mongodb java 查询不等于

转载

bigrobin 2024-09-15 15:13:04

文章标签 mongodb java 查询不等于 mongodb 数据分析 mongodb查询 mongodb类sql 文章分类 MongoDB 数据库

备注:
MongoDB 4.2 版本

文章目录

一.MongoDB查询介绍

2.1 所有记录
2.2 过滤记录
2.3 字段筛选
2.4 排序
2.5 比大小
2.6 正则(模糊匹配)
2.7 or操作
2.8 仅返回1条
2.9 count聚合
2.10 查询计划
2.11 sum

2.11.1 分组汇总
2.11.2 avg
2.11.3 min
2.11.4 max
2.11.5 push
2.11.6 addToSet
2.11.7 first
2.11.8 last
2.11.9 聚合汇总用例

二. 文档嵌套文档

测试数据:

-- 类似Oracle里scott下的emp表
db.emp.insert([
{EMPNO:7369,ENAME:'SMITH',JOB:'CLERK',MGR:7902,HIREDATE:new Date(1980,12,17),SAL:800,DEPTNO:20,dname:'RESEARCH',loc:'DALLAS'},
{EMPNO:7499,ENAME:'ALLEN',JOB:'SALESMAN',MGR:7698,HIREDATE:new Date(1981,2,20),SAL:1600,COMM:300,DEPTNO:30,dname:'SALES',loc:'CHICAGO'},
{EMPNO:7521,ENAME:'WARD',JOB:'SALESMAN',MGR:7698,HIREDATE:new Date(1981,2,22),SAL:1250,COMM:500,DEPTNO:30,dname:'SALES',loc:'CHICAGO'},
{EMPNO:7566,ENAME:'JONES',JOB:'MANAGER',MGR:7839,HIREDATE:new Date(1981,4,2),SAL:2975,DEPTNO:20,dname:'RESEARCH',loc:'DALLAS'},
{EMPNO:7654,ENAME:'MARTIN',JOB:'SALESMAN',MGR:7698,HIREDATE:new Date(1981,9,28),SAL:1250,COMM:1400,DEPTNO:30,dname:'SALES',loc:'CHICAGO'},
{EMPNO:7698,ENAME:'BLAKE',JOB:'MANAGER',MGR:7839,HIREDATE:new Date(1981,5,1),SAL:2850,DEPTNO:30,dname:'SALES',loc:'CHICAGO'},
{EMPNO:7782,ENAME:'CLARK',JOB:'MANAGER',MGR:7839,HIREDATE:new Date(1981,6,9),SAL:2450,DEPTNO:10,dname:'ACCOUNTING',loc:'NEW YORK'},
{EMPNO:7839,ENAME:'KING',JOB:'PRESIDENT',HIREDATE:new Date(1981,11,17),SAL:5000,DEPTNO:10,dname:'ACCOUNTING',loc:'NEW YORK'},
{EMPNO:7844,ENAME:'TURNER',JOB:'SALESMAN',MGR:7698,HIREDATE:new Date(1981,2,20),SAL:1500,COMM:0,DEPTNO:30,dname:'SALES',loc:'CHICAGO'},
{EMPNO:7900,ENAME:'JAMES',JOB:'CLERK',MGR:7698,HIREDATE:new Date(1981,8,9),SAL:950,DEPTNO:30,dname:'SALES',loc:'CHICAGO'},
{EMPNO:7902,ENAME:'FORD',JOB:'ANALYST',MGR:7566,HIREDATE:new Date(1981,12,3),SAL:3000,DEPTNO:20,dname:'RESEARCH',loc:'DALLAS'},
{EMPNO:7934,ENAME:'MILLER',JOB:'CLERK',MGR:7782,HIREDATE:new Date(1982,1,23),SAL:1300,DEPTNO:10,dname:'ACCOUNTING',loc:'NEW YORK'},
{DEPTNO:40,dname:'OPERATIONS',loc:'BOSTON'}
])

一.MongoDB查询介绍

作用	SQL	MongoDB
所有记录	select * from emp	db.emp.find()
empno=6379	select * from emp where empno=7369	db.emp.find({EMPNO:7369})
字段筛选	select empno,ename from emp where empno=7369	db.emp.find({EMPNO:7369},{EMPNO:1,ENAME:1})
排序	select * from emp where deptno = 10 order by ename	db.emp.find({DEPTNO:10}).sort({ENAME:1})
比大小	select * from emp where deptno > 20	db.emp.find({‘DEPTNO’:{$gt:20}})
正则(模糊匹配)	select * from emp where ename like ‘S%’	db.emp.find({ENAME:/^S/})
or操作	select * from emp where deptno = 10 or ename = ‘SMITH’	db.emp.find({$or :[{DEPTNO:10},{ENAME:‘SMITH’}]})
仅返回1条	select * from emp limit 1	db.user.findOne()
count聚合	select count(ename) from emp	db.emp.find({ENAME:{‘$exists’: true}}).count()
查询计划	explain select * from emp where empno = 7369	db.user.find({EMPNO:7369}).explain()

2.1 所有记录

测试记录:

> db.emp.find()
{ "_id" : ObjectId("5fa4b2eaeae97236d30995b3"), "EMPNO" : 7369, "ENAME" : "SMITH", "JOB" : "CLERK", "MGR" : 7902, "HIREDATE" : ISODate("1981-01-16T16:00:00Z"), "SAL" : 800, "DEPTNO" : 20, "dname" : "RESEARCH", "loc" : "DALLAS" }
{ "_id" : ObjectId("5fa4b2eaeae97236d30995b4"), "EMPNO" : 7499, "ENAME" : "ALLEN", "JOB" : "SALESMAN", "MGR" : 7698, "HIREDATE" : ISODate("1981-03-19T16:00:00Z"), "SAL" : 1600, "COMM" : 300, "DEPTNO" : 30, "dname" : "SALES", "loc" : "CHICAGO" }
{ "_id" : ObjectId("5fa4b2eaeae97236d30995b5"), "EMPNO" : 7521, "ENAME" : "WARD", "JOB" : "SALESMAN", "MGR" : 7698, "HIREDATE" : ISODate("1981-03-21T16:00:00Z"), "SAL" : 1250, "COMM" : 500, "DEPTNO" : 30, "dname" : "SALES", "loc" : "CHICAGO" }
{ "_id" : ObjectId("5fa4b2eaeae97236d30995b6"), "EMPNO" : 7566, "ENAME" : "JONES", "JOB" : "MANAGER", "MGR" : 7839, "HIREDATE" : ISODate("1981-05-01T16:00:00Z"), "SAL" : 2975, "DEPTNO" : 20, "dname" : "RESEARCH", "loc" : "DALLAS" }
{ "_id" : ObjectId("5fa4b2eaeae97236d30995b7"), "EMPNO" : 7654, "ENAME" : "MARTIN", "JOB" : "SALESMAN", "MGR" : 7698, "HIREDATE" : ISODate("1981-10-27T16:00:00Z"), "SAL" : 1250, "COMM" : 1400, "DEPTNO" : 30, "dname" : "SALES", "loc" : "CHICAGO" }
{ "_id" : ObjectId("5fa4b2eaeae97236d30995b8"), "EMPNO" : 7698, "ENAME" : "BLAKE", "JOB" : "MANAGER", "MGR" : 7839, "HIREDATE" : ISODate("1981-05-31T16:00:00Z"), "SAL" : 2850, "DEPTNO" : 30, "dname" : "SALES", "loc" : "CHICAGO" }
{ "_id" : ObjectId("5fa4b2eaeae97236d30995b9"), "EMPNO" : 7782, "ENAME" : "CLARK", "JOB" : "MANAGER", "MGR" : 7839, "HIREDATE" : ISODate("1981-07-08T16:00:00Z"), "SAL" : 2450, "DEPTNO" : 10, "dname" : "ACCOUNTING", "loc" : "NEW YORK" }
{ "_id" : ObjectId("5fa4b2eaeae97236d30995ba"), "EMPNO" : 7839, "ENAME" : "KING", "JOB" : "PRESIDENT", "HIREDATE" : ISODate("1981-12-16T16:00:00Z"), "SAL" : 5000, "DEPTNO" : 10, "dname" : "ACCOUNTING", "loc" : "NEW YORK" }
{ "_id" : ObjectId("5fa4b2eaeae97236d30995bb"), "EMPNO" : 7844, "ENAME" : "TURNER", "JOB" : "SALESMAN", "MGR" : 7698, "HIREDATE" : ISODate("1981-03-19T16:00:00Z"), "SAL" : 1500, "COMM" : 0, "DEPTNO" : 30, "dname" : "SALES", "loc" : "CHICAGO" }
{ "_id" : ObjectId("5fa4b2eaeae97236d30995bc"), "EMPNO" : 7900, "ENAME" : "JAMES", "JOB" : "CLERK", "MGR" : 7698, "HIREDATE" : ISODate("1981-09-08T16:00:00Z"), "SAL" : 950, "DEPTNO" : 30, "dname" : "SALES", "loc" : "CHICAGO" }
{ "_id" : ObjectId("5fa4b2eaeae97236d30995bd"), "EMPNO" : 7902, "ENAME" : "FORD", "JOB" : "ANALYST", "MGR" : 7566, "HIREDATE" : ISODate("1982-01-02T16:00:00Z"), "SAL" : 3000, "DEPTNO" : 20, "dname" : "RESEARCH", "loc" : "DALLAS" }
{ "_id" : ObjectId("5fa4b2eaeae97236d30995be"), "EMPNO" : 7934, "ENAME" : "MILLER", "JOB" : "CLERK", "MGR" : 7782, "HIREDATE" : ISODate("1982-02-22T16:00:00Z"), "SAL" : 1300, "DEPTNO" : 10, "dname" : "ACCOUNTING", "loc" : "NEW YORK" }
{ "_id" : ObjectId("5fa4b2eaeae97236d30995bf"), "DEPTNO" : 40, "dname" : "OPERATIONS", "loc" : "BOSTON" }
> 
>

2.2 过滤记录

测试记录:

> db.emp.find({empno:7369})
> 
> db.emp.find({EMPNO:7369})
{ "_id" : ObjectId("5fa4b2eaeae97236d30995b3"), "EMPNO" : 7369, "ENAME" : "SMITH", "JOB" : "CLERK", "MGR" : 7902, "HIREDATE" : ISODate("1981-01-16T16:00:00Z"), "SAL" : 800, "DEPTNO" : 20, "dname" : "RESEARCH", "loc" : "DALLAS" }
>

2.3 字段筛选

测试记录:

> db.emp.find({EMPNO:7369},{EMPNO:1,ENAME:1})
{ "_id" : ObjectId("5fa4b2eaeae97236d30995b3"), "EMPNO" : 7369, "ENAME" : "SMITH" }
>

2.4 排序

测试记录:

> db.emp.find({DEPTNO:10}).sort({ENAME:1})
{ "_id" : ObjectId("5fa4b2eaeae97236d30995b9"), "EMPNO" : 7782, "ENAME" : "CLARK", "JOB" : "MANAGER", "MGR" : 7839, "HIREDATE" : ISODate("1981-07-08T16:00:00Z"), "SAL" : 2450, "DEPTNO" : 10, "dname" : "ACCOUNTING", "loc" : "NEW YORK" }
{ "_id" : ObjectId("5fa4b2eaeae97236d30995ba"), "EMPNO" : 7839, "ENAME" : "KING", "JOB" : "PRESIDENT", "HIREDATE" : ISODate("1981-12-16T16:00:00Z"), "SAL" : 5000, "DEPTNO" : 10, "dname" : "ACCOUNTING", "loc" : "NEW YORK" }
{ "_id" : ObjectId("5fa4b2eaeae97236d30995be"), "EMPNO" : 7934, "ENAME" : "MILLER", "JOB" : "CLERK", "MGR" : 7782, "HIREDATE" : ISODate("1982-02-22T16:00:00Z"), "SAL" : 1300, "DEPTNO" : 10, "dname" : "ACCOUNTING", "loc" : "NEW YORK" }
>

2.5 比大小

测试记录:

> db.emp.find({'DEPTNO':{$gt:20}})
{ "_id" : ObjectId("5fa4b2eaeae97236d30995b4"), "EMPNO" : 7499, "ENAME" : "ALLEN", "JOB" : "SALESMAN", "MGR" : 7698, "HIREDATE" : ISODate("1981-03-19T16:00:00Z"), "SAL" : 1600, "COMM" : 300, "DEPTNO" : 30, "dname" : "SALES", "loc" : "CHICAGO" }
{ "_id" : ObjectId("5fa4b2eaeae97236d30995b5"), "EMPNO" : 7521, "ENAME" : "WARD", "JOB" : "SALESMAN", "MGR" : 7698, "HIREDATE" : ISODate("1981-03-21T16:00:00Z"), "SAL" : 1250, "COMM" : 500, "DEPTNO" : 30, "dname" : "SALES", "loc" : "CHICAGO" }
{ "_id" : ObjectId("5fa4b2eaeae97236d30995b7"), "EMPNO" : 7654, "ENAME" : "MARTIN", "JOB" : "SALESMAN", "MGR" : 7698, "HIREDATE" : ISODate("1981-10-27T16:00:00Z"), "SAL" : 1250, "COMM" : 1400, "DEPTNO" : 30, "dname" : "SALES", "loc" : "CHICAGO" }
{ "_id" : ObjectId("5fa4b2eaeae97236d30995b8"), "EMPNO" : 7698, "ENAME" : "BLAKE", "JOB" : "MANAGER", "MGR" : 7839, "HIREDATE" : ISODate("1981-05-31T16:00:00Z"), "SAL" : 2850, "DEPTNO" : 30, "dname" : "SALES", "loc" : "CHICAGO" }
{ "_id" : ObjectId("5fa4b2eaeae97236d30995bb"), "EMPNO" : 7844, "ENAME" : "TURNER", "JOB" : "SALESMAN", "MGR" : 7698, "HIREDATE" : ISODate("1981-03-19T16:00:00Z"), "SAL" : 1500, "COMM" : 0, "DEPTNO" : 30, "dname" : "SALES", "loc" : "CHICAGO" }
{ "_id" : ObjectId("5fa4b2eaeae97236d30995bc"), "EMPNO" : 7900, "ENAME" : "JAMES", "JOB" : "CLERK", "MGR" : 7698, "HIREDATE" : ISODate("1981-09-08T16:00:00Z"), "SAL" : 950, "DEPTNO" : 30, "dname" : "SALES", "loc" : "CHICAGO" }
{ "_id" : ObjectId("5fa4b2eaeae97236d30995bf"), "DEPTNO" : 40, "dname" : "OPERATIONS", "loc" : "BOSTON" }
>

2.6 正则(模糊匹配)

测试记录:

> db.emp.find({ENAME:/^S/}) 
{ "_id" : ObjectId("5fa4b2eaeae97236d30995b3"), "EMPNO" : 7369, "ENAME" : "SMITH", "JOB" : "CLERK", "MGR" : 7902, "HIREDATE" : ISODate("1981-01-16T16:00:00Z"), "SAL" : 800, "DEPTNO" : 20, "dname" : "RESEARCH", "loc" : "DALLAS" }
>

2.7 or操作

测试记录:

> db.emp.find({$or :[{DEPTNO:10},{ENAME:'SMITH'}]})
{ "_id" : ObjectId("5fa4b2eaeae97236d30995b3"), "EMPNO" : 7369, "ENAME" : "SMITH", "JOB" : "CLERK", "MGR" : 7902, "HIREDATE" : ISODate("1981-01-16T16:00:00Z"), "SAL" : 800, "DEPTNO" : 20, "dname" : "RESEARCH", "loc" : "DALLAS" }
{ "_id" : ObjectId("5fa4b2eaeae97236d30995b9"), "EMPNO" : 7782, "ENAME" : "CLARK", "JOB" : "MANAGER", "MGR" : 7839, "HIREDATE" : ISODate("1981-07-08T16:00:00Z"), "SAL" : 2450, "DEPTNO" : 10, "dname" : "ACCOUNTING", "loc" : "NEW YORK" }
{ "_id" : ObjectId("5fa4b2eaeae97236d30995ba"), "EMPNO" : 7839, "ENAME" : "KING", "JOB" : "PRESIDENT", "HIREDATE" : ISODate("1981-12-16T16:00:00Z"), "SAL" : 5000, "DEPTNO" : 10, "dname" : "ACCOUNTING", "loc" : "NEW YORK" }
{ "_id" : ObjectId("5fa4b2eaeae97236d30995be"), "EMPNO" : 7934, "ENAME" : "MILLER", "JOB" : "CLERK", "MGR" : 7782, "HIREDATE" : ISODate("1982-02-22T16:00:00Z"), "SAL" : 1300, "DEPTNO" : 10, "dname" : "ACCOUNTING", "loc" : "NEW YORK" }
> 
>

2.8 仅返回1条

测试记录:

> db.emp.findOne()
{
        "_id" : ObjectId("5fa4b2eaeae97236d30995b3"),
        "EMPNO" : 7369,
        "ENAME" : "SMITH",
        "JOB" : "CLERK",
        "MGR" : 7902,
        "HIREDATE" : ISODate("1981-01-16T16:00:00Z"),
        "SAL" : 800,
        "DEPTNO" : 20,
        "dname" : "RESEARCH",
        "loc" : "DALLAS"
}
>

2.9 count聚合

测试记录:

> db.emp.find({ENAME:{'$exists': true}}).count()
12
>

2.10 查询计划

测试记录:

> db.user.find({EMPNO:7369}).explain()
{
        "queryPlanner" : {
                "plannerVersion" : 1,
                "namespace" : "zqs.user",
                "indexFilterSet" : false,
                "parsedQuery" : {
                        "EMPNO" : {
                                "$eq" : 7369
                        }
                },
                "winningPlan" : {
                        "stage" : "EOF"
                },
                "rejectedPlans" : [ ]
        },
        "serverInfo" : {
                "host" : "10-31-1-124",
                "port" : 27017,
                "version" : "4.2.10",
                "gitVersion" : "88276238fa97b47c0ef14362b343c5317ecbd739"
        },
        "ok" : 1
}
>

2.11 sum

MongoDB 中聚合(aggregate)主要用于处理数据(诸如统计平均值，求和等)，并返回计算后的数据结果

语法:

db.collection.aggregate( [ <stage1>, <stage2>, ... ] )

表达式	描述	实例
$sum	计算总和
$avg	计算平均值
$min	获取集合中所有文档对应值得最小值
$max	获取集合中所有文档对应值得最大值
$push	在结果文档中插入值到一个数组中
$addToSet	在结果文档中插入值到一个数组中，但不创建副本
$first	根据资源文档的排序获取第一个文档数据
$last	根据资源文档的排序获取最后一个文档数据

2.11.1 分组汇总

代码:

db.emp.aggregate([
{$group : {_id : "$DEPTNO",emp_count : {$sum: 1}}}
])
-- 等价于下面的sql
select deptno,count(*) from emp group by deptno

db.emp.aggregate([
{$group : {_id : "$DEPTNO",sum_sal : {$sum: '$SAL'}}}
])
-- 等价于下面的sql
select deptno,sum(sal) from emp group by deptno

测试记录:

> db.emp.aggregate([
... {$group : {_id : "$DEPTNO",emp_count : {$sum: 1}}}
... ])
{ "_id" : 30, "emp_count" : 6 }
{ "_id" : 20, "emp_count" : 3 }
{ "_id" : 40, "emp_count" : 1 }
{ "_id" : 10, "emp_count" : 3 }
> 

> db.emp.aggregate([
... {$group : {_id : "$DEPTNO",sum_sal : {$sum: '$SAL'}}}
... ])
{ "_id" : 20, "sum_sal" : 6775 }
{ "_id" : 40, "sum_sal" : 0 }
{ "_id" : 30, "sum_sal" : 9400 }
{ "_id" : 10, "sum_sal" : 8750 }
>

2.11.2 avg

代码:

db.emp.aggregate([
{$group : {_id : "$DEPTNO",avg_sal : {$avg: '$SAL'}}}
])
-- 等价于下面这个sql
select deptno,avg(sal) avg_sal from emp

测试记录:

db.emp.aggregate([
{$group : {_id : "$DEPTNO",avg_sal : {$avg: '$SAL'}}}
])

2.11.3 min

代码：

db.emp.aggregate([
{$group : {_id : "$DEPTNO",min_sal : {$min: '$SAL'}}}
])
-- 等价于下面的sql
select deptno,min(sal) as min_sal from emp group by deptno

测试记录:

db.emp.aggregate([
{$group : {_id : "$DEPTNO",min_sal : {$min: '$SAL'}}}
])

2.11.4 max

代码：

db.emp.aggregate([
{$group : {_id : "$DEPTNO",max_sal : {$max: '$SAL'}}}
])
-- 等价于下面的sql
select deptno,max(sal) as max_sal from emp group by deptno

测试记录:

> db.emp.aggregate([
... {$group : {_id : "$DEPTNO",max_sal : {$max: '$SAL'}}}
... ])
{ "_id" : 20, "max_sal" : 3000 }
{ "_id" : 40, "max_sal" : null }
{ "_id" : 30, "max_sal" : 2850 }
{ "_id" : 10, "max_sal" : 5000 }
>

2.11.5 push

代码：

db.emp.aggregate([
{$group : {_id : "$DEPTNO",emps : {$push: '$ENAME'}}}
])
-- 等价于mysql里如下sql
select deptno,group_concat(ename) from emp group by deptno;

测试记录:

> db.emp.aggregate([
... {$group : {_id : "$DEPTNO",emps : {$push: '$ENAME'}}}
... ])
{ "_id" : 20, "emps" : [ "SMITH", "JONES", "FORD" ] }
{ "_id" : 40, "emps" : [ ] }
{ "_id" : 30, "emps" : [ "ALLEN", "WARD", "MARTIN", "BLAKE", "TURNER", "JAMES" ] }
{ "_id" : 10, "emps" : [ "CLARK", "KING", "MILLER" ] }
>

2.11.6 addToSet

代码：

db.emp.aggregate([
{$group : {_id : "$DEPTNO",emps : {$addToSet: '$ENAME'}}}
])
-- 等价于下面的sql
select  deptno,group_concat(ename)
from (select distinct deptno,ename from emp) e
group by deptno

测试记录:

> db.emp.aggregate([
... {$group : {_id : "$DEPTNO",emps : {$addToSet: '$ENAME'}}}
... ])
{ "_id" : 20, "emps" : [ "SMITH", "JONES", "FORD" ] }
{ "_id" : 40, "emps" : [ ] }
{ "_id" : 30, "emps" : [ "BLAKE", "TURNER", "JAMES", "WARD", "ALLEN", "MARTIN" ] }
{ "_id" : 10, "emps" : [ "KING", "CLARK", "MILLER" ] }
>

2.11.7 first

代码：

db.emp.aggregate([
{$group : {_id : "$DEPTNO",first_emp : {$first: '$ENAME'}}}
])
-- 这个用sql实现略微复杂

测试记录:

> db.emp.aggregate([
... {$group : {_id : "$DEPTNO",first_emp : {$first: '$ENAME'}}}
... ])
{ "_id" : 20, "first_emp" : "SMITH" }
{ "_id" : 40, "first_emp" : null }
{ "_id" : 30, "first_emp" : "ALLEN" }
{ "_id" : 10, "first_emp" : "CLARK" }

2.11.8 last

代码：

db.emp.aggregate([
{$group : {_id : "$DEPTNO",last_emp : {$last: '$ENAME'}}}
])
-- 这个用sql实现略微复杂

测试记录:

> db.emp.aggregate([
... {$group : {_id : "$DEPTNO",last_emp : {$last: '$ENAME'}}}
... ])
{ "_id" : 30, "last_emp" : "JAMES" }
{ "_id" : 20, "last_emp" : "FORD" }
{ "_id" : 40, "last_emp" : null }
{ "_id" : 10, "last_emp" : "MILLER" }

2.11.9 聚合汇总用例

代码:

db.emp.aggregate([
{$group : {_id : "$DEPTNO",
            emp_count : {$sum: 1},
            avg_sal : {$avg: '$SAL'},
            min_sal : {$min: '$SAL'},
            max_sal : {$max: '$SAL'},
            emps1 : {$push: '$ENAME'},
            emps2 : {$addToSet: '$ENAME'},
            first_emp : {$first: '$ENAME'},
            last_emp : {$last: '$ENAME'}         
 }}
])

测试记录；

> db.emp.aggregate([
... {$group : {_id : "$DEPTNO",
...             emp_count : {$sum: 1},
...             avg_sal : {$avg: '$SAL'},
...             min_sal : {$min: '$SAL'},
...             max_sal : {$max: '$SAL'},
...             emps1 : {$push: '$ENAME'},
...             emps2 : {$addToSet: '$ENAME'},
...             first_emp : {$first: '$ENAME'},
...             last_emp : {$last: '$ENAME'}         
...  }}
... ])
{ "_id" : 30, "emp_count" : 6, "avg_sal" : 1566.6666666666667, "min_sal" : 950, "max_sal" : 2850, "emps1" : [ "ALLEN", "WARD", "MARTIN", "BLAKE", "TURNER", "JAMES" ], "emps2" : [ "BLAKE", "TURNER", "JAMES", "WARD", "ALLEN", "MARTIN" ], "first_emp" : "ALLEN", "last_emp" : "JAMES" }
{ "_id" : 20, "emp_count" : 3, "avg_sal" : 2258.3333333333335, "min_sal" : 800, "max_sal" : 3000, "emps1" : [ "SMITH", "JONES", "FORD" ], "emps2" : [ "SMITH", "FORD", "JONES" ], "first_emp" : "SMITH", "last_emp" : "FORD" }
{ "_id" : 40, "emp_count" : 1, "avg_sal" : null, "min_sal" : null, "max_sal" : null, "emps1" : [ ], "emps2" : [ ], "first_emp" : null, "last_emp" : null }
{ "_id" : 10, "emp_count" : 3, "avg_sal" : 2916.6666666666665, "min_sal" : 1300, "max_sal" : 5000, "emps1" : [ "CLARK", "KING", "MILLER" ], "emps2" : [ "KING", "CLARK", "MILLER" ], "first_emp" : "CLARK", "last_emp" : "MILLER" }
>

二. 文档嵌套文档

因为MongoDB不支持文档join文档，所以会有很多嵌套的文档的操作。

本文章为转载内容，我们尊重原作者对文章享有的著作权。如有内容错误或侵权问题，欢迎原作者联系我们进行内容更正或删除文章。

上一篇：python语言程序设计教学比赛

下一篇：psm解决样本选择偏差

提问和评论都可以，用心的回复会被更多人看到评论

发布评论

相关文章

官方博客	全部文章	热门标签	班级博客
了解我们	网站地图	意见反馈

鸿蒙开发者社区	51CTO学堂
51CTO	软考资讯

mongodb java 查询 不等于

mongodb java 查询 不等于

文章目录

一.MongoDB查询介绍

2.1 所有记录

2.2 过滤记录

2.3 字段筛选

2.4 排序

2.5 比大小

2.6 正则(模糊匹配)

2.7 or操作

2.8 仅返回1条

2.9 count聚合

2.10 查询计划

2.11 sum

2.11.1 分组汇总

2.11.2 avg

2.11.3 min

2.11.4 max

2.11.5 push

2.11.6 addToSet

2.11.7 first

2.11.8 last

2.11.9 聚合汇总用例

二. 文档嵌套文档

51CTO博客

mongodb java 查询不等于

mongodb java 查询不等于