假设您的数据是这样的:
someCollection:
/* 1 */
{
"_id" : ObjectId("5dc9c61959f03a3d68cfb8d3"),"works" : []
}
/* 2 */
{
"_id" : ObjectId("5dc9c72e59f03a3d68cfd009"),"works" : [
{
"_id" : 123,"photoId" : ObjectId("5dc9c6ae59f03a3d68cfc584")
},{
"_id" : 456,"photoId" : ObjectId("5dc9c6b659f03a3d68cfc636")
}
]
}
照片集:
/* 1 */
{
"_id" : ObjectId("5dc9c6ae59f03a3d68cfc584"),"photo" : "yes"
}
/* 2 */
{
"_id" : ObjectId("5dc9c6b659f03a3d68cfc636"),"photo" : "no"
}
/* 3 */
{
"_id" : ObjectId("5dc9c6c259f03a3d68cfc714"),"photo" : "yesno"
}
猫鼬模式:
const photoSchema = new Schema({
_id: Schema.Types.ObjectId,photo: String,});
const someColSchema = new Schema({
_id: { type: Schema.Types.ObjectId },works: [{ _id: { type: Number },photoId: { type: Schema.Types.ObjectId,ref: 'photo' } }]
});
const someCol = mongoose.model('someCollection',someColSchema,'someCollection');
const photoCol = mongoose.model('photo',photoSchema,'photo');
代码:
1)使用猫鼬填充(Mongoose Populate):
let values = someCol.find({"works._id": 123},{_id: 0,'works.$': 1}).populate('works.photoId').lean(true).exec();
2)使用mongoDB的本机$ lookup(mongoDB $lookup):
someCol.aggregate([{ $match: { 'works._id': 123 } },{ $unwind: '$works' },{ $match: { 'works._id': 123 } },{
$lookup:
{
from: "photo",localField: "works.photoId",foreignField: "_id",as: "doc"
}
},{ $project: { _id: 0,doc: { $arrayElemAt: ["$doc",0] } } }])
两者的工作原理相似,在聚合中,我们正在$match
过滤给定的条件,而$unwind
展开包装工作数组,再次进行过滤以仅保留匹配过滤条件的数组中的值,然后做$lookup
来从其他集合中获取相应的文档。
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