Docs Menu

/

/

MongoDB CRUD Operations

/

Query Documents

Query on Embedded/Nested Documents

On this page

Match an Embedded/Nested Document

Query on Nested Field
Additional Query Tutorials

➤ Use the Select your language drop-down menu in the upper-right to set the language of the following examples.

This page provides examples of query operations on embedded/nested documents using the db.collection.find() method in mongosh.

The examples on this page use the inventory collection. Connect to a test database in your MongoDB instance then create the inventory collection:

This page provides examples of query operations on embedded/nested documents using MongoDB Compass.

The examples on this page use the inventory collection. Connect to a test database in your MongoDB instance then create the inventory collection:

This page provides examples of query operations on embedded/nested documents using the MongoCollection.Find() method in the MongoDB C# Driver.

The examples on this page use the inventory collection. Connect to a test database in your MongoDB instance then create the inventory collection:

This page provides examples of query operations on embedded/nested documents using the Collection.Find function in the MongoDB Go Driver.

The examples on this page use the inventory collection. Connect to a test database in your MongoDB instance then create the inventory collection:

This page provides examples of query operations on embedded/nested documents using the com.mongodb.reactivestreams.client.MongoCollection.find method in the MongoDB Java Reactive Streams Driver.

The examples on this page use the inventory collection. Connect to a test database in your MongoDB instance then create the inventory collection:

This page provides examples of query operations on embedded/nested documents using the com.mongodb.client.MongoCollection.find method in the MongoDB Java Synchronous Driver.

Tip

The driver provides com.mongodb.client.model.Filters helper methods to facilitate the creation of filter documents. The examples on this page use these methods to create the filter documents.

The examples on this page use the inventory collection. Connect to a test database in your MongoDB instance then create the inventory collection:

This page provides examples of query operations on embedded/nested documents using the motor.motor_asyncio.AsyncIOMotorCollection.find method in the Motor driver.

The examples on this page use the inventory collection. Connect to a test database in your MongoDB instance then create the inventory collection:

This page provides examples of query operations on embedded/nested documents using the Collection.find() method in the MongoDB Node.js Driver.

The examples on this page use the inventory collection. Connect to a test database in your MongoDB instance then create the inventory collection:

This page provides examples of query operations on embedded/nested documents using the MongoDB::Collection::find() method in the MongoDB Perl Driver.

The examples on this page use the inventory collection. Connect to a test database in your MongoDB instance then create the inventory collection:

This page provides examples of query operations on embedded/nested documents using the MongoDB\\Collection::find() method in the MongoDB PHP Library.

The examples on this page use the inventory collection. Connect to a test database in your MongoDB instance then create the inventory collection:

This page provides examples of query operations on embedded/nested documents using the pymongo.collection.Collection.find method in the PyMongo Python driver.

The examples on this page use the inventory collection. Connect to a test database in your MongoDB instance then create the inventory collection:

This page provides examples of query operations on embedded/nested documents using the Mongo::Collection#find() method in the MongoDB Ruby Driver.

The examples on this page use the inventory collection. Connect to a test database in your MongoDB instance then create the inventory collection:

This page provides examples of query operations on embedded/nested documents using the collection.find() method in the MongoDB Scala Driver.

The examples on this page use the inventory collection. Connect to a test database in your MongoDB instance then create the inventory collection:

db.inventory.insertMany( [
   { item: "journal", qty: 25, size: { h: 14, w: 21, uom: "cm" }, status: "A" },
   { item: "notebook", qty: 50, size: { h: 8.5, w: 11, uom: "in" }, status: "A" },
   { item: "paper", qty: 100, size: { h: 8.5, w: 11, uom: "in" }, status: "D" },
   { item: "planner", qty: 75, size: { h: 22.85, w: 30, uom: "cm" }, status: "D" },
   { item: "postcard", qty: 45, size: { h: 10, w: 15.25, uom: "cm" }, status: "A" }
]);

[
    { "item": "journal", "qty": 25, "size": { "h": 14, "w": 21, "uom": "cm" }, "status": "A" },
    { "item": "notebook", "qty": 50, "size": { "h": 8.5, "w": 11, "uom": "in" }, "status": "A" },
    { "item": "paper", "qty": 100, "size": { "h": 8.5, "w": 11, "uom": "in" }, "status": "D" },
    { "item": "planner", "qty": 75, "size": { "h": 22.85, "w": 30, "uom": "cm" }, "status": "D" },
    { "item": "postcard", "qty": 45, "size": { "h": 10, "w": 15.25, "uom": "cm" }, "status": "A" }
]

For instructions on inserting documents in MongoDB Compass, see Insert Documents.

var documents = new[]
{
    new BsonDocument
    {
        { "item", "journal" },
        { "qty", 25 },
        { "size", new BsonDocument { { "h", 14 }, { "w", 21 }, { "uom", "cm" } } },
        { "status", "A" }
    },
    new BsonDocument
    {
        { "item", "notebook" },
        { "qty", 50 },
        { "size", new BsonDocument { { "h", 8.5 }, { "w", 11 }, { "uom", "in" } } },
        { "status", "A" }
    },
    new BsonDocument
    {
        { "item", "paper" },
        { "qty", 100 },
        { "size", new BsonDocument { { "h", 8.5 }, { "w", 11 }, { "uom", "in" } } },
        { "status", "D" }
    },
    new BsonDocument
    {
        { "item", "planner" },
        { "qty", 75 },
        { "size", new BsonDocument { { "h", 22.85 }, { "w", 30 }, { "uom", "cm" } } },
        { "status", "D" }
    },
    new BsonDocument
    {
        { "item", "postcard" },
        { "qty", 45 },
        { "size", new BsonDocument { { "h", 10 }, { "w", 15.25 }, { "uom", "cm" } } },
        { "status", "A" } },
};
collection.InsertMany(documents);

docs := []interface{}{
	bson.D{
		{"item", "journal"},
		{"qty", 25},
		{"size", bson.D{
			{"h", 14},
			{"w", 21},
			{"uom", "cm"},
		}},
		{"status", "A"},
	},
	bson.D{
		{"item", "notebook"},
		{"qty", 50},
		{"size", bson.D{
			{"h", 8.5},
			{"w", 11},
			{"uom", "in"},
		}},
		{"status", "A"},
	},
	bson.D{
		{"item", "paper"},
		{"qty", 100},
		{"size", bson.D{
			{"h", 8.5},
			{"w", 11},
			{"uom", "in"},
		}},
		{"status", "D"},
	},
	bson.D{
		{"item", "planner"},
		{"qty", 75},
		{"size", bson.D{
			{"h", 22.85},
			{"w", 30},
			{"uom", "cm"},
		}},
		{"status", "D"},
	},
	bson.D{
		{"item", "postcard"},
		{"qty", 45},
		{"size", bson.D{
			{"h", 10},
			{"w", 15.25},
			{"uom", "cm"},
		}},
		{"status", "A"},
	},
}
result, err := coll.InsertMany(context.TODO(), docs)

Publisher<Success> insertManyPublisher = collection.insertMany(asList(
        Document.parse("{ item: 'journal', qty: 25, size: { h: 14, w: 21, uom: 'cm' }, status: 'A' }"),
        Document.parse("{ item: 'notebook', qty: 50, size: { h: 8.5, w: 11, uom: 'in' }, status: 'A' }"),
        Document.parse("{ item: 'paper', qty: 100, size: { h: 8.5, w: 11, uom: 'in' }, status: 'D' }"),
        Document.parse("{ item: 'planner', qty: 75, size: { h: 22.85, w: 30, uom: 'cm' }, status: 'D' }"),
        Document.parse("{ item: 'postcard', qty: 45, size: { h: 10, w: 15.25, uom: 'cm' }, status: 'A' }")
));

collection.insertMany(asList(
        Document.parse("{ item: 'journal', qty: 25, size: { h: 14, w: 21, uom: 'cm' }, status: 'A' }"),
        Document.parse("{ item: 'notebook', qty: 50, size: { h: 8.5, w: 11, uom: 'in' }, status: 'A' }"),
        Document.parse("{ item: 'paper', qty: 100, size: { h: 8.5, w: 11, uom: 'in' }, status: 'D' }"),
        Document.parse("{ item: 'planner', qty: 75, size: { h: 22.85, w: 30, uom: 'cm' }, status: 'D' }"),
        Document.parse("{ item: 'postcard', qty: 45, size: { h: 10, w: 15.25, uom: 'cm' }, status: 'A' }")
));

# Subdocument key order matters in a few of these examples so we have
# to use bson.son.SON instead of a Python dict.
from bson.son import SON
await db.inventory.insert_many(
    [
        {
            "item": "journal",
            "qty": 25,
            "size": SON([("h", 14), ("w", 21), ("uom", "cm")]),
            "status": "A",
        },
        {
            "item": "notebook",
            "qty": 50,
            "size": SON([("h", 8.5), ("w", 11), ("uom", "in")]),
            "status": "A",
        },
        {
            "item": "paper",
            "qty": 100,
            "size": SON([("h", 8.5), ("w", 11), ("uom", "in")]),
            "status": "D",
        },
        {
            "item": "planner",
            "qty": 75,
            "size": SON([("h", 22.85), ("w", 30), ("uom", "cm")]),
            "status": "D",
        },
        {
            "item": "postcard",
            "qty": 45,
            "size": SON([("h", 10), ("w", 15.25), ("uom", "cm")]),
            "status": "A",
        },
    ]
)

await db.collection('inventory').insertMany([
  {
    item: 'journal',
    qty: 25,
    size: { h: 14, w: 21, uom: 'cm' },
    status: 'A'
  },
  {
    item: 'notebook',
    qty: 50,
    size: { h: 8.5, w: 11, uom: 'in' },
    status: 'A'
  },
  {
    item: 'paper',
    qty: 100,
    size: { h: 8.5, w: 11, uom: 'in' },
    status: 'D'
  },
  {
    item: 'planner',
    qty: 75,
    size: { h: 22.85, w: 30, uom: 'cm' },
    status: 'D'
  },
  {
    item: 'postcard',
    qty: 45,
    size: { h: 10, w: 15.25, uom: 'cm' },
    status: 'A'
  }
]);

# Subdocument key order matters in this example so we have
# to use Tie::IxHash instead of a regular, unordered Perl hash.
$db->coll("inventory")->insert_many(
    [
        {
            item   => "journal",
            qty    => 25,
            size   => Tie::IxHash->new( h => 14, w => 21, uom => "cm" ),
            status => "A"
        },
        {
            item   => "notebook",
            qty    => 50,
            size   => Tie::IxHash->new( h => 8.5, w => 11, uom => "in" ),
            status => "A"
        },
        {
            item   => "paper",
            qty    => 100,
            size   => Tie::IxHash->new( h => 8.5, w => 11, uom => "in" ),
            status => "D"
        },
        {
            item   => "planner",
            qty    => 75,
            size   => Tie::IxHash->new( h => 22.85, w => 30, uom => "cm" ),
            status => "D"
        },
        {
            item   => "postcard",
            qty    => 45,
            size   => Tie::IxHash->new( h => 10, w => 15.25, uom => "cm" ),
            status => "A"
        }
    ]
);

$insertManyResult = $db->inventory->insertMany([
    [
        'item' => 'journal',
        'qty' => 25,
        'size' => ['h' => 14, 'w' => 21, 'uom' => 'cm'],
        'status' => 'A',
    ],
    [
        'item' => 'notebook',
        'qty' => 50,
        'size' => ['h' => 8.5, 'w' => 11, 'uom' => 'in'],
        'status' => 'A',
    ],
    [
        'item' => 'paper',
        'qty' => 100,
        'size' => ['h' => 8.5, 'w' => 11, 'uom' => 'in'],
        'status' => 'D',
    ],
    [
        'item' => 'planner',
        'qty' => 75,
        'size' => ['h' => 22.85, 'w' => 30, 'uom' => 'cm'],
        'status' => 'D',
    ],
    [
        'item' => 'postcard',
        'qty' => 45,
        'size' => ['h' => 10, 'w' => 15.25, 'uom' => 'cm'],
        'status' => 'A',
    ],
]);

# Subdocument key order matters in a few of these examples so we have
# to use bson.son.SON instead of a Python dict.
from bson.son import SON
db.inventory.insert_many(
    [
        {
            "item": "journal",
            "qty": 25,
            "size": SON([("h", 14), ("w", 21), ("uom", "cm")]),
            "status": "A",
        },
        {
            "item": "notebook",
            "qty": 50,
            "size": SON([("h", 8.5), ("w", 11), ("uom", "in")]),
            "status": "A",
        },
        {
            "item": "paper",
            "qty": 100,
            "size": SON([("h", 8.5), ("w", 11), ("uom", "in")]),
            "status": "D",
        },
        {
            "item": "planner",
            "qty": 75,
            "size": SON([("h", 22.85), ("w", 30), ("uom", "cm")]),
            "status": "D",
        },
        {
            "item": "postcard",
            "qty": 45,
            "size": SON([("h", 10), ("w", 15.25), ("uom", "cm")]),
            "status": "A",
        },
    ]
)

client[:inventory].insert_many([
                                { item: 'journal',
                                  qty: 25,
                                  size: { h: 14, w: 21, uom: 'cm' },
                                  status: 'A' },
                                { item: 'notebook',
                                  qty: 50,
                                  size: { h: 8.5, w: 11, uom: 'in' },
                                  status: 'A' },
                                { item: 'paper',
                                  qty: 100,
                                  size: { h: 8.5, w: 11, uom: 'in' },
                                  status: 'D' },
                                { item: 'planner',
                                  qty: 75,
                                  size: { h: 22.85, w: 30, uom: 'cm' },
                                  status: 'D' },
                                { item: 'postcard',
                                  qty: 45,
                                  size: { h: 10, w: 15.25, uom: 'cm' },
                                  status: 'A' }
                               ])

collection.insertMany(Seq(
  Document("""{ item: "journal", qty: 25, size: { h: 14, w: 21, uom: "cm" }, status: "A" }"""),
  Document("""{ item: "notebook", qty: 50, size: { h: 8.5, w: 11, uom: "in" }, status: "A" }"""),
  Document("""{ item: "paper", qty: 100, size: { h: 8.5, w: 11, uom: "in" }, status: "D" }"""),
  Document("""{ item: "planner", qty: 75, size: { h: 22.85, w: 30, uom: "cm" }, status: "D" }"""),
  Document("""{ item: "postcard", qty: 45, size: { h: 10, w: 15.25, uom: "cm" }, status: "A" }""")
)).execute()

Match an Embedded/Nested Document

To specify an equality condition on a field that is an embedded/nested document, use the query filter document { <field>: <value> } where <value> is the document to match.

To specify an equality condition on a field that is an embedded/nested document, use the query filter document { <field>: <value> } where <value> is the document to match.

To specify an equality condition on a field that is an embedded/nested document, construct a filter using the Eq method:

Builders<BsonDocument>.Filter.Eq(<field>, <value>)

<value> is the document to match.

To specify an equality condition on a field that is an embedded/nested document, use the filter document eq( <field1>, <value>) where <value> is the document to match.

To specify an equality condition on a field that is an embedded/nested document, use the filter document eq( <field1>, <value>) where <value> is the document to match.

To specify an equality condition on a field that is an embedded/nested document, use the query filter document { <field>: <value> } where <value> is the document to match.

To specify an equality condition on a field that is an embedded/nested document, use the query filter document { <field>: <value> } where <value> is the document to match.

To specify an equality condition on a field that is an embedded/nested document, use the query filter document { <field> => <value> } where <value> is the document to match.

To specify an equality condition on a field that is an embedded/nested document, use the query filter document [ <field> => <value> ] where <value> is the document to match.

To specify an equality condition on a field that is an embedded/nested document, use the query filter document { <field>: <value> } where <value> is the document to match.

To specify an equality condition on a field that is an embedded/nested document, use the query filter document { <field> => <value> } where <value> is the document to match.

To specify an equality condition on a field that is an embedded/nested document, use the filter document equal( <field1>, <value> ) where <value> is the document to match.

For example, the following query selects all documents where the field size equals the document { h: 14, w: 21, uom: "cm" }:

db.inventory.find( { size: { h: 14, w: 21, uom: "cm" } } )

Copy the following filter into the Compass query bar and click Find:

{ size: { h: 14, w: 21, uom: "cm" } }

Query embedded field

var filter = Builders<BsonDocument>.Filter.Eq("size", new BsonDocument { { "h", 14 }, { "w", 21 }, { "uom", "cm" } });
var result = collection.Find(filter).ToList();

cursor, err := coll.Find(
	context.TODO(),
	bson.D{
		{"size", bson.D{
			{"h", 14},
			{"w", 21},
			{"uom", "cm"},
		}},
	})

FindPublisher<Document> findPublisher = collection.find(eq("size", Document.parse("{ h: 14, w: 21, uom: 'cm' }")));

FindIterable<Document> findIterable = collection.find(eq("size", Document.parse("{ h: 14, w: 21, uom: 'cm' }")));

cursor = db.inventory.find({"size": SON([("h", 14), ("w", 21), ("uom", "cm")])})

const cursor = db.collection('inventory').find({
  size: { h: 14, w: 21, uom: 'cm' }
});

# Subdocument key order matters in this example so we have
# to use Tie::IxHash instead of a regular, unordered Perl hash.
$cursor = $db->coll("inventory")->find(
    { size => Tie::IxHash->new( h => 14, w => 21, uom => "cm" ) }
);

$cursor = $db->inventory->find(['size' => ['h' => 14, 'w' => 21, 'uom' => 'cm']]);

cursor = db.inventory.find({"size": SON([("h", 14), ("w", 21), ("uom", "cm")])})

client[:inventory].find(size: { h: 14, w: 21, uom: 'cm' })

var findObservable = collection.find(equal("size", Document("h" -> 14, "w" -> 21, "uom" -> "cm")))

Equality matches on the whole embedded document require an exact match of the specified <value> document, including the field order. For example, the following query does not match any documents in the inventory collection:

db.inventory.find(  { size: { w: 21, h: 14, uom: "cm" } }  )

Query embedded field

var filter = Builders<BsonDocument>.Filter.Eq("size", new BsonDocument { { "w", 21 }, { "h", 14 }, { "uom", "cm" } });
var result = collection.Find(filter).ToList();

cursor, err := coll.Find(
	context.TODO(),
	bson.D{
		{"size", bson.D{
			{"w", 21},
			{"h", 14},
			{"uom", "cm"},
		}},
	})

findPublisher = collection.find(eq("size", Document.parse("{ w: 21, h: 14, uom: 'cm' }")));

findIterable = collection.find(eq("size", Document.parse("{ w: 21, h: 14, uom: 'cm' }")));

cursor = db.inventory.find({"size": SON([("w", 21), ("h", 14), ("uom", "cm")])})

const cursor = db.collection('inventory').find({
  size: { w: 21, h: 14, uom: 'cm' }
});

# Subdocument key order matters in this example so we have
# to use Tie::IxHash instead of a regular, unordered Perl hash.
$cursor = $db->coll("inventory")->find(
    { size => Tie::IxHash->new( w => 21, h => 14, uom => "cm" ) }
);

$cursor = $db->inventory->find(['size' => ['w' => 21, 'h' => 14, 'uom' => 'cm']]);

cursor = db.inventory.find({"size": SON([("w", 21), ("h", 14), ("uom", "cm")])})

client[:inventory].find(size: { h: 21, w: 14, uom: 'cm' })

findObservable = collection.find(equal("size", Document("w" -> 21, "h" -> 14, "uom" -> "cm")))

Query on Nested Field

To specify a query condition on fields in an embedded/nested document, use dot notation ("field.nestedField").

Note

When querying using dot notation, the field and nested field must be inside quotation marks.

Specify Equality Match on a Nested Field

The following example selects all documents where the field uom nested in the size field equals "in":

db.inventory.find( { "size.uom": "in" } )

Copy the following filter into the Compass query bar and click Find:

{ "size.uom": "in" }

Query single nested field

var filter = Builders<BsonDocument>.Filter.Eq("size.uom", "in");
var result = collection.Find(filter).ToList();

cursor, err := coll.Find(
	context.TODO(),
	bson.D{{"size.uom", "in"}},
)

findPublisher = collection.find(eq("size.uom", "in"));

findIterable = collection.find(eq("size.uom", "in"));

cursor = db.inventory.find({"size.uom": "in"})

const cursor = db.collection('inventory').find({
  'size.uom': 'in'
});

$cursor = $db->coll("inventory")->find( { "size.uom" => "in" } );

$cursor = $db->inventory->find(['size.uom' => 'in']);

cursor = db.inventory.find({"size.uom": "in"})

client[:inventory].find('size.uom' => 'in')

findObservable = collection.find(equal("size.uom", "in"))

Specify Match using Query Operator

A query filter document can use the query operators to specify conditions in the following form:

{ <field1>: { <operator1>: <value1> }, ... }

A query filter document can use the query operators to specify conditions in the following form:

{ <field1>: { <operator1>: <value1> }, ... }

In addition to the equality filter, MongoDB provides various query operators to specify filter conditions. Use the FilterDefinitionBuilder methods to create a filter document. For example:

var builder = Builders<BsonDocument>.Filter;
builder.And(builder.Eq(<field1>, <value1>), builder.Lt(<field2>, <value2>));

In addition to the equality condition, MongoDB provides various query operators to specify filter conditions. Use the com.mongodb.client.model.Filters helper methods to facilitate the creation of filter documents. For example:

and(gte(<field1>, <value1>), lt(<field2>, <value2>), eq(<field3>, <value3>))

In addition to the equality condition, MongoDB provides various query operators to specify filter conditions. Use the com.mongodb.client.model.Filters helper methods to facilitate the creation of filter documents. For example:

and(gte(<field1>, <value1>), lt(<field2>, <value2>), eq(<field3>, <value3>))

A query filter document can use the query operators to specify conditions in the following form:

{ <field1>: { <operator1>: <value1> }, ... }

A query filter document can use the query operators to specify conditions in the following form:

{ <field1>: { <operator1>: <value1> }, ... }

A query filter document can use the query operators to specify conditions in the following form:

{ <field1> => { <operator1> => <value1> }, ... }

A query filter document can use the query operators to specify conditions in the following form:

[ <field1> => [ <operator1> => <value1> ], ... ]

A query filter document can use the query operators to specify conditions in the following form:

{ <field1>: { <operator1>: <value1> }, ... }

A query filter document can use the query operators to specify conditions in the following form:

{ <field1> => { <operator1> => <value1> }, ... }

In addition to the equality condition, MongoDB provides various query operators to specify filter conditions. Use the com.mongodb.client.model.Filters_ helper methods to facilitate the creation of filter documents. For example:

and(gte(<field1>, <value1>), lt(<field2>, <value2>), equal(<field3>, <value3>))

The following query uses the less than operator ($lt) on the field h embedded in the size field:

db.inventory.find( { "size.h": { $lt: 15 } } )

Copy the following filter into the Compass query bar and click Find:

{ "size.h": { $lt: 15 } }

Query single nested field

var filter = Builders<BsonDocument>.Filter.Lt("size.h", 15);
var result = collection.Find(filter).ToList();

cursor, err := coll.Find(
	context.TODO(),
	bson.D{
		{"size.h", bson.D{
			{"$lt", 15},
		}},
	})

findPublisher = collection.find(lt("size.h", 15));

findIterable = collection.find(lt("size.h", 15));

cursor = db.inventory.find({"size.h": {"$lt": 15}})

const cursor = db.collection('inventory').find({
  'size.h': { $lt: 15 }
});

$cursor = $db->coll("inventory")->find( { "size.h" => { '$lt' => 15 } } );

$cursor = $db->inventory->find(['size.h' => ['$lt' => 15]]);

cursor = db.inventory.find({"size.h": {"$lt": 15}})

client[:inventory].find('size.h' => { '$lt' =>  15 })

findObservable = collection.find(lt("size.h", 15))

Specify `AND` Condition

The following query selects all documents where the nested field h is less than 15, the nested field uom equals "in", and the status field equals "D":

db.inventory.find( { "size.h": { $lt: 15 }, "size.uom": "in", status: "D" } )

Copy the following filter into the Compass query bar and click Find:

{ "size.h": { $lt: 15 }, "size.uom": "in", status: "D" }

Query multiple nested fields

var builder = Builders<BsonDocument>.Filter;
var filter = builder.And(builder.Lt("size.h", 15), builder.Eq("size.uom", "in"), builder.Eq("status", "D"));
var result = collection.Find(filter).ToList();

cursor, err := coll.Find(
	context.TODO(),
	bson.D{
		{"size.h", bson.D{
			{"$lt", 15},
		}},
		{"size.uom", "in"},
		{"status", "D"},
	})

findPublisher = collection.find(and(
        lt("size.h", 15),
        eq("size.uom", "in"),
        eq("status", "D")
));

findIterable = collection.find(and(
        lt("size.h", 15),
        eq("size.uom", "in"),
        eq("status", "D")
));

cursor = db.inventory.find({"size.h": {"$lt": 15}, "size.uom": "in", "status": "D"})

const cursor = db.collection('inventory').find({
  'size.h': { $lt: 15 },
  'size.uom': 'in',
  status: 'D'
});

$cursor = $db->coll("inventory")->find(
    { "size.h" => { '$lt' => 15 }, "size.uom" => "in", status => "D" }
);

$cursor = $db->inventory->find([
    'size.h' => ['$lt' => 15],
    'size.uom' => 'in',
    'status' => 'D',
]);

cursor = db.inventory.find({"size.h": {"$lt": 15}, "size.uom": "in", "status": "D"})

client[:inventory].find('size.h'   => { '$lt' => 15 },
                        'size.uom' => 'in',
                        'status'   => 'D')

findObservable = collection.find(and(
  lt("size.h", 15),
  equal("size.uom", "in"),
  equal("status", "D")
))

Additional Query Tutorials

For additional query examples, see:

Back

Query Documents

Next

Query an Array

Select your language

On this page

Match an Embedded/Nested Document
Query on Nested Field
Additional Query Tutorials