Query on Embedded/Nested Documents嵌入式/嵌套文档查询

选择语言

On this page本页内容

➤ Use the Select your language drop-down menu in the upper-right to set the language of the examples on this page.使用右上角的选择语言下拉菜单设置此页面上示例的语言。

This page provides examples of query operations on embedded/nested documents using the db.collection.find() method in mongosh. 本页提供了使用mongosh中的db.collection.find()方法对嵌入/嵌套文档执行查询操作的示例。The examples on this page use the inventory collection. 本页上的示例使用inventory集合。To populate the inventory collection, run the following:要填充inventory集合，请运行以下命令：

This page provides examples of query operations on embedded/nested documents using MongoDB Compass. 本页提供了使用MongoDB Compass对嵌入式/嵌套文档进行查询操作的示例。The examples on this page use the inventory collection. 本页上的示例使用inventory集合。Populate the inventory collection with the following documents:使用以下文档填充inventory集合：

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 Collection.Find function in the MongoDB Go Driver. 本页提供了使用MongoDB Go Driver中的Collection.Find函数对嵌入式/嵌套文档执行查询操作的示例。The examples on this page use the inventory collection. To populate the inventory collection, run the following:要填充inventory集合，请运行以下命令：

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. 本页上的示例使用inventory集合。To populate the inventory collection, run the following:要填充inventory集合，请运行以下命令：

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提示

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 motor.motor_asyncio.AsyncIOMotorCollection.find method in the Motor 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 Node.js Driver. 本页提供了使用MongoDB Node.js驱动程序中的Collection.find()方法对嵌入式/嵌套文档执行查询操作的示例。The examples on this page use the inventory collection. 本页上的示例使用inventory集合。To populate the inventory collection, run the following:要填充inventory集合，请运行以下命令：

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 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 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 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:您可以在下面的web shell中运行该操作：

[
    { "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.有关在MongoDB Compass中插入文档的说明，请参阅插入文档。

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匹配嵌入/嵌套文档

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.要在嵌入/嵌套文档的字段上指定相等条件，请使用查询筛选器文档{ <field>: <value> }，其中<value>是要匹配的文档。

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.要在嵌入/嵌套文档的字段上指定相等条件，请使用查询筛选器文档{ <field>: <value> }，其中<value>是要匹配的文档。

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.要在嵌入/嵌套文档的字段上指定相等条件，请使用查询筛选器文档{ <field>: <value> }，其中<value>是要匹配的文档。

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.要在嵌入/嵌套文档的字段上指定相等条件，请使用查询筛选器文档[ <field> => <value> ]，其中<value>是要匹配的文档。

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" }:例如，以下查询选择字段size等于文档{ h: 14, w: 21, uom: "cm" }的所有文档：

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

Copy the following filter into the Compass query bar and click Find:将以下筛选器复制到Compass查询栏中，然后单击“查找”：

{ size: { h: 14, w: 21, uom: "cm" } }
Query embedded field
click to enlarge
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. 整个嵌入文档上的相等匹配要求与指定的<value>文档完全匹配，包括字段顺序。For example, the following query does not match any documents in the inventory collection:例如，以下查询与inventory集合中的任何文档都不匹配：

db.inventory.find(  { size: { w: 21, h: 14, uom: "cm" } }  )
Query embedded field
click to enlarge
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嵌套字段查询

To specify a query condition on fields in an embedded/nested document, use dot notation ("field.nestedField").要在嵌入/嵌套文档中的字段上指定查询条件，请使用点符号（"field.nestedField"）。

Note注意

When querying using dot notation, the field and nested field must be inside quotation marks.使用点表示法进行查询时，字段和嵌套字段必须在引号内。

Specify Equality Match on a Nested Field在嵌套字段上指定相等匹配

The following example selects all documents where the field uom nested in the size field equals "in":以下示例选择size字段中嵌套字段uom等于"in"的所有文档：

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

Copy the following filter into the Compass query bar and click Find:将以下筛选器复制到Compass查询栏中，然后单击“查找”：

{ "size.uom": "in" }
Query single nested field
click to enlarge
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.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使用查询运算符指定匹配

A query filter document can use the query operators to specify conditions in the following form:查询筛选文档可以使用查询运算符以以下形式指定条件：

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

A query filter document can use the query operators to specify conditions in the following form:查询筛选文档可以使用查询运算符以以下形式指定条件：

{ <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: 查询筛选文档可以使用查询运算符以以下形式指定条件：

{ <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 ($lt) on the field h embedded in the size field:以下查询在size字段中嵌入的字段h上使用小于运算符（$lt）：

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

Copy the following filter into the Compass query bar and click Find:将以下筛选器复制到Compass查询栏中，然后单击“查找”：

{ "size.h": { $lt: 15 } }
Query single nested field
click to enlarge
var filter = Builders<BsonDocument>.Filter.Lt("size.h", 15);
var result = collection.Find(filter).ToList();
cursor, err := coll.Find(
	context.TODO(),
	bson.D{
		{"size.h", bson.D{
			{"$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指定AND条件

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":以下查询选择嵌套字段h小于15、嵌套字段uom等于"in"、status字段等于"D"的所有文档：

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

Copy the following filter into the Compass query bar and click Find:将以下筛选器复制到Compass查询栏中，然后单击“查找”：

{ "size.h": { $lt: 15 }, "size.uom": "in", status: "D" }
Query multiple nested fields
click to enlarge
var builder = Builders<BsonDocument>.Filter;
var filter = builder.And(builder.Lt("size.h", 15), builder.Eq("size.uom", "in"), builder.Eq("status", "D"));
var result = collection.Find(filter).ToList();
cursor, err := coll.Find(
	context.TODO(),
	bson.D{
		{"size.h", bson.D{
			{"$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其他查询教程

For additional query examples, see:有关其他查询示例，请参阅：

←  Query DocumentsQuery an Array →