为此,请在MongoDB中使用$project。在其中,使用$filter。让我们创建一个包含文档的集合-
> db.demo457.insertOne( ... { ... _id: 101, ... details: [ ... { ProductName:"Product-1" , ProductPrice:90 }, ... { ProductName:"Product-2" , ProductPrice:190 } ... ] ... } ... ); { "acknowledged" : true, "insertedId" : 101 } > > db.demo457.insertOne( ... { ... _id: 102, ... details: [ ... { ProductName:"Product-3" , ProductPrice:150}, ... { ProductName:"Product-4" , ProductPrice:360 } ... ] ... } ... ); { "acknowledged" : true, "insertedId" : 102 }
在find()方法的帮助下显示集合中的所有文档-
> db.demo457.find();
这将产生以下输出-
{ "_id" : 101, "details" : [ { "ProductName" : "Product-1", "ProductPrice" : 90 }, { "ProductName" : "Product-2", "ProductPrice" : 190 } ] } { "_id" : 102, "details" : [ { "ProductName" : "Product-3", "ProductPrice" : 150 }, { "ProductName" : "Product-4", "ProductPrice" : 360 } ] }
以下是查询使用MongoDB返回带有过滤的子文档的文档-
> db.demo457.aggregate([ ... { ... $project: { ... details: { ... $filter: { ... input: "$details", ... as: "output", ... cond: { $gte: [ "$$output.ProductPrice", 170 ] } ... } ... } ... } ... } ... ])
这将产生以下输出-
{ "_id" : 101, "details" : [ { "ProductName" : "Product-2", "ProductPrice" : 190 } ] } { "_id" : 102, "details" : [ { "ProductName" : "Product-4", "ProductPrice" : 360 } ] }