数组相关操作 [1]_ ##################### 数组查询 ======== :: // 查询字段是数组 db.time_info.find({"begin_time":{$size:1}}) // 方法2 db.time_info.find({ "begin_time.0": {$exists:1} }) // 数组大小是某个范围(要求数组大小小于3) db.time_info.find({ $where: "this.begin_time.length < 3" }) //数组大小小于1,就意味着num[0]不存在 db.time_info.find({ "begin_time.0": {$exists:0} }) 实战 ==== 数据插入:: 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 } ] } ] ) 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" ] } 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" ] } 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" ] } 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 > 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 ] } 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': { $lte: 55}}, {"_id":1,points:1}) { "_id" : 3, "points" : [ { "points" : 81, "bonus" : 8 }, { "points" : 55, "bonus" : 20 } ] } { "_id" : 4, "points" : [ { "points" : 53, "bonus" : 15 }, { "points" : 51, "bonus" : 15 } ] } 数组元素操作符$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: { : { $elemMatch: { , , ... } } } 说明: 如果查询为单值查询条件,即只有,则无需指定$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 ] }, ... { _id: 2, results: [ 75, 88, 89 ] }]) { "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: { $lte: 70 }, bonus: 20}}},{"_id":1,points:1}) { "_id" : 3, "points" : [ { "points" : 81, "bonus" : 8 }, { "points" : 55, "bonus" : 20 } ] } 数组元素操作符$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:{ : { $all: [ , ... ] } } > db.users.find({badges:{$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({$and:[{badges:"blue"},{badges:"black"}]},{"_id":1,badges:1}) { "_id" : 1, "badges" : [ "blue", "black" ] } { "_id" : 6, "badges" : [ "black", "blue" ] } 数组元素操作符$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." } ] } $占位符,返回数组中第一个匹配的数组元素值(子集):: 使用样式: db.collection.find( { : ... }, { ".$": 1 } ) db.collection.find( { : ...}, { ".$": 1 } ) 使用示例 > db.students.insertMany([ { "_id" : 1, "semester" : 1, "grades" : [ 70, 87, 90 ] }, { "_id" : 2, "semester" : 1, "grades" : [ 90, 88, 92 ] }, { "_id" : 3, "semester" : 1, "grades" : [ 85, 100, 90 ] }, { "_id" : 4, "semester" : 2, "grades" : [ 79, 85, 80 ] }, { "_id" : 5, "semester" : 2, "grades" : [ 88, 88, 92 ] }, { "_id" : 6, "semester" : 2, "grades" : [ 95, 90, 96 ] }]) //通过下面的查询可知,仅仅只有第一个大于等于85的元素值被返回 //也就是说$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 } ] } .. [1] `MongoDB 数组查询 `_