【发布时间】：2021-06-18 12:32:54
【问题描述】：
我不明白如何在 mongoDB 中展开然后嵌套集合。基本上我有两个结构如下的集合：
问题文档：
{
"_id" : 1,
"questions" : [
{
"_id" : 1,
"body" : "What fabric is the top made of?",
"date_written" : "2018-01-04",
"asker_name" : "yankeelover",
"asker_email" : "first.last@gmail.com",
"reported" : 0,
"helpful" : 2
},
{
"_id" : 2,
"body" : "HEY THIS IS A WEIRD QUESTION!!!!?",
"date_written" : "2019-04-28",
"asker_name" : "jbilas",
"asker_email" : "first.last@gmail.com",
"reported" : 1,
"helpful" : 4
},
{
"_id" : 4,
"body" : "How long does it last?",
"date_written" : "2019-07-06",
"asker_name" : "funnygirl",
"asker_email" : "first.last@gmail.com",
"reported" : 0,
"helpful" : 6
},
答案文档：
{
"_id" : 1,
"answers" : [
{
"_id" : 8,
"body" : "DONT BUY IT! It's bad for the environment",
"date_written" : "2018-01-04",
"answerer_name" : "metslover",
"answerer_email" : "first.last@gmail.com",
"reported" : 0,
"helpful" : 8
},
{
"_id" : 7,
"body" : "Its the best! Seriously magic fabric",
"date_written" : "2018-01-04",
"answerer_name" : "metslover",
"answerer_email" : "first.last@gmail.com",
"reported" : 0,
"helpful" : 7
},
{
"_id" : 5,
"body" : "Something pretty soft but I can't be sure",
"date_written" : "2018-01-04",
"answerer_name" : "metslover",
"answerer_email" : "first.last@gmail.com",
"reported" : 0,
"helpful" : 5,
"photos" : [
{
"_id" : 1,
"url" : "https://images.unsplash.com/photo-1530519729491-aea5b51d1ee1?ixlib=rb-1.2.1&ixid=eyJhcHBfaWQiOjEyMDd9&auto=format&fit=crop&w=1651&q=80"
},
答案文档中的 _id 字段与作为答案的问题的 _id 字段相匹配。
最终目标是获得如下所示的数据：
{
"_id": "17762",
"questions": [
{
"question_id": 152829,
"question_body": "Why Does it look like this?",
"question_date": "2021-03-06T00:00:00.000Z",
"asker_name": "garethTheGreato",
"question_helpfulness": 60,
"reported": false,
"answers": {
"1443770": {
"id": 1443770,
"body": "This question was really helpful! Thank you.",
"date": "2021-03-09T00:00:00.000Z",
"answerer_name": "SatisfiedCustomer",
"helpfulness": 3,
"photos": []
},
"1443807": {
"id": 1443807,
"body": "mimk",
"date": "2021-03-09T00:00:00.000Z",
"answerer_name": "jij",
"helpfulness": 3,
"photos": [
"blob:http://localhost:3000/8f6375b3-0795-4210-bef7-f112feed8244"
]
},
"1443834": {
"id": 1443834,
"body": "10/10 would recomend.",
"date": "2021-03-09T00:00:00.000Z",
"answerer_name": "Krista",
"helpfulness": 2,
"photos": []
},
"1443845": {
"id": 1443845,
"body": "Thank you so much for playing my game!",
"date": "2021-03-10T00:00:00.000Z",
"answerer_name": "itsameemario",
"helpfulness": 1,
"photos": []
},
"1443880": {
"id": 1443880,
"body": "Tree",
"date": "2021-03-10T00:00:00.000Z",
"answerer_name": "Tree",
"helpfulness": 0,
"photos": [
"blob:http://localhost:3000/123051b6-4dfb-410a-a96f-d4a5128e3056"
]
}
}
},
{
"question_id": 152702,
"question_body": "Please write your question here",
"question_date": "2021-03-05T00:00:00.000Z",
"asker_name": "Your nickname",
"question_helpfulness": 32,
"reported": false,
"answers": {}
},
我遇到的问题是，当我运行查找时，我得到了一个与问题集合相关的答案数组，但由于答案深深嵌套，我不确定如何获得他们特定问题的每组答案.
这是我目前所拥有的：（暂时忽略切片和排序，这些是我稍后作为项目的另一部分需要用到的参数）
db.prodquests.aggregate([
{ $match: { _id: 5 } },
{ $unwind: '$questions' },
{ $match: { 'questions.reported': { $lt: 1 } } },
{ $sort: { 'questions.helpful': -1 } },
{ $group: { _id: '$_id', questions: { $push: '$questions' } } },
{ $project: { _id: 1, questions: { $slice: ['$questions', 0, 1] } } },
{ $unwind: '$questions' },
{
$lookup: {
from: 'groupansphotos',
localField: 'questions._id',
foreignField: '_id',
as: 'answers',
},
},
])
这条语句的返回如下：
{
"_id" : 5,
"questions" : {
"_id" : 37,
"body" : "Why is this product cheaper here than other sites?",
"date_written" : "2018-10-18",
"asker_name" : "willsmith",
"asker_email" : "first.last@gmail.com",
"reported" : 0,
"helpful" : 4
},
"answers" : [
{
"_id" : 37,
"answers" : [
{
"_id" : 68,
"body" : "We are selling it here without any markup from the middleman!",
"date_written" : "2018-08-18",
"answerer_name" : "Seller",
"answerer_email" : "null",
"reported" : 0,
"helpful" : 4
}
]
}
]
}
本质上，我只想将答案数组分组到 _id 字段匹配的相应问题下。
提前谢谢你！
【问题讨论】：
标签： database mongodb mongoose aggregation-framework document-database