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MongoDB 4.X basic tutorial

P粉469731340Original: 2022-07-18 10:09:141591browse

1. Introduction to MongoDB

##MongoDB is a database based on distributed file storage.
is written in C language. Designed to provide scalable, high-performance data storage solutions for WEB applications.
MongoDB is a product between a relational database and a non-relational database. It is the most feature-rich among non-relational databases and is most like a relational database.
The data structure supported by MongoDB is very loose and is a BJSON format similar to JSON, so it can store more complex data types. The biggest feature of Mongo is that the query language it supports is very powerful. Its syntax is somewhat similar to an object-oriented query language. It can almost realize most functions similar to single-table queries in relational databases, and it also supports indexing of data.
MongoDB data operation is based on json format

<span style="font-size: 16px;"> { "userName":"admin", "password":123456 }<br/></span>

2. MongoDB installation

1.MongoDB download

Website: https://www .mongodb.com/try/download/community
##The above picture is based on your own system when selecting the version Choose from Windows, LInux, CentOS, Ubuntu, etc.

2.MongoDB installation

Downloaded .msi file, double-click the file after downloading and follow the instructions to install it.
#During the installation process, you can set your installation directory by clicking the "Custom" button. It is recommended not to install on the C drive.

MongoDB 4.X basic tutorial

Click next to install, but you need to pay attention to this step. Here is the installation of visual components. The default is the selected state. You need to uncheck it here, otherwise the visual components will be downloaded during the installation process, which is relatively slow, and sometimes an error will be reported:

MongoDB 4.X basic tutorial

##3. MongoDB environment variable configuration

##Right-click this computer on the desktop>>>Properties> ;>>Advanced System Settings>>>Advanced>>>Environment Variables>>>Find path>>>Select Edit>>>New

MongoDB 4.X basic tutorial

Copy the bin path of the MongoDB installation in the opened environment variable to the newly created directory

MongoDB 4.X basic tutorial

Then click OK to complete the environment variable configuration

Open CMD In the command window, enter mongo. The following prompt message appears, indicating that the installation is successful.

<span style="font-size: 16px;">C:\Users\***.DESKTOP-C1RC9P2>mongo<br/>MongoDB shell version v4.4.2-rc0<br/>connecting to: mongodb://127.0.0.1:27017/?compressors=disabled&gssapiServiceName=mongodb<br/>Implicit session: session { "id" : UUID("df31999e-cb62-4f71-8a18-7db8723c514f") }<br/>MongoDB server version: 4.4.2-rc0<br/>---<br/>The server generated these startup warnings when booting:<br/>        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<br/>---<br/>---<br/>        Enable MongoDB&#39;s free cloud-based monitoring service, which will then receive and display<br/>        metrics about your deployment (disk utilization, CPU, operation statistics, etc).<br/><br/>        The monitoring data will be available on a MongoDB website with a unique URL accessible to you<br/>        and anyone you share the URL with. MongoDB may use this information to make product<br/>        improvements and to suggest MongoDB products and deployment options to you.<br/><br/>        To enable free monitoring, run the following command: db.enableFreeMonitoring()<br/>        To permanently disable this reminder, run the following command: db.disableFreeMonitoring()<br/></span>

MongoDB It is a non-relational database, and its database, tables, fields, etc. are somewhat different from relational databases (such as MySQL database);

Collections in MongoDB It is equivalent to the table in the relational database. The key of the json string in MongoDB is equivalent to the column name in the relational database;
When operating MongoDB data All times use json data format.

查看所有数据库名

<span style="font-size: 16px;">命令：<br/>  show dbs<br/></span>

<span style="font-size: 16px;">  > show dbs<br/>  admin   0.000GB<br/>  config  0.000GB<br/>  local   0.000GB<br/></span>

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 
> use admin switched to db admin > show collections system.version 
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() 
> db.system.version.find() { "_id" : "featureCompatibilityVersion", "version" : "4.4" } 
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 }) 
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 }) 
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 })
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() 
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 } 
2.去掉集合中重复的数据
命令： > db.集合名.distinct("ename") 
> 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" ] 
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 } 
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 } 
5. 查询age>30岁的员工数据
> db.emp.find({"age":{$gt:30}}) { "_id" : ObjectId("5f9c21855df291fa8194b920"), "empno" : 105, "ename" : "张四", "sex" : "男", "age" : 32, "salary" : 8000, "deptno" : 30 } { "_id" : ObjectId("5f9c219b5df291fa8194b921"), "empno" : 106, "ename" : "李四", "sex" : "男", "age" : 35, "salary" : 12000, "deptno" : 10 } { "_id" : ObjectId("5f9c21a75df291fa8194b922"), "empno" : 106, "ename" : "李四", "sex" : "男", "age" : 35, "salary" : 12000, "deptno" : 10 } { "_id" : ObjectId("5f9c22185df291fa8194b924"), "empno" : 108, "ename" : "李元芳", "sex" : "男", "age" : 35, "salary" : 8000, "deptno" : 30 } { "_id" : ObjectId("5f9c22445df291fa8194b925"), "empno" : 109, "ename" : "李元静", "sex" : "女", "age" : 35, "salary" : 15000, "deptno" : 36 } 
6. 查询age
> db.emp.find({"age":{$lt:25}}) { "_id" : ObjectId("5f9c1c5b5df291fa8194b91b"), "empno" : 100, "ename" : "admin", "sex" : "男", "age" : 20, "salary" : 800, "deptno" : 10 } 
7.查询age>=30的员工数据
> db.emp.find({"age":{$gte:30}}) { "_id" : ObjectId("5f9c1dfc5df291fa8194b91c"), "empno" : 101, "ename" : "张三", "sex" : "女", "age" : 30, "salary" : 2500, "deptno" : 20 } { "_id" : ObjectId("5f9c21055df291fa8194b91e"), "empno" : 103, "ename" : "李明", "sex" : "女", "age" : 30, "salary" : 1800, "deptno" : 30 } { "_id" : ObjectId("5f9c21855df291fa8194b920"), "empno" : 105, "ename" : "张四", "sex" : "男", "age" : 32, "salary" : 8000, "deptno" : 30 } { "_id" : ObjectId("5f9c219b5df291fa8194b921"), "empno" : 106, "ename" : "李四", "sex" : "男", "age" : 35, "salary" : 12000, "deptno" : 10 } { "_id" : ObjectId("5f9c21a75df291fa8194b922"), "empno" : 106, "ename" : "李四", "sex" : "男", "age" : 35, "salary" : 12000, "deptno" : 10 } { "_id" : ObjectId("5f9c22185df291fa8194b924"), "empno" : 108, "ename" : "李元芳", "sex" : "男", "age" : 35, "salary" : 8000, "deptno" : 30 } { "_id" : ObjectId("5f9c22445df291fa8194b925"), "empno" : 109, "ename" : "李元静", "sex" : "女", "age" : 35, "salary" : 15000, "deptno" : 36 } 
8. 查询age
> db.emp.find({"age":{$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 } 
9. 查询age>=25并且age
> 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 } 
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 } 
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 } 
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 } 
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 } 
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 } 
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 } 
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 } 
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 } 
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 } 
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 } 
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 } 
18. 查询集合中的总数据

一共12条数据
> db.emp.find().count() 12 
查询salary>=5000的员工数量
> db.emp.find({salary:{$gte:5000}}).count() 6 
验证（查询查询salary>=5000的员工数据，一共是6条。）
> db.emp.find({salary:{$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 } 
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 } 

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 } 
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 } 
或
> db.emp.find().limit(1) { "_id" : ObjectId("5f9c1c5b5df291fa8194b91b"), "empno" : 100, "ename" : "admin", "sex" : "男", "age" : 20, "salary" : 800, "deptno" : 10 } 

22. 查询当前表所在的数据库
> db.emp.getDB() company 
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"},{$set:{age:32}}) WriteResult({ "nMatched" : 1, "nUpserted" : 0, "nModified" : 1 }) 
验证(查询姓名是李元静的员工数据)
> db.emp.find({ename:"李元静"}) { "_id" : ObjectId("5f9c376a29491ade8d9d3e79"), "empno" : 109, "ename" : "李元静", "sex" : "女", "age" : 32, "salary" : 15000, "deptno" : 36 } 
2. 更新员工李元静的薪资为1600并且所在部门修改为30
> db.emp.update({ename:"李元静"},{$set:{salary:1600,deptno:30}}) WriteResult({ "nMatched" : 1, "nUpserted" : 0, "nModified" : 1 }) 
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 } 
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 }) 
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 }) 
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 } 
七、删除操作

1. 删除指定条件的数据
db.emp.remove({ename:"李元芳"}) 
2. 删除所有数据
db.emp.remove({}) 
3. 删除集合
db.emp.drop() 
4.删除数据库
db.dropDatabase() 
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 }) 
验证数据
> db.users.find().count() 600000 
2.无索引查询所耗费时间
命令： db.users.find({userNo:599999}).explain("executionStats") 
> 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 } 
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}) 
> db.users.ensureIndex({userNo:1}) { "createdCollectionAutomatically" : false, "numIndexesBefore" : 1, "numIndexesAfter" : 2, "ok" : 1 } 
4. 查询索引
命令： db.users.getIndexes() 
> db.users.getIndexes() [ { "v" : 2, "key" : { "_id" : 1 }, "name" : "_id_" }, { "v" : 2, "key" : { "userNo" : 1 }, "name" : "userNo_1" } ] 
_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 } 
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}) 
验证
> db.users.dropIndex({userNo:1}) { "nIndexesWas" : 2, "ok" : 1 } 
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 } 
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" } ] 

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 } 

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}) 
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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