe@example.net").append("location", Arrays.asList(-73.96485799999999, 40.761899))).append("stars", 4).append("categories", Arrays.asList("Bakery", "Cafe", "Coffee", "Dessert")),
    new Document("name", "Green Feast Pizzeria").append("contact", new Document().append("phone", "840-555-0102").append("email", "GreenFeastPizzeria@example.com").append("location", Arrays.asList(-74.1220973, 40.6129407))).append("stars", 2).append("categories", Arrays.asList("Pizza", "Italian")),
    new Document("name", "ZZZ Pasta Buffet").append("contact", new Document().append("phone", "769-555-0152").append("email", "ZZZPastaBuffet@example.com").append("location", Arrays.asList(-73.9446421, 40.7253944))).append("stars", 0).append("categories", Arrays.asList("Pasta", "Italian", "Buffet", "Cafeteria")),
    new Document("name", "XYZ Coffee Bar").append("contact", new Document().append("phone", "644-555-0193").append("email", "XYZCoffeeBar@example.net").append("location", Arrays.asList(-74.0166091, 40.6284767))).append("stars", 5).append("categories", Arrays.asList("Coffee", "Cafe", "Bakery", "Chocolates")),
    new Document("name", "456 Steak Restaurant").append("contact", new Document().append("phone", "990-555-0165").append("email", "456SteakRestaurant@example.com").append("location", Arrays.asList(-73.9365108, 40.8497077))).append("stars", 0).append("categories", Arrays.asList("Steak", "Seafood")),
    new Document("name", "456 Cookies Shop").append("contact", new Document().append("phone", "604-555-0149").append("email", "456CookiesShop@example.org").append("location", Arrays.asList(-73.8850023, 40.7494272))).append("stars", 4).append("categories", Arrays.asList("Bakery", "Cookies", "Cake", "Coffee")),
    new Document("name", "XYZ Steak Buffet").append("contact", new Document().append("phone", "229-555-0197").append("email", "XYZSteakBuffet@example.org").append("location", Arrays.asList(-73.9799932, 40.7660886))).append("stars", 3).append("categories", Arrays.asList("Steak", "Salad", "Chinese"))
));

Basic Aggregation Example

To perform an aggregation, pass a list of aggregation stages to the MongoCollection.aggregate() method.

The Java driver provides the Aggregates helper class that contains builders for aggregation stages.

In the following example, the aggregation pipeline:

  • Uses a $match stage to filter for documents whose categories array field contains the element Bakery. The example uses Aggregates.match to build the $match stage.

  • Uses a $group stage to group the matching documents by the stars field, accumulating a count of documents for each distinct value of stars.

Note

You can build the expressions used in this example using the aggregation builders.

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()));

The preceding aggregation produces the following results:

{"_id": 4, "count": 2}
{"_id": 5, "count": 1}

For more information about the methods and classes mentioned in this section, see the following API Documentation:

Explain Aggregation Example

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, which is the plan MongoDB executed, and any rejected plans.

Tip

To learn more about query plans and execution statistics, see Explain Results in the Server manual.

You can specify the level of detail of your explanation by passing a verbosity level to the explain() method.

The following table shows all verbosity levels for explanations and their intended use cases:

Verbosity Level
Use Case

ALL_PLANS_EXECUTIONS

You want to know which plan MongoDB will choose to run your query.

EXECUTION_STATS

You want to know if your query is performing well.

QUERY_PLANNER

You have a problem with your query and you want as much information as possible to diagnose the issue.

The following example prints the JSON representation of the winning plans for any aggregation stages that produce execution plans:

Document explanation = collection.aggregate(
        Arrays.asList(
                Aggregates.match(Filters.eq("categories", "Bakery")),
                Aggregates.group("$stars", Accumulators.sum("count", 1))
        )
).explain(ExplainVerbosity.EXECUTION_STATS);
String winningPlans = explanation
    .getEmbedded(
        Arrays.asList("queryPlanner", "winningPlan", "queryPlan"),
        Document.class
    )
    .toJson(JsonWriterSettings.builder().indent(true).build());
System.out.println(winningPlans);

The example produces the following output as the $group stage is the only stage that produces an execution plan:

{
  "stage": "GROUP",
  "planNodeId": 2,
  "inputStage": {
    "stage": "COLLSCAN",
    "planNodeId": 1,
    "filter": {
      "categories": {
        "$eq": "Bakery"
      }
    },
    "direction": "forward"
  }
}

For more information about the topics mentioned in this section, see the following resources:

Aggregation Expression Example

The Java driver provides builders for accumulator expressions for use with $group. You must declare all other expressions in JSON format or compatible document format.

Tip

The syntax in either of the following examples will define an $arrayElemAt expression.

The $ in front of "categories" tells MongoDB that this is a field path, using the categories field from the input document.

new Document("$arrayElemAt", Arrays.asList("$categories", 0))
Document.parse("{ $arrayElemAt: ['$categories', 0] }")

Alternatively, you can construct expressions by using the Aggregation Expression Operations API. To learn more, see 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 first element in the categories field.

collection.aggregate(
    Arrays.asList(
        Aggregates.project(
            Projections.fields(
                Projections.excludeId(),
                Projections.include("name"),
                Projections.computed(
                    "firstCategory",
                    new Document(
                        "$arrayElemAt", 
                        Arrays.asList("$categories", 0)
                    )
                )
            )
        )
    )
).forEach(doc -> System.out.println(doc.toJson()));

The preceding aggregation produces the following results:

{"name": "456 Cookies Shop", "firstCategory": "Bakery"}
{"name": "Sun Bakery Trattoria", "firstCategory": "Pizza"}
{"name": "456 Steak Restaurant", "firstCategory": "Steak"}
{"name": "Blue Bagels Grill", "firstCategory": "Bagels"}
{"name": "XYZ Steak Buffet", "firstCategory": "Steak"}
{"name": "Hot Bakery Cafe", "firstCategory": "Bakery"}
{"name": "Green Feast Pizzeria", "firstCategory": "Pizza"}
{"name": "ZZZ Pasta Buffet", "firstCategory": "Pasta"}
{"name": "XYZ Coffee Bar", "firstCategory": "Coffee"}
{"name": "XYZ Bagels Restaurant", "firstCategory": "Bagels"}

For more information about the methods and classes mentioned in this section, see the following API Documentation:

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