Is there a way to combine / produce a cross product of nested elements within MongoDB.
As an example I have
{
images:
[
{
name: 'A',
url: 'urlA'
},
{
name: 'B',
url: 'urlB'
}
],
tags: [
{
name: 'Tag1',
description: 'description1'
},
{
name: 'Tag2',
description: 'description2'
}
]
}
By preferred result should be
[
{
url: 'urlA',
name: 'Tag1'
},
{
url: 'urlA',
name: 'Tag2'
},
{
url: 'urlB',
name: 'Tag1'
},
{
url: 'urlB',
name: 'Tag2'
}
]
Is it possible to store the generated documents in a new collection?
MongoDB Query
db.test.aggregate([
{ $unwind: '$images' },
{ $unwind: '$tags' },
{ "$group" :
{ "_id" :
{ "url": "$images.url", "name": "$tags.name" },
}
},
{ "$group" :
{ "_id" : null,
"result":
{ "$addToSet" :
{ "url" : "$_id.url", "name" : "$_id.name" }
},
}
},
{"$project": { "_id":0, "result": 1 }}
]);
Output
{
"result": [
{
"url": "urlA",
"name": "Tag1"
},
{
"url": "urlA",
"name": "Tag2"
},
{
"url": "urlB",
"name": "Tag1"
},
{
"url": "urlB",
"name": "Tag2"
}
]}
Related
MongoDB 5.0.9
I am trying to get
value of application within course and their specification
value of paid application ( status : paid) based on course and their specification
courses collection having multiple courses with specification which might be there maybe not
[
{
"_id": {
"$oid": "62aab6669b3740313d881a30"
},
"course_name": "Master",
"fees": "Rs.1000.0/-",
"course_specialization": [
{
"spec_name": "Social Work",
"is_activated": true
}
],
"college_id": {
"$oid": "628dfd41ef796e8f757a5c13"
},
"is_pg": true
},
{
"_id": {
"$oid": "62aab6669b3740313d881a38"
},
"college_id": {
"$oid": "628dfd41ef796e8f757a5c13"
},
"course_name": "BBA",
"fees": "Rs.1000.0/-",
"is_pg": false,
"course_specialization": null
},
{
"_id": {
"$oid": "628f3967cb69fc0789e69181"
},
"course_name": "BTech",
"fees": "Rs.1000.0/-",
"course_specialization": [
{
"spec_name": "Computer Science and Engineering",
"is_activated": true
},
{
"spec_name": "Mutiple Specs",
"is_activated": true
}
],
"college_id": {
"$oid": "628dfd41ef796e8f757a5c13"
},
"is_pg": false
},
{
"_id": {
"$oid": "628f35a1cb69fc0789e6917e"
},
"course_name": "Bachelor",
"fees": "Rs.1000.0/-",
"course_specialization": [
{
"spec_name": "Social Work",
"is_activated": true
}
],
"college_id": {
"$oid": "628dfd41ef796e8f757a5c13"
},
"is_pg": false
}
],
Student Application forms collection where we are storing student application forms details
[
{
"_id": {
"$oid": "62cd476adbc878a0490e20ee"
},
"spec_name1": "Social Work",
"spec_name2": "",
"spec_name3": "",
"student_id": {
"$oid": "62cd1374dbc878a0490e20a5"
},
"course_id": {
"$oid": "62aab6669b3740313d881a30"
},
"current_stage": 2.5,
"declaration": true,
"payment_info": {
"payment_id": "123458",
"status": "paid"
},
"enquiry_date": {
"$date": {
"$numberLong": "1657620330432"
}
},
"last_updated_time": {
"$date": {
"$numberLong": "1657621796062"
}
}
},
{
"_id": {
"$oid": "62cd476adbc878a0490e20ef"
},
"spec_name1": "",
"spec_name2": "",
"spec_name3": "",
"student_id": {
"$oid": "62cd1374dbc878a0490e20a5"
},
"course_id": {
"$oid": "62aab6669b3740313d881a38"
},
"current_stage": 2.5,
"declaration": true,
"payment_info": {
"payment_id": "123458",
"status": "paid"
},
"enquiry_date": {
"$date": {
"$numberLong": "1657620330432"
}
},
"last_updated_time": {
"$date": {
"$numberLong": "1657621796062"
}
}
},
{
"_id": {
"$oid": "62cdc12000b820f5ea58cc60"
},
"spec_name1": "Social Work",
"spec_name2": "",
"spec_name3": "",
"student_id": {
"$oid": "62cdad90a9b64d58b15e6976"
},
"course_id": {
"$oid": "628f35a1cb69fc0789e6917e"
},
"current_stage": 6.25,
"declaration": false,
"payment_info": {
"payment_id": "",
"status": ""
},
"enquiry_date": {
"$date": {
"$numberLong": "1657651488511"
}
},
"last_updated_time": {
"$date": {
"$numberLong": "1657651987155"
}
}
}
]
Desired output with every specification within the course
[
"_id": {
"coursename": "Master",
"spec": "Social Work",
"Application_Count": 1,
"Paid_Application_Count:0
},
{
"_id": {
"coursename": "Bachelor"
"spec":"" ,
"Application_Count": 1,
"Paid_Application_Count:0
},
{
"_id": {
"coursename": "BBA"
"spec":"" ,
"Application_Count": 1,
"Paid_Application_Count:1
},
]
Aggregation Query
[{
$match: {
college_id: ObjectId('628dfd41ef796e8f757a5c13')
}
}, {
$project: {
_id: 1,
course_name: 1,
course_specialization: 1
}
}, {
$unwind: {
path: '$course_name',
includeArrayIndex: 'course_index',
preserveNullAndEmptyArrays: true
}
}, {
$unwind: {
path: '$course_specialization',
includeArrayIndex: 'course_specs_index',
preserveNullAndEmptyArrays: true
}
}, {
$lookup: {
from: 'studentApplicationForms',
'let': {
id: '$_id',
spec: '$course_specialization.spec_name'
},
pipeline: [
{
$match: {
$expr: {
$and: [
{
$eq: [
'$course_id',
'$$id'
]
},
{
$eq: [
'$spec_name1',
'$$spec'
]
}
]
}
}
},
{
$project: {
student_id: 1,
payment_info: 1,
spec_name1: 1,
spec_name2: 1,
spec_name3: 1
}
}
],
as: 'student_application'
}
}, {
$unwind: {
path: '$student_application',
includeArrayIndex: 'application',
preserveNullAndEmptyArrays: true
}
}, {
$facet: {
course: [
{
$group: {
_id: {
course_name: '$course_name',
spec: '$course_specialization'
},
count: {
$count: {}
}
}
}
],
declatration: [
{
$group: {
_id: {
course_name: '$course_name',
spec: '$course_specialization'
},
count_dec: {
$sum: {
$cond: [
'$student_application.declaration',
1,
0
]
}
}
}
}
],
payment: [
{
$group: {
_id: {
course_name: '$course_name',
spec: '$course_specialization'
},
payment: {
$sum: {
$eq: [
'$student_application.payment_info.status',
'paid'
]
}
}
}
}
]
}
}]
Problem :
I am able to get application count but it is not getting unique value if 2 specs are same then duplicate value is coming as you can see on sample application collection Social Work is in two different course . So my aggregations is not grouping them based in course name.specs
Not able to find correct Paid_Application_Count and Application_Count
Update :
Updated JSON Data Matching use cases with different type of data
MongoDB Playground
You can do it in several different ways, I took the liberty to simplify the pipeline a little bit.
I will just mention that the structure does not fully make sense to me, and there are some additional contradictions between the sample input you provided and the "text" description/pipeline description.
Just a tiny example is payment_info_status being paid in the sample and capture in the pipeline.
These things will not change the pipeline structure, will just need to be fixed by you based on the actual needs.
db.courses.aggregate([
{
$project: {
_id: 1,
course_name: 1,
course_specialization: 1
}
},
{
$unwind: {
path: "$course_specialization",
preserveNullAndEmptyArrays: true
}
},
{
$lookup: {
from: "studentApplicationForms",
"let": {
courseId: "$_id",
spec: {
$ifNull: [
"$course_specialization.spec_name",
""
]
}
},
pipeline: [
{
$match: {
$expr: {
$and: [
{
$eq: [
"$spec_name1",
"$$spec"
]
},
{
$eq: [
"$$courseId",
"$course_id"
]
}
]
}
}
},
{
$project: {
student_id: 1,
payment_info: 1,
spec_name1: 1,
spec_name2: 1,
spec_name3: 1,
declaration: 1,
}
},
{
$group: {
_id: null,
count: {
$sum: 1
},
declatration: {
$sum: {
$cond: [
"$declaration",
1,
0
]
}
},
paid: {
$sum: {
$cond: [
{
$eq: [
"$payment_info.status",
"paid"
]
},
1,
0
]
}
},
}
}
],
as: "student_application"
}
},
{
$project: {
_id: {
coursename: "$course_name",
spec: "$course_specialization.spec_name",
Application_count: {
$ifNull: [
{
$first: "$student_application.count"
},
0
]
},
Declaration_count: {
$ifNull: [
{
$first: "$student_application.declatration"
},
0
]
},
Paid_Application_Count: {
$ifNull: [
{
$first: "$student_application.paid"
},
0
]
},
}
}
}
])
Mongo Playground
I have aggregation like this:
Produk.aggregate([
{
$lookup: {
from: "kis_m_kategoriproduks",
localField: "idSubKategori",
foreignField: "subKategori._id",
as: "kategori",
},
},
{ $unwind: "$kategori" },
{ $sort: { produk: 1 } },
{
$project: {
_id: 0,
id: "$id",
dataKategori: {
idKategori: "$kategori._id",
kategori: "$kategori.kategori",
idSubKategori: "$idSubKategori",
subKategori: "$kategori.subKategori",
},
},
},
])
current result is :
{
"status": "success",
"data": [
{
"dataKategori": {
"idKategori": "6195bbec8ee419e6a9b8329d",
"kategori": "Kuliner",
"idSubKategori": "6195bc0f8ee419e6a9b832a2",
"subKategori": [
{
"nama": "Food",
"_id": "6195bc0f8ee419e6a9b832a2"
},
{
"nama": "Drink",
"_id": "6195bc258ee419e6a9b832a8"
}
]
}
}
]
}
I only want to display data in subKategori that the _id match with idSubKategori. this what I expected:
{
"status": "success",
"data": [
{
"dataKategori": {
"idKategori": "6195bbec8ee419e6a9b8329d",
"kategori": "Kuliner",
"idSubKategori": "6195bc0f8ee419e6a9b832a2",
"subKategori": [
{
"nama": "Food",
"_id": "6195bc0f8ee419e6a9b832a2"
}
]
}
}
]
}
here is my $kategori schema:
const schema = mongoose.Schema(
{
kategori: {
type: String,
required: true,
unique: true,
},
subKategori: [
{
id: mongoose.Types.ObjectId,
nama: String,
},
],
},
{
timestamps: false,
}
);
any suggestion?
I fix the problem by add $filter inside $project like this:
dataKategori: {
idKategori: "$kategori._id",
kategori: "$kategori.kategori",
subKategori: {
$arrayElemAt: [
{
$filter: {
input: "$kategori.subKategori",
as: "sub",
cond: { $eq: ["$$sub._id", "$idSubKategori"] },
},
},
0,
],
},
},
reference: https://stackoverflow.com/a/42490320/6412375
I have a collection datas like this:
[
{
"_id": 0,
"languages": { "en": true },
"translated_data": { "en": { "title": "eng title 1" } }
},
{
"_id": 1,
"languages": { "en": true },
"translated_data": { "en": { "title": "eng title 2" } }
}
]
And I need to transform it to a format like this:
[
{
"_id": 0,
"translations": [{ "language": "en", "data": { "title": "eng title 1" } }]
},
{
"_id": 1,
"translations": [{ "language": "en", "data": { "title": "eng title 2" } }]
}
]
I tried this update query but stuck
db.datas.updateMany({}, [
{
$set: {
translations: {
$map: {
input: {
$filter: {
input: {
$objectToArray: "$languages",
},
as: "language",
cond: { $eq: ["$$language.v", true] },
},
},
as: "language",
in: {
language: "$$language.k",
data: "???", // get value from $translated_data[$$language.k]
},
},
},
},
},
{
$unset: ["languages", "translated_data"],
},
]);
Try this:
db.datas.updateMany({},
[
{
$set: {
"translate_ok": {
$first: {
$map: {
input: { $objectToArray: "$languages" },
as: "language",
in: { $eq: ["$$language.v", true] },
}
}
}
}
},
{
$set: {
translations: {
$map: {
input: { $objectToArray: "$translated_data" },
as: "language",
in: {
$cond: [
"$translate_ok",
{
language: "$$language.k",
data: "$$language.v"
},
{
$arrayToObject: [["$$language"]]
}
]
}
}
}
}
},
{
$unset: ["languages", "translated_data", "translate_ok"]
}
]
);
Output:
/* 1 */
{
"_id" : 1,
"translations" : [
{
"language" : "en",
"data" : {
"title" : "eng title 1"
}
}
]
},
/* 2 */
{
"_id" : 2,
"translations" : [
{
"en" : {
"title" : "eng title 2"
}
}
]
}
My test data:
/* 1 */
{
"_id" : 1,
"languages" : {
"en" : true
},
"translated_data" : {
"en" : {
"title" : "eng title 1"
}
}
},
/* 2 */
{
"_id" : 2,
"languages" : {
"en" : false
},
"translated_data" : {
"en" : {
"title" : "eng title 2"
}
}
}
I have following schemas.
First: AdditionalFieldSchema
const AdditionalFieldSchema = new Schema({
names: [
{
type: Schema.Types.ObjectId,
ref: "multiLanguageContent",
required: true
}
],
...
});
Second: MultiLanguageContentSchema
const MultiLanguageContentSchema = new Schema({
value: {
type: String,
required: true
},
...
});
and I have the following mongoose aggregate query.
The goal is to fetch every employees with their additionalField attached.
const employees = await Employee.aggregate([
{
$match: {
status: "active",
$nor: [
{ email: "blablabla" },
{ email: "blobloblo" }
]
}
},
{
$lookup: {
from: AdditionalField.collection.name,
let: { af_id: "$_id" },
pipeline: [{
$match: {
$expr: {
$and: [
{ $eq: ["$ownership", "$$af_id"] },
{ $eq: ["$status", "active"] },
{ $eq: ["$functionalType", "blablabla"] }
]
}
}
}],
as: "afs"
}
},
{ $unwind: "$afs" },
{ $unwind: "$afs.names" },
{
$group: {
_id: "$_id",
email: { $first: "$email" },
afs: {
$push: {
value: "$afs.value",
names: "$afs.names"
}
}
}
}
]);
The query I run to test this aggregate function.
query TestQuery {
testQuery
{
email
afs {
names {
value
}
value
}
}
}
The result I have.
"data": {
"testQuery": [
{
"email": "blablabla#test.com"
"afs": [
{
"names": [
{
"value": "Name 1"
}
],
"value": "Value 1"
},
{
"names": [
{
"value": "Name 2"
}
],
"value": "Value 2"
},
...
]
},
...
Result is good, I have data I want.
But I would like to have a result like this below
"data": {
"testQuery": [
{
"email": "blablabla#test.com",
"afs": [
{
"names": "Name 1",
"value": "Value 1"
},
{
"names": "Name 2",
"value": "Value 2"
},
...
]
},
...
It seems like { $unwind: "$afs.names" }, is not working.
Any ideas ?
Thanks, Flo
This question already has an answer here:
Handling unwind for the non existing embedded document [duplicate]
(1 answer)
Closed 3 years ago.
If country doesn't have reference states and cities. $unwind removes country name from the collections.
Expected Output will be Mongodb should return country name even if the country doesn't any states and cities reference.
Country Collection:
[
{
"_id": "5d052c76df076d23a48d4a3b",
"name": "India"
},
{
"_id": "5d052c76df076d23a48d4b07",
"name": "Indonesia"
},
{
"_id": "5d052c76df076d23a48d22f4",
"name": "Iran"
}
]
State Collection:
[
{
"_id": "5d2236c37ed1112b3cc41397",
"name": "Andaman and Nicobar Islands",
"countryId": "5d052c76df076d23a48d4a3b"
},
{
"_id": "5d2236c37ed1112b3cc41398",
"name": "Andhra Pradesh",
"countryId": "5d052c76df076d23a48d4a3b"
}
]
City Collection:
[
{
"name": "Port Blair",
"stateId": "5d2236c37ed1112b3cc41397"
},
{
"name": "Adoni",
"stateId": "5d2236c37ed1112b3cc41398"
}
]
Query:
Country.aggregate([
{
$lookup:{
from: 'states',
localField:'_id',
foreignField:'countryId',
as:'states'
}
},
{
$unwind: {
path: "$states"
}
},
{
$lookup:{
from: 'cities',
localField:'states._id',
foreignField:'stateId',
as:'states.cities'
}
},
{
$group: {
_id: {
_id: '$_id',
name: '$name'
},
states: {
$push: '$states'
}
}
},
{
$project: {
_id: '$_id._id',
name: '$_id.name',
states: 1
}
}
])
Output:
[
{
"_id":"5d052c76df076d23a48d4a3b",
"name":"India",
"states":[
{
"_id":"5d2236c37ed1112b3cc41397",
"name":"Andaman and Nicobar Islands",
"countryId":"5d052c76df076d23a48d4a3b",
"cities":[
{
"name":"Port Blair",
"stateId":"5d2236c37ed1112b3cc41397"
}
]
},
{
"_id":"5d2236c37ed1112b3cc41398",
"name":"Andhra Pradesh",
"countryId":"5d052c76df076d23a48d4a3b",
"cities":[
{
"name":"Adoni",
"stateId":"5d2236c37ed1112b3cc41398"
}
]
}
]
}
]
Expected Output:
[
{
"_id":"5d052c76df076d23a48d4a3b",
"name":"India",
"states":[
{
"_id":"5d2236c37ed1112b3cc41397",
"name":"Andaman and Nicobar Islands",
"countryId":"5d052c76df076d23a48d4a3b",
"cities":[
{
"name":"Port Blair",
"stateId":"5d2236c37ed1112b3cc41397"
}
]
},
{
"_id":"5d2236c37ed1112b3cc41398",
"name":"Andhra Pradesh",
"countryId":"5d052c76df076d23a48d4a3b",
"cities":[
{
"name":"Adoni",
"stateId":"5d2236c37ed1112b3cc41398"
}
]
}
]
},
{
"_id":"5d052c76df076d23a48d4b07",
"name":"Indonesia",
"states":[
]
},
{
"_id":"5d052c76df076d23a48d22f4",
"name":"Iran",
"states":[
]
}
]
just add " preserveNullAndEmptyArrays: true " to $unwind
Country.aggregate([
{
$lookup:{
from: 'states',
localField:'_id',
foreignField:'countryId',
as:'states'
}
},
{
$unwind: {
path: "$states",
preserveNullAndEmptyArrays: true
}
},
{
$lookup:{
from: 'cities',
localField:'states._id',
foreignField:'stateId',
as:'states.cities'
}
},
{
$group: {
_id: {
_id: '$_id',
name: '$name'
},
states: {
$push: '$states'
}
}
},
{
$project: {
_id: '$_id._id',
name: '$_id.name',
states: 1
}
}
])
output
[
{
"states" : [
{
"cities" : []
}
],
"_id" : "5d052c76df076d23a48d22f4",
"name" : "Iran"
},
{
"states" : [
{
"cities" : []
}
],
"_id" : "5d052c76df076d23a48d4b07",
"name" : "Indonesia"
},
{
"states" : [
{
"_id" : "5d2236c37ed1112b3cc41397",
"name" : "Andaman and Nicobar Islands",
"countryId" : "5d052c76df076d23a48d4a3b",
"cities" : [
{
"_id" : ObjectId("5d38ccb6f9c5fa48bf099027"),
"name" : "Port Blair",
"stateId" : "5d2236c37ed1112b3cc41397"
}
]
},
{
"_id" : "5d2236c37ed1112b3cc41398",
"name" : "Andhra Pradesh",
"countryId" : "5d052c76df076d23a48d4a3b",
"cities" : [
{
"_id" : ObjectId("5d38ccbcf9c5fa48bf09902a"),
"name" : "Adoni",
"stateId" : "5d2236c37ed1112b3cc41398"
}
]
}
],
"_id" : "5d052c76df076d23a48d4a3b",
"name" : "India"
}
]