通过实例讲清楚MongoDB九种聚合操作

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 · 2022-07-06


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1 文章概述

1.1 基本概念

MongoDB是一种非关系型数据库,数据最终存储为BSON(Binary JSON)类型。MongoDB包含三个重要逻辑概念:数据库、集合和文档,与关系型数据库相关概念映射如下图:



1.2 数据准备

1.2.1 逻辑设计

bookdb数据库包含library与book两个集合,相关字段说明如下图:



1.2.2 新增数据

// 创建数据库
use bookdb

// 新增图书馆
db.library.insertMany([
{
"_id": 1,
"library_name": "图书馆_1"
},
{
"_id": 2,
"library_name": "图书馆_2"
},
{
"_id": 3,
"library_name": "图书馆_3"
}
])

// 新增图书
db.book.insertMany([
{
"_id": 1,
"book_type": 1,
"book_name": "图书_1",
"book_price": 10,
"book_count": 100,
"borrowers": [{
"name": "张三",
"id": 100
}, {
"name": "李四",
"id": 200
}],
"library_id": 1
},
{
"_id": 2,
"book_type": 2,
"book_name": "图书_2",
"book_price": 20,
"book_count": 100,
"borrowers": [{
"name": "张三",
"id": 100
}],
"library_id": 2
},
{
"_id": 3,
"book_type": 1,
"book_name": "图书_3",
"book_price": 30,
"book_count": 100,
"borrowers": [{
"name": "张三",
"id": 100
}, {
"name": "王五",
"id": 300
}],
"library_id": 2
}
])

2 聚合概念

2.1 基本语法

MongoDB聚合语法第一个参数是管道:文档在上个管道处理完后传递给下个管道,第二个参数是选项:设置聚合操作特性

db.collection.aggregate(pipeline, options)


2.2 聚合管道

常用聚合管道有以下九种类型:

$project:对文档进行投影

$limit:输出管道内前N个文档

$skip:跳过管道内前N个文档

$sort:对文档进行排序

$out:输出管道中文档

$match:对文档进行筛选

$unwind:铺平文档中的数组字段

$lookup:对文档进行查询

$group:对文档进行分组


3 聚合实例

3.1 project

1表示展示某字段

0表示不展示某字段

借阅人编号和姓名拆分成两个数组

db.book.aggregate({
$project: {
"_id": 0,
"book_name": 1,
"borrowerIds": "$borrowers.id",
"borrowerNames": "$borrowers.name"
}
})

---------------------------------------------------------

// 1
{
"book_name": "图书_1",
"borrowerIds": [
100,
200
],
"borrowerNames": [
"张三",
"李四"
]
}

// 2
{
"book_name": "图书_2",
"borrowerIds": [
100
],
"borrowerNames": [
"张三"
]
}

// 3
{
"book_name": "图书_3",
"borrowerIds": [
100,
300
],
"borrowerNames": [
"张三",
"王五"
]
}

3.2 limit

只展示一个投影结果

db.book.aggregate([
{
$project: {
"_id": 0,
"book_name": 1,
"borrowerIds": "$borrowers.id",
"borrowerNames": "$borrowers.name"
}
},
{
$limit: 1
}
])

---------------------------------------------------------

// 1
{
"book_name": "图书_1",
"borrowerIds": [
100,
200
],
"borrowerNames": [
"张三",
"李四"
]
}

3.3 skip

跳过一个且只展示一个投影结果

db.book.aggregate([
{
$project: {
"_id": 0,
"book_name": 1,
"borrowerIds": "$borrowers.id",
"borrowerNames": "$borrowers.name"
}
},
{
$skip: 1
},
{
$limit: 1
}
])

---------------------------------------------------------

// 1
{
"book_name": "图书_2",
"borrowerIds": [
100
],
"borrowerNames": [
"张三"
]
}

3.4 sort

db.book.aggregate([
{
$project: {
"_id": 1,
"book_name": 1,
"library_id": 1
}
},
{
$sort: {
"library_id": - 1, // 降序
"_id": 1 // 升序
}
}
])

---------------------------------------------------------

// 1
{
"_id": 2,
"book_name": "图书_2",
"library_id": 2
}

// 2
{
"_id": 3,
"book_name": "图书_3",
"library_id": 2
}

// 3
{
"_id": 1,
"book_name": "图书_1",
"library_id": 1
}

MongoDB内存排序有100M限制,如果排序数据过多需要设置选项allowDiskUse=true,表示数据可以写入临时文件进行排序

db.book.aggregate([
{
$project: {
"_id": 1,
"book_name": 1,
"library_id": 1
}
},
{
$sort: {
"library_id": - 1,
"_id": 1
}
}
], {
allowDiskUse: true
})

3.5 out

投影结果输出到新集合

db.book.aggregate([
{
$project: {
"_id": 0,
"book_name": 1,
"borrowerIds": "$borrowers.id",
"borrowerNames": "$borrowers.name"
}
},
{
$out: "newCollection"
}
])

db.newCollection.find()

---------------------------------------------------------

// 1
{
"_id": ObjectId("62bec0636f9c37787b9590b9"),
"book_name": "图书_1",
"borrowerIds": [
100,
200
],
"borrowerNames": [
"张三",
"李四"
]
}

// 2
{
"_id": ObjectId("62bec0636f9c37787b9590ba"),
"book_name": "图书_2",
"borrowerIds": [
100
],
"borrowerNames": [
"张三"
]
}

// 3
{
"_id": ObjectId("62bec0636f9c37787b9590bb"),
"book_name": "图书_3",
"borrowerIds": [
100,
300
],
"borrowerNames": [
"张三",
"王五"
]
}

3.6 match

where book_name = xxx

db.book.aggregate([
{
$match: {
"book_name": "图书_2"
}
},
{
$project: {
"_id": 1,
"book_name": 1,
"library_id": 1
}
}
])

---------------------------------------------------------

// 1
{
"_id": 2,
"book_name": "图书_2",
"library_id": 2
}

where library_id = 2 and price > 15

db.book.aggregate([
{
$match: {
$and: [
{
"library_id": 2
},
{
"book_price": {
$gt: 25
}
}
]
}
},
{
$project: {
"_id": 1,
"book_name": 1,
"library_id": 1,
"book_price": 1
}
}
])

---------------------------------------------------------

// 1
{
"_id": 3,
"book_name": "图书_3",
"book_price": 30,
"library_id": 2
}

3.7 unwind

文档按照借阅人数组铺平

includeArrayIndex表示索引

db.book.aggregate([
{
$unwind: {
path: "$borrowers",
includeArrayIndex: "idx"
}
}
])

---------------------------------------------------------

// 1
{
"_id": 1,
"book_type": 1,
"book_name": "图书_1",
"book_price": 10,
"book_count": 100,
"borrowers": {
"name": "张三",
"id": 100
},
"library_id": 1,
"idx": NumberLong("0")
}

// 2
{
"_id": 1,
"book_type": 1,
"book_name": "图书_1",
"book_price": 10,
"book_count": 100,
"borrowers": {
"name": "李四",
"id": 200
},
"library_id": 1,
"idx": NumberLong("1")
}

// 3
{
"_id": 2,
"book_type": 2,
"book_name": "图书_2",
"book_price": 20,
"book_count": 100,
"borrowers": {
"name": "张三",
"id": 100
},
"library_id": 2,
"idx": NumberLong("0")
}

// 4
{
"_id": 3,
"book_type": 1,
"book_name": "图书_3",
"book_price": 30,
"book_count": 100,
"borrowers": {
"name": "张三",
"id": 100
},
"library_id": 2,
"idx": NumberLong("0")
}

// 5
{
"_id": 3,
"book_type": 1,
"book_name": "图书_3",
"book_price": 30,
"book_count": 100,
"borrowers": {
"name": "王五",
"id": 300
},
"library_id": 2,
"idx": NumberLong("1")
}

3.8 lookup

查询图书馆有哪些图书

lookup可以实现连表查询

MongoDB 3.4之前聚合语法:

  • from:待关联集合【book】

  • localField: 本集合关联键【library】

  • foreignField:待关联键【book】

  • as:待关联集合数据【book】

db.library.aggregate([
{
$lookup:
{
from: "book",
localField: "_id",
foreignField: "library_id",
as: "books_info"
}
}
])

---------------------------------------------------------

// 1
{
"_id": 1,
"library_name": "图书馆_1",
"books_info": [
{
"_id": 1,
"book_type": 1,
"book_name": "图书_1",
"book_price": 10,
"book_count": 100,
"borrowers": [
{
"name": "张三",
"id": 100
},
{
"name": "李四",
"id": 200
}
],
"library_id": 1
}
]
}

// 2
{
"_id": 2,
"library_name": "图书馆_2",
"books_info": [
{
"_id": 2,
"book_type": 2,
"book_name": "图书_2",
"book_price": 20,
"book_count": 100,
"borrowers": [
{
"name": "张三",
"id": 100
}
],
"library_id": 2
},
{
"_id": 3,
"book_type": 1,
"book_name": "图书_3",
"book_price": 30,
"book_count": 100,
"borrowers": [
{
"name": "张三",
"id": 100
},
{
"name": "王五",
"id": 300
}
],
"library_id": 2
}
]
}

// 3
{
"_id": 3,
"library_name": "图书馆_3",
"books_info": [ ]
}

MongoDB 3.4之后聚合语法:

  • from:待关联集合【book】

  • let:声明本集合字段在管道使用

  • pipeline:操作管道

db.library.aggregate([
{
$lookup:
{
from: "book",
let: {
"lid": "$_id"
},
pipeline: [
{
$match: {
$expr: {
$and: [
{
$eq: ["$$lid", "$library_id"]
}
]
}
}
}
],
as: "books_info"
}
}
])

---------------------------------------------------------

// 1
{
"_id": 1,
"library_name": "图书馆_1",
"books_info": [
{
"_id": 1,
"book_type": 1,
"book_name": "图书_1",
"book_price": 10,
"book_count": 100,
"borrowers": [
{
"name": "张三",
"id": 100
},
{
"name": "李四",
"id": 200
}
],
"library_id": 1
}
]
}

// 2
{
"_id": 2,
"library_name": "图书馆_2",
"books_info": [
{
"_id": 2,
"book_type": 2,
"book_name": "图书_2",
"book_price": 20,
"book_count": 100,
"borrowers": [
{
"name": "张三",
"id": 100
}
],
"library_id": 2
},
{
"_id": 3,
"book_type": 1,
"book_name": "图书_3",
"book_price": 30,
"book_count": 100,
"borrowers": [
{
"name": "张三",
"id": 100
},
{
"name": "王五",
"id": 300
}
],
"library_id": 2
}
]
}

// 3
{
"_id": 3,
"library_name": "图书馆_3",
"books_info": [ ]
}

新增价格大于20查询条件

db.library.aggregate([
{
$lookup:
{
from: "book",
let: {
"lid": "$_id"
},
pipeline: [
{
$match: {
$expr: {
$and: [
{
$eq: ["$$lid", "$library_id"]
},
{
$gt: ["$book_price", 20]
}
]
}
}
}
],
as: "books_info"
}
}
])

---------------------------------------------------------

// 1
{
"_id": 1,
"library_name": "图书馆_1",
"books_info": [ ]
}

// 2
{
"_id": 2,
"library_name": "图书馆_2",
"books_info": [
{
"_id": 3,
"book_type": 1,
"book_name": "图书_3",
"book_price": 30,
"book_count": 100,
"borrowers": [
{
"name": "张三",
"id": 100
},
{
"name": "王五",
"id": 300
}
],
"library_id": 2
}
]
}

// 3
{
"_id": 3,
"library_name": "图书馆_3",
"books_info": [ ]
}

3.9 group

3.9.1 简单统计

_id:图书类型作为分组键

count:每个类型有多少种书

db.book.aggregate([
{
$group: {
_id: "$book_type",
count: {
$sum: 1
}
}
}
])

---------------------------------------------------------

// 1
{
"_id": 2,
"count": 1
}

// 2
{
"_id": 1,
"count": 2
}

3.9.2 复杂统计

_id:图书类型作为分组键

type_count:每个类型有多少种书

type_book_count:每个类型有多少本书

minTotalPrice:每个类型总价最小值

maxTotalPrice:每个类型总价最大值

totalPrice:每个类型总价

avgPrice:每个类型平均价

db.book.aggregate([
{
$group: {
_id: "$book_type",
type_count: {
$sum: 1
},
type_book_count: {
$sum: "$book_count"
},
minTotalPrice: {
$min: {
$multiply: ["$book_price", "$book_count"]
}
},
maxTotalPrice: {
$max: {
$multiply: ["$book_price", "$book_count"]
}
},
totalPrice: {
$sum: {
$multiply: ["$book_price", "$book_count"]
}
},
avgPrice: {
$avg: "$book_price"
}
}
}
])

---------------------------------------------------------

// 1
{
"_id": 2,
"type_count": 1,
"type_book_count": 100,
"minTotalPrice": 2000,
"maxTotalPrice": 2000,
"totalPrice": 2000,
"avgPrice": 20
}

// 2
{
"_id": 1,
"type_count": 2,
"type_book_count": 200,
"minTotalPrice": 1000,
"maxTotalPrice": 3000,
"totalPrice": 4000,
"avgPrice": 20
}

3.9.3 空分组键

_id:空分组键表示统计全量数据

db.book.aggregate([
{
$group: {
_id: null,
type_count: {
$sum: 1
},
type_book_count: {
$sum: "$book_count"
},
minTotalPrice: {
$min: {
$multiply: ["$book_price", "$book_count"]
}
},
maxTotalPrice: {
$max: {
$multiply: ["$book_price", "$book_count"]
}
},
totalPrice: {
$sum: {
$multiply: ["$book_price", "$book_count"]
}
},
avgPrice: {
$avg: "$book_price"
}
}
}
])

---------------------------------------------------------

// 1
{
"_id": null,
"type_count": 3,
"type_book_count": 300,
"minTotalPrice": 1000,
"maxTotalPrice": 3000,
"totalPrice": 6000,
"avgPrice": 20
}

4 文章总结

第一介绍了MongoDB与关系型数据库关系,并且准备本文需要的测试数据,第二介绍了聚合语法和聚合管道相关概念,第三通过实例介绍了如何使用聚合操作,希望本文对大家有所帮助。



JAVA前线 


欢迎大家关注公众号「JAVA前线」查看更多精彩分享,主要内容包括源码分析、实际应用、架构思维、职场分享、产品思考等等,同时也非常欢迎大家加我微信「java_front」一起交流学习


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