MongoDB 陣列查詢
阿新 • • 發佈：2018-11-12
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MongoDB在文件上支援陣列，其次陣列上可以實現巢狀，以及陣列元素也可以文件。因此，對於文件上陣列的操作，MongoDB提供很多種不同的方式，包括陣列的查詢，陣列元素的新增刪除等等。本文主要描述陣列查詢，供大家參考。
一、演示環境及資料
> 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 } ] } ] )
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二、演示陣列查詢
###1、陣列元素模糊匹配
//如下示例，陣列欄位badges每個包含該元素black的文件都將被返回 > db.users.find({badges:"black"},{"_id":1,badges:1}) { "_id" : 1, "badges" : [ "blue", "black" ] } { "_id" : 4, "badges" : [ "red", "black" ] } { "_id" : 6, "badges" : [ "black", "blue" ] }
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###2、陣列元素精確(全)匹配
//如下示例，陣列欄位badges的值為["black","blue"]的文件才能被返回(陣列元素值和元素順序全匹配) > db.users.find({badges:["black","blue"]},{"_id":1,badges:1}) { "_id" : 6, "badges" : [ "black", "blue" ] }
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###3、通過陣列下標返回指定的文件
陣列的下標從0開始，指定下標值則返回對應的文件 //如下示例，返回陣列badges中第一個元素值為black的文件 > db.users.find({"badges.1":"black"},{"_id":1,badges:1}) { "_id" : 1, "badges" : [ "blue", "black" ] } { "_id" : 4, "badges" : [ "red", "black" ] }
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###4、範圍條件任意元素匹配查詢
//查詢陣列finished的元素值既大於15，又小於20的文件 > 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 ] } //下面插入一個新的文件，僅包含單個數組元素 > db.users.insert({"_id":7,finished:[19]}) WriteResult({ "nInserted" : 1 }) //再次查詢，新增的文件也被返回，補充：僅一個元素滿足了這兩個條件也被返回@20181010 //感謝網友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 ] }
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###5、陣列內嵌文件查詢
//查詢陣列points元素1內嵌文件鍵points的值小於等於55的文件(精確匹配) > db.users.find( { 'points.0.points': { $lte: 55}},{"_id":1,points:1}) { "_id" : 4, "points" : [ { "points" : 53, "bonus" : 15 }, { "points" : 51, "bonus" : 15 } ] } //查詢陣列points內嵌文件鍵points的值小於等於55的文件，此處通過.成員的方式實現 > db.users.find( { 'points.points': { $lte: 55}},{"_id":1,points:1}) { "_id" : 3, "points" : [ { "points" : 81, "bonus" : 8 }, { "points" : 55, "bonus" : 20 } ] } { "_id" : 4, "points" : [ { "points" : 53, "bonus" : 15 }, { "points" : 51, "bonus" : 15 } ] }
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###6、陣列元素操作符$elemMatch
作用：陣列值中至少一個元素滿足所有指定的匹配條件 語法： { <field>: { $elemMatch: { <query1>, <query2>, ... } } } 說明： 如果查詢為單值查詢條件，即只有<query1>，則無需指定$elemMatch //如下示例,為無需指定$elemMatch情形 //查詢陣列內嵌文件欄位points.points的值為85的文件 > 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:{ $elemMatch:{points:85}}},{"_id":1,points:1}) { "_id" : 1, "points" : [ { "points" : 85, "bonus" : 20 }, { "points" : 85, "bonus" : 10 } ] } { "_id" : 2, "points" : [ { "points" : 85, "bonus" : 20 }, { "points" : 64, "bonus" : 12 } ] } //單陣列查詢($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, $lt: 85 } } }) { "_id" : 1, "results" : [ 82, 85, 88 ] } //陣列內嵌文件查詢示例($elemMatch示例) //查詢陣列內嵌文件欄位points.points的值大於等於70，並且bonus的值20的文件(要求2個條件都必須滿足) //也就是說陣列points的至少需要一個元素同時滿足以上2個條件，這樣的結果文件才會返回 //下面的查詢陣列值{ "points" : 55, "bonus" : 20 }滿足條件 > db.users.find( { points: { $elemMatch: { points: { $lte: 70 }, bonus: 20}}},{"_id":1,points:1}) { "_id" : 3, "points" : [ { "points" : 81, "bonus" : 8 }, { "points" : 55, "bonus" : 20 } ] }
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###7、陣列元素操作符$all
作用：陣列值中滿足所有指定的匹配條件，不考慮多出的元素以及元素順序問題 語法：{ <field>: { $all: [ <value1> , <value2> ... ] } } > db.users.find({badges:{$all:["black","blue"]}},{"_id":1,badges:1}) { "_id" : 1, "badges" : [ "blue", "black" ] } //此處查詢的結果不考慮元素的順序 { "_id" : 6, "badges" : [ "black", "blue" ] } //只要包含這2個元素的集合都被返回 等價的操作方式 > db.users.find({$and:[{badges:"blue"},{badges:"black"}]},{"_id":1,badges:1}) { "_id" : 1, "badges" : [ "blue", "black" ] } { "_id" : 6, "badges" : [ "black", "blue" ] }
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###8、陣列元素操作符$size
作用：返回元素個數總值等於指定值的文件 語法：db.collection.find( { field: { $size: 2 } } ); 說明：$size不支援指定範圍，而是一個具體的值。此外針對$size，沒有相關可用的索引來提高效能 //查詢陣列badges包含1個元素的文件 > db.users.find({badges:{$size:1}},{"_id":1,badges:1}) { "_id" : 2, "badges" : [ "green" ] } { "_id" : 5, "badges" : [ "orange" ] } //查詢陣列badges包含2個元素的文件 > db.users.find({badges:{$size:2}},{"_id":1,badges:1}) { "_id" : 1, "badges" : [ "blue", "black" ] } { "_id" : 3, "badges" : [ "blue", "red" ] } { "_id" : 4, "badges" : [ "red", "black" ] } { "_id" : 6, "badges" : [ "black", "blue" ] }
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###9、陣列元素操作符$slice
作用：用於返回指定位置的陣列元素值的子集(是數值元素值得一部分，不是所有的陣列元素值) 示例：db.collection.find( { field: value }, { array: {$slice: count } } ); //建立演示文件 > db.blog.insert( ... {_id:1,title:"mongodb unique index", ... comment: [ ... {"name" : "joe","content" : "nice post."}, ... {"name" : "bob","content" : "good post."}, ... {"name" : "john","content" : "greatly."}]} ... ) WriteResult({ "nInserted" : 1 }) //通過$slice返回集合中comment陣列第一條評論 > db.blog.find({},{comment:{$slice:1}}).pretty() { "_id" : 1, "title" : "mongodb unique index", "comment" : [ { "name" : "joe", "content" : "nice post." } ] } //通過$slice返回集合中comment陣列最後一條評論 > db.blog.find({},{comment:{$slice:-1}}).pretty() { "_id" : 1, "title" : "mongodb unique index", "comment" : [ { "name" : "john", "content" : "greatly." } ] } //通過$slice返回集合中comment陣列特定的評論(可以理解為分頁) //如下查詢，返回的是第2-3條評論，第一條被跳過 > db.blog.find({},{comment:{$slice:[1,3]}}).pretty() { "_id" : 1, "title" : "mongodb unique index", "comment" : [ { "name" : "bob", "content" : "good post." }, { "name" : "john", "content" : "greatly." } ] }
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###10、$佔位符，返回陣列中第一個匹配的陣列元素值(子集)
使用樣式： 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 ] }]) //通過下面的查詢可知，僅僅只有第一個大於等於85的元素值被返回 //也就是說$佔位符返回的是陣列的第一個匹配的值，是陣列的子集 > 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() //使用新的示例資料 > 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 } ] }]) //下面的查詢中，陣列的元素為內嵌文件，同樣如此，陣列元素第一個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 } ] }
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三、小結
a、陣列查詢有精確和模糊之分，精確匹配需要指定資料元素的全部值
b、陣列查詢可以通過下標的方式進行查詢
c、陣列內巢狀文件可以通過.成員的方式進行查詢
d、陣列至少一個元素滿足所有指定的匹配條件可以使用$elemMatch
e、陣列查詢中返回元素的子集可以通過$slice以及
佔位符來實現f、all滿足所有指定的匹配條件，不考慮多出的元素以及元素順序問題
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