【DataBase】MongoDB常用命令

MongoDB 常用命令

登陆和退出

mongo命令行直接加 MongoDB 服务的 IP 地址，就可以使用默认端口27017登陆 MongoDB,进入命令行交互环境。使用exit，回车则退出交互环境。

# mongo 127.0.0.1
MongoDB shell version v3.6.12
connecting to: mongodb://127.0.0.1:27017/test?gssapiServiceName=mongodb
Implicit session: session { "id" : UUID("0d27a9a2-b6d3-40d7-8af3-e1be57f89fb0") }
MongoDB server version: 3.6.12

数据库级操作

查看数据库

> show dbs
admin   0.000GB
config  0.000GB
local   0.000GB
wiki    0.001GB

使用指定库

>use wiki
switched to db wiki

查看所有数据集

> show collections
bruteforces
entries
sessions
settings
uplfiles
uplfolders
users

创建数据库

使用use可以直接创建数据库，不过直到插入数据时，使用 show dbs才能看到库

> use test
switched to db test
> show dbs
admin   0.000GB
config  0.000GB
local   0.000GB
wiki    0.001GB
> db.hello.insert({"name":"mongodb"})
WriteResult({ "nInserted" : 1 })
> show dbs
admin   0.000GB
config  0.000GB
local   0.000GB
test    0.000GB
wiki    0.001GB

查看当前使用的库

> db
test

删除数据库

> db.dropDatabase()
{ "dropped" : "test", "ok" : 1 }

> db
test
> show dbs
admin   0.000GB
config  0.000GB
local   0.000GB
wiki    0.001GB

Collection 级操作

新建 collection

> db.createCollection("user"){"ok":1}> show collections
hello
user

效果与使用 db.user.insert({"user":"xxx"})类似。

删除 collection

> db.user.drop()
true
> show collections
hello
> db.user.drop() ### 再删除已经不存在
false

重命名 collection

> show collections
hello
> db.hello.renameCollection("HELLO"){"ok":1}> show collections
HELLO

查看所有 collection

> show collections
HELLO

创建索引在 HELLO 集合上，建立对 Name 字段的索引,1 代表正序

> db.HELLO.ensureIndex({NAME:1})

Record 级的操作

使用实现存在的 test 数据库做测试，其中有个 Collection:user

插入数据

向 user 插入数据

> db.user.insert({'name':'Gal Gadot','gender':'female','age':28,'salary':11000})
> db.user.insert({'name':'Mikie Hara','gender':'female','age':26,'salary':7000})

也可以使用save插入

> db.user.save({'name':'Wentworth Earl Miller','gender':'male','age':41,'salary':33000})

查找记录

查看集合所有记录

> db.user.find(){"_id":ObjectId("5ce4f4c33e7e1703c34ec0d1"),"name":"Gal Gadot","gender":"female","age":28,"salary":11000}{"_id":ObjectId("5ce4f4d03e7e1703c34ec0d2"),"name":"Mikie Hara","gender":"female","age":26,"salary":7000}{"_id":ObjectId("5ce4f4dc3e7e1703c34ec0d3"),"name":"Wentworth Earl Miller","gender":"male","age":41,"salary":33000}

查找符合记录的记录

• Exact Equal

> db.user.find({"age":26}){"\_id":ObjectId("5ce4f4d03e7e1703c34ec0d2"),"name":"Mikie Hara","gender":"female","age":26,"salary":7000}

• Great Than

> db.user.find({salary:{\$gt:7000}})
> { "\_id" : ObjectId("5ce4f4c33e7e1703c34ec0d1"), "name" : "Gal Gadot", "gender" : "female", "age" : 28, "salary" : 11000 }
> { "\_id" : ObjectId("5ce4f4dc3e7e1703c34ec0d3"), "name" : "Wentworth Earl Miller", "gender" : "male", "age" : 41, "salary" : 33000 }

• Fuzzy Match

查看名称中包含‘a’的数据

> db.user.find({name:/a/}){"_id":ObjectId("5ce4f4c33e7e1703c34ec0d1"),"name":"Gal Gadot","gender":"female","age":28,"salary":11000}{"_id":ObjectId("5ce4f4d03e7e1703c34ec0d2"),"name":"Mikie Hara","gender":"female","age":26,"salary":7000}{"_id":ObjectId("5ce4f4dc3e7e1703c34ec0d3"),"name":"Wentworth Earl Miller","gender":"male","age":41,"salary":33000}

查询 name 以 W 打头的数据

> db.user.find({name:/^W/}){"_id":ObjectId("5ce4f4dc3e7e1703c34ec0d3"),"name":"Wentworth Earl Miller","gender":"male","age":41,"salary":33000}

• 多条件“与”

查询 age 小于 30，salary 大于 6000 的数据

> db.user.find({age:{$lt:30},salary:{$gt:6000}})
{ "_id" : ObjectId("5ce4f4c33e7e1703c34ec0d1"), "name" : "Gal Gadot", "gender" : "female", "age" : 28, "salary" : 11000 }
{ "_id" : ObjectId("5ce4f4d03e7e1703c34ec0d2"), "name" : "Mikie Hara", "gender" : "female", "age" : 26, "salary" : 7000 }

• 多条件“或”

查询 age 小于 25，或者 salary 大于 10000 的记录

> db.user.find({$or:[{salary:{$gt:10000}},{age:{$lt:25}}]})
{ "_id" : ObjectId("5ce4f4c33e7e1703c34ec0d1"), "name" : "Gal Gadot", "gender" : "female", "age" : 28, "salary" : 11000 }
{ "_id" : ObjectId("5ce4f4dc3e7e1703c34ec0d3"), "name" : "Wentworth Earl Miller", "gender" : "male","age" : 41, "salary" : 33000 }

• 查询一条记录

db.user.findOne({$or:[{salary:{$gt:10000}},{age:{\$lt:25}}]})
{
"\_id" : ObjectId("5ce4f4c33e7e1703c34ec0d1"),
"name" : "Gal Gadot",
"gender" : "female",
"age" : 28,
"salary" : 11000
}

• 查询记录中的指定列

> db.user.find({},{name:1,age:1,salary:1,sex_orientation:true}){"\_id":ObjectId("5ce4f4c33e7e1703c34ec0d1"),"name":"Gal Gadot","age":28,"salary":11000}{"\_id":ObjectId("5ce4f4d03e7e1703c34ec0d2"),"name":"Mikie Hara","age":26,"salary":7000}{"\_id":ObjectId("5ce4f4dc3e7e1703c34ec0d3"),"name":"Wentworth Earl Miller","age":41,"salary":33000}

这里的 1 表示显示此列的意思，也可以用 true 表示。

• 查询指定字段的数据，并去重

> db.user.distinct('gender')["female","male"]

对查询结果集的操作

mongo也提供了pretty print工具，db.collection.pretty()或者是db.collection.forEach(printjson)

• Pretty Print

> db.user.find().pretty(){"\_id":ObjectId("5ce4f4c33e7e1703c34ec0d1"),"name":"Gal Gadot","gender":"female","age":28,"salary":11000}{"\_id":ObjectId("5ce4f4d03e7e1703c34ec0d2"),"name":"Mikie Hara","gender":"female","age":26,"salary":7000}{"\_id":ObjectId("5ce4f4dc3e7e1703c34ec0d3"),"name":"Wentworth Earl Miller","gender":"male","age":41,"salary":33000}

• 指定结果集返回条目

> db.user.find().limit(2)
> { "\_id" : ObjectId("5ce4f4c33e7e1703c34ec0d1"), "name" : "Gal Gadot", "gender" : "female", "age" : 28, "salary" : 11000 }
> { "\_id" : ObjectId("5ce4f4d03e7e1703c34ec0d2"), "name" : "Mikie Hara", "gender" : "female", "age" : 26, "salary" : 7000 }

• 查询第一条以外的数据

> db.user.find().skip(1){"\_id":ObjectId("5ce4f4d03e7e1703c34ec0d2"),"name":"Mikie Hara","gender":"female","age":26,"salary":7000}{"\_id":ObjectId("5ce4f4dc3e7e1703c34ec0d3"),"name":"Wentworth Earl Miller","gender":"male","age":41,"salary":33000}

• 对结果集排序

升序

> db.user.find().sort({salary:1}){"_id":ObjectId("5ce4f4d03e7e1703c34ec0d2"),"name":"Mikie Hara","gender":"female","age":26,"salary":7000}{"_id":ObjectId("5ce4f4c33e7e1703c34ec0d1"),"name":"Gal Gadot","gender":"female","age":28,"salary":11000}{"_id":ObjectId("5ce4f4dc3e7e1703c34ec0d3"),"name":"Wentworth Earl Miller","gender":"male","age":41,"salary":33000}

降序

> db.user.find().sort({salary:-1}){"_id":ObjectId("5ce4f4dc3e7e1703c34ec0d3"),"name":"Wentworth Earl Miller","gender":"male","age":41,"salary":33000}{"_id":ObjectId("5ce4f4c33e7e1703c34ec0d1"),"name":"Gal Gadot","gender":"female","age":28,"salary":11000}{"_id":ObjectId("5ce4f4d03e7e1703c34ec0d2"),"name":"Mikie Hara","gender":"female","age":26,"salary":7000}

• 统计结果集中的记录数量

> db.user.find().count()
> 3

删除记录

删除整个集合中的所有数据

> db.test.remove()

删除集合中符合过滤条件的数据

> db.test.remove({name:/aws/})

删除符合条件的一条记录

> db.test.remove({name:/aws/},1)

更新操作

db.collection.update(criteria, objNew, upsert, multi )

• criteria:update 的查询条件，类似 sql update 查询内 where 后面的
• objNew:update 的对象和一些更新的操作符（如inc...）等，也可以理解为 sql update 查询内 set 后面的。
• upsert : 如果不存在 update 的记录，是否插入 objNew,true 为插入，默认是 false，不插入。
• multi : mongodb 默认是 false,只更新找到的第一条记录，如果这个参数为 true,就把按条件查出来多条记录全部更新。

> db.user.find()
> { "\_id" : ObjectId("52453cfb25e437dfea8fd4f4"), "name" : "Gal Gadot", "gender" : "female", "age" : 28, "salary" : 11000 }
> { "\_id" : ObjectId("52453d8525e437dfea8fd4f5"), "name" : "Mikie Hara", "gender" : "female", "age" : 26, "salary" : 7000 }
> { "\_id" : ObjectId("52453e2125e437dfea8fd4f6"), "name" : "Wentworth Earl Miller", "gender" : "male", "age" : 41, "salary" : 33000 }

更新符合过滤条件的信息

> db.user.update({name:'Gal Gadot'},{\$set:{age:23}},false,true)
> db.user.find()
> { "\_id" : ObjectId("52453cfb25e437dfea8fd4f4"), "name" : "Gal Gadot", "gender" : "female", "age" : 23, "salary" : 11000 }
> { "\_id" : ObjectId("52453d8525e437dfea8fd4f5"), "name" : "Mikie Hara", "gender" : "female", "age" : 26, "salary" : 7000 }
> { "\_id" : ObjectId("52453e2125e437dfea8fd4f6"), "name" : "Wentworth Earl Miller", "gender" : "male", "age" : 41, "salary" : 33000 }

添加新的字段

> db.user.update({name:'Mikie Hara'},{\$set:{interest:"CBA"}},false,true)
> db.user.find()
> { "\_id" : ObjectId("52453cfb25e437dfea8fd4f4"), "name" : "Gal Gadot", "gender" : "female", "age" : 23, "salary" : 11000 }
> { "\_id" : ObjectId("52453d8525e437dfea8fd4f5"), "name" : "Mikie Hara", "gender" : "female","interest" : "CBA", "age" : 26, "salary" : 7000 }
> { "\_id" : ObjectId("52453e2125e437dfea8fd4f6"), "name" : "Wentworth Earl Miller", "gender" : "male", "age" : 41, "salary" : 33000 }

使用函数 $inc

> db.user.update({gender:'female'},{\$inc:{salary:50}},false,true)
> db.user.find()
> { "\_id" : ObjectId("52453cfb25e437dfea8fd4f4"), "name" : "Gal Gadot", "gender" : "female", "age" : 23, "salary" : 11050 }
> { "\_id" : ObjectId("52453d8525e437dfea8fd4f5"), "name" : "Mikie Hara", "gender" : "female","interest" : "CBA", "age" : 26, "salary" : 7050 }
> { "\_id" : ObjectId("52453e2125e437dfea8fd4f6"), "name" : "Wentworth Earl Miller", "gender" : "male", "age" : 41, "salary" : 33000 }

关于更新操作db.collection.update(criteria, objNew, upsert, multi )，要说明的是，如果upsert为true，那么在没有找到符合更新条件的情况下，mongo 会在集合中插入一条记录其值满足更新条件的记录(其中的 字段只有更新条件中涉及的字段，字段的值满足更新条件)，然后将其更新（注意，如果更新条件是$lt 这种不等式条件，那么 upsert 插入的记录只会包含 更新操作涉及的字段，而不会有更新条件中的字段，因为没法为这种字段定值，mongo 索性就不取这些字段）。如果符合条件的记录中没有要更 新的字段，那么 mongo 会为其创建该字段，并更新。