資料結構
網路
RDBMS
作業系統
Java
MS Excel
iOS
HTML
CSS
Android
Python
C 程式設計
C++
C#
MongoDB
MySQL
Javascript
PHP
物理
化學
生物
數學
英語
經濟學
心理學
社會研究
時尚研究
法律研究MongoDB 聚合多個結果？
如需聚合多個結果，請在 MongoDB 中使用 $group。我們使用文件建立一個集合 −
> db.demo765.insertOne(
...
... {
... Name:"John",
... "Category":"ComputerScience",
... "SubjectName":"MongoDB",
... "Marks":75
... }
... );
{
"acknowledged" : true,
"insertedId" : ObjectId("5eb054525637cd592b2a4b01")
}
>
> db.demo765.insertOne(
... {
... Name:"John",
... "Category":"ComputerScience",
... "SubjectName":"MySQL",
... "Marks":85
... }
... );
{
"acknowledged" : true,
"insertedId" : ObjectId("5eb054525637cd592b2a4b02")
}
> db.demo765.insertOne(
... {
... Name:"Chris",
... "Category":"10th",
... "SubjectName":"Math",
... "Marks":98
... }
... );
{
"acknowledged" : true,
"insertedId" : ObjectId("5eb054535637cd592b2a4b03")
}使用 find() 方法顯示集合中的所有文件 −
> db.demo765.find();
這將會產生以下輸出 −
{ "_id" : ObjectId("5eb054525637cd592b2a4b01"), "Name" : "John", "Category" : "ComputerScience", "SubjectName" : "MongoDB", "Marks" : 75 }
{ "_id" : ObjectId("5eb054525637cd592b2a4b02"), "Name" : "John", "Category" : "ComputerScience", "SubjectName" : "MySQL", "Marks" : 85 }
{ "_id" : ObjectId("5eb054535637cd592b2a4b03"), "Name" : "Chris", "Category" : "10th", "SubjectName" : "Math", "Marks" : 98 }以下是聚合多個結果的查詢 −
> db.demo765.aggregate([
... { "$facet": {
... "ListOfName": [
... { "$group": {
... "_id": "$Name",
... "Marks": { "$sum": "$Marks" }
... }},
... { "$project": {
... "_id": false,
... "Name": "$_id",
... "Marks": 1
... }}
... ],
... "ListOfCategory": [
... { "$group": {
... "_id": "$Category",
... "Marks": { "$sum": "$Marks" }
... }},
... { "$project": {
... "_id": false,
... "Category": "$_id",
... "Marks": 1
... }}
... ]
... }}
... ]).pretty()這將會產生以下輸出 −
{
"ListOfName" : [
{
"Marks" : 98,
"Name" : "Chris"
},
{
"Marks" : 160,
"Name" : "John"
}
],
"ListOfCategory" : [
{
"Marks" : 98,
"Category" : "10th"
},
{
"Marks" : 160,
"Category" : "ComputerScience"
}
]
}
更新於： 01-7-2020
658 次瀏覽
廣告