我想只从我的两个对象数组file_history和uploaded_files中获得符合criteira的子文档。即使我发现这个stackoverflow回答＃2（Mongoose - finding subdocuments by criteria）它对我来说不起作用，或者我错过了什么。
var projectId = req.params.projectId
var uploadId = req.body.uploadId
let populateQuery = [
{path: 'owner'},
{path: 'uploaded_files.file', match: {upload_id: uploadId}},
{path: 'file_history.file', match: {upload_id: uploadId}}
]
Project.findOne({ project_id: projectId }).populate(populateQuery).then(project => {
console.log(project)
})
我的文档如下所示：
{
"_id" : ObjectId("5935a41f12f3fac949a5f925"),
"project_id" : 13,
"updated_at" : ISODate("2017-07-05T21:45:46.754Z"),
"created_at" : ISODate("2017-06-05T18:34:07.150Z"),
"owner" : ObjectId("591eea4439e1ce33b47e73c3"),
"name" : "RDemo project",
"uploaded_files" : [
{
"display_name" : "Log_28-6-2017_14-17-53-562.txt",
"file" : ObjectId("595c4c4f3ae2470700ea07e2"),
"upload_id" : ObjectId("595c0f7ea1d20247285be5f5"),
"created_at" : ISODate("2017-07-05T02:17:51.000Z")
},
{
"display_name" : "Coon.png",
"file" : ObjectId("595c4c553ae2470700ea07e4"),
"upload_id" : ObjectId("595c4c553ae2470700ea07e5"),
"created_at" : ISODate("2017-07-05T02:17:57.000Z")
}
],
"file_history" : [
{
"display_name" : "account working.txt",
"file" : ObjectId("595c0f7ea1d20247285be5f4"),
"upload_id" : ObjectId("595c0f7ea1d20247285be5f5"),
"created_at" : ISODate("2017-07-04T21:58:22.000Z")
},
{
"display_name" : "Log_28-6-2017_14-17-53-562.txt",
"file" : ObjectId("595c4c4f3ae2470700ea07e2"),
"upload_id" : ObjectId("595c0f7ea1d20247285be5f5"),
"created_at" : ISODate("2017-07-05T02:17:51.000Z")
}
]
}
它将打印项目及其file_history和uploaded_files中的所有子文档。但是我只想获得与给定的upload_id匹配的子文档。我做错了什么？
编辑：此问题是指使用mongoose解决问题。我无法在Mongoose中使用此问题的聚合语句（Retrieve only the queried element in an object array in MongoDB collection），因为它返回了一个空数组，但是我能够通过MongoDB运行它，它确实返回了所需的结果。那是我试过的代码：
let projectId = req.params.projectId // Project ID is an integer and no objectId
let uploadId = new mongoose.Types.ObjectId(req.body.uploadId)
console.log(`ProjectID: ${projectId}, uploadId: ${uploadId}, params: ${req.body.uploadId}`)
let populateQuery = [
{path: 'owner'},
{path: 'uploaded_files.file'},
{path: 'file_history.file'}
]
Project.aggregate(
{$match: {"project_id": projectId}},
{$project: {
uploaded_files: {$filter: {
input: '$uploaded_files',
as: 'uploadedFile',
cond: {$eq: ['$$uploadedFile.upload_id', uploadId]}
}}
}
}
).then(project => {
console.log(project)
})
console.log返回：ProjectID: 13, uploadId: 595c0f7ea1d20247285be5f5, params: 595c0f7ea1d20247285be5f5这是正确的（存在ID）
答案 0 :(得分：1)
你正在做一些可怕的错误而且不清楚那是什么。因此，向您展示的最佳方式是示例。
另请注意，单个匹配＆＃34;甚至不需要$filter。而standard positional projection只会在这里做：
const async = require('async'),
mongoose = require('mongoose'),
Schema = mongoose.Schema,
ObjectId = require('mongodb').ObjectID
mongoose.set('debug',true)
mongoose.Promise = global.Promise;
mongoose.connect('mongodb://localhost/test');
const doc =
{
"_id" : ObjectId("5935a41f12f3fac949a5f925"),
"project_id" : 13,
"updated_at" : new Date("2017-07-05T21:45:46.754Z"),
"created_at" : new Date("2017-06-05T18:34:07.150Z"),
"owner" : ObjectId("591eea4439e1ce33b47e73c3"),
"name" : "RDemo project",
"uploaded_files" : [
{
"display_name" : "Log_28-6-2017_14-17-53-562.txt",
"file" : ObjectId("595c4c4f3ae2470700ea07e2"),
"upload_id" : ObjectId("595c0f7ea1d20247285be5f5"),
"created_at" : new Date("2017-07-05T02:17:51.000Z")
},
{
"display_name" : "Coon.png",
"file" : ObjectId("595c4c553ae2470700ea07e4"),
"upload_id" : ObjectId("595c4c553ae2470700ea07e5"),
"created_at" : new Date("2017-07-05T02:17:57.000Z")
}
],
"file_history" : [
{
"display_name" : "account working.txt",
"file" : ObjectId("595c0f7ea1d20247285be5f4"),
"upload_id" : ObjectId("595c0f7ea1d20247285be5f5"),
"created_at" : new Date("2017-07-04T21:58:22.000Z")
},
{
"display_name" : "Log_28-6-2017_14-17-53-562.txt",
"file" : ObjectId("595c4c4f3ae2470700ea07e2"),
"upload_id" : ObjectId("595c0f7ea1d20247285be5f5"),
"created_at" : new Date("2017-07-05T02:17:51.000Z")
},
{
"display_name" : "Coon.png",
"file" : ObjectId("595c4c553ae2470700ea07e4"),
"upload_id" : ObjectId("595c4c553ae2470700ea07e5"),
"created_at" : new Date("2017-07-05T02:17:57.000Z")
},
{
"display_name" : "Coon.png",
"file" : ObjectId("595c4c553ae2470700ea07e4"),
"upload_id" : ObjectId("595c4c553ae2470700ea07e5"),
"created_at" : new Date("2017-07-05T02:17:57.000Z")
}
]
};
const Test = mongoose.model('Test', new Schema({}, { strict: false }) );
function log(data) {
console.log(JSON.stringify(data, undefined, 2))
}
async.series(
[
// Clean data
(callback) =>
async.each(mongoose.models,(model,callback) =>
model.remove({},callback),callback),
// Insert data
(callback) => Test.insertMany(doc,callback),
// Correct usage of $filter
(callback) =>
Test.aggregate(
[
{ "$match": { "project_id": 13 } },
{ "$addFields": {
"uploaded_files": {
"$filter": {
"input": "$uploaded_files",
"as": "f",
"cond": {
"$eq": [
"$$f.upload_id", ObjectId("595c0f7ea1d20247285be5f5")
]
}
}
},
"file_history": {
"$filter": {
"input": "$file_history",
"as": "f",
"cond": {
"$eq": [
"$$f.upload_id", ObjectId("595c0f7ea1d20247285be5f5")
]
}
}
}
}}
],
(err,results) => {
if (err) callback(err);
log(results);
callback();
}
),
// Just a normal positional project for 1 match
(callback) => Test.findOne(
{ "uploaded_files.upload_id": ObjectId("595c0f7ea1d20247285be5f5") },
{ "uploaded_files.$": 1 },
(err,result) => {
if (err) callback(err);
log(result);
callback();
}
)
],
(err) => {
if (err) throw err;
mongoose.disconnect();
}
)
产生所需的输出：
[
{
"_id": "5935a41f12f3fac949a5f925",
"__v": 0,
"project_id": 13,
"updated_at": "2017-07-05T21:45:46.754Z",
"created_at": "2017-06-05T18:34:07.150Z",
"owner": "591eea4439e1ce33b47e73c3",
"name": "RDemo project",
"uploaded_files": [
{
"created_at": "2017-07-05T02:17:51.000Z",
"upload_id": "595c0f7ea1d20247285be5f5",
"file": "595c4c4f3ae2470700ea07e2",
"display_name": "Log_28-6-2017_14-17-53-562.txt"
}
],
"file_history": [
{
"created_at": "2017-07-04T21:58:22.000Z",
"upload_id": "595c0f7ea1d20247285be5f5",
"file": "595c0f7ea1d20247285be5f4",
"display_name": "account working.txt"
},
{
"created_at": "2017-07-05T02:17:51.000Z",
"upload_id": "595c0f7ea1d20247285be5f5",
"file": "595c4c4f3ae2470700ea07e2",
"display_name": "Log_28-6-2017_14-17-53-562.txt"
}
]
}
]
Mongoose: tests.findOne({ 'uploaded_files.upload_id': ObjectId("595c0f7ea1d20247285be5f5") }, { fields: { 'uploaded_files.$': 1 } })
{
"_id": "5935a41f12f3fac949a5f925",
"uploaded_files": [
{
"display_name": "Log_28-6-2017_14-17-53-562.txt",
"file": "595c4c4f3ae2470700ea07e2",
"upload_id": "595c0f7ea1d20247285be5f5",
"created_at": "2017-07-05T02:17:51.000Z"
}
]
}