MongoDB 4.X basic tutorial

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