Query MongoDB - Java SDK

Atlas Device SDKs are deprecated. Refer to the deprecation page for details.

You can query data stored in MongoDB Atlas directly from your Android application code by using the Realm Java SDK's MongoClient with the Query API. Atlas App Services provides data access rules on collections to securely retrieve results based on the logged-in user or the content of each document.

The following actions enable access to a linked MongoDB Atlas cluster from an Android application using the Realm SDK.

Note

Each operation described on this page uses a query to match certain documents in the collection upon which the operation executes. When a filter matches multiple documents in a collection, they are returned in an indeterminate order unless you specify a sorting parameter. This means that if you do not specify a sort for the findOne(), updateOne(), or deleteOne() functions, your operation could match any document that matches the query. For more information on sorting, see cursor.sort().

Use Cases

There are a variety of reasons you might want to query a MongoDB data source. Working with data in your client via Atlas Device Sync is not always practical or possible. You might want to query MongoDB when:

The data set is large or the client device has constraints against loading the entire data set
You are creating or updating custom user data
You are retrieving documents that are not modeled in Realm
Your app needs to access collections that don't have strict schemas
A non-Realm service generates collections that you want to access

While not exhaustive, these are some common use cases for querying MongoDB directly.

Prerequisites

Before you can query MongoDB from your Android application, you must set up MongoDB Data Access in your App Services App. To learn how to set up your backend App to let the Realm SDK query Atlas, refer to Set Up MongoDB Data Access in the App Services documentation.

Set Up Your Project

Follow the steps in the Install the Realm Java SDK guide.

Link a MongoDB Atlas Service Cluster

Follow the steps in the Link a MongoDB data source guide. Assign your service a meaningful name -- you'll need it to connect to the cluster using the Realm SDK.

Import Realm Dependencies

For CRUD operations on a remote MongoDB collection, you will use one or more of the following import statements:

// Base Realm Packages
import io.realm.mongodb.App;
import io.realm.mongodb.AppConfiguration;
// Realm Authentication Packages
import io.realm.mongodb.User;
import io.realm.mongodb.Credentials;
// MongoDB Service Packages
import io.realm.mongodb.mongo.MongoClient;
import io.realm.mongodb.mongo.MongoDatabase;
import io.realm.mongodb.mongo.MongoCollection;
// Utility Packages
import org.bson.Document;

// Base Realm Packages
import io.realm.mongodb.App
import io.realm.mongodb.AppConfiguration
// Realm Authentication Packages
import io.realm.mongodb.User
import io.realm.mongodb.Credentials
// MongoDB Service Packages
import io.realm.mongodb.mongo.MongoClient
import io.realm.mongodb.mongo.MongoDatabase
import io.realm.mongodb.mongo.MongoCollection
// Utility Packages
import org.bson.Document

Instantiate a MongoDB Collection Handle

To connect to an instance of MongoDB, you'll need a user with access to a MongoDB collection. Log in to your application as such a user, then use the following code to instantiate a local MongoDB collection handle.

User user = app.currentUser();
MongoClient mongoClient =
        user.getMongoClient("mongodb-atlas");
MongoDatabase mongoDatabase =
        mongoClient.getDatabase("plant-data-database");
// registry to handle POJOs (Plain Old Java Objects)
CodecRegistry pojoCodecRegistry = fromRegistries(AppConfiguration.DEFAULT_BSON_CODEC_REGISTRY,
        fromProviders(PojoCodecProvider.builder().automatic(true).build()));
MongoCollection<Plant> mongoCollection =
        mongoDatabase.getCollection(
                "plant-data-collection",
                Plant.class).withCodecRegistry(pojoCodecRegistry);
Log.v("EXAMPLE", "Successfully instantiated the MongoDB collection handle");

val user = app.currentUser()
val mongoClient =
    user!!.getMongoClient("mongodb-atlas")
val mongoDatabase =
    mongoClient.getDatabase("plant-data-database")
// registry to handle POJOs (Plain Old Java Objects)
val pojoCodecRegistry = CodecRegistries.fromRegistries(
    AppConfiguration.DEFAULT_BSON_CODEC_REGISTRY,
    CodecRegistries.fromProviders(
        PojoCodecProvider.builder().automatic(true).build()))
val mongoCollection =
    mongoDatabase.getCollection(
        "plant-data-collection",
        Plant::class.java).withCodecRegistry(pojoCodecRegistry)
Log.v("EXAMPLE", "Successfully instantiated the MongoDB collection handle")

Note

Using Custom Classes with MongoDB

To use classes other than the built-in Document class with MongoDB, you can add codecs to your MongoCollection instances. In the above example, we add the PojoCodecProvider to support Plain Old Java Objects (POJOs). Custom object support requires two codec providers:

the default codec provider, which provides support for built-in Java types (accessed through AppConfiguration.DEFAULT_BSON_CODEC_REGISTRY)
PojoCodecProvider, which automatically creates new codecs to support POJO classes

The SDK checks registries in order until one returns a codec for the requested class. As a result, you should list the default codec registry first, and the PojoCodecProvider should always be the last CodecProvider since it can provide a codec for almost any class.

Example Data

The following examples operate on a MongoDB collection that describes inventory in a chain of plant stores. Consider the following collection of documents describing various plants for sale in a store:

Plant.java

import org.bson.codecs.pojo.annotations.BsonProperty;
import org.bson.types.ObjectId;
public class Plant {
    private ObjectId id;
    private String name;
    private String sunlight;
    private String color;
    private String type;
    @BsonProperty("_partition")
    private String partition;
    // empty constructor required for MongoDB Data Access POJO codec compatibility
    public Plant() {}
    public Plant(ObjectId id, String name, String sunlight, String color, String type, String partition) {
        this.id = id;
        this.name = name;
        this.sunlight = sunlight;
        this.color = color;
        this.type = type;
        this.partition = partition;
    }
    public ObjectId getId() { return id; }
    public void setId(ObjectId id) { this.id = id; }
    public String getName() { return name; }
    public void setName(String name) { this.name = name; }
    public String getSunlight() { return sunlight; }
    public void setSunlight(String sunlight) { this.sunlight = sunlight; }
    public String getColor() { return color; }
    public void setColor(String color) { this.color = color; }
    public String getType() { return type; }
    public void setType(String type) { this.type = type; }
    public String getPartition() { return partition; }
    public void setPartition(String partition) { this.partition = partition; }
    @Override
    public String toString() {
        return "Plant [id=" + id + ", name=" + name + ", sunlight=" + sunlight + ", color=" + color + ", type=" + type + ", partition=" + partition + "]";
    }
}

User user = app.currentUser();
MongoClient mongoClient =
        user.getMongoClient("mongodb-atlas");
MongoDatabase mongoDatabase =
        mongoClient.getDatabase("plant-data-database");
// registry to handle POJOs (Plain Old Java Objects)
CodecRegistry pojoCodecRegistry = fromRegistries(AppConfiguration.DEFAULT_BSON_CODEC_REGISTRY,
        fromProviders(PojoCodecProvider.builder().automatic(true).build()));
MongoCollection<Plant> mongoCollection =
        mongoDatabase.getCollection(
                "plant-data-collection",
                Plant.class).withCodecRegistry(pojoCodecRegistry);
mongoCollection.insertMany(Arrays.asList(
        new Plant(new ObjectId(),
                "venus flytrap",
                "full",
                "white",
                "perennial",
                "Store 42"),
        new Plant(new ObjectId(),
                "sweet basil",
                "partial",
                "green",
                "annual",
                "Store 42"),
        new Plant(new ObjectId(),
                "thai basil",
                "partial",
                "green",
                "perennial",
                "Store 42"),
        new Plant(new ObjectId(),
                "helianthus",
                "full",
                "yellow",
                "annual",
                "Store 42"),
        new Plant(new ObjectId(),
                "petunia",
                "full",
                "purple",
                "annual",
                "Store 47")));
Log.v("EXAMPLE", "Successfully inserted the sample data.");

Plant.kt

import org.bson.codecs.pojo.annotations.BsonProperty
import org.bson.types.ObjectId
open class Plant(val id : ObjectId = ObjectId(),
                 var name : String? = null,
                 var sunlight : String? = null,
                 var color : String? = null,
                 var type : String? = null,
                 @field:BsonProperty("_partition") // specify that this is a field-level annotation
                 var partition : String? = null) {
    override fun toString(): String {
        return "Plant [id=$id, name=$name, sunlight=$sunlight, color=$color, type=$type, partition=$partition]"
    }
}

val user = app.currentUser()
val mongoClient =
    user!!.getMongoClient("mongodb-atlas")
val mongoDatabase =
    mongoClient.getDatabase("plant-data-database")
// registry to handle POJOs (Plain Old Java Objects)
val pojoCodecRegistry = CodecRegistries.fromRegistries(
    AppConfiguration.DEFAULT_BSON_CODEC_REGISTRY,
    CodecRegistries.fromProviders(
        PojoCodecProvider.builder().automatic(true).build()))
val mongoCollection =
    mongoDatabase.getCollection(
        "plant-data-collection",
        Plant::class.java).withCodecRegistry(pojoCodecRegistry)
mongoCollection.insertMany(
    listOf(
        Plant(
            ObjectId(),
            "venus flytrap",
            "full",
            "white",
            "perennial",
            "Store 42"
        ),
        Plant(
            ObjectId(),
            "sweet basil",
            "partial",
            "green",
            "annual",
            "Store 42"
        ),
        Plant(
            ObjectId(),
            "thai basil",
            "partial",
            "green",
            "perennial",
            "Store 42"
        ),
        Plant(
            ObjectId(),
            "helianthus",
            "full",
            "yellow",
            "annual",
            "Store 42"
        ),
        Plant(
            ObjectId(),
            "petunia",
            "full",
            "purple",
            "annual",
            "Store 47"
        )
    )
)
Log.v("EXAMPLE", "Successfully Successfully inserted the sample data.")

Create Documents

These code snippets demonstrate how to insert one or more documents into a MongoDB collection from a mobile application. Insert operations take a document or documents to add to MongoDB as an argument and return a RealmResultTask that resolves to an object that contains the results of the execution of the operation.

Insert a Single Document

You can insert a single document using collection.insertOne().

The following snippet inserts a single document describing a "lily of the valley" plant into a collection of documents that describe plants for sale in a group of stores:

Plant plant = new Plant(
        new ObjectId(),
        "lily of the valley",
        "full",
        "white",
        "perennial",
        "Store 47");
mongoCollection.insertOne(plant).getAsync(task -> {
    if (task.isSuccess()) {
        Log.v("EXAMPLE", "successfully inserted a document with id: " + task.get().getInsertedId());
    } else {
        Log.e("EXAMPLE", "failed to insert documents with: " + task.getError().getErrorMessage());
    }
});

val plant = Plant(
    ObjectId(),
    "lily of the valley",
    "full",
    "white",
    "perennial",
    "Store 47"
)
mongoCollection?.insertOne(plant)?.getAsync { task ->
    if (task.isSuccess) {
        Log.v(
            "EXAMPLE",
            "successfully inserted a document with id: ${task.get().insertedId}"
        )
    } else {
        Log.e("EXAMPLE", "failed to insert documents with: ${task.error}")
    }
}

Running this snippet produces output resembling the following:

V/EXAMPLE: successfully inserted a document with id: BsonObjectId{value=5f19...}

Insert Multiple Documents

You can insert multiple documents at the same time using collection.insertMany().

The following snippet inserts three documents describing plants into a collection of documents that describe plants for sale in a group of stores:

List<Plant> plants  = Arrays.asList(
        new Plant(new ObjectId(),
                "rhubarb",
                "full",
                "red",
                "perennial",
                "Store 47"),
        new Plant(new ObjectId(),
                "wisteria lilac",
                "partial",
                "purple",
                "perennial",
                "Store 42"),
        new Plant(new ObjectId(),
                "daffodil",
                "full",
                "yellow",
                "perennial",
                "Store 42"));
mongoCollection.insertMany(plants).getAsync(task -> {
    if (task.isSuccess()) {
        int insertedCount = task.get().getInsertedIds().size();
        Log.v("EXAMPLE", "successfully inserted " + insertedCount + " documents into the collection.");
    } else {
        Log.e("EXAMPLE", "failed to insert documents with: ", task.getError());
    }
});

val plants = listOf(
    Plant(
        ObjectId(),
        "rhubarb",
        "full",
        "red",
        "perennial",
        "Store 47"
    ),
    Plant(
        ObjectId(),
        "wisteria lilac",
        "partial",
        "purple",
        "perennial",
        "Store 42"
    ),
    Plant(
        ObjectId(),
        "daffodil",
        "full",
        "yellow",
        "perennial",
        "Store 42"
    )
)
mongoCollection.insertMany(plants).getAsync { task ->
    if (task.isSuccess) {
        val insertedCount = task.get().insertedIds.size
        Log.v(
            "EXAMPLE",
            "successfully inserted $insertedCount documents into the collection."
        )
    } else {
        Log.e("EXAMPLE", "failed to insert documents with: ${task.error}")
    }
}

Running this snippet produces output resembling the following:

V/EXAMPLE: successfully inserted 3 documents into the collection.

Read Documents

These code snippets demonstrate how to read data stored in a MongoDB collection from a mobile application. Read operations use queries to specify which documents to return from the database. Read operations return a Task that resolves to either a single matched document (in the case of findOne()), a long numeric value (in the case of count()) or an iterator that allows you to traverse the collection of matched documents (in the case of find()).

Find a Single Document

You can find a single document using collection.findOne().

The following snippet finds a single document from the a collection of documents that describe plants for sale in a group of stores where the plant document's type field contains the string value "perennial":

Document queryFilter  = new Document("type", "perennial");
mongoCollection.findOne(queryFilter).getAsync(task -> {
    if (task.isSuccess()) {
        Plant result = task.get();
        Log.v("EXAMPLE", "successfully found a document: " + result);
    } else {
        Log.e("EXAMPLE", "failed to find document with: ", task.getError());
    }
});

val queryFilter = Document("type", "perennial")
mongoCollection.findOne(queryFilter)
    .getAsync { task ->
        if (task.isSuccess) {
            val result = task.get()
            Log.v("EXAMPLE", "successfully found a document: $result")
        } else {
            Log.e("EXAMPLE", "failed to find document with: ${task.error}")
        }
    }

Running this snippet produces output similar to the following:

V/EXAMPLE: successfully found a document: Plant [id=5f18..., name=venus flytrap, sunlight=full, color=white, type=perennial, partition=Store 42]

Find Multiple Documents

You can find multiple documents using collection.find().

The following snippet finds all documents in a collection of documents that describe plants for sale in a group of stores that contain a field named _partition with a value of "Store 42":

Document queryFilter  = new Document("_partition", "Store 42");
RealmResultTask<MongoCursor<Plant>> findTask = mongoCollection.find(queryFilter).iterator();
findTask.getAsync(task -> {
    if (task.isSuccess()) {
        MongoCursor<Plant> results = task.get();
        Log.v("EXAMPLE", "successfully found all plants for Store 42:");
        while (results.hasNext()) {
            Log.v("EXAMPLE", results.next().toString());
        }
    } else {
        Log.e("EXAMPLE", "failed to find documents with: ", task.getError());
    }
});

val queryFilter = Document("_partition", "Store 42")
val findTask = mongoCollection.find(queryFilter).iterator()
findTask.getAsync { task ->
    if (task.isSuccess) {
        val results = task.get()
        Log.v("EXAMPLE", "successfully found all plants for Store 42:")
        while (results.hasNext()) {
            Log.v("EXAMPLE", results.next().toString())
        }
    } else {
        Log.e("EXAMPLE", "failed to find documents with: ${task.error}")
    }
}

Running this snippet produces output resembling the following:

V/EXAMPLE: successfully found all plants for Store 42:
V/EXAMPLE: Plant [id=5f18..., name=venus flytrap, sunlight=full, color=white, type=perennial, partition=Store 42]
V/EXAMPLE: Plant [id=5f18..., name=sweet basil, sunlight=partial, color=green, type=annual, partition=Store 42]
V/EXAMPLE: Plant [id=5f18..., name=thai basil, sunlight=partial, color=green, type=perennial, partition=Store 42]
V/EXAMPLE: Plant [id=5f18..., name=helianthus, sunlight=full, color=yellow, type=annual, partition=Store 42]

Count Documents in the Collection

You can count documents in a collection using collection.count(). You can specify an optional query to determine which documents to count. If you don't specify a query, the action counts all documents in the collection.

The following snippet counts the number of documents in a collection of documents that describe plants for sale in a group of stores:

mongoCollection.count().getAsync(task -> {
    if (task.isSuccess()) {
        long count = task.get();
        Log.v("EXAMPLE",
                "successfully counted, number of documents in the collection: " +
                        count);
    } else {
        Log.e("EXAMPLE", "failed to count documents with: ", task.getError());
    }
});

mongoCollection.count().getAsync { task ->
    if (task.isSuccess) {
        val count = task.get()
        Log.v("EXAMPLE", "successfully counted, number of documents in the collection: $count")
    } else {
        Log.e("EXAMPLE", "failed to count documents with: ${task.error}")
    }
}

Running this snippet produces output resembling the following:

V/EXAMPLE: successfully counted, number of documents in the collection: 5

Update Documents

These code snippets demonstrate how to update data stored in a MongoDB collection from a mobile application. Update operations use queries to specify which documents to update and update operators to describe how to mutate documents that match the query. Update operations return a Task that resolves to an object that contains the results of the execution of the operation.

Update a Single Document

You can update a single document using collection.updateOne().

The following snippet updates a single document in a collection of documents that describe plants for sale in a group of stores. This operation queries for a document where the name field contains the value "petunia" and changes the value of the first matched document's sunlight field to "partial":

Document queryFilter = new Document("name", "petunia");
Document updateDocument = new Document("$set", new Document("sunlight", "partial"));
mongoCollection.updateOne(queryFilter, updateDocument).getAsync(task -> {
    if (task.isSuccess()) {
        long count = task.get().getModifiedCount();
        if (count == 1) {
            Log.v("EXAMPLE", "successfully updated a document.");
        } else {
            Log.v("EXAMPLE", "did not update a document.");
        }
    } else {
        Log.e("EXAMPLE", "failed to update document with: ", task.getError());
    }
});

val queryFilter = Document("name", "petunia")
val updateDocument = Document("\$set", Document("sunlight", "partial"))
mongoCollection.updateOne(queryFilter, updateDocument).getAsync { task ->
    if (task.isSuccess) {
        val count = task.get().modifiedCount
        if (count == 1L) {
            Log.v("EXAMPLE", "successfully updated a document.")
        } else {
            Log.v("EXAMPLE", "did not update a document.")
        }
    } else {
        Log.e("EXAMPLE", "failed to update document with: ${task.error}")
    }
}

Running this snippet produces output resembling the following:

V/EXAMPLE: successfully updated a document.

Update Multiple Documents

You can update multiple documents using collection.updateMany().

The following snippet updates multiple documents in a collection of documents that describe plants for sale in a group of stores. This operation queries for documents where the _partition field contains the value "Store 47" and changes the value of the _partition field of each matching document to "Store 51":

Document queryFilter = new Document("_partition", "Store 47");
Document updateDocument = new Document("$set", new Document("_partition", "Store 51"));
mongoCollection.updateMany(queryFilter, updateDocument).getAsync(task -> {
    if (task.isSuccess()) {
        long count = task.get().getModifiedCount();
        if (count != 0) {
            Log.v("EXAMPLE", "successfully updated " + count + " documents.");
        } else {
            Log.v("EXAMPLE", "did not update any documents.");
        }
    } else {
        Log.e("EXAMPLE", "failed to update documents with: ", task.getError());
    }
});

val queryFilter = Document("_partition", "Store 47")
val updateDocument = Document("\$set", Document("_partition", "Store 51"))
mongoCollection.updateMany(queryFilter, updateDocument).getAsync { task ->
    if (task.isSuccess) {
        val count = task.get().modifiedCount
        if (count != 0L) {
            Log.v("EXAMPLE", "successfully updated $count documents.")
        } else {
            Log.v("EXAMPLE", "did not update any documents.")
        }
    } else {
        Log.e("EXAMPLE", "failed to update documents with: ${task.error}")
    }
}

Running this snippet produces output resembling the following:

V/EXAMPLE: successfully updated 2 documents.

Upsert Documents

If an update operation does not match any document in the collection, you can automatically insert a single new document into the collection that matches the update query by setting the upsert option to true.

The following snippet updates a document in a collection of documents that describe plants for sale in a group of stores or inserts a new document if no document matches the query. This operation queries for documents where:

the sunlight field has a value of "full"
the type field has a value of "perennial"
the color field has a value of "green"
the _partition field has a value of "Store 47"

Because this snippet sets the upsert option to true, if no document matches the query, MongoDB creates a new document that includes both the query and specified updates:

Document queryFilter = new Document("sunlight", "full")
        .append("type", "perennial")
        .append("color", "green")
        .append("_partition", "Store 47");
Document updateDocument = new Document("$set", new Document("name", "sweet basil"));
UpdateOptions updateOptions = new UpdateOptions().upsert(true);
mongoCollection.updateOne(queryFilter, updateDocument, updateOptions).getAsync(task -> {
    if (task.isSuccess()) {
        if(task.get().getUpsertedId() != null) {
            Log.v("EXAMPLE", "successfully upserted a document with id " +
                    task.get().getUpsertedId());
        } else {
            Log.v("EXAMPLE", "successfully updated a document.");
        }
    } else {
        Log.e("EXAMPLE", "failed to update or insert document with: ",
                task.getError());
    }
});

val queryFilter = Document("sunlight", "full")
    .append("type", "perennial")
    .append("color", "green")
    .append("_partition", "Store 47")
val updateDocument = Document("\$set", Document("name", "sweet basil"))
val updateOptions = UpdateOptions().upsert(true)
mongoCollection.updateOne(queryFilter, updateDocument, updateOptions)
    .getAsync { task ->
        if (task.isSuccess) {
            if (task.get().upsertedId != null) {
                Log.v("EXAMPLE", "successfully upserted a document with id ${task.get().upsertedId}")
            } else {
                Log.v("EXAMPLE", "successfully updated a document.")
            }
        } else {
            Log.e("EXAMPLE", "failed to update or insert document with: ${task.error}")
        }
    }

Running this snippet produces output resembling the following:

V/EXAMPLE: successfully upserted a document with id: BsonObjectId{value=5f19...}

Delete Documents

These code snippets demonstrate how to delete documents that are stored in a MongoDB collection from a mobile application. Delete operations use a query to specify which documents to delete and return a Task that resolves to an object that contains the results of the execution of the operation.

Delete a Single Document

You can delete a single document from a collection using collection.deleteOne().

The following snippet deletes one document in a collection of documents that describe plants for sale in a group of stores. This operation queries for a document where the color field has a value of "green" and deletes the first document that matches the query:

Document queryFilter = new Document("color", "green");
mongoCollection.deleteOne(queryFilter).getAsync(task -> {
    if (task.isSuccess()) {
        long count = task.get().getDeletedCount();
        if (count == 1) {
            Log.v("EXAMPLE", "successfully deleted a document.");
        } else {
            Log.v("EXAMPLE", "did not delete a document.");
        }
    } else {
        Log.e("EXAMPLE", "failed to delete document with: ", task.getError());
    }
});

val queryFilter = Document("color", "green")
mongoCollection.deleteOne(queryFilter).getAsync { task ->
    if (task.isSuccess) {
        val count = task.get().deletedCount
        if (count == 1L) {
            Log.v("EXAMPLE", "successfully deleted a document.")
        } else {
            Log.v("EXAMPLE", "did not delete a document.")
        }
    } else {
        Log.e("EXAMPLE", "failed to delete document with: ${task.error}")
    }
}

Running this snippet produces output resembling the following:

V/EXAMPLE: successfully deleted a document.

Delete Multiple Documents

You can delete multiple items from a collection using collection.deleteMany().

The following snippet deletes all documents in a collection of documents that describe plants for sale in a group of stores that match the query that matches documents containing both a sunlight field value of "full" and a type field value of "annual".

Document queryFilter = new Document("sunlight", "full")
        .append("type", "annual");
mongoCollection.deleteMany(queryFilter).getAsync(task -> {
    if (task.isSuccess()) {
        long count = task.get().getDeletedCount();
        if (count != 0) {
            Log.v("EXAMPLE", "successfully deleted " + count + " documents.");
        } else {
            Log.v("EXAMPLE", "did not delete any documents.");
        }
    } else {
        Log.e("EXAMPLE", "failed to delete documents with: ", task.getError());
    }
});

val queryFilter = Document("sunlight", "full").append("type", "annual")
mongoCollection.deleteMany(queryFilter).getAsync { task ->
    if (task.isSuccess) {
        val count = task.get().deletedCount
        if (count != 0L) {
            Log.v("EXAMPLE", "successfully deleted $count documents.")
        } else {
            Log.v("EXAMPLE", "did not delete any documents.")
        }
    } else {
        Log.e("EXAMPLE", "failed to delete documents with: ${task.error}")
    }
}

Running this snippet produces output resembling the following:

V/EXAMPLE: succcessfully deleted 2 documents.

Watch for Changes

These code snippets demonstrate how to configure and run watch operations on a collection.

Important

Serverless Limitations

You cannot watch for changes if the data source is an Atlas serverless instance. MongoDB serverless currently does not support change streams, which are used on watched collections to listen for changes.

Watch for Changes in a Collection

You can open a stream of changes made to a collection by calling collection.watch() or collection.watchAsync(). You can watch for changes to specific documents in a collection by passing the object ids of the objects you would like to monitor as a variable number of arguments.

The following snippet watches for changes to any documents in the plants collection:

RealmEventStreamAsyncTask<Plant> watcher = mongoCollection.watchAsync();
watcher.get(result -> {
    if (result.isSuccess()) {
        Log.v("EXAMPLE", "Event type: " +
                result.get().getOperationType() + " full document: " +
                result.get().getFullDocument());
    } else {
        Log.e("EXAMPLE", "failed to subscribe to changes in the collection with : ",
                result.getError());
    }
});
Plant triffid = new Plant(
        new ObjectId(),
        "triffid",
        "low",
        "green",
        "perennial",
        "Store 47");
mongoCollection.insertOne(triffid).getAsync(task -> {
    if (task.isSuccess()) {
        BsonObjectId insertedId = task.get().getInsertedId().asObjectId();
        Log.v("EXAMPLE", "successfully inserted a document with id " + insertedId);
    } else {
        Log.e("EXAMPLE", "failed to insert document with: ", task.getError());
    }
});

val watcher = mongoCollection.watchAsync()
watcher[{ result ->
    if (result.isSuccess) {
        Log.v("EXAMPLE", "Event type: ${result.get().operationType} full document: ${result.get().fullDocument}")
    } else {
        Log.e("EXAMPLE", "failed to subscribe to changes in the collection with : ${result.error}")
    }
}]
val triffid =
    Plant(
        ObjectId(),
        "triffid",
        "low",
        "green",
        "perennial",
        "Store 47"
    )
mongoCollection.insertOne(triffid).getAsync { task ->
    if (task.isSuccess) {
        val insertedId = task.get().insertedId.asObjectId()
        Log.v("EXAMPLE", "successfully inserted a document with id $insertedId")
    } else {
        Log.e("EXAMPLE", "failed to insert document with: ${task.error}")
    }
}

Running this snippet produces output resembling the following:

V/EXAMPLE: successfully inserted a document with id BsonObjectId{value=5f6bb...}
V/EXAMPLE: Event type: INSERT full document: Plant [id=5f6bb..., name=triffid, sunlight=low, color=green, type=perennial, partition=Store 47]

Watch for Changes in a Collection with a Filter

You can open a stream of changes made to documents in a collection that fulfill certain criteria by calling collection.watchWithFilter() or collection.watchWithFilterAsync(). Both methods accept a Document or BsonDocument parameter that is used as the query of a $match operator to process each database event that occurs while watching the collection.

The following snippet watches for changes to documents in the plants collection, but only triggers the provided callback for events corresponding to documents belonging to the partition named "Store 42":

RealmEventStreamAsyncTask<Plant> watcher = mongoCollection
        .watchWithFilterAsync(new Document("fullDocument._partition", "Store 42"));
watcher.get(result -> {
    if (result.isSuccess()) {
        Log.v("EXAMPLE", "Event type: " +
                result.get().getOperationType() + " full document: " +
                result.get().getFullDocument());
    } else {
        Log.e("EXAMPLE",
                "failed to subscribe to filtered changes in the collection with : ",
                result.getError());
    }
});
List<Plant> plants  = Arrays.asList(
        new Plant(
                new ObjectId(),
                "triffid",
                "low",
                "green",
                "perennial",
                "Store 47"),
        new Plant(
                new ObjectId(),
                "venomous tentacula",
                "low",
                "brown",
                "annual",
                "Store 42"
        ));
mongoCollection.insertMany(plants).getAsync(task -> {
    if (task.isSuccess()) {
        int insertedCount = task.get().getInsertedIds().size();
        Log.v("EXAMPLE", "successfully inserted " +
                insertedCount + " documents into the collection.");
    } else {
        Log.e("EXAMPLE", "failed to insert documents with: ",
                task.getError());
    }
});

val watcher = mongoCollection
    .watchWithFilterAsync(Document("fullDocument._partition", "Store 42"))
watcher[{ result ->
    if (result.isSuccess) {
        Log.v("EXAMPLE", "Event type: ${result.get().operationType} full document: ${result.get().fullDocument}")
    } else {
        Log.e("EXAMPLE", "failed to subscribe to filtered changes in the collection with : ${result.error}")
    }
}]
val plants = listOf(
    Plant(
        ObjectId(),
        "triffid",
        "low",
        "green",
        "perennial",
        "Store 47"
    ),
    Plant(
        ObjectId(),
        "venomous tentacula",
        "low",
        "brown",
        "annual",
        "Store 42"
    )
)
mongoCollection.insertMany(plants).getAsync { task ->
    if (task.isSuccess) {
        val insertedCount = task.get().insertedIds.size
        Log.v("EXAMPLE", "successfully inserted $insertedCount documents into the collection.")
    } else {
        Log.e("EXAMPLE", "failed to insert documents with: ${task.error}")
    }
}

Running this snippet produces output resembling the following:

V/EXAMPLE: successfully inserted 2 documents into the collection
V/EXAMPLE: Event type: INSERT full document: Plant [id=5f6bb..., name=venomous tentacula, sunlight=low, color=brown, type=annual, partition=Store 42]

Aggregate Documents in a Collection

Aggregation operations run all documents in a collection through a series of data aggregation stages called an aggregation pipeline. Aggregation allows you to filter and transform documents, collect summary data about groups of related documents, and other complex data operations.

You can execute an aggregation pipeline using collection.aggregate().

An aggregation operation accepts a list of aggregation stages as input and returns a Task that resolves to a collection of documents processed by the pipeline.

Filter Documents

You can use the $match stage to filter documents according to a Query API query filter.

{
  "$match": {
    "<Field Name>": <Query Expression>,
    ...
  }
}

Example

The following $match stage filters documents to include only those where the type field has a value equal to "perennial":

// create an aggregation pipeline
List<Document> pipeline = Arrays.asList(
        new Document("$match",
                new Document("type",
                        new Document("$eq", "perennial"))));
// query mongodb using the pipeline
RealmResultTask<MongoCursor<Document>> aggregationTask =
        mongoCollection.aggregate(pipeline).iterator();
// handle success or failure of the query
aggregationTask.getAsync(task -> {
    if (task.isSuccess()) {
        MongoCursor<Document> results = task.get();
        // iterate over and print the results to the log
        Log.v("EXAMPLE", "successfully aggregated the plants. Results:");
        while (results.hasNext()) {
            Log.v("EXAMPLE", results.next().toString());
        }
    } else {
        Log.e("EXAMPLE", "failed to aggregate documents with: ",
                task.getError());
    }
});

// create an aggregation pipeline
val pipeline =
    listOf(
        Document("\$match",
            Document("type",
                Document("\$eq", "perennial")
            )
        )
    )
// query mongodb using the pipeline
val aggregationTask = mongoCollection.aggregate(pipeline).iterator()
// handle success or failure of the query
aggregationTask.getAsync { task: App.Result<MongoCursor<Document>> ->
    if (task.isSuccess) {
        val results = task.get()
        // iterate over and print the results to the log
        Log.v("EXAMPLE",
            "successfully aggregated the plants. Results:")
        while (results.hasNext()) {
            Log.v("EXAMPLE", results.next().toString())
        }
    } else {
        Log.e("EXAMPLE",
            "failed to aggregate documents with: ${task.error}")
    }
}

Group Documents

You can use the $group stage to aggregate summary data for one or more documents. MongoDB groups documents based on the expression defined in the _id field value of the $group stage. You can reference a specific document field by prefixing the field name with a $.

The following snippet groups all documents in the plants collection by their type value and aggregates a count of the number of each type:

// create an aggregation pipeline
List<Document> pipeline = Arrays.asList(
        new Document("$group", new Document("_id", "$type")
                .append("totalCount", new Document("$sum", 1))));
// query mongodb using the pipeline
RealmResultTask<MongoCursor<Document>> aggregationTask =
        mongoCollection.aggregate(pipeline).iterator();
// handle success or failure of the query
aggregationTask.getAsync(task -> {
    if (task.isSuccess()) {
        MongoCursor<Document> results = task.get();
        // iterate over and print the results to the log
        Log.v("EXAMPLE", "successfully aggregated the plants. Results:");
        while (results.hasNext()) {
            Log.v("EXAMPLE", results.next().toString());
        }
    } else {
        Log.e("EXAMPLE", "failed to aggregate documents with: ",
                task.getError());
    }
});

// create an aggregation pipeline
val pipeline =
    listOf(
        Document("\$group",
            Document("_id", "\$type")
                .append("totalCount", Document("\$sum", 1))
        )
    )
// query mongodb using the pipeline
val aggregationTask = mongoCollection.aggregate(pipeline).iterator()
// handle success or failure of the query
aggregationTask.getAsync { task: App.Result<MongoCursor<Document>> ->
    if (task.isSuccess) {
        val results = task.get()
        // iterate over and print the results to the log
        Log.v("EXAMPLE",
            "successfully aggregated the plants. Results:")
        while (results.hasNext()) {
            Log.v("EXAMPLE", results.next().toString())
        }
    } else {
        Log.e("EXAMPLE",
            "failed to aggregate documents with: ${task.error}")
    }
}

Project Document Fields

You can use the $project stage to include or omit specific fields from documents. Additionally, you can calculate new fields using aggregation operators. Projections work in two ways:

Explicitly include fields with a value of 1. This has the side-effect of implicitly excluding all unspecified fields.
Implicitly exclude fields with a value of 0. This has the side-effect of implicitly including all unspecified fields.

These two methods of projection are mutually exclusive: if you explicitly include fields, you cannot explicitly exclude fields, and vice versa.

Note

The _id field is a special case: it is always included in every query unless explicitly specified otherwise. For this reason, you can exclude the _id field with a 0 value while simultaneously including other fields, like _partition, with a 1. Only the special case of exclusion of the _id field allows both exclusion and inclusion in one $project stage.

{
  "$project": {
    "<Field Name>": <0 | 1 | Expression>,
    ...
  }
}

Example

The following $project stage omits the _id field, includes the name field, and creates a new field named storeNumber. The storeNumber is generated using two aggregation operators:

$split separates the _partition value into two string segments surrounding the space character. For example, the value "Store 42" split in this way returns an array with two elements: "Store" and "42".
$arrayElemAt selects a specific element from an array based on the second argument. In this case, the value 1 selects the second element from the array generated by the $split operator since arrays index from 0. For example, the value ["Store", "42"] passed to this operation would return a value of "42".

// create an aggregation pipeline
List<Document> pipeline = Arrays.asList(
        new Document("$project",
                new Document("_id", 0)
                    .append("name", 1)
                    .append("storeNumber",
                        new Document("$arrayElemAt",
                            Arrays.asList(
                                    new Document("$split",
                                            Arrays.asList("$_partition", " ")),
                                    1)))));
// query mongodb using the pipeline
RealmResultTask<MongoCursor<Document>> aggregationTask =
        mongoCollection.aggregate(pipeline).iterator();
// handle success or failure of the query
aggregationTask.getAsync(task -> {
    if (task.isSuccess()) {
        MongoCursor<Document> results = task.get();
        // iterate over and print the results to the log
        Log.v("EXAMPLE", "successfully aggregated the plants. Results:");
        while (results.hasNext()) {
            Log.v("EXAMPLE", results.next().toString());
        }
    } else {
        Log.e("EXAMPLE", "failed to aggregate documents with: ",
                task.getError());
    }
});

// create an aggregation pipeline
val pipeline =
    listOf(
        Document("\$project",
            Document("_id", 0)
                .append("name", 1)
                .append("storeNumber",
                    Document("\$arrayElemAt",
                        listOf(
                            Document("\$split",
                                listOf(
                                    "\$_partition",
                                    " "
                                )
                            ),
                            1
                        )
                    )
                )
        )
    )
// query mongodb using the pipeline
val aggregationTask = mongoCollection.aggregate(pipeline).iterator()
// handle success or failure of the query
aggregationTask.getAsync { task: App.Result<MongoCursor<Document>> ->
    if (task.isSuccess) {
        val results = task.get()
        // iterate over and print the results to the log
        Log.v("EXAMPLE",
            "successfully aggregated the plants. Results:")
        while (results.hasNext()) {
            Log.v("EXAMPLE", results.next().toString())
        }
    } else {
        Log.e("EXAMPLE",
            "failed to aggregate documents with: ${task.error}")
    }
}

Add Fields to Documents

You can use the $addFields stage to add new fields with calculated values using aggregation operators.

Note

$addFields is similar to $project but does not allow you to include or omit fields.

Example

The following $addFields stage creates a new field named storeNumber where the value is the output of two aggregate operators that transform the value of the _partition field.

// create an aggregation pipeline
List<Document> pipeline = Arrays.asList(
        new Document("$addFields",
                new Document("storeNumber",
                        new Document("$arrayElemAt", Arrays.asList(
                                new Document("$split", Arrays.asList(
                                        "$_partition", " ")), 1)))));
// query mongodb using the pipeline
RealmResultTask<MongoCursor<Document>> aggregationTask =
        mongoCollection.aggregate(pipeline).iterator();
// handle success or failure of the query
aggregationTask.getAsync(task -> {
    if (task.isSuccess()) {
        MongoCursor<Document> results = task.get();
        // iterate over and print the results to the log
        Log.v("EXAMPLE", "successfully aggregated the plants. Results:");
        while (results.hasNext()) {
            Log.v("EXAMPLE", results.next().toString());
        }
    } else {
        Log.e("EXAMPLE", "failed to aggregate documents with: ",
                task.getError());
    }
});

// create an aggregation pipeline
val pipeline =
    listOf(
        Document("\$addFields",
            Document("storeNumber",
                Document("\$arrayElemAt",
                    listOf(
                        Document("\$split",
                            listOf(
                                "\$_partition",
                                " "
                            )
                        ),
                        1
                    )
                )
            )
        )
    )
// query mongodb using the pipeline
val aggregationTask = mongoCollection.aggregate(pipeline).iterator()
// handle success or failure of the query
aggregationTask.getAsync { task: App.Result<MongoCursor<Document>> ->
    if (task.isSuccess) {
        val results = task.get()
        // iterate over and print the results to the log
        Log.v("EXAMPLE",
            "successfully aggregated the plants. Results:")
        while (results.hasNext()) {
            Log.v("EXAMPLE", results.next().toString())
        }
    } else {
        Log.e("EXAMPLE",
            "failed to aggregate documents with: ${task.error}")
    }
}

Unwind Array Values

You can use the $unwind stage to transform a single document containing an array into multiple documents containing individual values from that array. When you unwind an array field, MongoDB copies each document once for each element of the array field but replaces the array value with the array element in each copy.

{
  $unwind: {
    path: <Array Field Path>,
    includeArrayIndex: <string>,
    preserveNullAndEmptyArrays: <boolean>
  }
}

Example

The following $unwind stage creates a new document for each element of the items array in each document. It also adds a field called itemIndex to each new document that specifies the element's position index in the original array:

// create an aggregation pipeline
List<Document> pipeline = Arrays.asList(
        new Document("$unwind", new Document("path", "$items")
                .append("includeArrayIndex", "itemIndex")));
// query mongodb using the pipeline
RealmResultTask<MongoCursor<Document>> aggregationTask = mongoCollection.aggregate(pipeline).iterator();
// handle success or failure of the query
aggregationTask.getAsync(task -> {
    if (task.isSuccess()) {
        MongoCursor<Document> results = task.get();
        // iterate over and print the results to the log
        Log.v("EXAMPLE", "successfully aggregated the plants. Results:");
        while (results.hasNext()) {
            Log.v("EXAMPLE", results.next().toString());
        }
    } else {
        Log.e("EXAMPLE", "failed to aggregate documents with: ",
                task.getError());
    }
});

// create an aggregation pipeline
val pipeline =
    listOf(
        Document("\$unwind", Document("path", "\$items")
                .append("includeArrayIndex", "itemIndex"))
    )
// query mongodb using the pipeline
val aggregationTask = mongoCollection.aggregate(pipeline).iterator()
// handle success or failure of the query
aggregationTask.getAsync { task: App.Result<MongoCursor<Document>> ->
    if (task.isSuccess) {
        val results = task.get()
        // iterate over and print the results to the log
        Log.v("EXAMPLE",
            "successfully aggregated the plants. Results:")
        while (results.hasNext()) {
            Log.v("EXAMPLE", results.next().toString())
        }
    } else {
        Log.e("EXAMPLE",
            "failed to aggregate documents with: ${task.error}")
    }
}

Consider the following document from the a collection of purchases:

   {
     _id: 123,
     customerId: 24601,
     items: [
       { name: "Baseball", quantity: 5 },
       { name: "Baseball Mitt", quantity: 1 },
       { name: "Baseball Bat", quantity: 1 },
     ]
   }

If we apply the example $unwind stage to this document, the stage outputs the following three documents:

   {
     _id: 123,
     customerId: 24601,
     itemIndex: 0,
     items: { name: "Baseball", quantity: 5 }
   }, {
     _id: 123,
     customerId: 24601,
     itemIndex: 1,
     items: { name: "Baseball Mitt", quantity: 1 }
   }, {
     _id: 123,
     customerId: 24601,
     itemIndex: 2,
     items: { name: "Baseball Bat", quantity: 1 }
   }

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