Related
We would like to filter SKU's List which has verificationData data and differenceInStock difference greater than or Less than 0
Here is an example Data Set.
[
{
"_id": "636e0beaa13ef73324e613f0",
"status": "ACTIVE",
"inventory": 132,
"parentCategory": [
"Salt"
],
"title": "Aashirvaad MRP: 28Rs Salt 27 kg Bopp Bag (Set of 1 kg x 27)",
"createdAt": "2022-11-11T08:46:34.950Z",
"updatedAt": "2022-11-24T17:43:27.361Z",
"__v": 3,
"verificationData": [
{
"_id": "637c57ebbe783a9a138fc2d3",
"verificationDate": "2022-11-22T05:02:35.155Z",
"items": {
"listingId": "636e0beaa13ef73324e613f0",
"phyiscalVerification": [
{
"verifiedBy": "634534e72ef6462fcb681a39",
"closingStock": 178,
"phyiscalStock": 178,
"differenceInStock": 0,
"verifiedAt": "2022-11-22T10:19:38.388Z",
"_id": "637ca23abe783a9a1394f402"
}
],
"_id": "637ca23abe783a9a1394f401"
},
"yearMonthDayUTC": "2022-11-22"
},
{
"_id": "637d9b65be783a9a13998726",
"verificationDate": "2022-11-23T04:02:45.804Z",
"items": {
"listingId": "636e0beaa13ef73324e613f0",
"phyiscalVerification": [
{
"verifiedBy": "634534e72ef6462fcb681a39",
"closingStock": 161,
"phyiscalStock": 167,
"differenceInStock": 6,
"verifiedAt": "2022-11-23T09:52:36.815Z",
"_id": "637ded64be783a9a13a29d55"
}
],
"_id": "637ded64be783a9a13a29d54"
},
"yearMonthDayUTC": "2022-11-23"
},
{
"_id": "637f0254be783a9a13a94354",
"verificationDate": "2022-11-24T05:34:12.995Z",
"items": {
"listingId": "636e0beaa13ef73324e613f0",
"phyiscalVerification": [
{
"verifiedBy": "634534e72ef6462fcb681a39",
"closingStock": 144,
"phyiscalStock": 146,
"differenceInStock": 2,
"verifiedAt": "2022-11-24T12:02:28.123Z",
"_id": "637f5d54be783a9a13b1039a"
}
],
"_id": "637f5d54be783a9a13b10399"
},
"yearMonthDayUTC": "2022-11-24"
},
{
"_id": "2022-11-25",
"yearMonthDayUTC": "2022-11-25",
"items": null
}
]
},
{
"_id": "62b5c39062ddb963fc64c42d",
"status": "ACTIVE",
"inventory": 10,
"parentCategory": [
"Salt"
],
"finalMeasurementUnit": "kg",
"finalMeasure": "1 kg",
"title": "Marvella Citric Acid Lemon Salt 1 kg Pouch (Set of 500 gm x 2)",
"createdAt": "2022-06-24T14:00:49.052Z",
"updatedAt": "2022-11-21T11:04:21.643Z",
"__v": 2,
"verificationData": [
{
"_id": "2022-11-22",
"yearMonthDayUTC": "2022-11-22",
"items": null
},
{
"_id": "2022-11-23",
"yearMonthDayUTC": "2022-11-23",
"items": null
},
{
"_id": "2022-11-24",
"yearMonthDayUTC": "2022-11-24",
"items": null
},
{
"_id": "2022-11-25",
"yearMonthDayUTC": "2022-11-25",
"items": null
}
]
}
]
This could have array of 100+ SKU's
Our Aggregate Functions is as Follows
let reqData = await userListing.aggregate([
{
$match: {
warehouseId: { $eq: ObjectId(warehouseId) },
parentCategory: { $in: catList },
isWarehouseListing: { $eq: true },
isBlocked: { $ne: true },
isArchived: { $ne: true },
},
},
{ $sort: { whAddedAt: -1 } },
{
$lookup: {
from: "listingstockverifications",
let: { listId: "$_id" },
pipeline: [
{
$match: {
verificationDate: {
$gte: newFromDate,
$lt: newToDate,
},
},
},
{
$project: {
verificationDate: 1,
items: {
$filter: {
input: "$items",
cond: {
$and: [
/* {
"$$this.phyiscalVerification": {
$filter: {
input: "$$this.phyiscalVerification",
as: "psitem",
cond: { $gt: [ "$$psitem.differenceInStock", 0 ] },
},
},
}, */
{
$eq: ["$$this.listingId", "$$listId"],
},
],
},
},
},
yearMonthDayUTC: {
$dateToString: {
format: "%Y-%m-%d",
date: "$verificationDate",
},
},
},
},
{ $unwind: "$items" },
],
as: "stockVerification",
},
},
{
$addFields: {
verificationData: {
$map: {
input: dummyArray,
as: "date",
in: {
$let: {
vars: {
dateIndex: {
$indexOfArray: [
"$stockVerification.yearMonthDayUTC",
"$$date",
],
},
},
in: {
$cond: {
if: { $ne: ["$$dateIndex", -1] },
then: {
$arrayElemAt: ["$stockVerification", "$$dateIndex"],
},
else: {
_id: "$$date",
yearMonthDayUTC: "$$date",
items: null,
},
},
},
},
},
},
},
},
},
{
$project: {
stockVerification: 0,
},
},
]);
At Last now we would like to filter the SKU List the which has following Data
verificationData[].items.phyiscalVerification[].differenceInStock is Greater than or Less than 0
Expected Output in the following Exmaple would be 1st SKUs
as 2nd SKU does not have any Item Data
and even if in 3rd SKU if we got Item Data but should match the following condition
verificationData[].items.phyiscalVerification[].differenceInStock is Greater than or Less than 0
Thank you for taking your time to read and support.
You can add these two following stages to your aggregation, The idea is simple - just filter out all subdocuments that do not match the condition.
Because of the nested structure it's just not the sexiest of pipelines but it will suffice.
db.collection.aggregate([
{
$match: {
$or: [
{
"verificationData.items.phyiscalVerification.differenceInStock": {
$gt: 0
}
},
{
"verificationData.items.phyiscalVerification.differenceInStock": {
$lt: 0
}
}
]
}
},
{
$addFields: {
verificationData: {
$filter: {
input: {
$map: {
input: {
$filter: {
input: "$verificationData",
as: "verification",
cond: {
$ne: [
"$$verification.items",
null
]
}
}
},
as: "top",
in: {
$mergeObjects: [
"$$top",
{
"items": {
"$mergeObjects": [
"$$top.items",
{
phyiscalVerification: {
$filter: {
input: "$$top.items.phyiscalVerification",
as: "pshycical",
cond: {
$ne: [
"$$pshycical.differenceInStock",
0
]
}
}
}
}
]
}
}
]
}
}
},
cond: {
$gt: [
{
$size: "$$this.items.phyiscalVerification"
},
0
]
}
}
}
}
}
])
Mongo Playground
I have these two aggregations, as shown below.
The first one returns the clients that have zero visits(no visit objects created for the client).
The second one returns the clients with less visits than the others(at least 5).
I want to combine these two aggregations results into one so that they will be ordered like this:
[ no visits clients,
least visits clients ]
Is that possible without simply using Array concat method?
these two aggregations:
let clients = await clientModel.aggregate([
{
$lookup: {
from: "visits",
localField: "_id",
foreignField: "client",
as: "visits",
},
},
{
$project: {
_id: 1,
name: 1,
count: {
$size: "$visits",
},
},
},
{
$match: {
count: 0,
},
},
{
$project: {
_id: 1,
name: 1,
},
},
]);
with this result :
"Zero visits": [
{
"_id": "6182ebe5ea218257521cdc36",
"name": "cleint_807"
},
{
"_id": "6182ebfaea218257521cdc9a",
"name": "cleint_907"
},
{
"_id": "6182ec02ea218257521cdcbe",
"name": "cleint_943"
},
{
"_id": "6182ec20ea218257521cdd48",
"name": "cleint_71"
},
{
"_id": "6182ec29ea218257521cdd74",
"name": "cleint_115"
},
{
"_id": "6182ec54ea218257521cde5a",
"name": "cleint_345"
},
{
"_id": "6182ec61ea218257521cdea3",
"name": "cleint_418"
},
{
"_id": "6182ec71ea218257521cdef4",
"name": "cleint_499"
},
{
"_id": "6182ec96ea218257521cdfbc",
"name": "cleint_699"
}
],
Second aggregation:
visits = await visitModel.aggregate([
{ $match: { time: { $lte: +to, $gte: +from } } },
{
$project: {
date: {
$toDate: "$time",
},
client: 1,
},
},
{
$project: {
day: {
$dayOfWeek: "$date",
},
client: 1,
},
},
{
$match: {
day: 2,
},
},
{
$group: {
_id: {
client: "$client",
},
count: {
$sum: 1,
},
},
},
{
$sort: {
count: 1,
},
},
{
$limit: 10,
},
{
$lookup: {
from: "clients",
localField: "_id.client",
foreignField: "_id",
as: "client",
},
},
{
$unwind: {
path: "$client",
preserveNullAndEmptyArrays: false,
},
},
{
$project: {
_id: "$client._id",
name: "$client.name",
},
},
]);
with this result :
"Less visits": [
{
"_id": "6182eb73ea218257521cd9f6",
"name": "cleint_231"
},
{
"_id": "6182ebe9ea218257521cdc48",
"name": "cleint_825"
},
{
"_id": "6182ec7dea218257521cdf35",
"name": "cleint_564"
},
{
"_id": "6182ec2cea218257521cdd83",
"name": "cleint_130"
},
{
"_id": "6182ebd6ea218257521cdbe8",
"name": "cleint_729"
},
{
"_id": "6182ebc6ea218257521cdb9c",
"name": "cleint_653"
},
{
"_id": "6182ec0bea218257521cdced",
"name": "cleint_990"
},
{
"_id": "6182ebd3ea218257521cdbd8",
"name": "cleint_713"
},
{
"_id": "6182ec81ea218257521cdf48",
"name": "cleint_583"
},
{
"_id": "6182ec2cea218257521cdd85",
"name": "cleint_132"
}
]
Response
res.json({
success: true,
"Zero visits": clients,
"Less visits": visits,
});
};
I need to combine both results
Use $unionWith:
clientModel.aggregate([
<stage1>, ...
{ $unionWith: { coll: "visits", pipeline: [ <stage1>, ... ] } }
])
MongoDB 5.0.9
I am trying to get
value of application within course and their specification
value of paid application ( status : paid) based on course and their specification
courses collection having multiple courses with specification which might be there maybe not
[
{
"_id": {
"$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
Trying to sort the sub-key on the document.
Example of data from the pipeline. Incorrect sort order for subkey availability.startIso
{
"_id": "60e458d7b896de9c8e44d6c9",
"uid": "6233ed1d8b154aa79d1435b5",
"name": "Pale",
"phoneNumber": "+19999813917",
"profileMedia": {
"url": "https://storage.googleapis.com/refresh-me-dev.appspot.com/dummy_photos/dummy_1.jpg",
"type": "photo"
},
"createdIso": "2021-07-06T13:21:27.513Z",
"isDeleted": false,
"isFlagged": false,
"isBanned": false,
"isAdmin": false,
"isVendor": true,
"lastOpenedAppIso": "2021-07-06T13:21:27.513Z",
"vendorMeta": {
"servicesOffered": [
"swedish"
],
"location": [
0,
0
]
},
"distanceFromPoint": 0,
"availability": [
{
"_id": "60e458d7b896de9c8e44d6cc",
"uid": "dec97d4b1dea44f7b2fa45a5",
"vendorUid": "6233ed1d8b154aa79d1435b5",
"startIso": "2021-07-12T04:07:21.349Z",
"endIso": "2021-07-12T05:07:21.360Z"
},
{
"_id": "60e458d7b896de9c8e44d6ce",
"uid": "a5928ea5c18c4321bd6a9a9b",
"vendorUid": "6233ed1d8b154aa79d1435b5",
"startIso": "2021-07-11T01:52:18.323Z",
"endIso": "2021-07-11T02:52:18.335Z"
}
]
}
Example of the aggregation
let vendors = await mongoDb
.collection<User>(collectionNames.users)
.aggregate([
{
$geoNear: {
near: { type: "Point", coordinates: [lat, lng] },
spherical: true,
maxDistance: 7500,
distanceField: "distanceFromPoint",
},
},
{
$match: { isVendor: true },
},
{
$match: { "vendorMeta.servicesOffered": { $in: services } },
},
{
$lookup: {
from: "vendor.availability",
localField: "uid",
foreignField: "vendorUid",
as: "availability",
},
},
{
$addFields: {
availability: {
$filter: {
input: "$availability",
as: "availability",
cond: { $and: [{ $gte: ["$$availability.startIso", nowIso] }, { $lte: ["$$availability.endIso", nDaysIso] }] },
},
},
},
},
{ $sort: { "availability.startIso": 1 } },
{ $match: { availability: { $ne: [] } } },
])
.toArray();
This is working as intended, $sort does not work on arrays and can't be used like this. What you can do is $unwind, then $sort and end by $grouping to restore the structure, like so:
[
// ...,
{
$unwind: "$availability"
},
{ $sort: { "availability.startIso": 1 } },
{
$group: {
_id: '$_id',
root: {$first: "$$ROOT"},
availability: {$push: '$availability'}
}
},
{
$replaceRoot: {
newRoot: {
$mergeObjects: [
'$root',
{ availability: '$availability'}
]
}
}
}
]
Note that i removed the :
{ $match: { availability: { $ne: [] } } },
As it's no longer required because $unwind will remove those documents for you.
I am new to mongoose and mongodb.
In my addtocart schema I have added $lookups and projection to populate products in add to cart.
In current response product_purchase_quantity it was in array in add to cart collection it is key and value. So, in $lookups I tried to add {$unwind: '$product_purchase_quantity'} but after adding add_to_cart_products object prints twice. I don't know where the mistake was?
Below i have mentioned expected result.
AddToCart Schema:
lookups: [
{
from: 'shop_db_products',
let: {
productId: '$add_to_cart_products.product',
purchaseQuantity: '$add_to_cart_products.product_quantity',
productItemId: '$add_to_cart_products.product_item',
},
pipeline: [
{
$match: { $expr: { $in: ['$_id', '$$productId'] } },
},
{
$lookup: {
from: 'shop_db_products',
localField: 'product_id',
foreignField: '_id',
as: 'products',
},
},
{
$project: {
_id: true,
product: {
_id: '$_id',
product_name: '$product_name',
},
product_purchase_quantity: '$$purchaseQuantity',
product_item: {
$reduce: {
input: {
$filter: {
input: '$product_items',
cond: {
$in: ['$$this._id', '$$productItemId'],
},
},
},
initialValue: {},
in: {
_id: '$$this._id',
product_size: { $concat: [{ $toString: '$$this.product_size.value' }, '$$this.product_size.unit'] },
product_price: '$$this.product_price',
product_type: '$$this.product_type'
},
},
},
},
},
],
localField: '',
as: 'add_to_cart_products',
model: 'ProductModel',
},
],
AddToCart Collection
[
{
"add_to_cart_user": "5f0076b7bd530928fc0c0285",
"add_to_cart_products": [
{
"product": "5f05a0270b4f3a5c41c70826",
"product_item": "5f05a0270b4f3a5c41c70877",
"product_quantity": 5
},
{
"product": "5f05a0270b4f3a5c41c70827",
"product_item": "5f05a0270b4f3a5c41c70666",
"product_quantity": 3
}
],
"add_to_cart_product_total": 5,
"add_to_cart_discount": 50,
"add_to_tax": "5eae321d21924800122f978e",
"add_to_cart_grand_total": 500
}
]
Current Response:
{
"_id": "5fa2a09b3c6316482098f6ff",
"add_to_cart_status_is_active": true,
"add_to_cart_discount": 50,
"add_to_cart_tax": 8,
"add_to_cart_products": [
{
"product": {
"_id": "5f05a0270b4f3a5c41c70826",
"product_name": "Avery Apricot Sour"
},
"product_purchase_quantity": [
5,
3
],
"product_item": {
"_id": "5f05a0270b4f3a5c41c70877",
"product_size": "22oz",
"product_price": 13.99
}
},
{
"product": {
"_id": "5f05a0270b4f3a5c41c70827",
"product_name": "Avery Dugana"
},
"product_purchase_quantity": [
5,
3
],
"product_item": {
"_id": "5f05a0270b4f3a5c41c70666",
"product_size": "22oz",
"product_price": 8.99
}
}
]
}
Expected response:
{
"_id": "5fa2a09b3c6316482098f6ff",
"add_to_cart_status_is_active": true,
"add_to_cart_discount": 50,
"add_to_cart_tax": 8,
"add_to_cart_products": [
{
"product": {
"_id": "5f05a0270b4f3a5c41c70826",
"product_name": "Avery Apricot Sour"
},
"product_purchase_quantity": 5,
"product_item": {
"_id": "5f05a0270b4f3a5c41c70877",
"product_size": "22oz",
"product_price": 13.99
}
},
{
"product": {
"_id": "5f05a0270b4f3a5c41c70827",
"product_name": "Avery Dugana"
},
"product_purchase_quantity": 3,
"product_item": {
"_id": "5f05a0270b4f3a5c41c70666",
"product_size": "22oz",
"product_price": 8.99
}
}
]
}
Product (shop_db_products) collection:
[
{
"_id": "5f05a0270b4f3a5c41c70826",
"product_no": "PRO04087",
"product_store_no": "1001",
"product_dept_no": "Irish Whiskey",
"product_name": "2Gingers",
"product_overview": "No Overview",
"product_items": [
{
"_id": "5f05a0270b4f3a5c41c70877",
"product_item_number": "857566003019",
"product_price": 20.99,
"product_cost": 20.99,
"product_size": "750ml",
"product_type": "Bottle",
"product_value": 0,
"product_quantity": 0,
"product_images": [
"pro04087-857566003019-1.png"
],
"product_item_is_active": true
}
]
},
...
]
You have to $unwind add_to_cart_products before performing $lookup
db.addToCart.aggregate([
{
$unwind: "$add_to_cart_products"
},
{
$lookup: {
from: "shop_db_products",
let: {
productId: "$add_to_cart_products.product",
purchaseQuantity: "$add_to_cart_products.product_quantity",
productItemId: "$add_to_cart_products.product_item"
},
pipeline: [
{
$match: {
$expr: {
$eq: [
"$_id",
"$$productId"
]
}
}
},
{
$project: {
_id: true,
product: {
_id: "$_id",
product_name: "$product_name",
},
product_purchase_quantity: "$$purchaseQuantity",
product_item: {
$reduce: {
input: {
$filter: {
input: "$product_items",
cond: {
$eq: [
"$$this._id",
"$$productItemId"
],
},
},
},
initialValue: {},
in: {
_id: "$$this._id",
product_size: "$$this.product_size",
product_price: "$$this.product_price",
product_type: "$$this.product_type"
}
}
}
}
}
],
as: "add_to_cart_products"
}
},
{
$unwind: "$add_to_cart_products"
},
{
$group: {
_id: "$_id",
"add_to_cart_products": {
$push: "$add_to_cart_products"
}
}
}
])
MongoDB Playground
Another way
Without reducer, with $unwind
https://mongoplayground.net/p/3uWA5pVBv83
db.addToCart.aggregate([
{
"$unwind": "$add_to_cart_products"
},
{
"$lookup": {
"from": "shop_db_products",
"let": {
"productId": "$add_to_cart_products.product",
"purchaseQuantity": "$add_to_cart_products.product_quantity",
"productItemId": "$add_to_cart_products.product_item"
},
"pipeline": [
{
"$match": {
"$expr": {
"$eq": [
"$_id",
"$$productId"
]
}
}
},
{
"$unwind": "$product_items"
},
{
"$match": {
"$expr": {
"$eq": [
"$product_items._id",
"$$productItemId"
]
}
}
},
{
"$project": {
"_id": true,
"product": {
"_id": "$_id",
"product_name": "$product_name"
},
"product_purchase_quantity": "$$purchaseQuantity",
"product_item": "$product_items"
}
}
],
"as": "productResolved"
}
},
{
"$unwind": "$productResolved"
},
{
"$group": {
"_id": "$_id",
"add_to_cart_products": {
"$push": "$productResolved"
}
}
}
])