查询嵌入式文档数组

在此页面上

查询嵌套在数组中的文档

在文档数组中的字段上指定查询条件
为文档数组指定多个条件
使用 MongoDB Atlas 查询文档数组
其他查询教程

您可以使用以下方法查询MongoDB中的文档：

您的编程语言的驱动程序。
MongoDB Atlas 用户界面。要了解更多信息，请参阅使用 MongoDB Atlas 查询文档阵列。
MongoDB Compass。

➤ 使用右上角的 Select your language（选择语言）下拉菜单，设置以下示例的语言或选择 MongoDB Compass。

此页面中的示例展示了在 mongosh 中使用 db.collection.find() 方法对嵌套文档数组执行查询操作。

此页面上的示例使用的是 inventory 集合。连接到 MongoDB 实例中的测试数据库，然后创建 inventory 集合：

本页面中的示例展示了使用 MongoDB Compass 对嵌套文档数组执行查询操作。

此页面上的示例使用的是 inventory 集合。连接到 MongoDB 实例中的测试数据库，然后创建 inventory 集合：

本页提供了使用 mongoc_collection_find_with_opts 对嵌套文档大量进行查询操作的示例。

此页面上的示例使用的是 inventory 集合。连接到 MongoDB 实例中的测试数据库，然后创建 inventory 集合：

本页提供了使用 MongoDB C# 驱动程序中的 MongoCollection.Find() 方法对嵌入/嵌套文档进行查询操作的示例。

此页面上的示例使用的是 inventory 集合。连接到 MongoDB 实例中的测试数据库，然后创建 inventory 集合：

本页面中的示例展示了使用 MongoDB Go Driver 中的 Collection.Find 函数对嵌套文档数组进行查询操作。

此页面上的示例使用的是 inventory 集合。连接到 MongoDB 实例中的测试数据库，然后创建 inventory 集合：

本页面中的示例展示了使用 MongoDB Java Reactive Streams 驱动程序中的 com.mongodb.reactivestreams.client.MongoCollection.find 方法对嵌套文档数组执行查询操作。

此页面上的示例使用的是 inventory 集合。连接到 MongoDB 实例中的测试数据库，然后创建 inventory 集合：

此页面中的示例展示了使用 MongoDB Java 同步驱动程序中的 com.mongodb.client.MongoCollection.find 方法对嵌套文档数组执行的查询操作。

提示

此驱动程序提供了 com.mongodb.client.model.Filters 辅助方法，以便于创建过滤器文档。此页面中的示例使用这些方法创建过滤器文档。

此页面上的示例使用的是 inventory 集合。连接到 MongoDB 实例中的测试数据库，然后创建 inventory 集合：

本页提供的示例展示了使用 MongoCollection.find() 对嵌套文档大量进行查询操作。MongoDB Kotlin协程驱动程序中的方法。

提示

此驱动程序提供了 com.mongodb.client.model.Filters 辅助方法，以便于创建过滤器文档。此页面中的示例使用这些方法创建过滤器文档。

此页面上的示例使用的是 inventory 集合。连接到 MongoDB 实例中的测试数据库，然后创建 inventory 集合：

此页面中的示例展示了使用 Motor 驱动程序中的 motor.motor_asyncio.AsyncIOMotorCollection.find 方法对嵌套文档数组执行查询操作。

此页面上的示例使用的是 inventory 集合。连接到 MongoDB 实例中的测试数据库，然后创建 inventory 集合：

本页面提供的示例展示使用 Collection.find() 方法在 MongoDB Node.js 驱动程序中对嵌套文档的数组执行查询操作。

此页面上的示例使用的是 inventory 集合。连接到 MongoDB 实例中的测试数据库，然后创建 inventory 集合：

本页面提供了使用 MongoDB Perl 驱动程序中的 MongoDB::Collection::find() 方法对嵌套文档数组进行查询操作的示例。

此页面上的示例使用的是 inventory 集合。连接到 MongoDB 实例中的测试数据库，然后创建 inventory 集合：

此页面中的示例展示了使用 MongoDB PHP 库中的 MongoDB\\Collection::find() 方法对嵌套文档的数组执行查询操作。

此页面上的示例使用的是 inventory 集合。连接到 MongoDB 实例中的测试数据库，然后创建 inventory 集合：

本页提供的示例展示了使用对嵌套文档大量执行查询操作pymongo.collection.Collection.find PyMongo Python驾驶员中的方法。

此页面上的示例使用的是 inventory 集合。连接到 MongoDB 实例中的测试数据库，然后创建 inventory 集合：

本页提供了使用 MongoDB Ruby 驱动程序中的 Mongo::Collection#find() 方法对嵌套文档数组进行查询操作的示例。

此页面上的示例使用的是 inventory 集合。连接到 MongoDB 实例中的测试数据库，然后创建 inventory 集合：

本页面提供的示例展示使用 Collection.find() 方法在 MongoDB Scala 驱动程序中执行查询操作。

此页面上的示例使用的是 inventory 集合。连接到 MongoDB 实例中的测试数据库，然后创建 inventory 集合：

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 } ] }
]

有关在 MongoDB Compass 中插入文档的说明，请参阅插入文档。

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()

查询嵌套在数组中的文档

以下示例选择 instock 数组中的元素与指定文档匹配的所有文档：

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

将以下过滤器复制到 Compass 查询栏中，然后单击 Find：

{ "instock": { warehouse: "A", qty: 5 } }

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)))

整个嵌入式/嵌套文档的相等匹配要求与指定文档精确匹配，包括字段顺序。例如，以下查询不匹配 inventory 集合中的任何文档：

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

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")))

在文档数组中的字段上指定查询条件

在文档数组中嵌入的字段上指定查询条件

如果您不知道嵌套在数组中的文档的索引位置，请使用点 (.) 来连接数组字段的名称以及嵌套文档中的字段名称。

以下示例选择满足下列条件的所有文档——instock 数组至少有一份嵌入式文档包含字段 qty 且其值小于或等于 20：

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

将以下过滤器复制到 Compass 查询栏中，然后单击 Find：

{ 'instock.qty': { $lte: 20 } }

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))

使用数组索引查询嵌入式文档中的字段

使用点符号，可以在数组的特定索引或位置为文档中的字段指定查询条件。该数组使用从零开始的索引。

注意

使用点符号查询时，字段和索引必须位于引号内。

以下示例选择所有满足如下条件的文档——instock 数组的第一个元素是包含值小于或等于 20 的 qty 字段的文档：

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

将以下过滤器复制到 Compass 查询栏中，然后单击 Find：

{ 'instock.0.qty': { $lte: 20 } }

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))

为文档数组指定多个条件

对嵌套在文档数组中的多个字段指定条件时，可指定查询，以使单个文档满足这些条件，或使数组中任意文档（包括单个文档）的组合满足这些条件。

单个嵌套文档满足嵌套字段的多个查询条件

使用 $elemMatch 操作符在大量嵌入式文档中指定多个条件，以使至少一个嵌入式文档满足所有指定条件。

以下示例查询满足如下条件的文档——instock 数组至少有一份嵌入式文档，该文档同时包含等于 5 的字段 qty 和等于 A 的字段 warehouse：

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

将以下过滤器复制到 Compass 查询栏中，然后单击 Find：

{ "instock": { $elemMatch: { qty: 5, warehouse: "A" } } }

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")))

以下示例将查询 instock 数组至少包含一个嵌入文档，且该文档包含大于 qty 且小于或等于 20 的字段 10：

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

将以下过滤器复制到 Compass 查询栏中，然后单击 Find：

{ "instock": { $elemMatch: { qty: { $gt: 10, $lte: 20 } } } }

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 } }""")))

组合满足标准的元素

如果数组字段上的复合查询条件没有使用 $elemMatch 操作符，则查询会选择如下文档：数组中包含满足条件的任意元素的组合。

例如，以下查询匹配如下文档：嵌套在 instock 数组内的任何文档的 qty 字段大于 10 且该数组中的任何文档（不一定是同一份嵌入式文档）的 qty 字段小于或等于 20：

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

将以下过滤器复制到 Compass 查询栏中，然后单击 Find：

{ "instock.qty": { $gt: 10,  $lte: 20 } }

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)))

以下示例查询符合以下条件的文档 — instock 数组至少有一个包含等于 5 的字段 qty 的嵌入式文档，以及至少一个包含等于 A 的字段 warehouse 的嵌入式文档（但不一定是同一个嵌入式文档）：

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

将以下过滤器复制到 Compass 查询栏中，然后单击 Find：

{ "instock.qty": 5, "instock.warehouse": "A" }

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")))

使用 MongoDB Atlas 查询文档数组

本节中的示例使用示例训练数据集。要了解如何将示例数据集加载到您的 MongoDB Atlas 部署中，请参阅加载示例数据。

要在 MongoDB Atlas 中查询文档数组，请按照以下步骤操作：

在MongoDB Atlas用户界面中，转到项目的Clusters 页面。

如果尚未显示，请从导航栏上的 Organizations 菜单中选择包含所需项目的组织。
如果尚未显示，请从导航栏的 Projects 菜单中选择您的项目。
如果尚未显示，请单击侧边栏中的Clusters 。
会显示集群页面。

导航至集合

对于包含样本数据的集群，单击Browse Collections 。
在左侧导航窗格中，选择 sample_training 数据库。
选择 grades 集合。

指定筛选器字段

在 Filter 字段中指定查询筛选器文档。查询筛选器文档使用查询运算符来指定搜索条件。

将以下查询筛选器文档复制到 Filter 搜索栏：

{"scores.type": "exam"}

单击 Apply

此查询过滤器返回 sample_training.grades 集合中包含 scores 数组中子文档的所有文档，其中 type 设置为 exam。将返回包括整个 scores 数组在内的完整文档。有关修改返回数组的更多信息，请参阅已返回数组中特定于项目的数组元素。

其他查询教程

有关其他查询示例，请参阅：

后退

数组

来年

项目成果