文档操作补充与MongoDB查询

目录

  • 文档操作补充

  • 用户权限管理

  • 查询关键字

  • 分组与聚合

  • 其他查询补充

 

文档操作补充

涉及到数据的嵌套查找 支持直接点键或者索引

db.t1.deleteOne({'addr.counytry':'SH'})

db.t1.deleteOne({'hobby.1':'tea'})

 

 

 

用户权限管理

"""涉及到用户权限相关 引号推荐全部使用双引号"""
mongodb针对用户权限的创建,数据可以保存在不同的数据库下
之后在登录的时候只需要自己指定账户数据来源于哪个数据库即可
但是管理员用户数据一般情况下推荐保存到admin库下
而普通用户任意库都可以,我们为了便于管理可以在test库下创建

一、管理员账户需要在admin数据库下创建

1.切换到admin数据库下
        use admin
    2.创建账户并且赋予权限
        db.createUser(
          {
            user: "root",
            pwd: "123",
            roles: [ { role: "root", db: "admin" } ]
          }
        )

 

 

 其他用户在test数据库下创建

1.切换到test数据库下
        use test
    2.创建账户并赋予权限
        db.createUser(
          {
            user: "ben",
            pwd: "123",
            roles: [ { role: "readWrite", db: "test" },
                     { role: "read", db: "db1" } ]
          }
        )

# 针对test库用于读写的权限  针对db1库只拥有读的权限

二、使用管理员打开cmd操作下列命令

1.先停止服务
        net stop MongoDB
2.再移除服务
        MongoD --remove
3.再次添加
        mongod --bind_ip 0.0.0.0 --port 27017 --logpath D:\MongoDB\Server\4.4\log\mongod.log --logappend --dbpath D:\MongoDB\Server\4.4\data  --serviceName "MongoDB" --serviceDisplayName "MongoDB"  --install --auth
4.再次启动
        net start MongoDB
View Code

三、验证方式

1.直接在登录的时候验证
        mongo -u "root" -p "123" --port 27017 --authenticationDatabase "admin"
2.进入之后再验证
        mongo
        use admin
        db.auth("root","123")

 

 

 

数据准备

"""针对数据的主键值 不知道会默认创建知道了则使用指定的"""
# 插入单条
user0={
    "name":"jason",
    "age":10,
    'hobbies':['music','read','dancing'],
    'addr':{
        'country':'China',
        'city':'BJ'
    }
}

db.user.insert(user0)

# 插入多条
user1={
    "_id":1,
    "name":"ax",
    "age":10,
    'hobbies':['music','read','dancing'],
    'addr':{
        'country':'China',
        'city':'weifang'
    }
}

user2={
    "_id":2,
    "name":"wi",
    "age":20,
    'hobbies':['music','read','run'],
    'addr':{
        'country':'China',
        'city':'hebei'
    }
}

user3={
    "_id":3,
    "name":"yo",
    "age":30,
    'hobbies':['music','drink'],
    'addr':{
        'country':'China',
        'city':'heibei'
    }
}

user4={
    "_id":4,
    "name":"jg",
    "age":40,
    'hobbies':['music','read','dancing','tea'],
    'addr':{
        'country':'China',
        'city':'BJ'
    }
}

user5={
    "_id":5,
    "name":"jn",
    "age":50,
    'hobbies':['music','read',],
    'addr':{
        'country':'China',
        'city':'henan'
    }
}
db.user.insertMany([user1,user2,user3,user4,user5])
View Code

 

 

 

查询指定字段

# 1、select name,age from db1.user where id=3;
db.user.find(
    {'_id':3},
    {'_id':0,'name':1,'age':1}
)
'''0表示不要 1表示要'''

# 针对主键字段_id如果不指定默认是必拿的
# 普通字段不写就表示不拿

 

 

 

比较运算符

SQL:=,!=,>,<,>=,<=

MongoDB:{key:value}代表什么等于什么,"$ne","$gt","$lt","$gte","$lte"

#1、select * from db1.user where name = "jason";
db.user.find({'name':'jason'})

#2、select * from db1.user where name != "jason";
db.user.find({'name':{"$ne":'jason'}})

 

 

 

 

#3、select * from db1.user where id > 2;
db.user.find({'_id':{'$gt':2}})

#4、select * from db1.user where id < 3;
db.user.find({'_id':{'$lt':3}})

 

 

 

 

#5、select * from db1.user where id >= 2;
db.user.find({"_id":{"$gte":2,}})

#6、select * from db1.user where id <= 2;
db.user.find({"_id":{"$lte":2}})

 

 

 

 

逻辑运算符

# SQL:and,or,not
# MongoDB:字典中逗号分隔的多个条件是and关系"$or"的条件放到[ ]内 "$not"取反

#1、select * from db1.user where id >= 2 and id < 4;
db.user.find({'_id':{"$gte":2,"$lt":4}})

 

 

#2、select * from db1.user where id >= 2 and age < 40;
db.user.find({"_id":{"$gte":2},"age":{"$lt":40}})

 

 

#3、select * from db1.user where id >= 5 or name = "ax";
db.user.find({
    "$or":[
        {'_id':{"$gte":5}},
        {"name":"ax"}
        ]
})

 

 

#4、select * from db1.user where id % 2=1;
db.user.find({'_id':{"$mod":[2,1]}})

 

 

#5、上题,取反
db.user.find({'_id':{"$not":{"$mod":[2,1]}}})

 

 

成员运算

# SQL:in,not in
# MongoDB:"$in","$nin"

#1、select * from db1.user where age in (20,30,31);
db.user.find({"age":{"$in":[20,30,31]}})

 

 

#2、select * from db1.user where name not in ('ax','yo');
db.user.find({"name":{"$nin":['ax','yo']}})

 

 

#3、select * from db1.user where age in (20,30,31) or name!='jason';
db.user.find({
    '$or':[
        {'age':{'$in':[20,30,31]}},
        {'name':{'$ne':'jason'}}
    ]
})

 

 

正则匹配

# SQL: regexp 正则
# MongoDB: /正则表达/i

#1、select * from db1.user where name regexp '^j.*?(g|n)$';
db.user.find({'name':/^j.*?(g|n)$/i})

 

 

范围/模糊查询

MySQL
    关键字    like
    关键符号
        %    匹配任意个数的任意字符
        _   匹配单个个数的任意字符
MongoDB:
    通过句点符
    $all

#1、查看有dancing爱好的人

db.user.find({'hobbies':'dancing'})  # 默认就是范围查询

# find({查询条件},{筛选字段})

#2、查看既有dancing爱好又有tea爱好的人

db.user.find({
    'hobbies':{
        "$all":['dancing','tea']
        }
})

 

 #3、查看第4个爱好为tea的人

db.user.find({"hobbies.3":'tea'})

#4、查看所有人最后两个爱好

db.user.find({},{'_id':0,'name':1,'hobbies':{"$slice":-2}})

 

 #5、查看所有人前面两个爱好

db.user.find({},{'_id':0,'name':1,'hobbies':{"$slice":2}})

 

 #6、查看所有人中间的第2个到第3个爱好

db.user.find({},{"_id":0,"name":1,'hobbies':{"$slice":[1,2]}})

 

 

排序

# MySQL:
关键字 order by
升序 降序 asc desc
# MongoDB:
关键字 sort
升序 降序 1 -1

# select * from db.user order by age asc;
db.user.find().sort({"age":1})

 

 

# select * from db.user order by age desc,_id asc
db.user.find().sort({"age":-1,'_id':1})

 

 

分页(限制查询条数)

# MySQL
关键字 limit
分页 5,5
# MongoDB
关键字 limit
分页 skip

# 分页:limit代表取多少个document,skip代表跳过前多少个document 
# select * from db.user limit 2,1
db.user.find().sort({'age':1}).limit(1).skip(2)

 

 

杂项补充

# 获取数量

db.user.count({'age':{"$gt":30}}) 
--或者
db.user.find({'age':{"$gt":30}}).count()

 

 

# {'key':null} 匹配key的值为null或者没有这个key的数据

db.t2.insert({'a':10,'b':111})
db.t2.insert({'a':20})
db.t2.insert({'b':null})

> db.t2.find({"b":null})
{ "_id" : ObjectId("5a5cc2a7c1b4645aad959e5a"), "a" : 20 }
{ "_id" : ObjectId("5a5cc2a8c1b4645aad959e5b"), "b" : null }

# 查找所有

db.user.find() #等同于db.user.find({})

# 查找一个,与find用法一致,只是只取匹配成功的第一个

db.user.findOne({"_id":{"$gt":3}})

 

分组数据准备

from pymongo import MongoClient
import datetime

client=MongoClient('mongodb://root:123@localhost:27017')
table=client['db1']['emp']
# table.drop()

l=[
('jason','male',18,'20170301','老男孩驻沙河办事处外交大使',7300.33,401,1), #以下是教学部
('ax','male',78,'20150302','teacher',1000000.31,401,1),
('wxx','male',81,'20130305','teacher',8300,401,1),
('yh','male',73,'20140701','teacher',3500,401,1),
('lz','male',28,'20121101','teacher',2100,401,1),
('jly','female',18,'20110211','teacher',9000,401,1),
('jx','male',18,'19000301','teacher',30000,401,1),
('成龙','male',48,'20101111','teacher',10000,401,1),

('歪歪','female',48,'20150311','sale',3000.13,402,2),#以下是销售部门
('丫丫','female',38,'20101101','sale',2000.35,402,2),
('丁丁','female',18,'20110312','sale',1000.37,402,2),
('星星','female',18,'20160513','sale',3000.29,402,2),
('格格','female',28,'20170127','sale',4000.33,402,2),

('张野','male',28,'20160311','operation',10000.13,403,3), #以下是运营部门
('程咬金','male',18,'19970312','operation',20000,403,3),
('程咬银','female',18,'20130311','operation',19000,403,3),
('程咬铜','male',18,'20150411','operation',18000,403,3),
('程咬铁','female',18,'20140512','operation',17000,403,3)
]

for n,item in enumerate(l):
    d={
        "_id":n,
        'name':item[0],
        'sex':item[1],
        'age':item[2],
        'hire_date':datetime.datetime.strptime(item[3],'%Y%m%d'),
        'post':item[4],
        'salary':item[5]
    }
    table.save(d)
View Code

 

 

分组查询

1.按照部门分组

db.emp.aggregate({'$group':{'_id':'$post'}})

 

 2.求每个部门的平均年龄

db.emp.aggregate({
    '$group':{
        '_id':'$post',
        '平均年龄':{'$avg':'$age'}
    }
                 })

 

 3.求每个部门的最高薪资与最低薪资

db.emp.aggregate({
    '$group':{
        '_id':'$post',
        '最高薪资':{'$max':'$salary'},
        '最低薪资':{'$min':'$salary'}
    }
})

 

 4.查询岗位名以及各岗位内的员工姓名

# SQL语句:select post,group_concat(name) from emp group by post;
db.emp.aggregate({
    "$group":{"_id":"$post","names":{"$push":"$name"}}
})

 

 5.查询emp表中id>3的数据根据部门分组

# select * from db1.emp where id > 3 group by post;  
db.emp.aggregate(
    {"$match":{"_id":{"$gt":3}}},  # 分组之前筛选数据
    {"$group":{"_id":"$post"}}
)

 

 6.查询emp表中id>3的数据根据部门分组之后平均薪资>10000的部门

# select * from db1.emp where id > 3 group by post having avg(salary) > 10000;  
db.emp.aggregate(
    {"$match":{"_id":{"$gt":3}}},  # 出现在$group上面就是where
    {"$group":{"_id":"$post",'avg_salary':{"$avg":"$salary"}}},
    {"$match":{"avg_salary":{"$gt":10000}}}  # 出现在$group下面就是having
)

 

 

作业

1. 查询岗位名以及各岗位内的员工姓名
select post,group_concat(name) from emp group by post;

db.emp.aggregate({
    '$group':{
        '_id':'$post',
        'names':{'$push':'$name'}
    }
})
2. 查询岗位名以及各岗位内包含的员工个数
select post,count(id) from emp group by post;

db.emp.aggregate({
    '$group':{
        '_id':'$post',
        '$count':{'$sum':1}
    }
})
3. 查询公司内男员工和女员工的个数
select gender,count(id) from emp group by gender;

db.emp.aggregate({
    '$group':{
        '_id':'$gender',
        '$count':{'$sum':1}
    }
})
4. 查询岗位名以及各岗位的平均薪资、最高薪资、最低薪资
select post,avg(salary),max(salary),min(salary) from emp group by post;

db.emp.aggregate({
    '$group':{
        '_id':'$post',
        '平均薪资':{'$avg':'$salary'},
        '最高薪资':{'$max':'$salary'},
        '最低薪资':{'$min':'$salary'}
    }
})
5. 查询男员工与男员工的平均薪资,女员工与女员工的平均薪资
select gender,avg(salary) from emp group by gender;

db.emp.aggregate({
    '$group':{
        '_id':'$gender',
        '$avg':'$salary'
    }
})
6. 查询各岗位内包含的员工个数小于2的岗位名、岗位内包含员工名字、个数
select post,group_concat(name),count(id) from emp 
group by post 
having count(id)<2;

db.emp.aggregate({'$group':{
                    '_id':'$post',
                    'names':{'$push':'$name'},
                    'num':{'$count':{'$sum':1}}}},
                {'$match':{'num':{'$lt':2}}})
7. 查询各岗位平均薪资大于10000的岗位名、平均工资
select post,avg(salary) from emp 
group by post 
having avg(salary)>10000;

db.emp.aggregate(
    {'$group':{'_id':'$post',
               'ayg_salary':{'$avg':'$salary'}
              }},
    {'$match':{'avg_salary':{'$gt':10000}}}
)
8. 查询各岗位平均薪资大于10000且小于20000的岗位名、平均薪资
select post,avg(salary) from emp 
group by post 
having avg(salary)>10000 and avg(salary)<20000;

db.emp.aggregate(
    {'$group':{'_id':'$post',
               'avg_salary':{'$avg':'$salary'}
              }},
    {'$match':{'avg_salary':{'$gt':10000,'$lt':20000}}}
)
9. 查询所有员工信息,先按照age升序排序,如果age相同则按照hire_date降序排序
select * from emp order by age asc,hire_date desc;

db.emp.find().sort({'age':1,'hire_date':-1})
10. 查询各岗位平均薪资大于10000的岗位名、平均工资,结果按平均薪资升序排列
select post,avg(salary) from emp group by post having avg(salary)>10000 order by avg(salary) asc;

db.emp.aggregate(
    {'$group':{'_id':'$post',
               'avg_salary':{'$avg':'$salary'}
              }},
    {'$match':{'avg_salary':{'$gt':10000}}}
).sort({'avg_salary':1})

11. 查询各岗位平均薪资大于10000的岗位名、平均工资,结果按平均薪资降序排列,取前1个
select post,avg(salary) from emp 
group by post 
having avg(salary)>10000 
order by avg(salary) desc limit 1;

db.emp.aggregate(
    {'$group':{'_id':'$post',
               'avg_salary':{'$avg':'$salary'}
              }},
    {'$match':{'avg_salary':{'$gt':10000}}}
).sort({'avg_salary':-1}).limit(1).skip(0)
View Code

 

posted @ 2021-10-10 11:17  陌若安然  阅读(84)  评论(0)    收藏  举报