Learning MongoDB for the past two days and I am trying to aggregate three collections but unable to achieve it
Below are the four collection maintaining in the database
university
{
"_id" : "5834ecf7432d92675bde9d82",
"name": "NIFT"
}
college
{
"_id" : "5834ecf7432d92675bde9d83",
"name": "NIFT Hyderabad",
"university_id":"5834ecf7432d92675bde9d82"
}
departments
{
"_id" : "5834ecf7432d92675bde9d84",
"department_name": "Fashion Technology",
"college_id" : "5834ecf7432d92675bde9d83"
},
{
"_id" : "5834ecf7432d92675bde9d85",
"department_name": "Merchandising",
"college_id" : "5834ecf7432d92675bde9d83"
}
Sections
{
"_id" : "5834ecf7432d92675bde9d86",
"section_name": "A",
"students" : "56",
"department_id":"5834ecf7432d92675bde9d84"
},
{
"_id" : "5834ecf7432d92675bde9d87",
"section_name": "B",
"students" : "60",
"department_id":"5834ecf7432d92675bde9d84"
},
{
"_id" : "5834ecf7432d92675bde9d86",
"section_name": "A",
"students" : "55",
"department_id":"5834ecf7432d92675bde9d85"
},
{
"_id" : "5834ecf7432d92675bde9d87",
"section_name": "B",
"students" : "44",
"department_id":"5834ecf7432d92675bde9d85"
}
Here I am trying to achieve the output in the below format
Expected Output
[{
"_id": "5834ecf7432d92675bde9d83",
"name": "NIFT Hyderabad",
"university_id": "5834ecf7432d92675bde9d82",
"departments": [{
"_id": "5834ecf7432d92675bde9d84",
"department_name": "CSE",
"college_id": "5834ecf7432d92675bde9d83",
"sections": [{
"_id": "5834ecf7432d92675bde9d86",
"section_name": "A",
"students": "56",
"department_id": "5834ecf7432d92675bde9d84"
}, {
"_id": "5834ecf7432d92675bde9d87",
"section_name": "B",
"students": "60",
"department_id": "5834ecf7432d92675bde9d84"
}]
},
{
"_id": "5834ecf7432d92675bde9d85",
"department_name": "Mechanical",
"college_id": "5834ecf7432d92675bde9d83",
"sections": [{
"_id": "5834ecf7432d92675bde9d86",
"section_name": "A",
"students": "55",
"department_id": "5834ecf7432d92675bde9d85"
},
{
"_id": "5834ecf7432d92675bde9d87",
"section_name": "B",
"students": "44",
"department_id": "5834ecf7432d92675bde9d85"
}
]
}
]
}]
But, I am getting department and sections in separate arrays for college but not able to get like in the above format
Query
db.college.aggregate([
{"$match": { "university_id": "5834ecf7432d92675bde9d82" } },
{"$lookup": {
"localField": "_id",
"from": "departments",
"foreignField": "college_id",
"as": "departments"
}},
{"$unwind":"$departments"},
{$group : {_id : "$_id", departments : {$push : "$departments" }}},
{"$lookup": {
"localField": "departments._id",
"from": "sections",
"foreignField": "department_id",
"as": "sections"}
}
])
Can any one help me to solve this issue, it will be very helpful for me.
You can try below aggregation query.
The below query pushes the sections into department when they are joined and $group to push department to create the final structure.
db.college.aggregate([
{
"$match": {
"university_id": "5834ecf7432d92675bde9d82"
}
},
{
"$lookup": {
"localField": "_id",
"from": "departments",
"foreignField": "college_id",
"as": "departments"
}
},
{
"$unwind": {
"path": "$departments",
"preserveNullAndEmptyArrays": true
}
},
{
"$lookup": {
"localField": "departments._id",
"from": "sections",
"foreignField": "department_id",
"as": "departments.sections"
}
},
{
"$group": {
"_id": "$_id",
"name": {
"$first": "$name"
},
"university_id": {
"$first": "$university_id"
},
"departments": {
"$push": "$departments"
}
}
}
])
Related
Learning MongoDB for the past two days and I am trying to aggregate three collections but unable to achieve it
Below are the three collection maintaining in the database
t_credentials
{
"_id" : "619ca68b624c41e408348406",
"title" : "Company ID"
}
t_groups
{
"_id" : "61a253da88ca12a37218898d",
"group_name" : "Gold"
}
t_user_credentials
{
"_id" : "619ca88a624c41e408348424",
"credential_id" : "619ca68b624c41e408348406",
"group_id" : "61a253da88ca12a37218898d",
"identifiers" : {
"first_name" : "Lee",
"middle_name" : "Min",
"last_name" : "Ho"
},
"created_at" : "2021-12-01T17:20:49.000Z"
}
Here I am trying to achieve the output in the below format:
Expected Output
[{
"_id" : "619ca88a624c41e408348424",
"first_name" : ,
"middle_name" : ,
"last_name" : ,
"credential" : {
"_id:" : "619ca68b624c41e408348406",
"title" : "Company ID"
},
"group" : {
"_id" : "61a253da88ca12a37218898d",
"group_name" : "Gold"
},
"created_at" : "2021-12-01T17:20:49.000Z"
}]
But, I am getting the fields only from t_user_credentials but not able to get like in the above format
Query
db.t_user_credentials.aggregate([
{
$lookup: {
from: "t_credentials",
localField: "_id",
foreignField: "credential_id",
as: "credentials"
}
},
{
$unwind: {
path:'$credentials',
preserveNullAndEmptyArrays: true
}
},
{
$lookup: {
from: "t_groups",
localField: "_id",
foreignField: "group_id",
as: "groups"
}
},
{
$unwind: {
path: '$groups',
preserveNullAndEmptyArrays: true
}
},
{
$project: {
last_name: "$identifiers.last_name",
first_name: "$identifiers.first_name",
middle_name: "$identifiers.middle_name",
"credentials.title": 1,
created_at: 1,
group_id: 1
}
}
])
Can any one help me to solve this issue, it will be very helpful for me.
This query uses $replaceWith to merge the identifiers sub-document into the $$ROOT document. We also use $unset to remove fields we are no longer interested in. Before all of that we make sure to unwind our credential and group fields.
You can check out a live demo of this query here
Consider the following:
Database
db={
"t_credentials": [
{
"_id": "619ca68b624c41e408348406",
"title": "Company ID"
}
],
"t_groups": [
{
"_id": "61a253da88ca12a37218898d",
"group_name": "Gold"
}
],
"t_user_credentials": [
{
"_id": "619ca88a624c41e408348424",
"credential_id": "619ca68b624c41e408348406",
"group_id": "61a253da88ca12a37218898d",
"identifiers": {
"first_name": "Lee",
"middle_name": "Min",
"last_name": "Ho"
},
"created_at": "2021-12-01T17:20:49.000Z"
}
]
}
Query
db.t_user_credentials.aggregate([
{
"$lookup": {
"from": "t_credentials",
"localField": "credential_id",
"foreignField": "_id",
"as": "credential"
}
},
{
"$lookup": {
"from": "t_groups",
"localField": "group_id",
"foreignField": "_id",
"as": "group"
}
},
{
$unwind: "$group",
},
{
$unwind: "$credential"
},
{
$replaceWith: {
$mergeObjects: [
"$$ROOT",
"$identifiers"
]
}
},
{
$unset: [
"group_id",
"credential_id",
"identifiers"
]
}
])
Result
[
{
"_id": "619ca88a624c41e408348424",
"created_at": "2021-12-01T17:20:49.000Z",
"credential": {
"_id": "619ca68b624c41e408348406",
"title": "Company ID"
},
"first_name": "Lee",
"group": {
"_id": "61a253da88ca12a37218898d",
"group_name": "Gold"
},
"last_name": "Ho",
"middle_name": "Min"
}
]
I currently have 5 tables that need to joined due to their coupling.
Using $lookup I can join the Order table with the Plan table and get what I need, but how do I go about the other tables?
Here is each table, and the Id/table it needs to connect with
Plan - _id, unassignedOrderIds(array)
DriverPlan - _id, planId, orderIds(array), driverId, vehicleId
Driver - _id, vehicleId
Vehicle - _id
Orders - _id
In the end I'm looking for mongoDb to return a Plan object that has UnassignedOrders loaded and DriverPlans loaded. Followed by DriverPlans having its Orders,Driver, and Vehicle loaded.
Here is what I have so far:
db.Plan.aggregate([
// Unwind the source
{ "$unwind": "$UnassignedOrderIds" },
// Do the lookup matching
{ "$lookup": {
"from": "Order",
"localField": "UnassignedOrderIds",
"foreignField": "_id",
"as": "UnassignedOrders"
}},
// Unwind the result arrays ( likely one or none )
{ "$unwind": "$UnassignedOrders" },
// Group back to arrays
{ "$group": {
"_id": "$_id",
"Order": { "$push": "$Order" },
"UnassignedOrders": { "$push": "$UnassignedOrders" }
}}
])
Sample Document:
//Plan
{
"_id" : ObjectId("5c1d244de707b20cece645f1"),
"UnassignedOrderIds" : [
ObjectId("5c1d247fe707b20cece6462e"),
ObjectId("5c1d035de707b20cece63104")
]
}
//DriverPlan
[{
"_id" : ObjectId("123d247fe707b20cece6462e"),
"PlanId" : ObjectId("5c1d244de707b20cece645f1"),
"DriverId" : ObjectId("1c1d247fe707b20cece64622"),
"VehicleId" : ObjectId("3c1d247fe707b20cece64633"),
"OrderIds": [
ObjectId("5c1d247fe707b20cece64621"),
ObjectId("5c1d247fe707b20cece64624")
]
},{
"_id" : ObjectId("123d247fe707b20cece64655"),
"PlanId" : ObjectId("5c1d244de707b20cece645f1"),
"DriverId" : ObjectId("2c1d035de707b20cece63104"),
"VehicleId" : null,
"OrderIds": [
ObjectId("5c1d247fe707b20cece64625")
]
}]
//Orders
[{
"_id" : ObjectId("5c1d247fe707b20cece6462e"),
"name" "Order1"
},{
"_id" : ObjectId("5c1d035de707b20cece63104"),
"name" "Order2"
},{
"_id" : ObjectId("5c1d247fe707b20cece64621"),
"name" "Order3"
},{
"_id" : ObjectId("5c1d247fe707b20cece64624"),
"name" "Order4"
},{
"_id" : ObjectId("5c1d247fe707b20cece64625"),
"name" "Order5"
}]
//Driver
[{
"_id" : ObjectId("1c1d247fe707b20cece64622"),
"vehicleId" : ObjectId("3c1d247fe707b20cece6462e"),
"name" "Driver1"
},{
"_id" : ObjectId("2c1d035de707b20cece63104"),
"vehicleId" : null,
"name" "Driver2"
},{
"_id" : ObjectId("3c1d247fe707b20cece64621"),
"vehicleId" : ObjectId("3c1d035de707b20cece63104"),
"name" "Driver3"
}]
//Vehicle
[{
"_id" : ObjectId("3c1d247fe707b20cece6462e"),
"name" "Vehicle1"
},{
"_id" : ObjectId("3c1d035de707b20cece63104"),
"name" "Vehicle2"
},{
"_id" : ObjectId("3c1d247fe707b20cece64633"),
"name" "Vehicle3"
}]
The Expected output is json object as follows
//Plan with children loaded
{
"_id" : ObjectId("5c1d244de707b20cece645f1"),
"UnassignedOrderIds" : [
ObjectId("5c1d247fe707b20cece6462e"),
ObjectId("5c1d035de707b20cece63104")
],
"UnassignedOrders": [{
"_id" : ObjectId("5c1d247fe707b20cece6462e"),
"name" "Order1"
},{
"_id" : ObjectId("5c1d035de707b20cece63104"),
"name" "Order2"
}],
"DriverPlans" :
[{
"_id" : ObjectId("123d247fe707b20cece6462e"),
"PlanId" : ObjectId("5c1d244de707b20cece645f1"),
"DriverId" : ObjectId("1c1d247fe707b20cece64622"),
"Driver": {
"_id" : ObjectId("1c1d247fe707b20cece64622"),
"vehicleId" : ObjectId("3c1d247fe707b20cece6462e"),
"name" "Driver1"
},
"VehicleId" : ObjectId("3c1d247fe707b20cece64633"),
"Vehicle" : {
"_id" : ObjectId("3c1d247fe707b20cece64633"),
"name" "Vehicle3"
},
"OrderIds": [
ObjectId("5c1d247fe707b20cece64621"),
ObjectId("5c1d247fe707b20cece64624")
],
"Orders" : [
{
"_id" : ObjectId("5c1d247fe707b20cece64621"),
"name" "Order3"
},{
"_id" : ObjectId("5c1d247fe707b20cece64624"),
"name" "Order4"
}]
},{
"_id" : ObjectId("123d247fe707b20cece64655"),
"PlanId" : ObjectId("5c1d244de707b20cece645f1"),
"DriverId" : ObjectId("2c1d035de707b20cece63104"),
"Driver" : {
"_id" : ObjectId("2c1d035de707b20cece63104"),
"vehicleId" : null,
"name" "Driver2"
}
"VehicleId" : null,
"Vehicle" : null,
"OrderIds": [
ObjectId("5c1d247fe707b20cece64625")
],
"Orders": [{
"_id" : ObjectId("5c1d247fe707b20cece64625"),
"name" "Order5"
}
]
}]
}
You can use below aggregation
db.Plan.aggregate([
{ "$lookup": {
"from": Order.collection.name,
"let": { "unassignedOrderIds": "$UnassignedOrderIds" },
"pipeline": [
{ "$match": { "$expr": { "$in": ["$_id", "$$unassignedOrderIds"] } } }
],
"as": "UnassignedOrderIds"
}},
{ "$lookup": {
"from": DriverPlan.collection.name,
"let": { "planId": "$_id" },
"pipeline": [
{ "$match": { "$expr": { "$eq": ["$PlanId", "$$planId"] } } },
{ "$lookup": {
"from": Driver.collection.name,
"let": { "driveId": "$DriverId" },
"pipeline": [
{ "$match": { "$expr": { "$eq": ["$_id", "$$driveId"] } } }
],
"as": "Driver"
}},
{ "$lookup": {
"from": Vehicle.collection.name,
"let": { "vehicleId": "$VehicleId" },
"pipeline": [
{ "$match": { "$expr": { "$eq": ["$_id", "$$vehicleId"] } } }
],
"as": "Vehicle"
}},
{ "$lookup": {
"from": Order.collection.name,
"let": { "orderIds": "$OrderIds" },
"pipeline": [
{ "$match": { "$expr": { "$in": ["$_id", "$$orderIds"] } } }
],
"as": "Orders"
}}
],
"as": "DriverPlans"
}}
])
With mongodb 3.4 and below $lookup syntax
db.Plan.aggregate([
{ "$lookup": {
"from": Order.collection.name,
"localField": "UnassignedOrderIds",
"foreignField": "_id",
"as": "UnassignedOrderIds"
}},
{ "$lookup": {
"from": DriverPlan.collection.name,
"localField": "_id",
"foreignField": "PlanId",
"as": "DriverPlans"
}},
{ "$unwind": "$DriverPlans" },
{ "$lookup": {
"from": Driver.collection.name,
"localField": "DriverPlans.DriverId",
"foreignField": "_id",
"as": "DriverPlans.Driver"
}},
{ "$unwind": "$DriverPlans.Driver" },
{ "$lookup": {
"from": Vehicle.collection.name,
"localField": "DriverPlans.VehicleId",
"foreignField": "_id",
"as": "DriverPlans.Vehicle"
}},
{ "$unwind": "$DriverPlans.Vehicle" },
{ "$lookup": {
"from": Order.collection.name,
"localField": "DriverPlans.OrderIds",
"foreignField": "_id",
"as": "DriverPlans.Orders"
}},
{ "$group": {
"_id": "$_id",
"DriverPlans": { "$push": "$DriverPlans" }
}}
])
How do I combine 2 array objects using mongoDB NoSQL? Because I have tried to find some of the same problems here that I got, but I have not found the answers and problems that match what I got.
If someone here wants to help me, here are the problems I want to solve.
Example: I tried using noSQL in mongoDB like this:
db.tables.aggregate([
{ $lookup: { from: 'reservations', localField: '_id', foreignField: 'tableId', as: 'reservation' }},
{ $unwind: { path: '$reservation', 'preserveNullAndEmptyArrays': true }},
{ $lookup: { from: 'orders', localField: 'reservation._id', foreignField: 'reservationId', as: 'orders' }},
{ $lookup: { from: 'products', localField: 'orders.productId', foreignField: '_id', as: 'products' }},
{
$project: {
'_id': 1,
'initial': 1,
'description': 1,
'reservation._id': 1,
'reservation.guest': 1,
'orders._id': 1,
'orders.status': 1,
'orders.quantity': 1,
'orders.productId': 1,
'products._id': 1,
'products.name': 1
}
},
]);
After running noSQL mongoDB above, I got the results below:
{
"_id" : ObjectId("5b63e519514cf01c2864749a"),
"description" : "Kursi VIP 01",
"reservation" : {
"_id" : ObjectId("5b63f104514cf01c286474b6"),
"guest" : "Jhon Doe"
},
"orders" : [
{
"_id" : ObjectId("5b63f239514cf01c286474bb"),
"productId" : ObjectId("5b63e72d514cf01c286474a3"),
"status" : "3",
"quantity" : "2"
},
{
"_id" : ObjectId("5b63f252514cf01c286474bc"),
"productId" : ObjectId("5b63e7de514cf01c286474a6"),
"status" : "2",
"quantity" : "3"
},
{
"_id" : ObjectId("5b63f267514cf01c286474bd"),
"productId" : ObjectId("5b63e937514cf01c286474ac"),
"status" : "0",
"quantity" : "2"
}
],
"products" : [
{
"_id" : ObjectId("5b63e72d514cf01c286474a3"),
"name" : "AQUA 600ML"
},
{
"_id" : ObjectId("5b63e7de514cf01c286474a6"),
"name" : "Nasi Goreng Kecap Asin"
},
{
"_id" : ObjectId("5b63e937514cf01c286474ac"),
"name" : "Daging Ayam Goreng"
}
]
}
Now, my Question is. How to merge/combine 2 Object Array ("orders and products"), So I can get results like this:
{
"_id" : ObjectId("5b63e519514cf01c2864749a"),
"description" : "Kursi VIP 01",
"reservation" : {
"_id" : ObjectId("5b63f104514cf01c286474b6"),
"guest" : "Jhon Doe"
},
"orders" : [
{
"_id" : ObjectId("5b63f239514cf01c286474bb"),
"productId" : ObjectId("5b63e72d514cf01c286474a3"),
"name" : "AQUA 600ML",
"status" : "3",
"quantity" : "2"
},
{
"_id" : ObjectId("5b63f252514cf01c286474bc"),
"productId" : ObjectId("5b63e7de514cf01c286474a6"),
"name" : "Nasi Goreng Kecap Asin",
"status" : "2",
"quantity" : "3"
},
{
"_id" : ObjectId("5b63f267514cf01c286474bd"),
"productId" : ObjectId("5b63e937514cf01c286474ac"),
"name" : "Daging Ayam Goreng"
"status" : "0",
"quantity" : "2"
}
]
}
I hope, someone can help me.
Thanks in advance.
You can try below aggregation with mongodb 3.4
You need to $unwind the orders array to add the field($addFields) name inside orders and then $group to rollback orders again to the make an array field
db.tables.aggregate([
{ "$lookup": {
"from": "reservations",
"localField": "_id",
"foreignField": "tableId",
"as": "reservation"
}},
{ "$unwind": { "path": '$reservation', 'preserveNullAndEmptyArrays': true }},
{ "$lookup": {
"from": "orders",
"localField": "reservation._id",
"foreignField": "reservationId",
"as": "orders",
}},
{ "$unwind": { "path": '$orders', 'preserveNullAndEmptyArrays': true }},
{ "$lookup": {
"from": "products",
"localField": "orders.productId",
"foreignField": "_id",
"as": "orders.products"
}},
{ "$unwind": { "path": '$orders.products', 'preserveNullAndEmptyArrays': true }},
{ "$addFields": {
"orders.name": "$orders.products.name"
}},
{ "$group": {
"_id": "$_id",
"description": { "$first": "$description" },
"reservation": { "$first": "$reservation" },
"orders": { "$push": "$orders" }
}},
{ "$project": { "orders.products": 0 }}
])
Which is far simple with mongodb 3.6 nested $lookup version
db.tables.aggregate([
{ "$lookup": {
"from": "reservations",
"let": { "reservationId": "$_id" },
"pipeline": [
{ "$match": { "$expr": { "$eq": [ "$tableId", "$$reservationId" ] } } }
],
"as": "reservations"
}},
{ "$lookup": {
"from": "orders",
"let": { "reservationId": "$reservation._id" },
"pipeline": [
{ "$match": { "$expr": { "$eq": [ "$reservationId", "$$reservationId" ] } } },
{ "$lookup": {
"from": "products",
"let": { "productId": "$productId" },
"pipeline": [
{ "$match": { "$expr": { "$eq": [ "$_id", "$$productId" ] } } },
{ "$project": { "_id": false }}
],
"as": "products"
}},
{ "$unwind": "$products" },
{ "$addFields": { "name": "$products.name" } },
{ "$project": { "products": 0 }}
],
"as": "orders"
}}
])
MongoDB version 3.4.10 (Application is using Meteor framework)
Objective: Aggregate documents that are referenced by _id into the containing document as required at runtime.
I have Materials, Models, and Catalog collections with the following documents:
Materials
{ "_id" : "cf4KgXw7ZK6ukdzR7", "name" : "parquet_wood_mahogany" }
Models
{
"_id" : "Mwp5eYYZ4GZzvZuoK",
"name" : "top_square_chamfered",
"type" : "top"
}
{
"_id" : "CqhS2m2RcLZ2Bm4eb",
"name" : "skirt_square",
"type" : "skirt"
}
{
"_id" : "dYP22ajALnWBwpBj2",
"name" : "leg_square",
"type" : "leg"
}
Catalog
{
"_id" : "EcRGzPAq79giYKrbY",
...,
"specs" : {
...,
"models" : [
{
"mesh" : "Mwp5eYYZ4GZzvZuoK",
"material" : "cf4KgXw7ZK6ukdzR7"
},
{
"mesh" : "CqhS2m2RcLZ2Bm4eb",
"material" : "cf4KgXw7ZK6ukdzR7"
},
{
"mesh" : "dYP22ajALnWBwpBj2",
"material" : "cf4KgXw7ZK6ukdzR7"
}
]
}
}
Desired returned document format after aggregation:
{
"_id" : "EcRGzPAq79giYKrbY",
...,
"specs" : {
"dimensions" : {
...,
},
"models" : [
{
"mesh" : {
"_id" : "Mwp5eYYZ4GZzvZuoK",
"name" : "top_square_chamfered",
"type" : "top"
},
"material" : {
"_id" : "cf4KgXw7ZK6ukdzR7",
"name" : "parquet_wood_mahogany"
}
},
{
"mesh" : {
"_id" : "CqhS2m2RcLZ2Bm4eb",
"name" : "skirt_square",
"type" : "skirt"
},
"material" : {
"_id" : "cf4KgXw7ZK6ukdzR7",
"name" : "parquet_wood_mahogany"
}
},
{
"mesh" : {
"_id" : "dYP22ajALnWBwpBj2",
"name" : "leg_square",
"type" : "leg"
},
"material" : {
"_id" : "cf4KgXw7ZK6ukdzR7",
"name" : "parquet_wood_mahogany"
}
}
]
}
}
I haven't included any of my query code because it is so far off the mark as to just be noise. I've been trying to use aggregate, with $lookup combinations, but I'm not getting anywhere close to what I'm after. The MongoDB v3.6 pipeline syntax would make this much easier... but I'm at a complete loss in v3.4.
I would like to avoid using multiple database requests to combine this information if at all possible. Any assistance of advice would be greatly appreciated!
EDIT: Working solution -
db.catalog.aggregate([
{ "$lookup": {
"from": 'models',
"localField": "specs.models.mesh",
"foreignField": "_id",
"as": "models.mesh"
}},
{ "$lookup": {
"from": 'materials',
"localField": "specs.models.material",
"foreignField": "_id",
"as": "models.material"
}},
{ "$unwind": "$models.mesh" },
{ "$unwind": "$models.material" },
{ "$group":{
"_id": "$_id",
"title": { "$first": "$title" },
"desc": { "$first": "$desc" },
"thumbnail": { "$first": "$thumbnail" },
"createdBy": { "$first": "$createdBy" },
"createdAt": { "$first": "$createdAt" },
"specs": { "$first": "$specs" },
"models": { "$push": "$models" }
}},
{ "$project": {
"_id": "$_id",
"title": "$title",
"desc": "$desc",
"thumbnail": "$thumbnail",
"createdBy": "$createdBy",
"createdAt": "$createdAt",
"specs.dimensions": "$specs.dimensions",
"specs.models": "$models",
}}
])
You can try below aggregation
db.catalog.aggregate([
{ "$lookup": {
"from": 'models',
"localField": "specs.models.mesh",
"foreignField": "_id",
"as": "models.mesh"
}},
{ "$lookup": {
"from": 'materials',
"localField": "specs.models.material",
"foreignField": "_id",
"as": "models.material"
}},
{ "$unwind": "$models.mesh" },
{ "$unwind": "$models.material" },
{ "$group":{
"_id": "$_id",
"title": { "$first": "$title" },
"desc": { "$first": "$desc" },
"thumbnail": { "$first": "$thumbnail" },
"createdBy": { "$first": "$createdBy" },
"createdAt": { "$first": "$createdAt" },
"specs": { "$first": "$specs" },
"models": { "$push": "$models" }
}},
{ "$project": {
"title": "$title",
"desc": "$desc",
"thumbnail": "$thumbnail",
"createdBy": "$createdBy",
"createdAt": "$createdAt",
"specs.dimensions": "$specs.dimensions",
"specs.models": "$models",
}}
])
I am struggling with the newish (lovely) lookup operator in MongoDB. I have 3 collections:
artists
{
"_id" : ObjectId("5b0d2b2c7ac4792df69a9942"),
"name" : "Dream Theater",
"started_in" : NumberInt(1985),
"active" : true,
"country" : "US",
"current_members" : [
ObjectId("5b0d2a7c7ac4792df69a9941")
],
"previous_members" : [
ObjectId("5b0d2bf57ac4792df69a9954")
],
"albums" : [
ObjectId("5b0d16ee7ac4792df69a9924"),
ObjectId("5b0d47667ac4792df69a9994")
],
"genres" : [
"prog metal",
"prog rock"
]
}
Albums
{
"_id" : ObjectId("5b0d16ee7ac4792df69a9924"),
"title" : "Images and words",
"released" : ISODate("1992-07-07T00:00:00.000+0000"),
"songs" : [
ObjectId("5b0d15ab7ac4792df69a9916"),
ObjectId("5b0d15ee7ac4792df69a991e"),
ObjectId("5b0d2db37ac4792df69a995d"),
ObjectId("5b0d2dbe7ac4792df69a995e"),
ObjectId("5b0d2dcb7ac4792df69a995f"),
ObjectId("5b0d2dd87ac4792df69a9960"),
ObjectId("5b0d2de27ac4792df69a9961"),
ObjectId("5b0d2dec7ac4792df69a9962")
],
"type" : "LP"
}
{
"title" : "Awake",
"released" : ISODate("1994-10-04T00:00:00.000+0000"),
"songs" : [
ObjectId("5b0d470d7ac4792df69a9991")
],
"type" : "LP",
"_id" : ObjectId("5b0d47667ac4792df69a9994")
}
Songs
{
"_id" : ObjectId("5b0d15ab7ac4792df69a9916"),
"title" : "Pull me under"
}
{
"_id" : ObjectId("5b0d15ee7ac4792df69a991e"),
"title" : "Another day"
}
{
"title" : "Take the time",
"_id" : ObjectId("5b0d2db37ac4792df69a995d")
}
{
"title" : "Surrounded",
"_id" : ObjectId("5b0d2dbe7ac4792df69a995e")
}
{
"title" : "Metropolis - part I",
"_id" : ObjectId("5b0d2dcb7ac4792df69a995f")
}
{
"title" : "Under a glass moon",
"_id" : ObjectId("5b0d2dd87ac4792df69a9960")
}
{
"title" : "Wait for sleep",
"_id" : ObjectId("5b0d2de27ac4792df69a9961")
}
{
"title" : "Learning to live",
"_id" : ObjectId("5b0d2dec7ac4792df69a9962")
}
{
"title" : "6:00",
"_id" : ObjectId("5b0d470d7ac4792df69a9991")
}
I can easily do an aggregation with $lookup to get the detailed albums array, but how do I get also the detailed songs in the corresponding albums?
I would like to extend the following query:
db.artists.aggregate([ {
$lookup: {
from: "albums",
localField: "albums",
foreignField: "_id",
as: "albums"
}
}]).pretty()
If you have mongodb version 3.6 then you can try with nested $lookup aggregation...
db.collection.aggregate([
{ "$lookup": {
"from": Albums.collection.name,
"let": { "albums": "$albums" },
"pipeline": [
{ "$match": { "$expr": { "$in": [ "$_id", "$$albums" ] } } },
{ "$lookup": {
"from": Songs.collection.name,
"let": { "songs": "$songs" },
"pipeline": [
{ "$match": { "$expr": { "$in": [ "$_id", "$$songs" ] } } }
],
"as": "songs"
}}
],
"as": "albums"
}}
])
And for long-winded explanation you can go through $lookup multiple levels without $unwind?
Or If you have mongodb version prior to 3.6
db.collection.aggregate([
{ "$lookup": {
"from": Albums.collection.name,
"localField": "albums",
"foreignField": "_id",
"as": "albums"
}},
{ "$unwind": "$albums" },
{ "$lookup": {
"from": Songs.collection.name,
"localField": "albums.songs",
"foreignField": "_id",
"as": "albums.songs",
}},
{ "$group": {
"_id": "$_id",
"name": { "$first": "$name" },
"started_in": { "$first": "$started_in" },
"active": { "$first": "$active" },
"country": { "$first": "$country" },
"albums": {
"$push": {
"_id": "$albums._id",
"title": "$albums.title",
"released": "$albums.released",
"type": "$albums.type",
"songs": "$albums.songs"
}
}
}}
])