This is a new requirement I need to implement in my personal project. I successfully joined two collections using aggregate (previous question). Now, I have a new collection that I need to join. Please see codes below:
Student model:
{
fullname: { type: String, required: true },
email: { type: String, required: true },
}
Exams model:
{
test: { type: String, required: false },
top10: [
type: {
studentId: { type: String, required: true },
score: { type: Number, required: false },
}
]
}
Aggregated collections:
db.exams.aggregate([
{ $unwind: "$top10" },
{
$lookup: {
from: "students",
localField: "top10.studentId",
foreignField: "_id",
as: "students"
}
},
{ $addFields: { students: { $arrayElemAt: ["$students", 0] } } },
{
$group: {
_id: "$_id",
test: { $first: "$test" },
students: {
$push: {
studentId: "$top10.studentId",
score: "$top10.score",
fullname: "$students.fullname"
}
}
}
}
])
Now, the 3rd collection is called Teacher.
Teacher model:
{
fullName: { type: String, required: false },
studentId: { type: String, required: false }
}
Expected output should be:
{
"test": "Sample Test #1",
"students": [
{
"studentId": "5f22ef443f17d8235332bbbe",
"fullname": "John Smith",
"score": 11,
"teacher": "Dr. Hofstadter"
},
{
"studentId": "5f281ad0838c6885856b6c01",
"fullname": "Erlanie Jones",
"score": 9,
"teacher": "Mr. Roberts"
},
{
"studentId": "5f64add93dc79c0d534a51d0",
"fullname": "Krishna Kumar",
"score": 5,
"teacher": "Ms. Jamestown"
}
]
}
Appreciate kind of help. Thanks!
You can add these 2 more pipelines before the $group pipeline,
$lookup join collection with teacher
$addFields to get convert array to object
$group to add teacher name in students array
{
$lookup: {
from: "teacher",
localField: "top10.studentId",
foreignField: "studentId",
as: "students.teacher"
}
},
{
$addFields: {
"students.teacher": { $arrayElemAt: ["$students.teacher", 0] }
}
},
{
$group: {
_id: "$_id",
test: { $first: "$test" },
students: {
$push: {
studentId: "$top10.studentId",
score: "$top10.score",
fullname: "$students.fullname",
teacher: { $ifNull: ["$students.teacher.fullname", ""] }
}
}
}
}
Playground
Related
How to display "hardest category" based on in which "study" size of notLearnedWords was the highest. MongoDB Aggregation
I have these 3 models:
Study
WordSet
Category
Study model has reference into WordSet, then WordSet has reference into Category.
And based on Studies i'm displaying statistics.
How i can display "The hardest category" based on size of "notLearnedWords" was the highest?
I don't know on which place i should start with that querying.
For now i display "hardestCategory" as element that is most used.
I think that condition would look something like this:
{ $max: { $size: '$notLearnedWords' } } // size of the study with most notLearnedWords
I would achieve a response like this:
"stats": [
{
"_id": null,
"numberOfStudies": 4,
"averageStudyTime": 82.5,
"allStudyTime": 330,
"longestStudy": 120,
"allLearnedWords": 8
"hardestCategory": "Work" // only this field is missing
}
]
I've tried to do it like this:
const stats = await Study.aggregate([
{ $match: { user: new ObjectID(currentUserId) } },
{
$lookup: {
from: 'users',
localField: 'user',
foreignField: '_id',
as: 'currentUser',
},
},
{
$lookup: {
from: 'wordsets',
let: { wordSetId: '$learnedWordSet' },
pipeline: [
{ $match: { $expr: { $eq: ['$_id', '$$wordSetId'] } } },
{
$project: {
_id: 0,
category: 1,
},
},
{ $unwind: '$category' },
{
$group: {
_id: '$category',
count: { $sum: 1 },
},
},
{ $sort: { count: -1 } },
{ $limit: 1 },
{
$lookup: {
from: 'categories',
localField: '_id',
foreignField: '_id',
as: 'category',
},
},
{
$project: {
_id: 0,
category: { $arrayElemAt: ['$category.name', 0] },
},
},
],
as: 'wordSet',
},
},
{
$group: {
_id: null,
numberOfStudies: { $sum: 1 },
averageStudyTime: { $avg: '$studyTime' },
allStudyTime: { $sum: '$studyTime' },
longestStudy: { $max: '$studyTime' },
allLearnedWords: {
$sum: { $size: '$learnedWords' },
},
hardestCategory: {
$first: {
$first: '$wordSet.category',
},
},
studyWithMostNotLearnedWords: { $max: { $size: '$notLearnedWords' } },
},
},
]);
Study
const studySchema = new mongoose.Schema({
name: {
type: String,
},
studyTime: {
type: Number,
},
learnedWords: [String],
notLearnedWords: [String],
learnedWordSet: {
type: mongoose.Schema.Types.ObjectId,
ref: 'WordSet',
},
user: {
type: mongoose.Schema.Types.ObjectId,
ref: 'User',
},
});
WordSet
const wordSetSchema = new mongoose.Schema({
name: {
type: String,
},
category: {
type: [
{
type: mongoose.Schema.Types.ObjectId,
ref: 'Category',
required: true,
},
],
},
});
Category
const categorySchema = new mongoose.Schema({
name: {
type: String,
},
});
I have a product collection in MongoDb which sole fields like _id, category, user_id.
I want to check and count the sum number of each category in collection given the matching the user_id and then sum up all the count again at the end.
my solution is :
return Product.aggregate([
{ $match: { "user_id": "id if user that added the product" } },
{ "$unwind": "$category" },
{
"$group": {
"_id": {
'category': '$category',
},
"count": { "$sum": 1 }
}
},
{ "$sort": { "_id.category": 1 } },
{
"$group": {
"_id": "$_id.category",
"count": { "$first": "$count" }
}
}
])
the code gives me the count of each category without matching the condition of user_id. But when I add the $match it fails.
Product Schema:
const ProductSchema = new Schema({
title: {
type: String,
required: true
},
description: {
type: String,
required: true
},
quantity: {
type: Number,
default: -1
},
category:
{
type: String,
required: true
},
manufactured_by: {
type: String,
required: true
},
user_id: {
type: Schema.Types.ObjectId,
ref: 'user',
required: true
}
})
my result if I dont add the condition:
[
{
"_id": "A Tables",
"count": 1
},
{
"_id": "C Tables",
"count": 4
},
{
"_id": "B Tables",
"count": 2
}
]
Not sure what you are trying to achieve from the last stage in your pipeline.
But the following should give you desired output (without any complications that you added)
async getSellerStatistics(seller_id) {
return await Product.aggregate([
{ $match: { user_id: seller_id } }
{ $unwind: "$category" },
{
$group: {
_id: "$category",
count: { $sum: 1 },
},
},
{ $sort: { _id: 1 } },
])
}
I have a problem joining two collections in mongoose. I have two collections namely: student and exams.
Student model:
{
fullname: { type: String, required: true },
email: { type: String, required: true },
}
Exams model:
{
test: { type: String, required: false },
top10: [
type: {
studentId: { type: String, required: true },
score: { type: Number, required: false },
}
]
}
Now, I want to join them two by studentId. The result should be:
{
"test": "Sample Test #1",
"students": [
{
"studentId": "5f22ef443f17d8235332bbbe",
"fullname": "John Smith",
"score": 11
},
{
"studentId": "5f281ad0838c6885856b6c01",
"fullname": "Erlanie Jones",
"score": 9
},
{
"studentId": "5f64add93dc79c0d534a51d0",
"fullname": "Krishna Kumar",
"score": 5
}
]
}
What I did was to use aggregate:
return await Exams.aggregate([
{$lookup:
{
from: 'students',
localField: 'top10.studentId',
foreignField: '_id',
as: 'students'
}
}
]);
But this result is not what I had hoped it should be. Any ideas how to achieve this? I would gladly appreciate any help. Thanks!
You can try,
$lookup with students collection
$project to show required fields, $map to iterate loop of top10 array and inside use $reduce to get fullname from students and merge with top10 object using $mergeObjects
db.exams.aggregate([
{
$lookup: {
from: "students",
localField: "top10.studentId",
foreignField: "_id",
as: "students"
}
},
{
$project: {
test: 1,
students: {
$map: {
input: "$top10",
as: "top10",
in: {
$mergeObjects: [
"$$top10",
{
fullname: {
$reduce: {
input: "$students",
initialValue: 0,
in: {
$cond: [
{ $eq: ["$$this._id", "$$top10.studentId"] },
"$$this.fullname",
"$$value"
]
}
}
}
}
]
}
}
}
}
}
])
Playground
Second option you can use $unwind before $lookup,
$unwind deconstruct top10 array
$lookup with students collection
$addFields to convert students array to object using $arrayElemtAt
$group by _id and construct students array and push required fields
db.exams.aggregate([
{ $unwind: "$top10" },
{
$lookup: {
from: "students",
localField: "top10.studentId",
foreignField: "_id",
as: "students"
}
},
{ $addFields: { students: { $arrayElemAt: ["$students", 0] } } },
{
$group: {
_id: "$_id",
test: { $first: "$test" },
students: {
$push: {
studentId: "$top10.studentId",
score: "$top10.score",
fullname: "$students.fullname"
}
}
}
}
])
Playground
I want to aggregate the collections (Review and Account) below but couldn't manage it properly so I needed to ask you guys.
Current Review Collection is written below
{
lawyerId: { type: mongoose.Schema.Types.ObjectId },
reviews: [
{
userId: { type: mongoose.Schema.Types.ObjectId, unique: true },
message: { type: String },
rate: { type: Number },
createdAt: { type: Date, default: Date.now },
},
],
}
If you recommend Review Collection can be refactored like this
{
lawyerId: { type: mongoose.Schema.Types.ObjectId },
userId: { type: mongoose.Schema.Types.ObjectId },
message: { type: String },
rate: { type: Number },
createdAt: { type: Date, default: Date.now },
}
Account Collection
{
_id: { type: mongoose.Schema.Types.ObjectId}
email: { type: String, unique: true },
firstName: { type: String },
lastName: { type: String },
},
The expected result of fetching reviews
{
averageRate: 3.2,
reviews: [
{
firstName: 'Jack',
lastName: 'Harden',
message: 'I dont like it',
rate: 2,
createdAt: '2020-01-01T14:58:23.330+00:00'
},
{
firstName: 'Takeshi',
lastName: 'San',
message: 'Thats nice',
rate: 5,
createdAt: '2020-03-02T10:45:10.120+00:00'
}
],
}
You should be able to achieve this using an aggregation.
You can view a live demo here, which allows you to run this query.
The Query:
// Assuming we are searching for an lawyerId of 3
db.review.aggregate([
{
$match: {
lawyerId: 3
}
},
{
$lookup: {
from: "account",
localField: "userId",
foreignField: "_id",
as: "user"
}
},
{
$unwind: "$user"
},
{
$group: {
_id: "$lawyerId",
averageRate: {
$avg: "$rate"
},
reviews: {
$push: {
createdAt: "$createdAt",
firstName: "$user.firstName",
lastName: "$user.lastName",
message: "$message",
rate: "$rate"
}
}
}
},
{ // *******************************************
$project: { // *******************************************
_id: 0, // If you comment out/remove all of these lines
averageRate: 1, // then the return also contains the 'lawyerId',
reviews: 1 // as '_id', which I would find useful...
} // *******************************************
} // *******************************************
])
The Results:
The query from above, using the data set from above, produces the following results:
[
{
"averageRate": 3.25,
"reviews": [
{
"createdAt": ISODate("2015-02-28T00:00:00Z"),
"firstName": "First",
"lastName": "Uno",
"message": "Message meh",
"rate": 3
},
{
"createdAt": ISODate("2015-02-28T00:00:00Z"),
"firstName": "Second",
"lastName": "Dos",
"message": "Message blah",
"rate": 4
},
{
"createdAt": ISODate("2015-02-28T00:00:00Z"),
"firstName": "First",
"lastName": "Uno",
"message": "Message foo",
"rate": 4
},
{
"createdAt": ISODate("2015-02-28T00:00:00Z"),
"firstName": "Third",
"lastName": "Tres",
"message": "Message bar",
"rate": 2
}
]
}
]
The Dataset:
In Mongo Playground, you can build out databases with multiple collections, this explains the data structure:
db={ // <---- Database 'db'
"account": [ // <---- Collection 'account'
{
_id: 21,
email: "first.uno#gmail.com",
firstName: "First",
lastName: "Uno"
},
{
_id: 22,
email: "second.dos#yahoo.com",
firstName: "Second",
lastName: "Dos"
},
{
_id: 23,
email: "third.tres#hotmail.com",
firstName: "Third",
lastName: "Tres"
}
],
"review": [ // <---- Collection 'review'
{
lawyerId: 3,
userId: 21,
message: "Message meh",
rate: 3,
createdAt: ISODate("2015-02-28T00:00:00Z")
},
{
lawyerId: 3,
userId: 22,
message: "Message blah",
rate: 4,
createdAt: ISODate("2015-02-28T00:00:00Z")
},
{
lawyerId: 3,
userId: 21,
message: "Message foo",
rate: 4,
createdAt: ISODate("2015-02-28T00:00:00Z")
},
{
lawyerId: 3,
userId: 23,
message: "Message bar",
rate: 2,
createdAt: ISODate("2015-02-28T00:00:00Z")
}
]
}
You can try this pipeline to get all reviews from review collection:
db.reviews.aggregate([
{
$lookup: {
from: "accounts",
localField: "userId",
foreignField: "_id",
as: "user"
}
},
{
$unwind: "$user"
},
{
$addFields: {
"firstName": "$user.firstName",
"lastName": "$user.lastName"
}
},
{
$group: {
"_id": null,
"average_rate": {
$avg: "$rate"
},
"reviews": {
$push: "$$ROOT"
}
}
},
{
$unset: [
"_id",
"reviews._id",
"reviews.user",
"reviews.userId",
"reviews.lawyerId"
]
}
])
Results:
[
{
"average_rate": 3.5,
"reviews": [
{
"createdAt": "Some Review Date",
"firstName": "Jack",
"lastName": "Harden",
"message": "I dont like it",
"rate": 2
},
{
"createdAt": "Some Review Date",
"firstName": "Takeshi",
"lastName": "San",
"message": "That's nice",
"rate": 5
}
]
}
]
Demo here
I have the following model and I want to query a specific user on _id field and populate the inbox.messages array with the necessary data that matches the corresponding _id field in the users model and more importantly i also want to group each message by the 'from' field and return that result
const UserSchema = new Schema({
username: {
type: String,
required: true,
},
blockedUsers: {
users: [
{
userId: {type: Schema.Types.ObjectId, ref: 'User', required: true },
}
]
},
favorites: {
users: [
{
userId: {type: Schema.Types.ObjectId, ref: 'User', required: true },
}
]
},
profileViews: {
views: [
{
userId: {type: Schema.Types.ObjectId, ref: 'User', required: true },
date: {type: Date}
}
]
},
inbox: {
messages: [
{
messageId: {type: Schema.Types.ObjectId},
from: {type: Schema.Types.ObjectId, ref: 'User', required: true },
content: {type: String, required: true},
date: {type: Date}
}
]
},
images: {
"imagePaths": [
{
imageId: {type: Schema.Types.ObjectId},
path: { type: String, required: true},
date: {type: Date}
}
],
}
})
what I have so far
let incomingId = '5e29fd75fdfd5320d0e42bc4';
let myUser = await User.aggregate([
{ $match: {"_id": mongoose.Types.ObjectId(incomingId) }},
{ $lookup: { }}
])
Not sure exactly what to put in the $lookup field or if this is even correct.
As a sample I would like the documents to look like:
[
{
"from": "5e240f7480a24e07d832c7bd",
"username":"hable0",
"images": {
imagePaths: [
'images/2020-09-24-Z_34234342_12.jpg'
],
},
"inbox": {
"messages": [
{
"messageId": "5e2a110a21c64d63f451e39e",
"content": "Message content",
"date": "2020-01-23T21:32:58.126Z"
},
{
"messageId": "5e2a111321c64d63f451e3a0",
"content": "Message content",
"date": "2020-01-23T21:33:07.378Z"
},
{
"messageId": "5e2a112321c64d63f451e3a2",
"content": "Message content",
"date": "2020-01-23T21:33:23.036Z"
}
]
}
}
]
You could try the following pipeline with aggregate().
Find the document that matches the id
Unwind inbox.messages
Group by from field
Perform a $lookup to get another document
Perform a $unwind to destruct the array
Specify fields to be included in the output
let myUser = await User.aggregate([
{
$match: { "_id": mongoose.Types.ObjectId(incomingId) }
},
{
$unwind: "$inbox.messages"
},
{
$group: {
_id: { from: "$inbox.messages.from" },
messages: {
$push: {
messageId: "$inbox.messages.messageId"
// Add more info of the message here as needed
}
}
},
},
{
$lookup: {
from: "User",
localField: "_id.from",
foreignField: "_id",
as: "extraUserInfo"
}
},
{
$unwind: "$extraUserInfo"
},
{
$project: {
_id: 0,
from: "$_id.from",
inbox: { messages: "$messages" },
username: "$extraUserInfo.username",
images: "$extraUserInfo.images"
}
}
]);
Sample output:
{
"from": "user1",
"inbox": {
"messages": [{
"messageId": "message1-from-user1"
}]
},
"username": "user1-username",
"images": {
"imagePaths": ["image-path-user1"]
}
} {
"from": "user2",
"inbox": {
"messages": [{
"messageId": "message1-from-user2"
}, {
"messageId": "message2-from-user2"
}, {
"messageId": "message3-from-user2"
}]
},
"username": "user2-username",
"images": {
"imagePaths": ["image-path-user2"]
}
} {
"from": "user3",
"inbox": {
"messages": [{
"messageId": "message1-from-user3"
}, {
"messageId": "message2-from-user3"
}]
},
"username": "user3-username",
"images": {
"imagePaths": ["image-path-user3"]
}
}
Hope this answers part of your question. Though I'm not very clear how you would like to populate the messages array with the user info who sent the messages. But you can perform a $lookup() with a pipeline after $group() operation to attach additional info from the sender to the result.
Read more about $unwind, $group, $project and $lookup.