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Query an Array of Embedded Documents

On this page

  • Query for a Document Nested in an Array
  • Specify a Query Condition on a Field in an Array of Documents
  • Specify Multiple Conditions for Array of Documents
  • Query an Array of Documents with MongoDB Atlas
  • Additional Query Tutorials

You can query documents in MongoDB by using the following methods:

  • Your programming language's driver.

  • The MongoDB Atlas UI. To learn more, see Query an Array of Documents with MongoDB Atlas.

  • MongoDB Compass.


Use the Select your language drop-down menu in the upper-right to set the language of the following examples or select MongoDB Compass.


This page provides examples of query operations on an array of 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 an array of 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 an array of nested documents using mongoc_collection_find_with_opts.

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 an array of 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 an array of 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 an array of 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 an array of 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 an array of nested documents by using the MongoCollection.find() method in the MongoDB Kotlin Coroutine 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 an array of 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 an array of 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 an array of 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 an array of 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 an array of 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 an array of 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 an array of 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", instock: [ { warehouse: "A", qty: 5 }, { warehouse: "C", qty: 15 } ] },
{ item: "notebook", instock: [ { warehouse: "C", qty: 5 } ] },
{ item: "paper", instock: [ { warehouse: "A", qty: 60 }, { warehouse: "B", qty: 15 } ] },
{ item: "planner", instock: [ { warehouse: "A", qty: 40 }, { warehouse: "B", qty: 5 } ] },
{ item: "postcard", instock: [ { warehouse: "B", qty: 15 }, { warehouse: "C", qty: 35 } ] }
]);
[
{ "item": "journal", "instock": [ { "warehouse": "A", "qty": 5 }, { "warehouse": "C", "qty": 15 } ] },
{ "item": "notebook", "instock": [ { "warehouse": "C", "qty": 5 } ] },
{ "item": "paper", "instock": [ { "warehouse": "A", "qty": 60 }, { "warehouse": "B", "qty": 15 } ] },
{ "item": "planner", "instock": [ { "warehouse": "A", "qty": 40 }, { "warehouse": "B", "qty": 5 } ] },
{ "item": "postcard", "instock": [ { "warehouse": "B","qty": 15 }, { "warehouse": "C", "qty": 35 } ] }
]

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

mongoc_collection_t *collection;
mongoc_bulk_operation_t *bulk;
bson_t *doc;
bool r;
bson_error_t error;
bson_t reply;
collection = mongoc_database_get_collection (db, "inventory");
bulk = mongoc_collection_create_bulk_operation_with_opts (collection, NULL);
doc = BCON_NEW (
"item", BCON_UTF8 ("journal"),
"instock", "[",
"{",
"warehouse", BCON_UTF8 ("A"),
"qty", BCON_INT64 (5),
"}","{",
"warehouse", BCON_UTF8 ("C"),
"qty", BCON_INT64 (15),
"}",
"]");
r = mongoc_bulk_operation_insert_with_opts (bulk, doc, NULL, &error);
bson_destroy (doc);
if (!r) {
MONGOC_ERROR ("%s\n", error.message);
goto done;
}
doc = BCON_NEW (
"item", BCON_UTF8 ("notebook"),
"instock", "[",
"{",
"warehouse", BCON_UTF8 ("C"),
"qty", BCON_INT64 (5),
"}",
"]");
r = mongoc_bulk_operation_insert_with_opts (bulk, doc, NULL, &error);
bson_destroy (doc);
if (!r) {
MONGOC_ERROR ("%s\n", error.message);
goto done;
}
doc = BCON_NEW (
"item", BCON_UTF8 ("paper"),
"instock", "[",
"{",
"warehouse", BCON_UTF8 ("A"),
"qty", BCON_INT64 (60),
"}","{",
"warehouse", BCON_UTF8 ("B"),
"qty", BCON_INT64 (15),
"}",
"]");
r = mongoc_bulk_operation_insert_with_opts (bulk, doc, NULL, &error);
bson_destroy (doc);
if (!r) {
MONGOC_ERROR ("%s\n", error.message);
goto done;
}
doc = BCON_NEW (
"item", BCON_UTF8 ("planner"),
"instock", "[",
"{",
"warehouse", BCON_UTF8 ("A"),
"qty", BCON_INT64 (40),
"}","{",
"warehouse", BCON_UTF8 ("B"),
"qty", BCON_INT64 (5),
"}",
"]");
r = mongoc_bulk_operation_insert_with_opts (bulk, doc, NULL, &error);
bson_destroy (doc);
if (!r) {
MONGOC_ERROR ("%s\n", error.message);
goto done;
}
doc = BCON_NEW (
"item", BCON_UTF8 ("postcard"),
"instock", "[",
"{",
"warehouse", BCON_UTF8 ("B"),
"qty", BCON_INT64 (15),
"}","{",
"warehouse", BCON_UTF8 ("C"),
"qty", BCON_INT64 (35),
"}",
"]");
r = mongoc_bulk_operation_insert_with_opts (bulk, doc, NULL, &error);
bson_destroy (doc);
if (!r) {
MONGOC_ERROR ("%s\n", error.message);
goto done;
}
/* "reply" is initialized on success or error */
r = (bool) mongoc_bulk_operation_execute (bulk, &reply, &error);
if (!r) {
MONGOC_ERROR ("%s\n", error.message);
}
var documents = new[]
{
new BsonDocument
{
{ "item", "journal" },
{ "instock", new BsonArray
{
new BsonDocument { { "warehouse", "A" }, { "qty", 5 } },
new BsonDocument { { "warehouse", "C" }, { "qty", 15 } } }
}
},
new BsonDocument
{
{ "item", "notebook" },
{ "instock", new BsonArray
{
new BsonDocument { { "warehouse", "C" }, { "qty", 5 } } }
}
},
new BsonDocument
{
{ "item", "paper" },
{ "instock", new BsonArray
{
new BsonDocument { { "warehouse", "A" }, { "qty", 60 } },
new BsonDocument { { "warehouse", "B" }, { "qty", 15 } } }
}
},
new BsonDocument
{
{ "item", "planner" },
{ "instock", new BsonArray
{
new BsonDocument { { "warehouse", "A" }, { "qty", 40 } },
new BsonDocument { { "warehouse", "B" }, { "qty", 5 } } }
}
},
new BsonDocument
{
{ "item", "postcard" },
{ "instock", new BsonArray
{
new BsonDocument { { "warehouse", "B" }, { "qty", 15 } },
new BsonDocument { { "warehouse", "C" }, { "qty", 35 } } }
}
}
};
collection.InsertMany(documents);
docs := []interface{}{
bson.D{
{"item", "journal"},
{"instock", bson.A{
bson.D{
{"warehouse", "A"},
{"qty", 5},
},
bson.D{
{"warehouse", "C"},
{"qty", 15},
},
}},
},
bson.D{
{"item", "notebook"},
{"instock", bson.A{
bson.D{
{"warehouse", "C"},
{"qty", 5},
},
}},
},
bson.D{
{"item", "paper"},
{"instock", bson.A{
bson.D{
{"warehouse", "A"},
{"qty", 60},
},
bson.D{
{"warehouse", "B"},
{"qty", 15},
},
}},
},
bson.D{
{"item", "planner"},
{"instock", bson.A{
bson.D{
{"warehouse", "A"},
{"qty", 40},
},
bson.D{
{"warehouse", "B"},
{"qty", 5},
},
}},
},
bson.D{
{"item", "postcard"},
{"instock", bson.A{
bson.D{
{"warehouse", "B"},
{"qty", 15},
},
bson.D{
{"warehouse", "C"},
{"qty", 35},
},
}},
},
}
result, err := coll.InsertMany(context.TODO(), docs)
Publisher<Success> insertManyPublisher = collection.insertMany(asList(
Document.parse("{ item: 'journal', instock: [ { warehouse: 'A', qty: 5 }, { warehouse: 'C', qty: 15 } ] }"),
Document.parse("{ item: 'notebook', instock: [ { warehouse: 'C', qty: 5 } ] }"),
Document.parse("{ item: 'paper', instock: [ { warehouse: 'A', qty: 60 }, { warehouse: 'B', qty: 15 } ] }"),
Document.parse("{ item: 'planner', instock: [ { warehouse: 'A', qty: 40 }, { warehouse: 'B', qty: 5 } ] }"),
Document.parse("{ item: 'postcard', instock: [ { warehouse: 'B', qty: 15 }, { warehouse: 'C', qty: 35 } ] }")
));
collection.insertMany(asList(
Document.parse("{ item: 'journal', instock: [ { warehouse: 'A', qty: 5 }, { warehouse: 'C', qty: 15 } ] }"),
Document.parse("{ item: 'notebook', instock: [ { warehouse: 'C', qty: 5 } ] }"),
Document.parse("{ item: 'paper', instock: [ { warehouse: 'A', qty: 60 }, { warehouse: 'B', qty: 15 } ] }"),
Document.parse("{ item: 'planner', instock: [ { warehouse: 'A', qty: 40 }, { warehouse: 'B', qty: 5 } ] }"),
Document.parse("{ item: 'postcard', instock: [ { warehouse: 'B', qty: 15 }, { warehouse: 'C', qty: 35 } ] }")
));
collection.insertMany(
listOf(
Document("item", "journal")
.append("instock", listOf(
Document("warehouse", "A").append("qty", 5),
Document("warehouse", "C").append("qty", 15)
)),
Document("item", "notebook")
.append("instock", listOf(
Document("warehouse", "C").append("qty", 5)
)),
Document("item", "paper")
.append("instock", listOf(
Document("warehouse", "A").append("qty", 60),
Document("warehouse", "B").append("qty", 15)
)),
Document("item", "planner")
.append("instock", listOf(
Document("warehouse", "A").append("qty", 40),
Document("warehouse", "B").append("qty", 5)
)),
Document("item", "postcard")
.append("instock", listOf(
Document("warehouse", "B").append("qty", 15),
Document("warehouse", "C").append("qty", 35)
)),
)
)
# 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",
"instock": [
SON([("warehouse", "A"), ("qty", 5)]),
SON([("warehouse", "C"), ("qty", 15)]),
],
},
{"item": "notebook", "instock": [SON([("warehouse", "C"), ("qty", 5)])]},
{
"item": "paper",
"instock": [
SON([("warehouse", "A"), ("qty", 60)]),
SON([("warehouse", "B"), ("qty", 15)]),
],
},
{
"item": "planner",
"instock": [
SON([("warehouse", "A"), ("qty", 40)]),
SON([("warehouse", "B"), ("qty", 5)]),
],
},
{
"item": "postcard",
"instock": [
SON([("warehouse", "B"), ("qty", 15)]),
SON([("warehouse", "C"), ("qty", 35)]),
],
},
]
)
await db.collection('inventory').insertMany([
{
item: 'journal',
instock: [
{ warehouse: 'A', qty: 5 },
{ warehouse: 'C', qty: 15 }
]
},
{
item: 'notebook',
instock: [{ warehouse: 'C', qty: 5 }]
},
{
item: 'paper',
instock: [
{ warehouse: 'A', qty: 60 },
{ warehouse: 'B', qty: 15 }
]
},
{
item: 'planner',
instock: [
{ warehouse: 'A', qty: 40 },
{ warehouse: 'B', qty: 5 }
]
},
{
item: 'postcard',
instock: [
{ warehouse: 'B', qty: 15 },
{ warehouse: 'C', qty: 35 }
]
}
]);
# 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",
instock => [
Tie::IxHash->new( warehouse => "A", qty => 5 ),
Tie::IxHash->new( warehouse => "C", qty => 15 )
]
},
{
item => "notebook",
instock => [ Tie::IxHash->new( warehouse => "C", qty => 5 ) ]
},
{
item => "paper",
instock => [
Tie::IxHash->new( warehouse => "A", qty => 60 ),
Tie::IxHash->new( warehouse => "B", qty => 15 )
]
},
{
item => "planner",
instock => [
Tie::IxHash->new( warehouse => "A", qty => 40 ),
Tie::IxHash->new( warehouse => "B", qty => 5 )
]
},
{
item => "postcard",
instock => [
Tie::IxHash->new( warehouse => "B", qty => 15 ),
Tie::IxHash->new( warehouse => "C", qty => 35 )
]
}
]
);
$insertManyResult = $db->inventory->insertMany([
[
'item' => 'journal',
'instock' => [
['warehouse' => 'A', 'qty' => 5],
['warehouse' => 'C', 'qty' => 15],
],
],
[
'item' => 'notebook',
'instock' => [
['warehouse' => 'C', 'qty' => 5],
],
],
[
'item' => 'paper',
'instock' => [
['warehouse' => 'A', 'qty' => 60],
['warehouse' => 'B', 'qty' => 15],
],
],
[
'item' => 'planner',
'instock' => [
['warehouse' => 'A', 'qty' => 40],
['warehouse' => 'B', 'qty' => 5],
],
],
[
'item' => 'postcard',
'instock' => [
['warehouse' => 'B', 'qty' => 15],
['warehouse' => 'C', 'qty' => 35],
],
],
]);
# 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",
"instock": [
SON([("warehouse", "A"), ("qty", 5)]),
SON([("warehouse", "C"), ("qty", 15)]),
],
},
{"item": "notebook", "instock": [SON([("warehouse", "C"), ("qty", 5)])]},
{
"item": "paper",
"instock": [
SON([("warehouse", "A"), ("qty", 60)]),
SON([("warehouse", "B"), ("qty", 15)]),
],
},
{
"item": "planner",
"instock": [
SON([("warehouse", "A"), ("qty", 40)]),
SON([("warehouse", "B"), ("qty", 5)]),
],
},
{
"item": "postcard",
"instock": [
SON([("warehouse", "B"), ("qty", 15)]),
SON([("warehouse", "C"), ("qty", 35)]),
],
},
]
)
client[:inventory].insert_many([{ item: 'journal',
instock: [ { warehouse: 'A', qty: 5 },
{ warehouse: 'C', qty: 15 }] },
{ item: 'notebook',
instock: [ { warehouse: 'C', qty: 5 }] },
{ item: 'paper',
instock: [ { warehouse: 'A', qty: 60 },
{ warehouse: 'B', qty: 15 }] },
{ item: 'planner',
instock: [ { warehouse: 'A', qty: 40 },
{ warehouse: 'B', qty: 5 }] },
{ item: 'postcard',
instock: [ { warehouse: 'B', qty: 15 },
{ warehouse: 'C', qty: 35 }] }
])
collection.insertMany(Seq(
Document("""{ item: "journal", instock: [ { warehouse: "A", qty: 5 }, { warehouse: "C", qty: 15 } ] }"""),
Document("""{ item: "notebook", instock: [ { warehouse: "C", qty: 5 } ] }"""),
Document("""{ item: "paper", instock: [ { warehouse: "A", qty: 60 }, { warehouse: "B", qty: 15 } ] }"""),
Document("""{ item: "planner", instock: [ { warehouse: "A", qty: 40 }, { warehouse: "B", qty: 5 } ] }"""),
Document("""{ item: "postcard", instock: [ { warehouse: "B", qty: 15 }, { warehouse: "C", qty: 35 } ] }""")
)).execute()

The following example selects all documents where an element in the instock array matches the specified document:

db.inventory.find( { "instock": { warehouse: "A", qty: 5 } } )

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

{ "instock": { warehouse: "A", qty: 5 } }
Query for nested array element
mongoc_collection_t *collection;
bson_t *filter;
mongoc_cursor_t *cursor;
collection = mongoc_database_get_collection (db, "inventory");
filter = BCON_NEW (
"instock", "{",
"warehouse", BCON_UTF8 ("A"),
"qty", BCON_INT64 (5),
"}");
cursor = mongoc_collection_find_with_opts (collection, filter, NULL, NULL);
var filter = Builders<BsonDocument>.Filter.AnyEq("instock", new BsonDocument { { "warehouse", "A" }, { "qty", 5 } });
var result = collection.Find(filter).ToList();
cursor, err := coll.Find(
context.TODO(),
bson.D{
{"instock", bson.D{
{"warehouse", "A"},
{"qty", 5},
}},
})
FindPublisher<Document> findPublisher = collection.find(eq("instock", Document.parse("{ warehouse: 'A', qty: 5 }")));
FindIterable<Document> findIterable = collection.find(eq("instock", Document.parse("{ warehouse: 'A', qty: 5 }")));
val findFlow = collection
.find(eq("instock", Document.parse("{ warehouse: 'A', qty: 5 }")))
cursor = db.inventory.find({"instock": SON([("warehouse", "A"), ("qty", 5)])})
const cursor = db.collection('inventory').find({
instock: { warehouse: 'A', qty: 5 }
});
# 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(
{ instock => Tie::IxHash->new( warehouse => "A", qty => 5 ) }
);
$cursor = $db->inventory->find(['instock' => ['warehouse' => 'A', 'qty' => 5]]);
cursor = db.inventory.find({"instock": SON([("warehouse", "A"), ("qty", 5)])})
client[:inventory].find(instock: { warehouse: 'A', qty: 5 })
var findObservable = collection.find(equal("instock", Document("warehouse" -> "A", "qty" -> 5)))

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

db.inventory.find( { "instock": { qty: 5, warehouse: "A" } } )
Query for nested array element
mongoc_collection_t *collection;
bson_t *filter;
mongoc_cursor_t *cursor;
collection = mongoc_database_get_collection (db, "inventory");
filter = BCON_NEW (
"instock", "{",
"qty", BCON_INT64 (5),
"warehouse", BCON_UTF8 ("A"),
"}");
cursor = mongoc_collection_find_with_opts (collection, filter, NULL, NULL);
var filter = Builders<BsonDocument>.Filter.AnyEq("instock", new BsonDocument { { "qty", 5 }, { "warehouse", "A" } });
var result = collection.Find(filter).ToList();
cursor, err := coll.Find(
context.TODO(),
bson.D{
{"instock", bson.D{
{"qty", 5},
{"warehouse", "A"},
}},
})
findPublisher = collection.find(eq("instock", Document.parse("{ qty: 5, warehouse: 'A' }")));
findIterable = collection.find(eq("instock", Document.parse("{ qty: 5, warehouse: 'A' }")));
val findFlow = collection
.find(eq("instock", Document.parse("{ qty: 5, warehouse: 'A' }")))
cursor = db.inventory.find({"instock": SON([("qty", 5), ("warehouse", "A")])})
const cursor = db.collection('inventory').find({
instock: { qty: 5, warehouse: 'A' }
});
# 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(
{ instock => Tie::IxHash->new( qty => 5, warehouse => "A" ) }
);
$cursor = $db->inventory->find(['instock' => ['qty' => 5, 'warehouse' => 'A']]);
cursor = db.inventory.find({"instock": SON([("qty", 5), ("warehouse", "A")])})
client[:inventory].find(instock: { qty: 5, warehouse: 'A' } )
findObservable = collection.find(equal("instock", Document("qty" -> 5, "warehouse" -> "A")))

If you do not know the index position of the document nested in the array, concatenate the name of the array field, with a dot (.) and the name of the field in the nested document.

The following example selects all documents where the instock array has at least one embedded document that contains the field qty whose value is less than or equal to 20:

db.inventory.find( { 'instock.qty': { $lte: 20 } } )

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

{ 'instock.qty': { $lte: 20 } }
Query for embedded field matching single condition
mongoc_collection_t *collection;
bson_t *filter;
mongoc_cursor_t *cursor;
collection = mongoc_database_get_collection (db, "inventory");
filter = BCON_NEW (
"instock.qty", "{",
"$lte", BCON_INT64 (20),
"}");
cursor = mongoc_collection_find_with_opts (collection, filter, NULL, NULL);
var filter = Builders<BsonDocument>.Filter.Lte("instock.qty", 20);
var result = collection.Find(filter).ToList();
cursor, err := coll.Find(
context.TODO(),
bson.D{
{"instock.qty", bson.D{
{"$lte", 20},
}},
})
findPublisher = collection.find(lte("instock.qty", 20));
findIterable = collection.find(lte("instock.qty", 20));
val findFlow = collection
.find(lte("instock.qty", 20))
cursor = db.inventory.find({"instock.qty": {"$lte": 20}})
const cursor = db.collection('inventory').find({
'instock.qty': { $lte: 20 }
});
$cursor = $db->coll("inventory")->find( { 'instock.qty' => { '$lte' => 20 } } );
$cursor = $db->inventory->find(['instock.qty' => ['$lte' => 20]]);
cursor = db.inventory.find({"instock.qty": {"$lte": 20}})
client[:inventory].find('instock.qty' => { '$lte' => 20 })
findObservable = collection.find(lte("instock.qty", 20))

Using dot notation, you can specify query conditions for field in a document at a particular index or position of the array. The array uses zero-based indexing.

Note

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

The following example selects all documents where the instock array has as its first element a document that contains the field qty whose value is less than or equal to 20:

db.inventory.find( { 'instock.0.qty': { $lte: 20 } } )

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

{ 'instock.0.qty': { $lte: 20 } }
Query for array element matching single condition
mongoc_collection_t *collection;
bson_t *filter;
mongoc_cursor_t *cursor;
collection = mongoc_database_get_collection (db, "inventory");
filter = BCON_NEW (
"instock.0.qty", "{",
"$lte", BCON_INT64 (20),
"}");
cursor = mongoc_collection_find_with_opts (collection, filter, NULL, NULL);
var filter = Builders<BsonDocument>.Filter.Lte("instock.0.qty", 20);
var result = collection.Find(filter).ToList();
cursor, err := coll.Find(
context.TODO(),
bson.D{
{"instock.0.qty", bson.D{
{"$lte", 20},
}},
})
findPublisher = collection.find(lte("instock.0.qty", 20));
findIterable = collection.find(lte("instock.0.qty", 20));
val findFlow = collection
.find(lte("instock.0.qty", 20))
cursor = db.inventory.find({"instock.0.qty": {"$lte": 20}})
const cursor = db.collection('inventory').find({
'instock.0.qty': { $lte: 20 }
});
$cursor = $db->coll("inventory")->find( { 'instock.0.qty' => { '$lte' => 20 } } );
$cursor = $db->inventory->find(['instock.0.qty' => ['$lte' => 20]]);
cursor = db.inventory.find({"instock.0.qty": {"$lte": 20}})
client[:inventory].find('instock.0.qty' => { '$lte' => 20 })
findObservable = collection.find(lte("instock.0.qty", 20))

When specifying conditions on more than one field nested in an array of documents, you can specify the query such that either a single document meets these condition or any combination of documents (including a single document) in the array meets the conditions.

Use $elemMatch operator to specify multiple criteria on an array of embedded documents such that at least one embedded document satisfies all the specified criteria.

The following example queries for documents where the instock array has at least one embedded document that contains both the field qty equal to 5 and the field warehouse equal to A:

db.inventory.find( { "instock": { $elemMatch: { qty: 5, warehouse: "A" } } } )

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

{ "instock": { $elemMatch: { qty: 5, warehouse: "A" } } }
Query for single document matching multiple conditions
mongoc_collection_t *collection;
bson_t *filter;
mongoc_cursor_t *cursor;
collection = mongoc_database_get_collection (db, "inventory");
filter = BCON_NEW (
"instock", "{",
"$elemMatch", "{",
"qty", BCON_INT64 (5),
"warehouse", BCON_UTF8 ("A"),
"}",
"}");
cursor = mongoc_collection_find_with_opts (collection, filter, NULL, NULL);
var filter = Builders<BsonDocument>.Filter.ElemMatch<BsonValue>("instock", new BsonDocument { { "qty", 5 }, { "warehouse", "A" } });
var result = collection.Find(filter).ToList();
cursor, err := coll.Find(
context.TODO(),
bson.D{
{"instock", bson.D{
{"$elemMatch", bson.D{
{"qty", 5},
{"warehouse", "A"},
}},
}},
})
findPublisher = collection.find(elemMatch("instock", Document.parse("{ qty: 5, warehouse: 'A' }")));
findIterable = collection.find(elemMatch("instock", Document.parse("{ qty: 5, warehouse: 'A' }")));
val findFlow = collection
.find(elemMatch("instock", Document.parse("{ qty: 5, warehouse: 'A' }")))
cursor = db.inventory.find({"instock": {"$elemMatch": {"qty": 5, "warehouse": "A"}}})
const cursor = db.collection('inventory').find({
instock: { $elemMatch: { qty: 5, warehouse: 'A' } }
});
$cursor = $db->coll("inventory")->find(
{ instock => { '$elemMatch' => { qty => 5, warehouse => "A" } } }
);
$cursor = $db->inventory->find(['instock' => ['$elemMatch' => ['qty' => 5, 'warehouse' => 'A']]]);
cursor = db.inventory.find({"instock": {"$elemMatch": {"qty": 5, "warehouse": "A"}}})
client[:inventory].find(instock: { '$elemMatch' => { qty: 5,
warehouse: 'A' } })
findObservable = collection.find(elemMatch("instock", Document("qty" -> 5, "warehouse" -> "A")))

The following example queries for documents where the instock array has at least one embedded document that contains the field qty that is greater than 10 and less than or equal to 20:

db.inventory.find( { "instock": { $elemMatch: { qty: { $gt: 10, $lte: 20 } } } } )

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

{ "instock": { $elemMatch: { qty: { $gt: 10, $lte: 20 } } } }
Query for single document matching multiple conditions
mongoc_collection_t *collection;
bson_t *filter;
mongoc_cursor_t *cursor;
collection = mongoc_database_get_collection (db, "inventory");
filter = BCON_NEW (
"instock", "{",
"$elemMatch", "{",
"qty", "{",
"$gt", BCON_INT64 (10),
"$lte", BCON_INT64 (20),
"}",
"}",
"}");
cursor = mongoc_collection_find_with_opts (collection, filter, NULL, NULL);
var filter = Builders<BsonDocument>.Filter.ElemMatch<BsonValue>("instock", new BsonDocument { { "qty", new BsonDocument { { "$gt", 10 }, { "$lte", 20 } } } });
var result = collection.Find(filter).ToList();
cursor, err := coll.Find(
context.TODO(),
bson.D{
{"instock", bson.D{
{"$elemMatch", bson.D{
{"qty", bson.D{
{"$gt", 10},
{"$lte", 20},
}},
}},
}},
})
findPublisher = collection.find(elemMatch("instock", Document.parse("{ qty: { $gt: 10, $lte: 20 } }")));
findIterable = collection.find(elemMatch("instock", Document.parse("{ qty: { $gt: 10, $lte: 20 } }")));
val findFlow = collection
.find(elemMatch("instock", Document.parse("{ qty: { \$gt: 10, \$lte: 20 } }")))
cursor = db.inventory.find({"instock": {"$elemMatch": {"qty": {"$gt": 10, "$lte": 20}}}})
const cursor = db.collection('inventory').find({
instock: { $elemMatch: { qty: { $gt: 10, $lte: 20 } } }
});
$cursor = $db->coll("inventory") ->find(
{ instock => { '$elemMatch' => { qty => { '$gt' => 10, '$lte' => 20 } } } }
);
$cursor = $db->inventory->find(['instock' => ['$elemMatch' => ['qty' => ['$gt' => 10, '$lte' => 20]]]]);
cursor = db.inventory.find({"instock": {"$elemMatch": {"qty": {"$gt": 10, "$lte": 20}}}})
client[:inventory].find(instock: { '$elemMatch' => { qty: { '$gt' => 10,
'$lte' => 20 } } })
findObservable = collection.find(elemMatch("instock", Document("""{ qty: { $gt: 10, $lte: 20 } }""")))

If the compound query conditions on an array field do not use the $elemMatch operator, the query selects those documents whose array contains any combination of elements that satisfies the conditions.

For example, the following query matches documents where any document nested in the instock array has the qty field greater than 10 and any document (but not necessarily the same embedded document) in the array has the qty field less than or equal to 20:

db.inventory.find( { "instock.qty": { $gt: 10, $lte: 20 } } )

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

{ "instock.qty": { $gt: 10, $lte: 20 } }
Query quantity value within range
mongoc_collection_t *collection;
bson_t *filter;
mongoc_cursor_t *cursor;
collection = mongoc_database_get_collection (db, "inventory");
filter = BCON_NEW (
"instock.qty", "{",
"$gt", BCON_INT64 (10),
"$lte", BCON_INT64 (20),
"}");
cursor = mongoc_collection_find_with_opts (collection, filter, NULL, NULL);
var builder = Builders<BsonDocument>.Filter;
var filter = builder.And(builder.Gt("instock.qty", 10), builder.Lte("instock.qty", 20));
var result = collection.Find(filter).ToList();
cursor, err := coll.Find(
context.TODO(),
bson.D{
{"instock.qty", bson.D{
{"$gt", 10},
{"$lte", 20},
}},
})
findPublisher = collection.find(and(gt("instock.qty", 10), lte("instock.qty", 20)));
findIterable = collection.find(and(gt("instock.qty", 10), lte("instock.qty", 20)));
val findFlow = collection
.find(and(gt("instock.qty", 10), lte("instock.qty", 20)))
cursor = db.inventory.find({"instock.qty": {"$gt": 10, "$lte": 20}})
const cursor = db.collection('inventory').find({
'instock.qty': { $gt: 10, $lte: 20 }
});
$cursor = $db->coll("inventory")->find(
{ "instock.qty" => { '$gt' => 10, '$lte' => 20 } }
);
$cursor = $db->inventory->find(['instock.qty' => ['$gt' => 10, '$lte' => 20]]);
cursor = db.inventory.find({"instock.qty": {"$gt": 10, "$lte": 20}})
client[:inventory].find('instock.qty' => { '$gt' => 10, '$lte' => 20 })
findObservable = collection.find(and(gt("instock.qty", 10), lte("instock.qty", 20)))

The following example queries for documents where the instock array has at least one embedded document that contains the field qty equal to 5 and at least one embedded document (but not necessarily the same embedded document) that contains the field warehouse equal to A:

db.inventory.find( { "instock.qty": 5, "instock.warehouse": "A" } )

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

{ "instock.qty": 5, "instock.warehouse": "A" }
Query matching quantity and warehouse location
mongoc_collection_t *collection;
bson_t *filter;
mongoc_cursor_t *cursor;
collection = mongoc_database_get_collection (db, "inventory");
filter = BCON_NEW (
"instock.qty", BCON_INT64 (5),
"instock.warehouse", BCON_UTF8 ("A"));
cursor = mongoc_collection_find_with_opts (collection, filter, NULL, NULL);
var builder = Builders<BsonDocument>.Filter;
var filter = builder.And(builder.Eq("instock.qty", 5), builder.Eq("instock.warehouse", "A"));
var result = collection.Find(filter).ToList();
cursor, err := coll.Find(
context.TODO(),
bson.D{
{"instock.qty", 5},
{"instock.warehouse", "A"},
})
findPublisher = collection.find(and(eq("instock.qty", 5), eq("instock.warehouse", "A")));
findIterable = collection.find(and(eq("instock.qty", 5), eq("instock.warehouse", "A")));
val findFlow = collection
.find(and(eq("instock.qty", 5), eq("instock.warehouse", "A")))
cursor = db.inventory.find({"instock.qty": 5, "instock.warehouse": "A"})
const cursor = db.collection('inventory').find({
'instock.qty': 5,
'instock.warehouse': 'A'
});
$cursor = $db->coll("inventory")->find(
{ "instock.qty" => 5, "instock.warehouse" => "A" }
);
$cursor = $db->inventory->find(['instock.qty' => 5, 'instock.warehouse' => 'A']);
cursor = db.inventory.find({"instock.qty": 5, "instock.warehouse": "A"})
client[:inventory].find('instock.qty' => 5,
'instock.warehouse' => 'A')
findObservable = collection.find(and(equal("instock.qty", 5), equal("instock.warehouse", "A")))

The example in this section uses the sample training dataset. To learn how to load the sample dataset into your MongoDB Atlas deployment, see Load Sample Data.

To query an array of documents in MongoDB Atlas, follow these steps:

1
  1. If it is not already displayed, select the organization that contains your desired project from the Organizations menu in the navigation bar.

  2. If it is not already displayed, select your project from the Projects menu in the navigation bar.

  3. If the Clusters page is not already displayed, click Database in the sidebar.

2
  1. For the cluster that contains the sample data, click Browse Collections.

  2. In the left navigation pane, select the sample_training database.

  3. Select the grades collection.

3

Specify the query filter document in the Filter field. A query filter document uses query operators to specify search conditions.

Copy the following query filter document into the Filter search bar:

{"scores.type": "exam"}
4

This query filter returns all documents in the sample_training.grades collection that contain a subdocument in the scores array where type is set to exam. The full document, including the entire scores array, is returned. For more information on modifying the returned array, see Project Specific Array Elements in the Returned Array.

For additional query examples, see:

Back

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