Mongodb 中文文档
查询嵌入/嵌套文档
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:
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:
This page provides examples of query operations on embedded/nested documents using MongoDB Compass. The examples on this page use the inventory collection. Populate the inventory collection with the following documents:
[
{ 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.
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:
# 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"}])
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. To populate the inventory collection, run the following:
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' }")
));
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:
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'
}
]);
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:
$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',
],
]);
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:
# 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"}])
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. To populate the inventory collection, run the following:
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' }")
));
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:
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);
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:
# 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"
}
]
);
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:
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' }
])
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:
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()
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.
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, 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, 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.
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:
{ 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' }")));
const cursor = db.collection('inventory').find({
size: { 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")])})
FindPublisher<Document> findPublisher = collection.find(eq("size", Document.parse("{ 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")))
整个嵌入式文档上的相等匹配要求与指定的<value>文档进行“精确”匹配，包括字段 Sequences。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" } } )
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' }")));
const cursor = db.collection('inventory').find({
size: { 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")])})
findPublisher = collection.find(eq("size", Document.parse("{ 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")))
查询嵌套字段
要在嵌入/嵌套文档中的字段上指定查询条件，请使用dot notation("field.nestedField")。
Note
使用点符号查询时，该字段和嵌套字段必须在引号内。
在嵌套字段上指定相等匹配
以下示例选择嵌套在size字段中的字段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:
{ "size.uom": "in" }
cursor = db.inventory.find({"size.uom": "in"})
findIterable = collection.find(eq("size.uom", "in"));
const cursor = db.collection('inventory').find({
'size.uom': 'in'
});
$cursor = $db->inventory->find(['size.uom' => 'in']);
cursor = db.inventory.find({"size.uom": "in"})
findPublisher = collection.find(eq("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"))
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:
{ <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>), 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> }, ... }
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 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>))
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:
{ "size.h": { $lt: 15 } }
cursor = db.inventory.find({"size.h": {"$lt": 15}})
findIterable = collection.find(lt("size.h", 15));
const cursor = db.collection('inventory').find({
'size.h': { $lt: 15 }
});
$cursor = $db->inventory->find(['size.h' => ['$lt' => 15]]);
cursor = db.inventory.find({"size.h": {"$lt": 15}})
findPublisher = collection.find(lt("size.h", 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))
指定 AND 条件
以下查询选择嵌套字段h小于15，嵌套字段uom等于"in"且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:
{ "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")
));
const 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',
]);
cursor = db.inventory.find(
{"size.h": {"$lt": 15}, "size.uom": "in", "status": "D"})
findPublisher = collection.find(and(
lt("size.h", 15),
eq("size.uom", "in"),
eq("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")
))
其他查询教程
有关其他查询示例，请参见：