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Query on Embedded/Nested Documents

This page provides examples of query operations on embedded/nested documents using the db.collection.find() method in the mongo shell. The examples on this page use the inventory collection. To populate the inventory collection, run the following:

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. To populate the inventory collection, run the following:

This page provides examples of query operations on embedded/nested documents using the com.mongodb.client.MongoCollection.find method in the 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. To populate the inventory collection, run the following:

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. To populate the inventory collection, run the following:

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. To populate the inventory collection, run the following:

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. To populate the inventory collection, run the following:

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. To populate the inventory collection, run the following:

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. To populate the inventory collection, run the following:

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. To populate the inventory collection, run the following:

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" }
]);

You can run the operation in the web shell below:

# 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"}])
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' }")
));
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"}
])
.then(function(result) {
  // process result
})
$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',
    ],
]);
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);
# 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"
        }
    ]
);
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, 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, 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 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" } } )
cursor = db.inventory.find(
    {"size": SON([("h", 14), ("w", 21), ("uom", "cm")])})
FindIterable<Document> findIterable = collection.find(eq("size", Document.parse("{ h: 14, w: 21, uom: 'cm' }")));
var cursor = db.collection('inventory').find({ 
  size: { h: 14, w: 21, uom: "cm" }
});
$cursor = $db->inventory->find(['size' => ['h' => 14, 'w' => 21, 'uom' => 'cm']]);
var filter = Builders<BsonDocument>.Filter.Eq("size", new BsonDocument { { "h", 14 }, { "w", 21 }, { "uom", "cm" } });
var result = collection.Find(filter).ToList();
# 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" ) }
);
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" } }  )
cursor = db.inventory.find(
    {"size": SON([("w", 21), ("h", 14), ("uom", "cm")])})
findIterable = collection.find(eq("size", Document.parse("{ w: 21, h: 14, uom: 'cm' }")));
var cursor = db.collection('inventory').find({ 
  size: { w: 21, h: 14, uom: "cm" }
});
$cursor = $db->inventory->find(['size' => ['w' => 21, 'h' => 14, 'uom' => 'cm']]);
var filter = Builders<BsonDocument>.Filter.Eq("size", new BsonDocument { { "w", 21 }, { "h", 14 }, { "uom", "cm" } });
var result = collection.Find(filter).ToList();
# 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" ) }
);
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 the dot notation ("field.nestedField").

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" } )
cursor = db.inventory.find({"size.uom": "in"})
findIterable = collection.find(eq("size.uom", "in"));
var cursor = db.collection('inventory').find({ 
  "size.uom": "in"
});
$cursor = $db->inventory->find(['size.uom' => 'in']);
var filter = Builders<BsonDocument>.Filter.Eq("size.uom", "in");
var result = collection.Find(filter).ToList();
$cursor = $db->coll("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 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> ], ... ]

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>));

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": { $lt: 15 } } )
cursor = db.inventory.find({"size.h": {"$lt": 15}})
findIterable = collection.find(lt("size.h", 15));
var cursor = db.collection('inventory').find({ 
  "size.h": { $lt: 15 }
});
$cursor = $db->inventory->find(['size.h' => ['$lt' => 15]]);
var filter = Builders<BsonDocument>.Filter.Lt("size.h", 15);
var result = collection.Find(filter).ToList();
$cursor = $db->coll("inventory")->find( { "size.h" => { '$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": { $lt: 15 }, "size.uom": "in", status: "D" } )
cursor = db.inventory.find(
    {"size.h": {"$lt": 15}, "size.uom": "in", "status": "D"})
findIterable = collection.find(and(
        lt("size.h", 15),
        eq("size.uom", "in"),
        eq("status", "D")
));
var cursor = db.collection('inventory').find({ 
  "size.h": { $lt: 15 }, 
  "size.uom": "in", 
  status: "D"
});
$cursor = $db->inventory->find([
    'size.h' => ['$lt' => 15],
    'size.uom' => 'in',
    'status' => 'D',
]);
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 = $db->coll("inventory")->find(
    { "size.h" => { '$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: