MongoDB 4.X基础教程

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一、MongoDB介绍

MongoDB是一个基于分布式文件存储的数据库。
由C++语言编写。旨在为WEB应用提供可扩展的高性能数据存储解决方案。
MongoDB是一个介于关系型数据库和非关系数据库之间的产品，是非关系数据库当中功能最丰富，最像关系数据库的。
MongoDB支持的数据结构非常松散，是类似JSON的BJSON格式，因此可以存储比较复杂的数据类型。Mongo最大的特点是它支持的查询语言非常强大，其语法有点类似于面向对象的查询语言，几乎可以实现类似关系数据库单表查询的绝大部分功能，而且还支持对数据建立索引。
MongoDB数据操作基于json格式

 { "userName":"admin", "password":123456 }

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二、MongoDB安装

1.MongoDB下载

网址：https://www.mongodb.com/try/download/community
上图在选择版本的时候根据自己系统选择，有Windowns、LInux、CentOS、Ubuntu等可供选择。

2.MongoDB安装

下载的 .msi 文件，下载后双击该文件，按操作提示安装即可。
安装过程中，你可以通过点击 "Custom(自定义)" 按钮来设置你的安装目录，建议不要安装在C 盘。

全程点击next安装，但是这一步需要注意，这里是安装可视化组件，默认是选择状态，这里需要取消选中，否则在安装的过程中要下载可视化组件，比较慢，甚至有时候会报错：

3.MongoDB环境变量配置

在桌面右键此电脑>>>属性>>>高级系统设置>>>高级>>>环境变量>>>找到path>>>选择编辑 >>>新建

在打开的环境变量中MongoDB安装的bin路径复制到新建目录中

然后点击所有的确定即可完成环境变量配置

4.验证安装是否成功

打开CMD命令窗口，输入mongo，出现以下提示信息，说明安装成功。

C:\Users\***.DESKTOP-C1RC9P2>mongo
MongoDB shell version v4.4.2-rc0
connecting to: mongodb://127.0.0.1:27017/?compressors=disabled&gssapiServiceName=mongodb
Implicit session: session { "id" : UUID("df31999e-cb62-4f71-8a18-7db8723c514f") }
MongoDB server version: 4.4.2-rc0
---
The server generated these startup warnings when booting:
        2020-10-30T16:25:16.503+08:00: Access control is not enabled for the database. Read and write access to data and configuration is unrestricted
---
---
        Enable MongoDB's free cloud-based monitoring service, which will then receive and display
        metrics about your deployment (disk utilization, CPU, operation statistics, etc).

        The monitoring data will be available on a MongoDB website with a unique URL accessible to you
        and anyone you share the URL with. MongoDB may use this information to make product
        improvements and to suggest MongoDB products and deployment options to you.

        To enable free monitoring, run the following command: db.enableFreeMonitoring()
        To permanently disable this reminder, run the following command: db.disableFreeMonitoring()

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三、MongoDB使用基本介绍

MongoDB属于非关系型数据库，其数据库、表、字段等和关系型数据库（如：MySQL数据库）有一定的差别；
MongoDB中的集合就相当于关系型数据库中的表 MongoDB中的json字符串的键相当于关系型数据库中的列名；
在操作MongoDB数据的时候全部使用json数据格式。

1.查看数据库名

查看所有数据库名

命令：
  show dbs

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  > show dbs
  admin   0.000GB
  config  0.000GB
  local   0.000GB

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这三个数据库是默认系统数据库，不能删除。

2. 查看集合

查看集合前提是要先指定使用哪一个数据库

命令：
ues 数据库名 show collections

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> use admin 
switched to db admin 
> show collections 
system.version

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system.version 就是admin这个数据库中的表

3.查询集合中的数据

这里先简单介绍查询集合中的所有数据，方便后面学习。
查询集合中的所有数据，这里查询的是系统数据库admin中的 system.version 集合

命令：
	db.集合名.find()

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> db.system.version.find()
{ "_id" : "featureCompatibilityVersion", "version" : "4.4" }

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这里的_id是集合的键，每个集合里面默认存在，version是集合中的另一个键，相当于关系型数据库中的字段

四、创建数据库及添加数据

MongoDB不能够直接创建数据库，需要添加一条数据才能创建

1.创建数据库和插入数据

先指定创建的数据
然后执行添加数据命令

> use company
switched to db company
> db.emp.insert({"empno":100,"ename":"admin","sex":"男","age":20,"salary":800.00,"deptno":10})
WriteResult({ "nInserted" : 1 })

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这里插入了6列数据，分别是员工的编号，姓名，性别，年龄，薪资及所在的部门

WriteResult({ "nInserted" : 1 })

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表示一行数据插入成功,说明创建数据成功，同时添加了一套数据,我们可以继续添加

>  db.emp.insert({"empno":101,"ename":"张三","sex":"女","age":30,"salary":2500.00,"deptno":20})})})})
WriteResult({ "nInserted" : 1 })

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随着数据的插入，数据库也随着创建成功。

五、查询数据

查询所有数据，在查询数据前要先指定使用哪个数据库，再查询数据库中的所有集合，根据相应集合再查询数据。

1.查询所有数据

命令：
db.集合名.find()

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指定对哪个数据库操作
	> use company
	switched to db company
查询指定数据库后里面的所有集合
	> show collections
emp
查询所有数据，一共12条数据：
	> db.emp.find()

{ "_id" : ObjectId("5f9c1c5b5df291fa8194b91b"), "empno" : 100, "ename" : "admin", "sex" : "男", "age" : 20, "salary" : 800, "deptno" : 10 }
{ "_id" : ObjectId("5f9c1dfc5df291fa8194b91c"), "empno" : 101, "ename" : "张三", "sex" : "女", "age" : 30, "salary" : 2500, "deptno" : 20 }
{ "_id" : ObjectId("5f9c20945df291fa8194b91d"), "empno" : 102, "ename" : "张良", "sex" : "男", "age" : 25, "salary" : 3000, "deptno" : 20 }
{ "_id" : ObjectId("5f9c21055df291fa8194b91e"), "empno" : 103, "ename" : "李明", "sex" : "女", "age" : 30, "salary" : 1800, "deptno" : 30 }
{ "_id" : ObjectId("5f9c215f5df291fa8194b91f"), "empno" : 104, "ename" : "李菲菲", "sex" : "女", "age" : 28, "salary" : 4200, "deptno" : 20 }
{ "_id" : ObjectId("5f9c219b5df291fa8194b921"), "empno" : 106, "ename" : "李四", "sex" : "男", "age" : 34, "salary" : 12000, "deptno" : 10 }
{ "_id" : ObjectId("5f9c21a75df291fa8194b922"), "empno" : 106, "ename" : "李四", "sex" : "男", "age" : 34, "salary" : 12000, "deptno" : 10 }
{ "_id" : ObjectId("5f9c21d85df291fa8194b923"), "empno" : 107, "ename" : "王三", "sex" : "女", "age" : 27, "salary" : 5000, "deptno" : 20 }
{ "_id" : ObjectId("5f9c22185df291fa8194b924"), "empno" : 108, "ename" : "李元芳", "sex" : "男", "age" : 33, "salary" : 10000, "deptno" : 30 }
{ "_id" : ObjectId("5f9c227d5df291fa8194b926"), "empno" : 110, "ename" : "刘静", "sex" : "女", "age" : 25, "salary" : 3500, "deptno" : 10 }
{ "_id" : ObjectId("5f9c371b5df291fa8194b927"), "empno" : 105, "ename" : "张四", "sex" : "男", "age" : 32, "salary" : 8000, "deptno" : 30 }
{ "_id" : ObjectId("5f9c376a29491ade8d9d3e79"), "empno" : 109, "ename" : "李元静", "sex" : "女", "age" : 32, "salary" : 1600, "deptno" : 30 }

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2.去掉集合中重复的数据

命令：
> db.集合名.distinct("ename")

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> db.emp.distinct("ename")

[
        "admin",
        "刘静",
        "张三",
        "张四",
        "张良",
        "李元芳",
        "李元静",
        "李四",
        "李明",
        "李菲菲",
        "王三"
]

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上面的结果“李四”重复被去掉了

3. 查询年龄等于25的数据

这里的“age”可以不加“ ”，直接写成{age:25}

> db.emp.find({"age":25})

{ "_id" : ObjectId("5f9c20945df291fa8194b91d"), "empno" : 102, "ename" : "张良", "sex" : "男", "age" : 25, "salary" : 3000, "deptno" : 20 }
{ "_id" : ObjectId("5f9c227d5df291fa8194b926"), "empno" : 110, "ename" : "刘静", "sex" : "女", "age" : 25, "salary" : 3500, "deptno" : 10 }

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4. 查询ename=“李元芳“的数据

> db.emp.find({"ename":"李元芳"})

{ "_id" : ObjectId("5f9c22185df291fa8194b924"), "empno" : 108, "ename" : "李元芳", "sex" : "男", "age" : 35, "salary" : 8000, "deptno" : 30 }

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5. 查询age>30岁的员工数据

> db.emp.find({"age":{$gt:30}})

{ "_id" : ObjectId("5f9c21855df291fa8194b920"), "empno" : 105, "ename" : "张四", "sex" : "男", "age" : 32, "salary" : 8000, "deptno" : 30 }
{ "_id" : ObjectId("5f9c219b5df291fa8194b921"), "empno" : 106, "ename" : "李四", "sex" : "男", "age" : 35, "salary" : 12000, "deptno" : 10 }
{ "_id" : ObjectId("5f9c21a75df291fa8194b922"), "empno" : 106, "ename" : "李四", "sex" : "男", "age" : 35, "salary" : 12000, "deptno" : 10 }
{ "_id" : ObjectId("5f9c22185df291fa8194b924"), "empno" : 108, "ename" : "李元芳", "sex" : "男", "age" : 35, "salary" : 8000, "deptno" : 30 }
{ "_id" : ObjectId("5f9c22445df291fa8194b925"), "empno" : 109, "ename" : "李元静", "sex" : "女", "age" : 35, "salary" : 15000, "deptno" : 36 }

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6. 查询age<25的员工数据

> db.emp.find({"age":{$lt:25}})

{ "_id" : ObjectId("5f9c1c5b5df291fa8194b91b"), "empno" : 100, "ename" : "admin", "sex" : "男", "age" : 20, "salary" : 800, "deptno" : 10 }

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7.查询age>=30的员工数据

> db.emp.find({"age":{$gte:30}})

{ "_id" : ObjectId("5f9c1dfc5df291fa8194b91c"), "empno" : 101, "ename" : "张三", "sex" : "女", "age" : 30, "salary" : 2500, "deptno" : 20 }
{ "_id" : ObjectId("5f9c21055df291fa8194b91e"), "empno" : 103, "ename" : "李明", "sex" : "女", "age" : 30, "salary" : 1800, "deptno" : 30 }
{ "_id" : ObjectId("5f9c21855df291fa8194b920"), "empno" : 105, "ename" : "张四", "sex" : "男", "age" : 32, "salary" : 8000, "deptno" : 30 }
{ "_id" : ObjectId("5f9c219b5df291fa8194b921"), "empno" : 106, "ename" : "李四", "sex" : "男", "age" : 35, "salary" : 12000, "deptno" : 10 }
{ "_id" : ObjectId("5f9c21a75df291fa8194b922"), "empno" : 106, "ename" : "李四", "sex" : "男", "age" : 35, "salary" : 12000, "deptno" : 10 }
{ "_id" : ObjectId("5f9c22185df291fa8194b924"), "empno" : 108, "ename" : "李元芳", "sex" : "男", "age" : 35, "salary" : 8000, "deptno" : 30 }
{ "_id" : ObjectId("5f9c22445df291fa8194b925"), "empno" : 109, "ename" : "李元静", "sex" : "女", "age" : 35, "salary" : 15000, "deptno" : 36 }

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8. 查询age<=30的员工数据

> db.emp.find({"age":{$lte:30}})

{ "_id" : ObjectId("5f9c1c5b5df291fa8194b91b"), "empno" : 100, "ename" : "admin", "sex" : "男", "age" : 20, "salary" : 800, "deptno" : 10 }
{ "_id" : ObjectId("5f9c1dfc5df291fa8194b91c"), "empno" : 101, "ename" : "张三", "sex" : "女", "age" : 30, "salary" : 2500, "deptno" : 20 }
{ "_id" : ObjectId("5f9c20945df291fa8194b91d"), "empno" : 102, "ename" : "张良", "sex" : "男", "age" : 25, "salary" : 3000, "deptno" : 20 }
{ "_id" : ObjectId("5f9c21055df291fa8194b91e"), "empno" : 103, "ename" : "李明", "sex" : "女", "age" : 30, "salary" : 1800, "deptno" : 30 }
{ "_id" : ObjectId("5f9c215f5df291fa8194b91f"), "empno" : 104, "ename" : "李菲菲", "sex" : "女", "age" : 28, "salary" : 4200, "deptno" : 20 }
{ "_id" : ObjectId("5f9c21d85df291fa8194b923"), "empno" : 107, "ename" : "王三", "sex" : "女", "age" : 27, "salary" : 5000, "deptno" : 20 }
{ "_id" : ObjectId("5f9c227d5df291fa8194b926"), "empno" : 110, "ename" : "刘静", "sex" : "女", "age" : 25, "salary" : 3500, "deptno" : 10 }

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9. 查询age>=25并且age<=30的员工数据

> db.emp.find({"age":{$gte:25,$lte:30}})

{ "_id" : ObjectId("5f9c1dfc5df291fa8194b91c"), "empno" : 101, "ename" : "张三", "sex" : "女", "age" : 30, "salary" : 2500, "deptno" : 20 }
{ "_id" : ObjectId("5f9c20945df291fa8194b91d"), "empno" : 102, "ename" : "张良", "sex" : "男", "age" : 25, "salary" : 3000, "deptno" : 20 }
{ "_id" : ObjectId("5f9c21055df291fa8194b91e"), "empno" : 103, "ename" : "李明", "sex" : "女", "age" : 30, "salary" : 1800, "deptno" : 30 }
{ "_id" : ObjectId("5f9c215f5df291fa8194b91f"), "empno" : 104, "ename" : "李菲菲", "sex" : "女", "age" : 28, "salary" : 4200, "deptno" : 20 }
{ "_id" : ObjectId("5f9c21d85df291fa8194b923"), "empno" : 107, "ename" : "王三", "sex" : "女", "age" : 27, "salary" : 5000, "deptno" : 20 }
{ "_id" : ObjectId("5f9c227d5df291fa8194b926"), "empno" : 110, "ename" : "刘静", "sex" : "女", "age" : 25, "salary" : 3500, "deptno" : 10 }

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10. 查询全部姓李的员工数据（模糊查询）

模糊查询一般用于查询数据量比较小的集合数据

> db.emp.find({"ename":/李/})

{ "_id" : ObjectId("5f9c21055df291fa8194b91e"), "empno" : 103, "ename" : "李明", "sex" : "女", "age" : 30, "salary" : 1800, "deptno" : 30 }
{ "_id" : ObjectId("5f9c215f5df291fa8194b91f"), "empno" : 104, "ename" : "李菲菲", "sex" : "女", "age" : 28, "salary" : 4200, "deptno" : 20 }
{ "_id" : ObjectId("5f9c219b5df291fa8194b921"), "empno" : 106, "ename" : "李四", "sex" : "男", "age" : 35, "salary" : 12000, "deptno" : 10 }
{ "_id" : ObjectId("5f9c21a75df291fa8194b922"), "empno" : 106, "ename" : "李四", "sex" : "男", "age" : 35, "salary" : 12000, "deptno" : 10 }
{ "_id" : ObjectId("5f9c22185df291fa8194b924"), "empno" : 108, "ename" : "李元芳", "sex" : "男", "age" : 35, "salary" : 8000, "deptno" : 30 }
{ "_id" : ObjectId("5f9c22445df291fa8194b925"), "empno" : 109, "ename" : "李元静", "sex" : "女", "age" : 35, "salary" : 15000, "deptno" : 36 }

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11. 查询姓名以“张”开头的员工数据

> db.emp.find({"ename":/^张/})

{ "_id" : ObjectId("5f9c1dfc5df291fa8194b91c"), "empno" : 101, "ename" : "张三", "sex" : "女", "age" : 30, "salary" : 2500, "deptno" : 20 }
{ "_id" : ObjectId("5f9c20945df291fa8194b91d"), "empno" : 102, "ename" : "张良", "sex" : "男", "age" : 25, "salary" : 3000, "deptno" : 20 }
{ "_id" : ObjectId("5f9c21855df291fa8194b920"), "empno" : 105, "ename" : "张四", "sex" : "男", "age" : 32, "salary" : 8000, "deptno" : 30 }

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12. 查询以姓名以“静”结尾的员工数据

> db.emp.find({"ename":/静$/})

{ "_id" : ObjectId("5f9c22445df291fa8194b925"), "empno" : 109, "ename" : "李元静", "sex" : "女", "age" : 35, "salary" : 15000, "deptno" : 36 }
{ "_id" : ObjectId("5f9c227d5df291fa8194b926"), "empno" : 110, "ename" : "刘静", "sex" : "女", "age" : 25, "salary" : 3500, "deptno" : 10 }

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13. 查询指定列的员工数据

查询所有员工年龄的数据

> db.emp.find({},{"age":1})

{ "_id" : ObjectId("5f9c1c5b5df291fa8194b91b"), "age" : 20 }
{ "_id" : ObjectId("5f9c1dfc5df291fa8194b91c"), "age" : 30 }
{ "_id" : ObjectId("5f9c20945df291fa8194b91d"), "age" : 25 }
{ "_id" : ObjectId("5f9c21055df291fa8194b91e"), "age" : 30 }
{ "_id" : ObjectId("5f9c215f5df291fa8194b91f"), "age" : 28 }
{ "_id" : ObjectId("5f9c21855df291fa8194b920"), "age" : 32 }
{ "_id" : ObjectId("5f9c219b5df291fa8194b921"), "age" : 35 }
{ "_id" : ObjectId("5f9c21a75df291fa8194b922"), "age" : 35 }
{ "_id" : ObjectId("5f9c21d85df291fa8194b923"), "age" : 27 }
{ "_id" : ObjectId("5f9c22185df291fa8194b924"), "age" : 35 }
{ "_id" : ObjectId("5f9c22445df291fa8194b925"), "age" : 35 }
{ "_id" : ObjectId("5f9c227d5df291fa8194b926"), "age" : 25 }

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查询所有员工的姓名和年龄的数据

> db.emp.find({},{"ename":1,"age":1})

{ "_id" : ObjectId("5f9c1c5b5df291fa8194b91b"), "ename" : "admin", "age" : 20 }
{ "_id" : ObjectId("5f9c1dfc5df291fa8194b91c"), "ename" : "张三", "age" : 30 }
{ "_id" : ObjectId("5f9c20945df291fa8194b91d"), "ename" : "张良", "age" : 25 }
{ "_id" : ObjectId("5f9c21055df291fa8194b91e"), "ename" : "李明", "age" : 30 }
{ "_id" : ObjectId("5f9c215f5df291fa8194b91f"), "ename" : "李菲菲", "age" : 28 }
{ "_id" : ObjectId("5f9c21855df291fa8194b920"), "ename" : "张四", "age" : 32 }
{ "_id" : ObjectId("5f9c219b5df291fa8194b921"), "ename" : "李四", "age" : 35 }
{ "_id" : ObjectId("5f9c21a75df291fa8194b922"), "ename" : "李四", "age" : 35 }
{ "_id" : ObjectId("5f9c21d85df291fa8194b923"), "ename" : "王三", "age" : 27 }
{ "_id" : ObjectId("5f9c22185df291fa8194b924"), "ename" : "李元芳", "age" : 35 }
{ "_id" : ObjectId("5f9c22445df291fa8194b925"), "ename" : "李元静", "age" : 35 }
{ "_id" : ObjectId("5f9c227d5df291fa8194b926"), "ename" : "刘静", "age" : 25 }

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查询age>=30的员工姓名、年龄和薪资

> db.emp.find({"age":{$gte:30}},{"ename":1,"age":1,"salary":1})

{ "_id" : ObjectId("5f9c1dfc5df291fa8194b91c"), "ename" : "张三", "age" : 30, "salary" : 2500 }
{ "_id" : ObjectId("5f9c21055df291fa8194b91e"), "ename" : "李明", "age" : 30, "salary" : 1800 }
{ "_id" : ObjectId("5f9c21855df291fa8194b920"), "ename" : "张四", "age" : 32, "salary" : 8000 }
{ "_id" : ObjectId("5f9c219b5df291fa8194b921"), "ename" : "李四", "age" : 35, "salary" : 12000 }
{ "_id" : ObjectId("5f9c21a75df291fa8194b922"), "ename" : "李四", "age" : 35, "salary" : 12000 }
{ "_id" : ObjectId("5f9c22185df291fa8194b924"), "ename" : "李元芳", "age" : 35, "salary" : 8000 }
{ "_id" : ObjectId("5f9c22445df291fa8194b925"), "ename" : "李元静", "age" : 35, "salary" : 15000 }

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14. 排序

按照年龄升序排列

> db.emp.find().sort({"age":1})

{ "_id" : ObjectId("5f9c1c5b5df291fa8194b91b"), "empno" : 100, "ename" : "admin", "sex" : "男", "age" : 20, "salary" : 800, "deptno" : 10 }
{ "_id" : ObjectId("5f9c20945df291fa8194b91d"), "empno" : 102, "ename" : "张良", "sex" : "男", "age" : 25, "salary" : 3000, "deptno" : 20 }
{ "_id" : ObjectId("5f9c227d5df291fa8194b926"), "empno" : 110, "ename" : "刘静", "sex" : "女", "age" : 25, "salary" : 3500, "deptno" : 10 }
{ "_id" : ObjectId("5f9c21d85df291fa8194b923"), "empno" : 107, "ename" : "王三", "sex" : "女", "age" : 27, "salary" : 5000, "deptno" : 20 }
{ "_id" : ObjectId("5f9c215f5df291fa8194b91f"), "empno" : 104, "ename" : "李菲菲", "sex" : "女", "age" : 28, "salary" : 4200, "deptno" : 20 }
{ "_id" : ObjectId("5f9c1dfc5df291fa8194b91c"), "empno" : 101, "ename" : "张三", "sex" : "女", "age" : 30, "salary" : 2500, "deptno" : 20 }
{ "_id" : ObjectId("5f9c21055df291fa8194b91e"), "empno" : 103, "ename" : "李明", "sex" : "女", "age" : 30, "salary" : 1800, "deptno" : 30 }
{ "_id" : ObjectId("5f9c21855df291fa8194b920"), "empno" : 105, "ename" : "张四", "sex" : "男", "age" : 32, "salary" : 8000, "deptno" : 30 }
{ "_id" : ObjectId("5f9c219b5df291fa8194b921"), "empno" : 106, "ename" : "李四", "sex" : "男", "age" : 35, "salary" : 12000, "deptno" : 10 }
{ "_id" : ObjectId("5f9c21a75df291fa8194b922"), "empno" : 106, "ename" : "李四", "sex" : "男", "age" : 35, "salary" : 12000, "deptno" : 10 }
{ "_id" : ObjectId("5f9c22185df291fa8194b924"), "empno" : 108, "ename" : "李元芳", "sex" : "男", "age" : 35, "salary" : 8000, "deptno" : 30 }
{ "_id" : ObjectId("5f9c22445df291fa8194b925"), "empno" : 109, "ename" : "李元静", "sex" : "女", "age" : 35, "salary" : 15000, "deptno" : 36 }

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按照薪资降序排列

> db.emp.find().sort({salary:-1})

{ "_id" : ObjectId("5f9c22445df291fa8194b925"), "empno" : 109, "ename" : "李元静", "sex" : "女", "age" : 35, "salary" : 15000, "deptno" : 36 }
{ "_id" : ObjectId("5f9c219b5df291fa8194b921"), "empno" : 106, "ename" : "李四", "sex" : "男", "age" : 35, "salary" : 12000, "deptno" : 10 }
{ "_id" : ObjectId("5f9c21a75df291fa8194b922"), "empno" : 106, "ename" : "李四", "sex" : "男", "age" : 35, "salary" : 12000, "deptno" : 10 }
{ "_id" : ObjectId("5f9c21855df291fa8194b920"), "empno" : 105, "ename" : "张四", "sex" : "男", "age" : 32, "salary" : 8000, "deptno" : 30 }
{ "_id" : ObjectId("5f9c22185df291fa8194b924"), "empno" : 108, "ename" : "李元芳", "sex" : "男", "age" : 35, "salary" : 8000, "deptno" : 30 }
{ "_id" : ObjectId("5f9c21d85df291fa8194b923"), "empno" : 107, "ename" : "王三", "sex" : "女", "age" : 27, "salary" : 5000, "deptno" : 20 }
{ "_id" : ObjectId("5f9c215f5df291fa8194b91f"), "empno" : 104, "ename" : "李菲菲", "sex" : "女", "age" : 28, "salary" : 4200, "deptno" : 20 }
{ "_id" : ObjectId("5f9c227d5df291fa8194b926"), "empno" : 110, "ename" : "刘静", "sex" : "女", "age" : 25, "salary" : 3500, "deptno" : 10 }
{ "_id" : ObjectId("5f9c20945df291fa8194b91d"), "empno" : 102, "ename" : "张良", "sex" : "男", "age" : 25, "salary" : 3000, "deptno" : 20 }
{ "_id" : ObjectId("5f9c1dfc5df291fa8194b91c"), "empno" : 101, "ename" : "张三", "sex" : "女", "age" : 30, "salary" : 2500, "deptno" : 20 }
{ "_id" : ObjectId("5f9c21055df291fa8194b91e"), "empno" : 103, "ename" : "李明", "sex" : "女", "age" : 30, "salary" : 1800, "deptno" : 30 }
{ "_id" : ObjectId("5f9c1c5b5df291fa8194b91b"), "empno" : 100, "ename" : "admin", "sex" : "男", "age" : 20, "salary" : 800, "deptno" : 10 }

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15. 查询ename=admin且age=20的员工数据

> db.emp.find({ename:"admin",age:20})

{ "_id" : ObjectId("5f9c1c5b5df291fa8194b91b"), "empno" : 100, "ename" : "admin", "sex" : "男", "age" : 20, "salary" : 800, "deptno" : 10 }

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16. 查询前5条数据

> db.emp.find().limit(5)

{ "_id" : ObjectId("5f9c1c5b5df291fa8194b91b"), "empno" : 100, "ename" : "admin", "sex" : "男", "age" : 20, "salary" : 800, "deptno" : 10 }
{ "_id" : ObjectId("5f9c1dfc5df291fa8194b91c"), "empno" : 101, "ename" : "张三", "sex" : "女", "age" : 30, "salary" : 2500, "deptno" : 20 }
{ "_id" : ObjectId("5f9c20945df291fa8194b91d"), "empno" : 102, "ename" : "张良", "sex" : "男", "age" : 25, "salary" : 3000, "deptno" : 20 }
{ "_id" : ObjectId("5f9c21055df291fa8194b91e"), "empno" : 103, "ename" : "李明", "sex" : "女", "age" : 30, "salary" : 1800, "deptno" : 30 }
{ "_id" : ObjectId("5f9c215f5df291fa8194b91f"), "empno" : 104, "ename" : "李菲菲", "sex" : "女", "age" : 28, "salary" : 4200, "deptno" : 20 }

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17. 查询10条以后的数据

这里一共12条数据，查询10条以后的数据，结果是两条数据。

> db.emp.find().skip(10)

{ "_id" : ObjectId("5f9c22445df291fa8194b925"), "empno" : 109, "ename" : "李元静", "sex" : "女", "age" : 35, "salary" : 15000, "deptno" : 36 }
{ "_id" : ObjectId("5f9c227d5df291fa8194b926"), "empno" : 110, "ename" : "刘静", "sex" : "女", "age" : 25, "salary" : 3500, "deptno" : 10 }

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18. 查询集合中的总数据

一共12条数据

> db.emp.find().count()

12

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查询salary>=5000的员工数量

> db.emp.find({salary:{$gte:5000}}).count()

6

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验证（查询查询salary>=5000的员工数据，一共是6条。）

> db.emp.find({salary:{$gte:5000}})

{ "_id" : ObjectId("5f9c21855df291fa8194b920"), "empno" : 105, "ename" : "张四", "sex" : "男", "age" : 32, "salary" : 8000, "deptno" : 30 }
{ "_id" : ObjectId("5f9c219b5df291fa8194b921"), "empno" : 106, "ename" : "李四", "sex" : "男", "age" : 35, "salary" : 12000, "deptno" : 10 }
{ "_id" : ObjectId("5f9c21a75df291fa8194b922"), "empno" : 106, "ename" : "李四", "sex" : "男", "age" : 35, "salary" : 12000, "deptno" : 10 }
{ "_id" : ObjectId("5f9c21d85df291fa8194b923"), "empno" : 107, "ename" : "王三", "sex" : "女", "age" : 27, "salary" : 5000, "deptno" : 20 }
{ "_id" : ObjectId("5f9c22185df291fa8194b924"), "empno" : 108, "ename" : "李元芳", "sex" : "男", "age" : 35, "salary" : 8000, "deptno" : 30 }
{ "_id" : ObjectId("5f9c22445df291fa8194b925"), "empno" : 109, "ename" : "李元静", "sex" : "女", "age" : 35, "salary" : 15000, "deptno" : 36 }

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19. 分页查询

按照每页显示5条数据查询，一共12条数据，就要查询3页

第一页：
> db.emp.find().skip(0).limit(5)

{ "_id" : ObjectId("5f9c1c5b5df291fa8194b91b"), "empno" : 100, "ename" : "admin", "sex" : "男", "age" : 20, "salary" : 800, "deptno" : 10 }
{ "_id" : ObjectId("5f9c1dfc5df291fa8194b91c"), "empno" : 101, "ename" : "张三", "sex" : "女", "age" : 30, "salary" : 2500, "deptno" : 20 }
{ "_id" : ObjectId("5f9c20945df291fa8194b91d"), "empno" : 102, "ename" : "张良", "sex" : "男", "age" : 25, "salary" : 3000, "deptno" : 20 }
{ "_id" : ObjectId("5f9c21055df291fa8194b91e"), "empno" : 103, "ename" : "李明", "sex" : "女", "age" : 30, "salary" : 1800, "deptno" : 30 }
{ "_id" : ObjectId("5f9c215f5df291fa8194b91f"), "empno" : 104, "ename" : "李菲菲", "sex" : "女", "age" : 28, "salary" : 4200, "deptno" : 20 }

第二页：
> db.emp.find().skip(5).limit(5)

{ "_id" : ObjectId("5f9c21855df291fa8194b920"), "empno" : 105, "ename" : "张四", "sex" : "男", "age" : 32, "salary" : 8000, "deptno" : 30 }
{ "_id" : ObjectId("5f9c219b5df291fa8194b921"), "empno" : 106, "ename" : "李四", "sex" : "男", "age" : 35, "salary" : 12000, "deptno" : 10 }
{ "_id" : ObjectId("5f9c21a75df291fa8194b922"), "empno" : 106, "ename" : "李四", "sex" : "男", "age" : 35, "salary" : 12000, "deptno" : 10 }
{ "_id" : ObjectId("5f9c21d85df291fa8194b923"), "empno" : 107, "ename" : "王三", "sex" : "女", "age" : 27, "salary" : 5000, "deptno" : 20 }
{ "_id" : ObjectId("5f9c22185df291fa8194b924"), "empno" : 108, "ename" : "李元芳", "sex" : "男", "age" : 35, "salary" : 8000, "deptno" : 30 }

第三页：
> db.emp.find().skip(10).limit(5)

{ "_id" : ObjectId("5f9c22445df291fa8194b925"), "empno" : 109, "ename" : "李元静", "sex" : "女", "age" : 35, "salary" : 15000, "deptno" : 36 }
{ "_id" : ObjectId("5f9c227d5df291fa8194b926"), "empno" : 110, "ename" : "刘静", "sex" : "女", "age" : 25, "salary" : 3500, "deptno" : 10 }

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skip的值=（页数-1）* 每页显示数量
skip（N）：表示要查询第N条数据后的数据

20.关键字or的查询方式

查询年龄是30或者年龄是35的员工数据(注意写法)

> db.emp.find({$or:[{age:30},{age:35}]})

{ "_id" : ObjectId("5f9c1dfc5df291fa8194b91c"), "empno" : 101, "ename" : "张三", "sex" : "女", "age" : 30, "salary" : 2500, "deptno" : 20 }
{ "_id" : ObjectId("5f9c21055df291fa8194b91e"), "empno" : 103, "ename" : "李明", "sex" : "女", "age" : 30, "salary" : 1800, "deptno" : 30 }
{ "_id" : ObjectId("5f9c219b5df291fa8194b921"), "empno" : 106, "ename" : "李四", "sex" : "男", "age" : 35, "salary" : 12000, "deptno" : 10 }
{ "_id" : ObjectId("5f9c21a75df291fa8194b922"), "empno" : 106, "ename" : "李四", "sex" : "男", "age" : 35, "salary" : 12000, "deptno" : 10 }
{ "_id" : ObjectId("5f9c22185df291fa8194b924"), "empno" : 108, "ename" : "李元芳", "sex" : "男", "age" : 35, "salary" : 8000, "deptno" : 30 }
{ "_id" : ObjectId("5f9c22445df291fa8194b925"), "empno" : 109, "ename" : "李元静", "sex" : "女", "age" : 35, "salary" : 15000, "deptno" : 36 }

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21. 查询第一条数据

> db.emp.findOne()
{
        "_id" : ObjectId("5f9c1c5b5df291fa8194b91b"),
        "empno" : 100,
        "ename" : "admin",
        "sex" : "男",
        "age" : 20,
        "salary" : 800,
        "deptno" : 10
}

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或

> db.emp.find().limit(1)

{ "_id" : ObjectId("5f9c1c5b5df291fa8194b91b"), "empno" : 100, "ename" : "admin", "sex" : "男", "age" : 20, "salary" : 800, "deptno" : 10 }

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22. 查询当前表所在的数据库

> db.emp.getDB()

company

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六、更新数据

更新数据一定要有条件限制，并且需要加上$set否则会全部修改
第一个参数是条件，后面的参数是要修改的数据或者是其他操作，比如批量操作

1. 更新员工李元静的年龄为32岁

> db.emp.update({ename:"李元静"},{$set:{age:32}})

WriteResult({ "nMatched" : 1, "nUpserted" : 0, "nModified" : 1 })

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验证(查询姓名是李元静的员工数据)

> db.emp.find({ename:"李元静"})

{ "_id" : ObjectId("5f9c376a29491ade8d9d3e79"), "empno" : 109, "ename" : "李元静", "sex" : "女", "age" : 32, "salary" : 15000, "deptno" : 36 }

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2. 更新员工李元静的薪资为1600并且所在部门修改为30

> db.emp.update({ename:"李元静"},{$set:{salary:1600,deptno:30}})

WriteResult({ "nMatched" : 1, "nUpserted" : 0, "nModified" : 1 })

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验证(查询姓名是李元静的员工数据)

> db.emp.find({ename:"李元静"})

{ "_id" : ObjectId("5f9c376a29491ade8d9d3e79"), "empno" : 109, "ename" : "李元静", "sex" : "女", "age" : 32, "salary" : 1600, "deptno" : 30 }

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3. 批量更新数据

把年龄是35岁的更新为34岁
设置第三个参数：{multi:true}

> db.emp.update({age:35},{$set:{age:34}},{multi:true})

WriteResult({ "nMatched" : 3, "nUpserted" : 0, "nModified" : 3 })

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通过db.emp.find()验证所有数据没有年龄为35的员工

4. $inc使用

$inc将一个字段的值增加或者减少
把李元芳的年龄减少1岁，同时薪资加2000

> db.emp.update({ename:"李元芳"},{$inc:{age:-1,salary:2000}})

WriteResult({ "nMatched" : 1, "nUpserted" : 0, "nModified" : 1 })

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验证

> db.emp.find({ename:"李元芳"})

{ "_id" : ObjectId("5f9c22185df291fa8194b924"), "empno" : 108, "ename" : "李元芳", "sex" : "男", "age" : 33, "salary" : 10000, "deptno" : 30 }

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七、删除操作

1. 删除指定条件的数据

db.emp.remove({ename:"李元芳"})

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2. 删除所有数据

db.emp.remove({})

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3. 删除集合

db.emp.drop()

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4.删除数据库

db.dropDatabase()

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5. 温馨提示

对数据库数据执行删除操作时，记得加条件！

八、MongoDB数据库索引

MongoDB数据库索引是指对数据库集合中的一列或者多列进行排序的一种结构，可以大大缩减我们在使用数据库查询时候的时间，其用法和关系型数据库一样。

1. 模拟批量插入数据

在使用数据库前，我们创建一个com数据库和users集合，模拟60万条数据
PS:插入60万条数据大概需要5分钟

> use com
switched to db com
> for(var i=0;i<600000;i++){
... db.users.insert({userNo:i,userName:"张三"+i,age:28,phone:"13000"+i})
... }
WriteResult({ "nInserted" : 1 })

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验证数据

> db.users.find().count()
600000

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2.无索引查询所耗费时间

命令： 
db.users.find({userNo:599999}).explain("executionStats")

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> db.users.find({userNo:599999}).explain("executionStats")
{
        "queryPlanner" : {
                "plannerVersion" : 1,
                "namespace" : "com.users",
                "indexFilterSet" : false,
                "parsedQuery" : {
                        "userNo" : {
                                "$eq" : 599999
                        }
                },
                "winningPlan" : {
                        "stage" : "COLLSCAN",
                        "filter" : {
                                "userNo" : {
                                        "$eq" : 599999
                                }
                        },
                        "direction" : "forward"
                },
                "rejectedPlans" : [ ]
        },
        "executionStats" : {
                "executionSuccess" : true,
                "nReturned" : 1,
                "executionTimeMillis" : 254,
                "totalKeysExamined" : 0,
                "totalDocsExamined" : 600000,
                "executionStages" : {
                        "stage" : "COLLSCAN",
                        "filter" : {
                                "userNo" : {
                                        "$eq" : 599999
                                }
                        },
                        "nReturned" : 1,
                        "executionTimeMillisEstimate" : 3,
                        "works" : 600002,
                        "advanced" : 1,
                        "needTime" : 600000,
                        "needYield" : 0,
                        "saveState" : 600,
                        "restoreState" : 600,
                        "isEOF" : 1,
                        "direction" : "forward",
                        "docsExamined" : 600000
                }
        },
        "serverInfo" : {
                "host" : "thinkPadE580",
                "port" : 27017,
                "version" : "4.4.2-rc0",
                "gitVersion" : "b5fafa1f87dda6f8773c5a8a1a5e7776d4d94da7"
        },
        "ok" : 1
}

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通过"executionTimeMillis" : 254可以知道查询所耗费时间为254毫秒，当然这与计算机配置性能有关。

3. 创建索引

为userNo创建索引

命令：
	db.users.ensureIndex({userNo:1})

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> db.users.ensureIndex({userNo:1})
{
        "createdCollectionAutomatically" : false,
        "numIndexesBefore" : 1,
        "numIndexesAfter" : 2,
        "ok" : 1
}

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4. 查询索引

命令：
	db.users.getIndexes()

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> db.users.getIndexes()
[
        {
                "v" : 2,
                "key" : {
                        "_id" : 1
                },
                "name" : "_id_"
        },
        {
                "v" : 2,
                "key" : {
                        "userNo" : 1
                },
                "name" : "userNo_1"
        }
]

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_id为集合默认id索引,userNo是自定义索引

5. 使用索引查询所耗费时间

> db.users.find({userNo:599999}).explain("executionStats")
{
        "queryPlanner" : {
                "plannerVersion" : 1,
                "namespace" : "com.users",
                "indexFilterSet" : false,
                "parsedQuery" : {
                        "userNo" : {
                                "$eq" : 599999
                        }
                },
                "winningPlan" : {
                        "stage" : "FETCH",
                        "inputStage" : {
                                "stage" : "IXSCAN",
                                "keyPattern" : {
                                        "userNo" : 1
                                },
                                "indexName" : "userNo_1",
                                "isMultiKey" : false,
                                "multiKeyPaths" : {
                                        "userNo" : [ ]
                                },
                                "isUnique" : false,
                                "isSparse" : false,
                                "isPartial" : false,
                                "indexVersion" : 2,
                                "direction" : "forward",
                                "indexBounds" : {
                                        "userNo" : [
                                                "[599999.0, 599999.0]"
                                        ]
                                }
                        }
                },
                "rejectedPlans" : [ ]
        },
        "executionStats" : {
                "executionSuccess" : true,
                "nReturned" : 1,
                "executionTimeMillis" : 84,
                "totalKeysExamined" : 1,
                "totalDocsExamined" : 1,
                "executionStages" : {
                        "stage" : "FETCH",
                        "nReturned" : 1,
                        "executionTimeMillisEstimate" : 0,
                        "works" : 2,
                        "advanced" : 1,
                        "needTime" : 0,
                        "needYield" : 0,
                        "saveState" : 0,
                        "restoreState" : 0,
                        "isEOF" : 1,
                        "docsExamined" : 1,
                        "alreadyHasObj" : 0,
                        "inputStage" : {
                                "stage" : "IXSCAN",
                                "nReturned" : 1,
                                "executionTimeMillisEstimate" : 0,
                                "works" : 2,
                                "advanced" : 1,
                                "needTime" : 0,
                                "needYield" : 0,
                                "saveState" : 0,
                                "restoreState" : 0,
                                "isEOF" : 1,
                                "keyPattern" : {
                                        "userNo" : 1
                                },
                                "indexName" : "userNo_1",
                                "isMultiKey" : false,
                                "multiKeyPaths" : {
                                        "userNo" : [ ]
                                },
                                "isUnique" : false,
                                "isSparse" : false,
                                "isPartial" : false,
                                "indexVersion" : 2,
                                "direction" : "forward",
                                "indexBounds" : {
                                        "userNo" : [
                                                "[599999.0, 599999.0]"
                                        ]
                                },
                                "keysExamined" : 1,
                                "seeks" : 1,
                                "dupsTested" : 0,
                                "dupsDropped" : 0
                        }
                }
        },
        "serverInfo" : {
                "host" : "thinkPadE580",
                "port" : 27017,
                "version" : "4.4.2-rc0",
                "gitVersion" : "b5fafa1f87dda6f8773c5a8a1a5e7776d4d94da7"
        },
        "ok" : 1
}

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用索引查询userNo的值，可以通过"executionTimeMillisEstimate" : 0知道，所耗费的时间为0毫秒，大大缩短了查询速度

6. 删除索引

命令：
	 db.users.dropIndex({userNo:1})

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验证

> db.users.dropIndex({userNo:1})
{ "nIndexesWas" : 2, "ok" : 1 }

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可以看出，我们自定义的索引已经删除

7. 复合索引

当要对多个字段进行经常性大量查询的时候，我们可以设置复合索引

> db.users.ensureIndex({userNo:1,userName:1})
{
        "createdCollectionAutomatically" : false,
        "numIndexesBefore" : 1,
        "numIndexesAfter" : 2,
        "ok" : 1
}

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查看复合索引

> db.users.getIndexes()
[
        {
                "v" : 2,
                "key" : {
                        "_id" : 1
                },
                "name" : "_id_"
        },
        {
                "v" : 2,
                "key" : {
                        "userNo" : 1,
                        "userName" : 1
                },
                "name" : "userNo_1_userName_1"
        }
]

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userNo和userName是我们自定义的索引
查询userName:”张三599999”所耗费时间

> db.users.find({userNo:599999,userName:"张三599999"}).explain("executionStats")))
{
        "queryPlanner" : {
                "plannerVersion" : 1,
                "namespace" : "com.users",
                "indexFilterSet" : false,
                "parsedQuery" : {
                        "$and" : [
                                {
                                        "userName" : {
                                                "$eq" : "张三599999"
                                        }
                                },
                                {
                                        "userNo" : {
                                                "$eq" : 599999
                                        }
                                }
                        ]
                },
                "winningPlan" : {
                        "stage" : "FETCH",
                        "inputStage" : {
                                "stage" : "IXSCAN",
                                "keyPattern" : {
                                        "userNo" : 1,
                                        "userName" : 1
                                },
                                "indexName" : "userNo_1_userName_1",
                                "isMultiKey" : false,
                                "multiKeyPaths" : {
                                        "userNo" : [ ],
                                        "userName" : [ ]
                                },
                                "isUnique" : false,
                                "isSparse" : false,
                                "isPartial" : false,
                                "indexVersion" : 2,
                                "direction" : "forward",
                                "indexBounds" : {
                                        "userNo" : [
                                                "[599999.0, 599999.0]"
                                        ],
                                        "userName" : [
                                                "[\"张三599999\", \"张三599999\"]"
                                        ]
                                }
                        }
                },
                "rejectedPlans" : [ ]
        },
        "executionStats" : {
                "executionSuccess" : true,
                "nReturned" : 1,
                "executionTimeMillis" : 2,
                "totalKeysExamined" : 1,
                "totalDocsExamined" : 1,
                "executionStages" : {
                        "stage" : "FETCH",
                        "nReturned" : 1,
                        "executionTimeMillisEstimate" : 0,
                        "works" : 2,
                        "advanced" : 1,
                        "needTime" : 0,
                        "needYield" : 0,
                        "saveState" : 0,
                        "restoreState" : 0,
                        "isEOF" : 1,
                        "docsExamined" : 1,
                        "alreadyHasObj" : 0,
                        "inputStage" : {
                                "stage" : "IXSCAN",
                                "nReturned" : 1,
                                "executionTimeMillisEstimate" : 0,
                                "works" : 2,
                                "advanced" : 1,
                                "needTime" : 0,
                                "needYield" : 0,
                                "saveState" : 0,
                                "restoreState" : 0,
                                "isEOF" : 1,
                                "keyPattern" : {
                                        "userNo" : 1,
                                        "userName" : 1
                                },
                                "indexName" : "userNo_1_userName_1",
                                "isMultiKey" : false,
                                "multiKeyPaths" : {
                                        "userNo" : [ ],
                                        "userName" : [ ]
                                },
                                "isUnique" : false,
                                "isSparse" : false,
                                "isPartial" : false,
                                "indexVersion" : 2,
                                "direction" : "forward",
                                "indexBounds" : {
                                        "userNo" : [
                                                "[599999.0, 599999.0]"
                                        ],
                                        "userName" : [
                                                "[\"张三599999\", \"张三599999\"]"
                                        ]
                                },
                                "keysExamined" : 1,
                                "seeks" : 1,
                                "dupsTested" : 0,
                                "dupsDropped" : 0
                        }
                }
        },
        "serverInfo" : {
                "host" : "thinkPadE580",
                "port" : 27017,
                "version" : "4.4.2-rc0",
                "gitVersion" : "b5fafa1f87dda6f8773c5a8a1a5e7776d4d94da7"
        },
        "ok" : 1
}

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通过"executionTimeMillis" : 2,可以看出，查询userNo和userName只需要2毫秒
注意：如果在一个集合中，对多个字段设置索引N（N!=1），在使用复合索引查询的时候，要连同第一个索引字段一起查询，如果只单单查询第N个,索引将没有效果。

8.唯一索引

创建唯一索引的条件是，集合中字段的数据不能重复，但在缺省情况下创建是索引均不是唯一索引
由于集合中的age都是一样的值，在给age创建唯一索引的时候会报错

命令：
	> db.users.ensure({age:1},{unique:true})

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为age创建唯一索引，失败

> db.users.ensure({age:1},{unique:true})
TypeError: db.users.ensure is not a function :
@(shell):1:1

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以上就是MongoDB 4.X基础教程的详细内容，转载自php中文网

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浏览次数：1056 次浏览
发布日期：2023-05-24 10:01:01
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