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Aggregation![](/docs/drivers/java/sync/v4.3/assets/link.svg)
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Overview![](/docs/drivers/java/sync/v4.3/assets/link.svg)
In this guide, you can learn how to use aggregation operations in the MongoDB Java driver.
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.
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.
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![](/docs/drivers/java/sync/v4.3/assets/link.svg)
Using find
operations, you can:
select what documents to return
select what fields to return
sort the results
Using aggregation
operations, you can:
perform all
find
operationsrename fields
calculate fields
summarize data
group values
Aggregation operations have some limitations you must keep in mind:
Returned documents must not violate the BSON document size limit of 16 megabytes.
Pipeline stages have a memory limit of 100 megabytes by default. If required, you may exceed this limit by using the allowDiskUse method.
Important
$graphLookup exception
The $graphLookup stage has a strict memory limit of 100 megabytes and will ignore
allowDiskUse
.
Useful References![](/docs/drivers/java/sync/v4.3/assets/link.svg)
Runnable Examples![](/docs/drivers/java/sync/v4.3/assets/link.svg)
Base Setup![](/docs/drivers/java/sync/v4.3/assets/link.svg)
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 java.util.Arrays;
Connect to a MongoDB Deployment![](/docs/drivers/java/sync/v4.3/assets/link.svg)
public class AggTour { public static void main(String[] args) { // Replace the uri string with your MongoDB deployment's connection string String uri = "<connection string uri>"; MongoClient mongoClient = MongoClients.create(uri); MongoDatabase database = mongoClient.getDatabase("aggregation"); MongoCollection<Document> collection = database.getCollection("restaurants"); // aggregation here } }
Tip
See also:
For information on connecting to MongoDB, see the Connection Guide
Insert the Data![](/docs/drivers/java/sync/v4.3/assets/link.svg)
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![](/docs/drivers/java/sync/v4.3/assets/link.svg)
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 $match stage to filter for documents whose
categories
array field contains the elementBakery
. The example usesAggregates.match
to build the$match
stage.Uses a $group stage to group the matching documents by the
stars
field, accumulating a count of documents for each distinct value ofstars
.
Tip
See also:
You can build the expressions used in this example using the aggregation builders.
collection.aggregate( Arrays.asList( Aggregates.match(Filters.eq("categories", "Bakery")), Aggregates.group("$stars", Accumulators.sum("count", 1)) ) ).forEach(doc -> System.out.println(doc.toJson()));
The preceding aggregation should produce 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![](/docs/drivers/java/sync/v4.3/assets/link.svg)
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.
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. |
In the following example, we print the JSON representation of the winning plans for aggregation stages that produce execution plans:
Document explanation = collection.aggregate( Arrays.asList( Aggregates.match(Filters.eq("categories", "bakery")), Aggregates.group("$stars", Accumulators.sum("count", 1)) ) ).explain(ExplainVerbosity.EXECUTION_STATS); List<Document> stages = explanation.get("stages", List.class); List<String> keys = Arrays.asList("queryPlanner", "winningPlan"); for (Document stage : stages) { Document cursorStage = stage.get("$cursor", Document.class); if (cursorStage != null) { System.out.println(cursorStage.getEmbedded(keys, Document.class).toJson()); } }
The preceding code snippet should produce the following output:
{ "stage": "PROJECTION_SIMPLE", "transformBy": {"stars": 1, "_id": 0}, "inputStage": { "stage": "COLLSCAN", "filter": { "categories": {"$eq":"bakery"}}, "direction": "forward"}}
For more information about the topics mentioned in this section, see the following resources:
Explain Output Server Manual Entry
Query Plans Server Manual Entry
ExplainVerbosity API Documentation
explain() API Documentation
AggregateIterable API Documentation
Aggregation Expression Example![](/docs/drivers/java/sync/v4.3/assets/link.svg)
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] }")
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 should produce 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: