mongodb 数组查询

Posted 2021-01-25 我和你并没有不同

转发自：https://blog.csdn.net/leshami/article/details/55049891

一、演示环境及数据
> db.version()
3.2.11

> db.users.insertMany(
[
{
_id: 1,
name: "sue",
age: 19,
type: 1,
status: "P",
favorites: { artist: "Picasso", food: "pizza" },
finished: [ 17, 3 ],
badges: [ "blue", "black" ],
points: [
{ points: 85, bonus: 20 },
{ points: 85, bonus: 10 }
]
},
{
_id: 2,
name: "bob",
age: 42,
type: 1,
status: "A",
favorites: { artist: "Miro", food: "meringue" },
finished: [ 11, 25 ],
badges: [ "green" ],
points: [
{ points: 85, bonus: 20 },
{ points: 64, bonus: 12 }
]
},
{
_id: 3,
name: "ahn",
age: 22,
type: 2,
status: "A",
favorites: { artist: "Cassatt", food: "cake" },
finished: [ 6 ],
badges: [ "blue", "red" ],
points: [
{ points: 81, bonus: 8 },
{ points: 55, bonus: 20 }
]
},
{
_id: 4,
name: "xi",
age: 34,
type: 2,
status: "D",
favorites: { artist: "Chagall", food: "chocolate" },
finished: [ 5, 11 ],
badges: [ "red", "black" ],
points: [
{ points: 53, bonus: 15 },
{ points: 51, bonus: 15 }
]
},
{
_id: 5,
name: "xyz",
age: 23,
type: 2,
status: "D",
favorites: { artist: "Noguchi", food: "nougat" },
finished: [ 14, 6 ],
badges: [ "orange" ],
points: [
{ points: 71, bonus: 20 }
]
},
{
_id: 6,
name: "abc",
age: 43,
type: 1,
status: "A",
favorites: { food: "pizza", artist: "Picasso" },
finished: [ 18, 12 ],
badges: [ "black", "blue" ],
points: [
{ points: 78, bonus: 8 },
{ points: 57, bonus: 7 }
]
}
]
)
 
二、演示数组查询
###1、数组元素模糊匹配

//如下示例，数组字段badges每个包含该元素black的文档都将被返回
> db.users.find({badges:"black"},{"_id":1,badges:1})
{ "_id" : 1, "badges" : [ "blue", "black" ] }
{ "_id" : 4, "badges" : [ "red", "black" ] }
{ "_id" : 6, "badges" : [ "black", "blue" ] }
 
###2、数组元素精确(全)匹配

//如下示例，数组字段badges的值为["black","blue"]的文档才能被返回(数组元素值和元素顺序全匹配)
> db.users.find({badges:["black","blue"]},{"_id":1,badges:1})
{ "_id" : 6, "badges" : [ "black", "blue" ] }
 
###3、通过数组下标返回指定的文档

数组的下标从0开始，指定下标值则返回对应的文档
//如下示例，返回数组badges中第一个元素值为black的文档
> db.users.find({"badges.1":"black"},{"_id":1,badges:1})
{ "_id" : 1, "badges" : [ "blue", "black" ] }
{ "_id" : 4, "badges" : [ "red", "black" ] }
 
###4、范围条件任意元素匹配查询

//查询数组finished的元素值既大于15，又小于20的文档
> db.users.find( { finished: { $gt: 15, $lt: 20}},{"_id":1,finished:1})
{ "_id" : 1, "finished" : [ 17, 3 ] }
{ "_id" : 2, "finished" : [ 11, 25 ] }
{ "_id" : 6, "finished" : [ 18, 12 ] }

//下面插入一个新的文档，仅包含单个数组元素
> db.users.insert({"_id":7,finished:[19]})
WriteResult({ "nInserted" : 1 })

//再次查询，新增的文档也被返回，补充：仅一个元素满足了这两个条件也被返回@20181010
//感谢网友Land提出。
> db.users.find( { finished: { $gt: 15, $lt: 20}},{"_id":1,finished:1})
{ "_id" : 1, "finished" : [ 17, 3 ] }
{ "_id" : 2, "finished" : [ 11, 25 ] }
{ "_id" : 6, "finished" : [ 18, 12 ] }
{ "_id" : 7, "finished" : [ 19 ] }
 
###5、数组内嵌文档查询

//查询数组points元素1内嵌文档键points的值小于等于55的文档(精确匹配)
> db.users.find( { ‘points.0.points‘: { $lte: 55}},{"_id":1,points:1})
{ "_id" : 4, "points" : [ { "points" : 53, "bonus" : 15 }, { "points" : 51, "bonus" : 15 } ] }

//查询数组points内嵌文档键points的值小于等于55的文档，此处通过.成员的方式实现
> db.users.find( { ‘points.points‘: { $lte: 55}},{"_id":1,points:1})
{ "_id" : 3, "points" : [ { "points" : 81, "bonus" : 8 }, { "points" : 55, "bonus" : 20 } ] }
{ "_id" : 4, "points" : [ { "points" : 53, "bonus" : 15 }, { "points" : 51, "bonus" : 15 } ] }
 
###6、数组元素操作符$elemMatch

作用：数组值中至少一个元素满足所有指定的匹配条件
语法： { <field>: { $elemMatch: { <query1>, <query2>, ... } } }
说明： 如果查询为单值查询条件，即只有<query1>，则无需指定$elemMatch

//如下示例,为无需指定$elemMatch情形
//查询数组内嵌文档字段points.points的值为85的文档
> db.users.find( { "points.points": 85},{"_id":1,points:1})
{ "_id" : 1, "points" : [ { "points" : 85, "bonus" : 20 }, { "points" : 85, "bonus" : 10 } ] }
{ "_id" : 2, "points" : [ { "points" : 85, "bonus" : 20 }, { "points" : 64, "bonus" : 12 } ] }

> db.users.find( { points:{ $elemMatch:{points:85}}},{"_id":1,points:1})
{ "_id" : 1, "points" : [ { "points" : 85, "bonus" : 20 }, { "points" : 85, "bonus" : 10 } ] }
{ "_id" : 2, "points" : [ { "points" : 85, "bonus" : 20 }, { "points" : 64, "bonus" : 12 } ] }

//单数组查询($elemMatch示例)
> db.scores.insertMany(
... [{ _id: 1, results: [ 82, 85, 88 ] }, //Author : Leshami
... { _id: 2, results: [ 75, 88, 89 ] }]) //Blog : http://blog.csdn.net/leshami
{ "acknowledged" : true, "insertedIds" : [ 1, 2 ] }
> db.scores.find({ results: { $elemMatch: { $gte: 80, $lt: 85 } } })
{ "_id" : 1, "results" : [ 82, 85, 88 ] }

//数组内嵌文档查询示例($elemMatch示例)
//查询数组内嵌文档字段points.points的值大于等于70，并且bonus的值20的文档(要求2个条件都必须满足)
//也就是说数组points的至少需要一个元素同时满足以上2个条件，这样的结果文档才会返回
//下面的查询数组值{ "points" : 55, "bonus" : 20 }满足条件
> db.users.find( { points: { $elemMatch: { points: { $lte: 70 }, bonus: 20}}},{"_id":1,points:1})
{ "_id" : 3, "points" : [ { "points" : 81, "bonus" : 8 }, { "points" : 55, "bonus" : 20 } ] }
 
###7、数组元素操作符$all

作用：数组值中满足所有指定的匹配条件，不考虑多出的元素以及元素顺序问题
语法：{ <field>: { $all: [ <value1> , <value2> ... ] } }

> db.users.find({badges:{$all:["black","blue"]}},{"_id":1,badges:1})
{ "_id" : 1, "badges" : [ "blue", "black" ] } //此处查询的结果不考虑元素的顺序
{ "_id" : 6, "badges" : [ "black", "blue" ] } //只要包含这2个元素的集合都被返回

等价的操作方式
> db.users.find({$and:[{badges:"blue"},{badges:"black"}]},{"_id":1,badges:1})
{ "_id" : 1, "badges" : [ "blue", "black" ] }
{ "_id" : 6, "badges" : [ "black", "blue" ] }
 
###8、数组元素操作符$size

作用：返回元素个数总值等于指定值的文档
语法：db.collection.find( { field: { $size: 2 } } );
说明：$size不支持指定范围，而是一个具体的值。此外针对$size，没有相关可用的索引来提高性能

//查询数组badges包含1个元素的文档
> db.users.find({badges:{$size:1}},{"_id":1,badges:1})
{ "_id" : 2, "badges" : [ "green" ] }
{ "_id" : 5, "badges" : [ "orange" ] }

//查询数组badges包含2个元素的文档
> db.users.find({badges:{$size:2}},{"_id":1,badges:1})
{ "_id" : 1, "badges" : [ "blue", "black" ] }
{ "_id" : 3, "badges" : [ "blue", "red" ] }
{ "_id" : 4, "badges" : [ "red", "black" ] }
{ "_id" : 6, "badges" : [ "black", "blue" ] }
 
###9、数组元素操作符$slice

作用：用于返回指定位置的数组元素值的子集(是数值元素值得一部分，不是所有的数组元素值)
示例：db.collection.find( { field: value }, { array: {$slice: count } } );

//创建演示文档
> db.blog.insert(
... {_id:1,title:"mongodb unique index",
... comment: [
... {"name" : "joe","content" : "nice post."},
... {"name" : "bob","content" : "good post."},
... {"name" : "john","content" : "greatly."}]}
... )
WriteResult({ "nInserted" : 1 })

//通过$slice返回集合中comment数组第一条评论
> db.blog.find({},{comment:{$slice:1}}).pretty()
{
"_id" : 1,
"title" : "mongodb unique index",
"comment" : [
{
"name" : "joe",
"content" : "nice post."
}
]
}

//通过$slice返回集合中comment数组最后一条评论
> db.blog.find({},{comment:{$slice:-1}}).pretty()
{
"_id" : 1,
"title" : "mongodb unique index",
"comment" : [
{
"name" : "john",
"content" : "greatly."
}
]
}

//通过$slice返回集合中comment数组特定的评论(可以理解为分页)
//如下查询，返回的是第2-3条评论，第一条被跳过
> db.blog.find({},{comment:{$slice:[1,3]}}).pretty()
{
"_id" : 1,
"title" : "mongodb unique index",
"comment" : [
{
"name" : "bob",
"content" : "good post."
},
{
"name" : "john",
"content" : "greatly."
}
]
}
 
###10、$占位符，返回数组中第一个匹配的数组元素值(子集)

使用样式：
db.collection.find( { <array>: <value> ... },
{ "<array>.$": 1 } )
db.collection.find( { <array.field>: <value> ...},
{ "<array>.$": 1 } )

使用示例
> db.students.insertMany([
{ "_id" : 1, "semester" : 1, "grades" : [ 70, 87, 90 ] },
{ "_id" : 2, "semester" : 1, "grades" : [ 90, 88, 92 ] },
{ "_id" : 3, "semester" : 1, "grades" : [ 85, 100, 90 ] },
{ "_id" : 4, "semester" : 2, "grades" : [ 79, 85, 80 ] },
{ "_id" : 5, "semester" : 2, "grades" : [ 88, 88, 92 ] },
{ "_id" : 6, "semester" : 2, "grades" : [ 95, 90, 96 ] }])

//通过下面的查询可知，仅仅只有第一个大于等于85的元素值被返回
//也就是说$占位符返回的是数组的第一个匹配的值，是数组的子集
> db.students.find( { semester: 1, grades: { $gte: 85 } },
... { "grades.$": 1 } )
{ "_id" : 1, "grades" : [ 87 ] }
{ "_id" : 2, "grades" : [ 90 ] }
{ "_id" : 3, "grades" : [ 85 ] }


> db.students.drop()

//使用新的示例数据
> db.students.insertMany([
{ "_id" : 7, semester: 3, "grades" : [ { grade: 80, mean: 75, std: 8 },
{ grade: 85, mean: 90, std: 5 },
{ grade: 90, mean: 85, std: 3 } ] },
{ "_id" : 8, semester: 3, "grades" : [ { grade: 92, mean: 88, std: 8 },
{ grade: 78, mean: 90, std: 5 },
{ grade: 88, mean: 85, std: 3 } ] }])

//下面的查询中，数组的元素为内嵌文档，同样如此，数组元素第一个匹配的元素值被返回
> db.students.find(
... { "grades.mean": { $gt: 70 } },
... { "grades.$": 1 }
... )
{ "_id" : 7, "grades" : [ { "grade" : 80, "mean" : 75, "std" : 8 } ] }
{ "_id" : 8, "grades" : [ { "grade" : 92, "mean" : 88, "std" : 8 } ] }
 
三、小结
a、数组查询有精确和模糊之分，精确匹配需要指定数据元素的全部值
b、数组查询可以通过下标的方式进行查询
c、数组内嵌套文档可以通过.成员的方式进行查询
d、数组至少一个元素满足所有指定的匹配条件可以使用$elemMatch
e、数组查询中返回元素的子集可以通过$slice以及占位符来实现f、 占位符来实现f、占位符来实现f、all满足所有指定的匹配条件，不考虑多出的元素以及元素顺序问题
---------------------
作者：Leshami
来源：CSDN
原文：https://blog.csdn.net/leshami/article/details/55049891
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