MongoDB数据库入门到精通看这一篇就够了

文章目录

一、MongoDB简介

1、MongoDB介绍

MongoDB是为快速开发互联网Web应用而设计的数据库系统。

MongoDB的设许目标是极简、灵活、作为Web应用栈的一部分。

MongoDB的数据模型是面向文档的, 所谓文档是一种类似于JSON的结构，简单理解MongoDB这个数据库中存的是各种各样的JSON。( BSON )

2、MongoDB中三个概念

数据库( database )：数据库是一个仓库，在仓库中可以存放集合。

集合( collection )：集合类似于数组，在集合中可以存放文档。

文档( document )：文档数据库中的最小单位,我们存储和操作的内容都是文档。

3、MongoDB优势

易扩展： NoSQL数据库种类繁多， 但是⼀个共同的特点都是去掉关系数据库的关系型特性。 数据之间⽆关系， 这样就⾮常容易扩展

⼤数据量， ⾼性能： NoSQL数据库都具有⾮常⾼的读写性能， 尤其在⼤数据量下， 同样表现优秀。 这得益于它的⽆关系性， 数据库的结构简单

灵活的数据模型： NoSQL⽆需事先为要存储的数据建⽴字段， 随时可以存储⾃定义的数据格式。 ⽽在关系数据库⾥， 增删字段是⼀件⾮常麻烦的事情。 如果是⾮常⼤数据量的表， 增加字段简直就是⼀个噩梦

二、环境搭建

1、下载

官网下载地址：https://www.mongodb.com/try/download


注意：在MongoDB版本的版本偶数版为稳定版通常用于生产环境，如3.2.x、3.4.x、3.6.x，奇数版本为开发版本：3.1.x、3.3.x、3.5.x表示开发版

2、安装

点击开始安装

3、安装失败问题解决

在安装MongoDB数据库的时候，有可能出现安装速度较慢，然后取消安装以后，再一次重新去安装的时候，在安装的最后一步可能会出现无法启动服务的现象

这种情况直接点击Ignore，完成安装以后

以管理员身份运行命令行窗口，使用该命令将MongDB服务删除掉

sc delete MongoDB

删除以后我们自己在

data

目录下创建一个

db文件夹

；

log目录

下创建一个

MongoDB.log

文件，如下：

重新装一个MongoDB服务就可以了，在安装目录的bin中打开控制台窗口输入命令：

mongod --dbpath=F:\mongodb\data\db  --logpath=F:\mongodb\log\MongoDB.log --install --serviceName "MongoDB"

注意：第一个路径表示的是数据存放地址；第二个路径表示日志存放文件
如图所示：

再输入

net start MongoDB

启动服务

执行结果如下图：

设置环境变量

设置完毕后，需要重启一下电脑
在cmd控制输入，

mongod -version

，出现版本号表示安装成功

4、启动

cmd控制输出：

mongo

回车，出现大于符号表示进入MongoDB数据库了

5、图形化工具

1）下载

官网下载地址（英文版，试用14天）：https://www.mongodbmanager.com/download （ 傻瓜式安装，一路next到完成即可）

2）连接客户端

1、确保mongodb已经启动

2、如果没有特别设置账户权限，默认情况下无需修改新建连接信息

3）基本操作

1、点击

+

展开数据库集合

2、输入sql语句

3、操作集合

4、集合其他操作

选择集合并右击

三、基础入门

1、基础命令

• 查看所有的数据库：show dbs /show databases
• 切换数据库：use db_name
• 查看使用当前的数据库：db
• 删除当前的数据库：db.dropDatabase()
• 查看数据库中所有集合（表）：show collections
• 查看指定集合下所有文档（JSON数据）：db.集合名称.find()

2、集合命令

不手动创建集合：向不存在的集合中第⼀次加⼊数据时， 集合会被创建出来

手动创建结合：

• db.createCollection(name,options)
• db.createCollection("stu")
• db.createCollection("sub", { capped : true, size : 10 } )
• 参数capped： 默认值为false表示不设置上限,值为true表示设置上限
• 参数size： 当capped值为true时， 需要指定此参数， 表示上限⼤⼩,当⽂档达到上限时， 会将之前的数据覆盖， 单位为字节

查看集合：

show collections

删除集合：

db.集合名称.drop()

3、数据类型

数据类型介绍Object ID⽂档IDString字符串， 最常⽤， 必须是有效的UTF-8Boolean存储⼀个布尔值， true或falseInteger整数可以是32位或64位， 这取决于服务器Double存储浮点值Arrays数组或列表， 多个值存储到⼀个键Object⽤于嵌⼊式的⽂档， 即⼀个值为⼀个⽂档 Null存储Null值Timestamp时间戳， 表示从1970-1-1到现在的总秒数Date存储当前⽇期或时间的UNIX时间格式

4、注意点

创建⽇期语句如下 ：参数的格式为YYYY-MM-DD

new Date('2017-12-20')

**每个⽂档都有⼀个属性， 为

_id

， 保证每个⽂档的唯⼀性**

可以⾃⼰去设置_id插⼊⽂档，如果没有提供， 那么MongoDB为每个⽂档提供了⼀个独特的_id， 类型为objectID

objectID是⼀个12字节的⼗六进制数：

• 前4个字节为当前时间戳
• 接下来3个字节的机器ID
• 接下来的2个字节中MongoDB的服务进程id
• 最后3个字节是简单的增量值

5、插入数据

语法如下：

• db.集合名称.insert(JSON对象)
• 插入1条数据：db.集合名称.insertOne(JSON对象)
• 插入多条数据：db.集合名称.insertMany([JSON 1，JSON 2，JSON 3，...JSON n])
• 指定_id参数：db.集合名称.insert({_id:"001", name:"gj", gender:1})

注意：

• 插入数据时不需要专门去创建集合(表)，因为插入数据时会自动创建集合
• 插⼊⽂档时， 如果不指定_id参数， MongoDB会为⽂档分配⼀个唯⼀的ObjectId
• 如果⽂档的_id已经存在则报错

案例：

// 插入1条数据
db.test001.insert({name: "张三", age: 18, sex: "男", hobby: "美女"});

db.test001.insertOne({name: "张三", age: 18, sex: "男", hobby: "美女"});// 插入多条数据
db.test001.insertMany([
    {name: "张三", age: 18, sex: "男", hobby: "美女"},
    {name: "李四", age: 20, sex: "男", hobby: "跑车"},
    {name: "王五", age: 21, sex: "男", hobby: "黑丝"},]);

6、简单查询

查看当前集合所有数据（json文件）

格式：

db.集合名称.find()

案例：

> db.test001.find()
{ "_id" : ObjectId("62177e62cec136e6f853bbe9"),"name" : "张三","age" : 18,"sex" : "男","hobby" : "美女" }
{ "_id" : ObjectId("62177e62cec136e6f853bbea"),"name" : "李四","age" : 20,"sex" : "男","hobby" : "跑车" }
{ "_id" : ObjectId("62177e62cec136e6f853bbeb"),"name" : "王五","age" : 21,"sex" : "男","hobby" : "黑丝" }

7、保存数据

格式：

db.集合名称.save(document)

注意：如果⽂档的_id已经存在则修改， 如果⽂档的_id不存在则添加

案例：

8、修改数据

语法格式：

• db.集合名称.update(<query> ,<update>,{multi: <boolean>})
• 更新一条（字段全部替换）：db.集合名称.update({name:'原始数据'},{name:'修改后数据'})
• 更新一条（仅更新一个字段）：db.集合名称.update({name:'原始数据'},{$set:{name:'修改后数据'}}) ，推荐使用
• 更新全部：db.集合名称.update({name:'原始数据'},{$set:{name:'修改后数据'}},{multi:true})
• 参数query：查询条件
• 参数update：更新操作符
• 参数multi：可选， 默认是false，表示只更新找到的第⼀条记录， 值为true表示把满⾜条件的⽂档全部更新

注意：

{multi:true}

需要和

$set

配合使用

案例1：

//把名字为小黑的更新为小白> db.test001.update({name: '小黑'},{name:'小白'})))
WriteResult({ "nMatched" : 1,"nUpserted" : 0,"nModified" : 1 })> db.test001.find()                         
{ "_id" : ObjectId("621780b5cec136e6f853bbef"),"name" : "张三","age" : 18,"sex" : "男","hobby" : "美女" }
{ "_id" : ObjectId("621780b5cec136e6f853bbf0"),"name" : "李四","age" : 20,"sex" : "男","hobby" : "跑车" }
{ "_id" : ObjectId("621780b5cec136e6f853bbf1"),"name" : "王五","age" : 21,"sex" : "男","hobby" : "黑丝" }
{ "_id" : 1,"name" : "小白" } 

• 注意：这种写法会替换掉其他的字段（全部替换），age、sex、hobby都没有了

案例2：

//把名字为王五的更新为小王> db.test001.update({name:'王五'},{$set:{name:'小王'}})
WriteResult({ "nMatched" : 1,"nUpserted" : 0,"nModified" : 1 })> db.test001.find()                                '}})
{ "_id" : ObjectId("621780b5cec136e6f853bbef"),"name" : "张三","age" : 18,"sex" : "男","hobby" : "美女" }
{ "_id" : ObjectId("621780b5cec136e6f853bbf0"),"name" : "李四","age" : 20,"sex" : "男","hobby" : "跑车" }
{ "_id" : ObjectId("621780b5cec136e6f853bbf1"),"name" : "小王","age" : 21,"sex" : "男","hobby" : "黑丝" }
{ "_id" : 1,"name" : "小白" }

• 可以看出加上$set:后仅更新了name一个字段

案例3：

//修改所有人的性别> db.test001.update({sex: '男'},{$set:{sex: '女'}},{multi:true})
WriteResult({ "nMatched" : 0,"nUpserted" : 0,"nModified" : 0 })> db.test001.find())      }))  })
{ "_id" : ObjectId("621780b5cec136e6f853bbef"),"name" : "张三","age" : 18,"sex" : "女","hobby" : "美女" }
{ "_id" : ObjectId("621780b5cec136e6f853bbf0"),"name" : "李四","age" : 20,"sex" : "女","hobby" : "跑车" }
{ "_id" : ObjectId("621780b5cec136e6f853bbf1"),"name" : "小王","age" : 21,"sex" : "女","hobby" : "黑丝" }
{ "_id" : 1,"name" : "小白" }

• {multi:true}：起到全部JSON替换的功能

9、删除数据

格式：

db.集合名称.remove(<query>,{justOne: <boolean>})

• 参数query:可选，删除的⽂档的条件
• 参数justOne:可选， 如果设为true或1， 则只删除⼀条， 默认false， 表示删除多条

案例：

//先删除一条数据> db.test001.remove({sex: '女'}, {justOne:true})
WriteResult({ "nRemoved" : 1 })> db.test001.find()
{ "_id" : ObjectId("621780b5cec136e6f853bbf0"),"name" : "李四","age" : 20,"sex" : "女","hobby" : "跑车" }
{ "_id" : ObjectId("621780b5cec136e6f853bbf1"),"name" : "小王","age" : 21,"sex" : "女","hobby" : "黑丝" }
{ "_id" : 1,"name" : "小白" }
// 全部删除> db.test001.remove({sex: '女'})
WriteResult({ "nRemoved" : 2 })> db.test001.find())
{ "_id" : 1,"name" : "小白" }

四、高级查询

数据准备（三国争霸）：

db.test002.insertMany([
    {name: "张飞", hometown: "蜀国", age: 30, sex: "男"},
    {name: "关羽", hometown: "蜀国", age: 40, sex: "男"},
    {name: "刘备", hometown: "蜀国", age: 50, sex: "男"},
    {name: "曹操", hometown: "魏国", age: 45, sex: "男"},
    {name: "司马懿", hometown: "魏国", age: 45, sex: "男"},
    {name: "孙权", hometown: "吴国", age: 50, sex: "男"}
]);

1、数据查询

• 条件查询：db.集合名称.find({条件⽂档})
• 查询只返回第⼀个：db.集合名称.findOne({条件⽂档})
• 将结果格式化：db.集合名称.find({条件⽂档}).pretty()

案例1：

// 查询年龄为50> db.test002.find({age:50})
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e7"),"name" : "刘备","hometown" : "蜀国","age" : 50,"sex" : "男" }
{ "_id" : ObjectId("6219a246d1ca96a61ceca3ea"),"name" : "孙权","hometown" : "吴国","age" : 50,"sex" : "男" }

// 查询年龄为45> db.test002.find({age:45})
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e8"),"name" : "曹操","hometown" : "魏国","age" : 45,"sex" : "男" }
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e9"),"name" : "司马懿","hometown" : "魏国","age" : 45,"sex" : "男" }

案例2：

//查询一个年龄为50> db.test002.findOne({age:50})
{
        "_id" : ObjectId("6219a246d1ca96a61ceca3e7"),"name" : "刘备","hometown" : "蜀国","age" : 50,"sex" : "男"
}

//查询一个年龄为45> db.test002.findOne({age:45})
{
        "_id" : ObjectId("6219a246d1ca96a61ceca3e8"),"name" : "曹操","hometown" : "魏国","age" : 45,"sex" : "男"
}

案例3：

//美化输出年龄为50> db.test002.find({age:50}).pretty()
{
        "_id" : ObjectId("6219a246d1ca96a61ceca3e7"),"name" : "刘备","hometown" : "蜀国","age" : 50,"sex" : "男"
}
{
        "_id" : ObjectId("6219a246d1ca96a61ceca3ea"),"name" : "孙权","hometown" : "吴国","age" : 50,"sex" : "男"
}

2、比较运算符

等于： 默认是等于判断， 没有运算符

⼩于：

$lt

（less than）

⼩于等于：

$lte

（less than equal）

⼤于：

$gt

（greater than）

⼤于等于：

$gte

不等于：

$ne

格式：

db.集合名称.find({age:{$gte:18}})

案例：

//年龄小于45> db.test002.find({age:{$lt:45}})
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e5"),"name" : "张飞","hometown" : "蜀国","age" : 30,"sex" : "男" }
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e6"),"name" : "关羽","hometown" : "蜀国","age" : 40,"sex" : "男" }

//年龄小于等于45> db.test002.find({age:{$lte:45}})
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e5"),"name" : "张飞","hometown" : "蜀国","age" : 30,"sex" : "男" }
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e6"),"name" : "关羽","hometown" : "蜀国","age" : 40,"sex" : "男" }
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e8"),"name" : "曹操","hometown" : "魏国","age" : 45,"sex" : "男" }
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e9"),"name" : "司马懿","hometown" : "魏国","age" : 45,"sex" : "男" }

//年龄大于45> db.test002.find({age:{$gt:45}})
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e7"),"name" : "刘备","hometown" : "蜀国","age" : 50,"sex" : "男" }
{ "_id" : ObjectId("6219a246d1ca96a61ceca3ea"),"name" : "孙权","hometown" : "吴国","age" : 50,"sex" : "男" }

//年龄大于等于45> db.test002.find({age:{$gte:45}})
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e7"),"name" : "刘备","hometown" : "蜀国","age" : 50,"sex" : "男" }
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e8"),"name" : "曹操","hometown" : "魏国","age" : 45,"sex" : "男" }
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e9"),"name" : "司马懿","hometown" : "魏国","age" : 45,"sex" : "男" }
{ "_id" : ObjectId("6219a246d1ca96a61ceca3ea"),"name" : "孙权","hometown" : "吴国","age" : 50,"sex" : "男" }

//年龄不等于45> db.test002.find({age:{$ne:45}})
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e5"),"name" : "张飞","hometown" : "蜀国","age" : 30,"sex" : "男" }
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e6"),"name" : "关羽","hometown" : "蜀国","age" : 40,"sex" : "男" }
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e7"),"name" : "刘备","hometown" : "蜀国","age" : 50,"sex" : "男" }
{ "_id" : ObjectId("6219a246d1ca96a61ceca3ea"),"name" : "孙权","hometown" : "吴国","age" : 50,"sex" : "男" }

3、范围运算符

判断是否在某个范围内：使⽤

$in

，

$nin

格式：

db.集合名字.find({age:{$in:[18,28]}})

案例：

//年龄为30,40,50> db.test002.find({age:{$in:[30,40,50]}})
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e5"),"name" : "张飞","hometown" : "蜀国","age" : 30,"sex" : "男" }
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e6"),"name" : "关羽","hometown" : "蜀国","age" : 40,"sex" : "男" }
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e7"),"name" : "刘备","hometown" : "蜀国","age" : 50,"sex" : "男" }
{ "_id" : ObjectId("6219a246d1ca96a61ceca3ea"),"name" : "孙权","hometown" : "吴国","age" : 50,"sex" : "男" }

//年龄不为30,40,50> db.test002.find({age:{$nin:[30,40,50]}})
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e8"),"name" : "曹操","hometown" : "魏国","age" : 45,"sex" : "男" }
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e9"),"name" : "司马懿","hometown" : "魏国","age" : 45,"sex" : "男" }

4、逻辑运算符

and：在json中写多个条件即可

格式：

db.集合名称.find({条件1, 条件2})

or：使⽤

$or

， 值为数组， 数组中每个元素为json

格式：

db.集合名词.find({$or:[{条件1}, {条件2}]})

案例：

//年龄为40的蜀国人> db.test002.find({age: 40, hometown: "蜀国"})
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e6"),"name" : "关羽","hometown" : "蜀国","age" : 40,"sex" : "男" }

//年龄小于50或者为吴国人> db.test002.find({$or:[{age:{$lt:50}}, {hometown: "吴国"}]})
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e5"),"name" : "张飞","hometown" : "蜀国","age" : 30,"sex" : "男" }
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e6"),"name" : "关羽","hometown" : "蜀国","age" : 40,"sex" : "男" }
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e8"),"name" : "曹操","hometown" : "魏国","age" : 45,"sex" : "男" }
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e9"),"name" : "司马懿","hometown" : "魏国","age" : 45,"sex" : "男" }
{ "_id" : ObjectId("6219a246d1ca96a61ceca3ea"),"name" : "孙权","hometown" : "吴国","age" : 50,"sex" : "男" }

5、正则表达式

使⽤

//

或

$regex

编写正则表达式

格式1：

db.集合名称.find({name:/^张/})

格式2：

db.集合名词.find({name:{$regex:'^张'}})

案例：

//查询姓名以张开头> db.test002.find({name:/^张/})
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e5"),"name" : "张飞","hometown" : "蜀国","age" : 30,"sex" : "男" }
> db.test002.find({name:{$regex:'^张'}})
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e5"),"name" : "张飞","hometown" : "蜀国","age" : 30,"sex" : "男" }

6、limit和skip

⽤于读取指定数量的⽂档：

db.集合名称.find().limit(number)

⽤于跳过指定数量的⽂档：

db.集合名称.find().skip(number)

同时使用：

db.集合名称.find().limit(number).skip(number)
或
db.集合名称.find().skip(number).limit(number)//推荐使用效率会更高

案例：

//查询前两条数据> db.test002.find().limit(2)
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e5"),"name" : "张飞","hometown" : "蜀国","age" : 30,"sex" : "男" }
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e6"),"name" : "关羽","hometown" : "蜀国","age" : 40,"sex" : "男" }

//查询除前两条以外的数据> db.test002.find().skip(2)
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e7"),"name" : "刘备","hometown" : "蜀国","age" : 50,"sex" : "男" }
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e8"),"name" : "曹操","hometown" : "魏国","age" : 45,"sex" : "男" }
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e9"),"name" : "司马懿","hometown" : "魏国","age" : 45,"sex" : "男" }
{ "_id" : ObjectId("6219a246d1ca96a61ceca3ea"),"name" : "孙权","hometown" : "吴国","age" : 50,"sex" : "男" }

//查询前五条数据中后两条> db.test002.find().limit(5).skip(3)
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e8"),"name" : "曹操","hometown" : "魏国","age" : 45,"sex" : "男" }
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e9"),"name" : "司马懿","hometown" : "魏国","age" : 45,"sex" : "男" }

//查询后三条数据中的前两条> db.test002.find().skip(3).limit(2)
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e8"),"name" : "曹操","hometown" : "魏国","age" : 45,"sex" : "男" }
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e9"),"name" : "司马懿","hometown" : "魏国","age" : 45,"sex" : "男" }

7、自定义查询

使⽤

$where

后⾯写⼀个函数， 返回满⾜条件的数据

格式：

db.集合名称.find({
    $where:function() {
        return this.条件;}
})

案例：

//查询年龄大于40> db.test002.find({
     $where:function() {
         return this.age>40;}
  })
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e7"),"name" : "刘备","hometown" : "蜀国","age" : 50,"sex" : "男" }
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e8"),"name" : "曹操","hometown" : "魏国","age" : 45,"sex" : "男" }
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e9"),"name" : "司马懿","hometown" : "魏国","age" : 45,"sex" : "男" }
{ "_id" : ObjectId("6219a246d1ca96a61ceca3ea"),"name" : "孙权","hometown" : "吴国","age" : 50,"sex" : "男" }

8、投影

在查询到的返回结果中， 只选择必要的字段：

db.集合名称.find({条件（可省略）},{字段名称:1,...})

• 参数为字段与值， 值为1表示显示， 不显示则不用写
• 特殊： 对于_id列默认是显示的， 如果不显示需要明确设置为0

案例1：

//显示name和age字段> db.test002.find({},{name:1, age:1})
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e5"),"name" : "张飞","age" : 30 }
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e6"),"name" : "关羽","age" : 40 }
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e7"),"name" : "刘备","age" : 50 }
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e8"),"name" : "曹操","age" : 45 }
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e9"),"name" : "司马懿","age" : 45 }
{ "_id" : ObjectId("6219a246d1ca96a61ceca3ea"),"name" : "孙权","age" : 50 }

• 可以看出_id列默认是显示的

案例2：

//仅显示name字段> db.test002.find({},{name:1, _id:0})
{ "name" : "张飞" }
{ "name" : "关羽" }
{ "name" : "刘备" }
{ "name" : "曹操" }
{ "name" : "司马懿" }
{ "name" : "孙权" }

9、排序

对集合进⾏排序：

db.集合名称.find().sort({字段:1,...})

• 参数1为升序排列
• 参数-1为降序排列

案例：

//根据年龄升序排序> db.test002.find().sort({age:1})
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e5"),"name" : "张飞","hometown" : "蜀国","age" : 30,"sex" : "男" }
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e6"),"name" : "关羽","hometown" : "蜀国","age" : 40,"sex" : "男" }
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e8"),"name" : "曹操","hometown" : "魏国","age" : 45,"sex" : "男" }
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e9"),"name" : "司马懿","hometown" : "魏国","age" : 45,"sex" : "男" }
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e7"),"name" : "刘备","hometown" : "蜀国","age" : 50,"sex" : "男" }
{ "_id" : ObjectId("6219a246d1ca96a61ceca3ea"),"name" : "孙权","hometown" : "吴国","age" : 50,"sex" : "男" }

//根据年龄降序排序> db.test002.find().sort({age:-1})
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e7"),"name" : "刘备","hometown" : "蜀国","age" : 50,"sex" : "男" }
{ "_id" : ObjectId("6219a246d1ca96a61ceca3ea"),"name" : "孙权","hometown" : "吴国","age" : 50,"sex" : "男" }
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e8"),"name" : "曹操","hometown" : "魏国","age" : 45,"sex" : "男" }
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e9"),"name" : "司马懿","hometown" : "魏国","age" : 45,"sex" : "男" }
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e6"),"name" : "关羽","hometown" : "蜀国","age" : 40,"sex" : "男" }
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e5"),"name" : "张飞","hometown" : "蜀国","age" : 30,"sex" : "男" }

//根据name降序，再根据age降序> db.test002.find().sort({name:-1, age:-1})
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e8"),"name" : "曹操","hometown" : "魏国","age" : 45,"sex" : "男" }
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e5"),"name" : "张飞","hometown" : "蜀国","age" : 30,"sex" : "男" }
{ "_id" : ObjectId("6219a246d1ca96a61ceca3ea"),"name" : "孙权","hometown" : "吴国","age" : 50,"sex" : "男" }
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e9"),"name" : "司马懿","hometown" : "魏国","age" : 45,"sex" : "男" }
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e7"),"name" : "刘备","hometown" : "蜀国","age" : 50,"sex" : "男" }
{ "_id" : ObjectId("6219a246d1ca96a61ceca3e6"),"name" : "关羽","hometown" : "蜀国","age" : 40,"sex" : "男" }

10、统计个数

统计结果集中⽂档条数：

• db.集合名称.find({条件}).count()
• db.集合名称.count({条件})

案例：

//统计蜀国人个数> db.test002.find({hometown: "蜀国"}).count()3> db.test002.count({hometown: "蜀国"})3

注意：如果有

find()

，需要在

find()

中写条件

11、去除重复

数据进⾏去重：

db.集合名称.distinct('去重字段',{条件})

案例：

//对hometown去重> db.test002.distinct('hometown')["吴国","蜀国","魏国"]//对age去重> db.test002.distinct('age')[30,40,45,50]//对age去重，并且为蜀国人> db.test002.distinct('age',{hometown:"蜀国"})[30,40,50]

五、聚合和管道

数据准备：

db.test003.insertMany([
    {name: "张飞", hometown: "蜀国", age: 30, sex: "男"},
    {name: "关羽", hometown: "蜀国", age: 40, sex: "男"},
    {name: "刘备", hometown: "蜀国", age: 50, sex: "男"},
    {name: "曹操", hometown: "魏国", age: 45, sex: "男"},
    {name: "司马懿", hometown: "魏国", age: 45, sex: "男"},
    {name: "孙权", hometown: "吴国", age: 50, sex: "男"},
    {name: "貂蝉", hometown: "未知", age: 18, sex: "女"},
    {name: "西施", hometown: "越国", age: 18, sex: "女"},
    {name: "王昭君", hometown: "西汉", age: 18, sex: "女"},
    {name: "杨玉环", hometown: "唐朝", age: 18, sex: "女"}
]);

1、聚合简介

聚合(aggregate)是基于数据处理的聚合管道，每个文档通过一个由多个阶段（stage）组成的管道，可以对每个阶段的管道进行分组、过滤等功能，然后经过一系列的处理，输出相应的结果。

语法格式：

db.集合名称.aggregate({管道:{表达式}})

2、常用管道

在mongodb中，⽂档处理完毕后， 通过管道进⾏下⼀次处理

常用管道如下：

$group

： 将集合中的⽂档分组， 可⽤于统计结果

$match

： 过滤数据， 只输出符合条件的⽂档

$project

： 修改输⼊⽂档的结构， 如重命名、 增加、 删除字段、 创建计算结果

$sort

： 将输⼊⽂档排序后输出

$limit

： 限制聚合管道返回的⽂档数

$skip

： 跳过指定数量的⽂档， 并返回余下的⽂档

$unwind

： 将数组类型的字段进⾏拆分

3、表达式

处理输⼊⽂档并输出

语法格式：

表达式:'$列名'

常⽤表达式:

$sum

： 计算总和， $sum:1 表示以⼀倍计数

$avg

： 计算平均值

$min

： 获取最⼩值

$max

： 获取最⼤值

$push

： 在结果⽂档中插⼊值到⼀个数组中

$first

： 根据资源⽂档的排序获取第⼀个⽂档数据

$last

： 根据资源⽂档的排序获取最后⼀个⽂档数据

4、$group

将集合中的文档分组，可用于统计结果

_id

表示分组的依据，使用某个字段的格式为’

$字段

’

案例：

// 返回sex有哪些值> db.test003.aggregate(
    {$group:{
        _id:"$sex"
        }
    }
)
{ "_id" : "男" }
{ "_id" : "女" }

//统计男生、女生分别的总人数> db.test003.aggregate(
    {$group:
        {
        _id:"$sex",
        count:{$sum:1}
        }
    }
)
{ "_id" : "男","count" : 6 }
{ "_id" : "女","count" : 4 }

//统计男、女分别的平均年龄> db.test003.aggregate(
    {$group:
        {
        _id:"$sex",
        count:{$sum:1},
        avg_age:{$avg:"$age"}
        }
    }
)
{ "_id" : "男","count" : 6,"avg_age" : 43.333333333333336 }
{ "_id" : "女","count" : 4,"avg_age" : 18 }

//按照hometown进行分组，获取不同组的平均年龄> db.test003.aggregate(
    {$group:
        {
        _id:"$hometown",
        avg_age:{$avg:"$age"}
        }
    }
)
{ "_id" : "蜀国","avg_age" : 40 }
{ "_id" : "唐朝","avg_age" : 18 }
{ "_id" : "越国","avg_age" : 18 }
{ "_id" : "吴国","avg_age" : 50 }
{ "_id" : "西汉","avg_age" : 18 }
{ "_id" : "未知","avg_age" : 18 }
{ "_id" : "魏国","avg_age" : 45 }

//统计不同性别的人物名字> db.test003.aggregate(
    {$group:
        {
        _id:"$sex",
        name:{$push:"$name"}
        }
    }
)
{ "_id" : "男","name" : ["张飞","关羽","刘备","曹操","司马懿","孙权"] }
{ "_id" : "女","name" : ["貂蝉","西施","王昭君","杨玉环"] }

// 使用$$ROOT可以将文档内容加入到结果集的数组中> db.test003.aggregate(
    {$group:
        {
        _id:"$sex",
        name:{$push:"$$ROOT"}
        }
    }
)
{ "_id" : "男","name" : [ { "_id" : ObjectId("621cbd0aea5c14fd51410b33"),"name" : "张飞","hometown" : "蜀国","age" : 30,"sex" : "男" }, { "_id" : ObjectId("621cbd0aea5c14fd51410b34"),"name" : "关羽","hometown" : "蜀国","age" : 40,"sex" : "男" }, { "_id" : ObjectId("621cbd0aea5c14fd51410b35"),"name" : " 刘备","hometown" : "蜀国","age" : 50,"sex" : "男" }, { "_id" : ObjectId("621cbd0aea5c14fd51410b36"),"name" : "曹操","hometown" : "魏国","age" : 45,"sex" : "男" }, { "_id" : ObjectId("621cbd0aea5c14fd51410b37"),"name" : "司马懿","hometown" : "魏国","age" : 45,"sex" : "男" }, { "_id" : ObjectId("621cbd0aea5c14fd51410b38"),"name" : "孙权","hometown" : "吴国","age" : 50,"sex" : "男" } ] }
{ "_id" : "女","name" : [ { "_id" : ObjectId("621cbd0aea5c14fd51410b39"),"name" : "貂蝉","hometown" : "未知","age" : 18,"sex" : "女" }, { "_id" : ObjectId("621cbd0aea5c14fd51410b3a"),"name" : "西施","hometown" : "越国","age" : 18,"sex" : "女" }, { "_id" : ObjectId("621cbd0aea5c14fd51410b3b"),"name" : " 王昭君","hometown" : "西汉","age" : 18,"sex" : "女" }, { "_id" : ObjectId("621cbd0aea5c14fd51410b3c"),"name" : "杨玉环","hometown" : "唐朝","age" : 18,"sex" : "女" } ] }

_id:null

：将集合中所有文档分为一组

案例：求总人数、平均年龄

> db.test003.aggregate(
    {$group:
        {
        _id:null,
        count:{$sum:1},
        avg_age:{$avg:"$age"}
        }
    }
)
{ "_id" : null,"count" : 10,"avg_age" : 33.2 }

总结：

• $group对应的字典中有几个键，结果中就有几个键
• 分组依据需要放到_ id后面
• 取不同的字段的值需要使用$，如：$hometown、$age、$sex
• 取字典嵌套的字典中值的时候$_id.字段名
• 同时取多个键进行分组：{$group:{_id:{字段名1:"$字段名1",字段名2:"字段名2"}}}；输出结果：{_id:{字段名1:"",字段名2:""}

5、$project

修改输入文档的结构，如重命名、增加、删除字段、创建计算结果；简单来说就是修改输入输出的值

案例1：查询姓名、年龄

> db.test003.aggregate({$project:{_id:0, name:1, age:1}})
{ "name" : "张飞","age" : 30 }
{ "name" : "关羽","age" : 40 }
{ "name" : "刘备","age" : 50 }
{ "name" : "曹操","age" : 45 }
{ "name" : "司马懿","age" : 45 }
{ "name" : "孙权","age" : 50 }
{ "name" : "貂蝉","age" : 18 }
{ "name" : "西施","age" : 18 }
{ "name" : "王昭君","age" : 18 }
{ "name" : "杨玉环","age" : 18 }

案例2：查询男、女人数，输出人数

> db.test003.aggregate(
    {$group:{_id:'$sex', count:{$sum:1}}},
    {$project:{_id:0, count:1}}
)
{ "count" : 4 }
{ "count" : 6 }

6、$match

用于过滤数据，只输出符合条件的文档

• 使用MongoDB的标准查询操作
• match是管道命令，能将结果交给后一个管道，但是find不可以

案例1：查询年龄大于20的

> db.test003.aggregate(
    {$match:{age:{$gt:20}}}
)
{ "_id" : ObjectId("621cbd0aea5c14fd51410b33"),"name" : "张飞","hometown" : "蜀国","age" : 30,"sex" : "男" }
{ "_id" : ObjectId("621cbd0aea5c14fd51410b34"),"name" : "关羽","hometown" : "蜀国","age" : 40,"sex" : "男" }
{ "_id" : ObjectId("621cbd0aea5c14fd51410b35"),"name" : "刘备","hometown" : "蜀国","age" : 50,"sex" : "男" }
{ "_id" : ObjectId("621cbd0aea5c14fd51410b36"),"name" : "曹操","hometown" : "魏国","age" : 45,"sex" : "男" }
{ "_id" : ObjectId("621cbd0aea5c14fd51410b37"),"name" : "司马懿","hometown" : "魏国","age" : 45,"sex" : "男" }
{ "_id" : ObjectId("621cbd0aea5c14fd51410b38"),"name" : "孙权","hometown" : "吴国","age" : 50,"sex" : "男" }

案例2：查询年龄大于等于18的男生、女生人数

> db.test003.aggregate(
    {$match:{age:{$gte:18}}},
    {$group:{_id:'$sex',count:{$sum:1}}}
)
{ "_id" : "男","count" : 6 }
{ "_id" : "女","count" : 4 }

7、$sort

将输入文档排序后输出

例1：查询学生信息，按年龄升序

> db.test003.aggregate({$sort:{age:1}})
{ "_id" : ObjectId("622080a6d0f7b3df134da712"),"name" : "貂蝉","hometown" : "未知","age" : 18,"sex" : "女" }
{ "_id" : ObjectId("622080a6d0f7b3df134da713"),"name" : "西施","hometown" : "越国","age" : 18,"sex" : "女" }
{ "_id" : ObjectId("622080a6d0f7b3df134da714"),"name" : "王昭君","hometown" : "西汉","age" : 18,"sex" : "女" }
{ "_id" : ObjectId("622080a6d0f7b3df134da715"),"name" : "杨玉环","hometown" : "唐朝","age" : 18,"sex" : "女" }
{ "_id" : ObjectId("622080a6d0f7b3df134da70c"),"name" : "张飞","hometown" : "蜀国","age" : 30,"sex" : "男" }
{ "_id" : ObjectId("622080a6d0f7b3df134da70d"),"name" : "关羽","hometown" : "蜀国","age" : 40,"sex" : "男" }
{ "_id" : ObjectId("622080a6d0f7b3df134da70f"),"name" : "曹操","hometown" : "魏国","age" : 45,"sex" : "男" }
{ "_id" : ObjectId("622080a6d0f7b3df134da710"),"name" : "司马懿","hometown" : "魏国","age" : 45,"sex" : "男" }
{ "_id" : ObjectId("622080a6d0f7b3df134da70e"),"name" : "刘备","hometown" : "蜀国","age" : 50,"sex" : "男" }
{ "_id" : ObjectId("622080a6d0f7b3df134da711"),"name" : "孙权","hometown" : "吴国","age" : 50,"sex" : "男" }

例2：查询男生、女生人数，按人数降序

> db.test003.aggregate(
    {$group:{_id:'$sex',counter:{$sum:1}}},
    {$sort:{age:-1}}
)
{ "_id" : "男","counter" : 6 }
{ "_id" : "女","counter" : 4 }

8、$limit

限制聚合管道返回的文档数量

案例：查询2条学生信息

> db.test003.aggregate({$limit:2})
{ "_id" : ObjectId("622080a6d0f7b3df134da70c"),"name" : "张飞","hometown" : "蜀国","age" : 30,"sex" : "男" }
{ "_id" : ObjectId("622080a6d0f7b3df134da70d"),"name" : "关羽","hometown" : "蜀国","age" : 40,"sex" : "男" }

9、$skip

跳过指定数量的文档，并返回余下的文档

例1：查询从第3条开始:人物信息

> db.test003.aggregate({$skip:2})
{ "_id" : ObjectId("622080a6d0f7b3df134da70e"),"name" : "刘备","hometown" : "蜀国","age" : 50,"sex" : "男" }
{ "_id" : ObjectId("622080a6d0f7b3df134da70f"),"name" : "曹操","hometown" : "魏国","age" : 45,"sex" : "男" }
{ "_id" : ObjectId("622080a6d0f7b3df134da710"),"name" : "司马懿","hometown" : "魏国","age" : 45,"sex" : "男" }
{ "_id" : ObjectId("622080a6d0f7b3df134da711"),"name" : "孙权","hometown" : "吴国","age" : 50,"sex" : "男" }
{ "_id" : ObjectId("622080a6d0f7b3df134da712"),"name" : "貂蝉","hometown" : "未知","age" : 18,"sex" : "女" }
{ "_id" : ObjectId("622080a6d0f7b3df134da713"),"name" : "西施","hometown" : "越国","age" : 18,"sex" : "女" }
{ "_id" : ObjectId("622080a6d0f7b3df134da714"),"name" : "王昭君","hometown" : "西汉","age" : 18,"sex" : "女" }
{ "_id" : ObjectId("622080a6d0f7b3df134da715"),"name" : "杨玉环","hometown" : "唐朝","age" : 18,"sex" : "女" }

例2：查询从第3条开始，取第二条数据

> db.test003.aggregate(
    {$skip:2},
    {$limit:1}
)
{ "_id" : ObjectId("622080a6d0f7b3df134da70e"),"name" : "刘备","hometown" : "蜀国","age" : 50,"sex" : "男" }

• 注意顺序：先写skip, 再写limit

10、$unwind

将文档中的某一个数组类型字段拆分成多条，每条包含数组中的一个值

语法格式：

db. 集合名称.aggregate({$unwind:'$字段名称’}) 

案例：

> db.test004.insert({_id:1, item:'t-shirt', size:['S','M','L']})
WriteResult({ "nInserted" : 1 })> db.test004.aggregate({$unwind: '$size'})
{ "_id" : 1,"item" : "t-shirt","size" : "S" }
{ "_id" : 1,"item" : "t-shirt","size" : "M" }
{ "_id" : 1,"item" : "t-shirt","size" : "L" }

练习：数据库中有一条数据：{“username”:“Alex”,“tags”: [‘C#’,‘Java’,‘C++’]}，如何获取该tag列表的长度？

//先插入数据> db.test004.insert({"username":"Alex","tags": ['C#','Java','C++']})
WriteResult({ "nInserted" : 1 })//查看数据> db.test004.find()
{ "_id" : ObjectId("6220b04d383dd803412e9a3f"),"username" : "Alex","tags" : ["C#","Java","C++"] }
//拆分数据> db.test004.aggregate({$match:{username:"Alex"}},{$unwind:"$tags"})
{ "_id" : ObjectId("6220b04d383dd803412e9a3f"),"username" : "Alex","tags" : "C#" }
{ "_id" : ObjectId("6220b04d383dd803412e9a3f"),"username" : "Alex","tags" : "Java" }
{ "_id" : ObjectId("6220b04d383dd803412e9a3f"),"username" : "Alex","tags" : "C++" }
//把上面得三条结果给$group，然后统计条数> db.test004.aggregate({$match:{username:"Alex"}},{$unwind:"$tags"},{$group:{_id:null, sum:{$sum:1}}})
{ "_id" : null,"sum" : 3 }

属性

preserveNullAndEmptyArrays

值为true表示保留属性值为空的⽂档；值为false表示丢弃属性值为空的⽂档

用法：

六、索引

1、创建索引

索引：以提升查询速度

测试：插入10万条数据到数据库中

>for(i=0;i<100000;i++){db.test005.insert({name:'test'+i,age:i})}
WriteResult({ "nInserted" : 1 })> db.test005.find().count()100000

查询运行时间：

语句后面+.explain('executionStats')

//案例> db.test005.find({name:'test10000'}).explain('executionStats')

建立索引语法：

db.集合名称.ensureIndex({字段名:1})

；其中 1 表示升序， -1 表示降序

建立索引之后对比：

> db.test005.ensureIndex({name:1})
{
        "createdCollectionAutomatically" : false,"numIndexesBefore" : 1,"numIndexesAfter" : 2,"ok" : 1
}
> db.test005.find({name:'test10000'}).explain('executionStats')

2、索引操作

查看当前集合的所有索引：

> db.test005.getIndexes()[
        {
                "v" : 2,"key" : {
                        "_id" : 1
                },"name" : "_id_"
        },
        {
                "v" : 2,"key" : {
                        "name" : 1
                },"name" : "name_1"
        }
]

删除索引：

db.集合名称.dropIndex({'索引名称'})

> db.test005.dropIndex({'name':1})
{ "nIndexesWas" : 2,"ok" : 1 }
//再次查看全部索引> db.test005.getIndexes()[ { "v" : 2,"key" : { "_id" : 1 },"name" : "_id_" } ]

创建唯一索引（索引的值是唯一的；在默认情况下索引字段的值可以相同）：

> db.test005.ensureIndex({"name":1}, {"unique":true})
{
        "ok" : 0,"errmsg" : "Index build failed: eab854cd-330b-414f-ae86-9cfb317efbf5: Collection test.test005 ( 45744ab1-2a71-4722-8f84-99812ccc9ffb ) :: caused by :: E11000 duplicate key error collection: test.test005 index: name_1 dup key: { name: \"test0\" }","code" : 11000,"codeName" : "DuplicateKey","keyPattern" : {
                "name" : 1
        },"keyValue" : {
                "name" : "test0"
        }
}

建立联合索引（什么时候需要联合索引）

> db.test005.ensureIndex({name:1, age:1})
{
        "createdCollectionAutomatically" : false,"numIndexesBefore" : 1,"numIndexesAfter" : 2,"ok" : 1
}
> db.test005.getIndexes()[
        {
                "v" : 2,"key" : {
                        "_id" : 1
                },"name" : "_id_"
        },
        {
                "v" : 2,"key" : {
                        "name" : 1,"age" : 1
                },"name" : "name_1_age_1"
        }
]

七、备份和恢复

1、备份

备份的语法：

mongodump -h dbhost -d dbname -o dbdirectory

• -h： 指定服务器地址；如果是当前本机数据库可以去掉-h
• -port ：指定端口号；如果是默认端口可以去掉
• -d： 需要备份的数据库名称；如果不指定则导出所有数据库
• -o： 备份的数据存放位置， 此⽬录中存放着备份出来的数据
• -c： 指定集合名称；如果不指定则全部导出
• -u： 用户名；如果没有用户，可以不用指定
• -p： 密码；如果没有密码，可以不用指定

注意：

• 命名需要在终端输出，而不是数据库命令行
• 每个参数前后是有空格

mongodump -h 192.168.196.128:27017 -d test1 -o ~/Desktop/test1bak

案例：

//保存本地数据库中test库在桌面
mongodump  -d test -o ~C:\Users\ym\Desktop\

2、恢复

恢复语法：

mongorestore -h dbhost -d dbname --dir dbdirectory

• -h： 服务器地址
• -d： 需要恢复的数据库实例
• --dir： 备份数据所在位置

mongorestore -h 192.168.196.128:27017 -d test2 --dir ~/Desktop/test1bak/test1