Nested lookup in mongo db query - mongodb

Question

I am making a airline dummy webside, and i need get all sold tickets per flight for all airlines, i have 3 collections: airlines, flights and sales
I tried using a nested lookups in mongodb query, but i cant sum the total tickets, here is the current query and the result:
Airline.aggregate([{
$lookup: {
from: "flights",
localField: "id_airline",
foreignField: "id_airline",
as: "flights"
}
}, {
$unwind: {
path: "$flights",
preserveNullAndEmptyArrays: true
}
}, {
$lookup: {
from: "sales",
localField: "flights.id_flight",
foreignField: "id_flight",
as: "flights.sales",
}
}, {
$group: {
_id : "$_id",
idAirline: { $first: "$id_airline" },
flights: { $push: "$flights" }
}
}, {
$project: {
_id: 1,
idAirline: 1,
"flights.id_flight": 1,
"flights.price": 1,
"flights.sold":{$sum:"$flights.sales.tickets"}
}
}]
And the result is:
... },
{
"_id": "5db381cb18518043c40e3ecd",
"idAirline": "AVI-242",
"flights": [
{
"id_flight": "CPA-001",
"price": "125",
"sold": 0
},
{
"id_flight": "CGA-002",
"price": "150",
"sold": 0
},
{
"id_flight": "CHA-003",
"price": "135",
"sold": 0
}
]
},
....
Actually the fligth CPA-001 has 6 tickets sold but i cant sum a get the result.
Here are the documents:
Airlines
{"_id":{"$oid":"5db3823718518043c40e3ece"},"country":["Panamá","El Salvador","Belice"],"id_airline":"VOL-643","name_airport":"Juan Santamaría","name_airline":"Volaris","createdAt":{"$date":{"$numberLong":"1572045367094"}},"updatedAt":{"$date":{"$numberLong":"1572045367094"}},"__v":{"$numberInt":"0"}}
Flights
{"_id":{"$oid":"5db9a225154a1b1b08cc77c3"},"restrictions":["No Liquids"],"features":[],"id_flight":"CPA-001","id_airline":"AVI-242","date_departure":{"$date":{"$numberLong":"1546300800000"}},"date_arrival":{"$date":{"$numberLong":"1559779200000"}},"name":"CosPan","origin":"Costa Rica","destination":"Panamá","itinerary":"50 breakfasts","price":"125","status":"On Time","max_capacity":"50","createdAt":{"$date":{"$numberLong":"1572446757327"}},"updatedAt":{"$date":{"$numberLong":"1572447464367"}},"__v":{"$numberInt":"0"}}
Sales
{"_id":{"$oid":"5db9b643b50c0d1540b8db89"},"id_user":"304780391","id_flight":"CPA-001","origin":"Costa Rica","destination":"Panamá","date_departure":{"$date":{"$numberLong":"1546300800000"}},"date_arrival":{"$date":{"$numberLong":"1559779200000"}},"tickets":{"$numberInt":"4"},"suitcases":{"$numberInt":"1"},"status":"Bought","seat":{"$numberInt":"-1"},"createdAt":{"$date":{"$numberLong":"1572451907375"}},"updatedAt":{"$date":{"$numberLong":"1572451907375"}},"__v":{"$numberInt":"0"}}

Answer 1

I think the nested arrays are causing some difficulties. I added another $unwind between $lookup and $group. Let me know what you think...
db.airlines.aggregate([
{ $lookup: {
from: "flights",
localField: "id_airline",
foreignField: "id_airline",
as: "flights"
}
},
{ $unwind: {
path: "$flights",
preserveNullAndEmptyArrays: true
}
},
{ $lookup: {
from: "sales",
localField: "flights.id_flight",
foreignField: "id_flight",
as: "flights.sales",
}
},
{ $unwind: {
path: "$flights.sales",
preserveNullAndEmptyArrays: true
}
},
{ $group: {
_id : "$_id",
idAirline: { $first: "$id_airline" },
flights: { $push: "$flights" }
}
},
{ $project: {
_id: 1,
idAirline: 1,
"flights.id_flight": 1,
"flights.price": 1,
"flights.sold":{$sum: "$flights.sales.tickets"}
}
}
]).pretty()
Documents used to test:
flights
{
"_id" : ObjectId("5db9a225154a1b1b08cc77c3"),
"restrictions" : [
"No Liquids"
],
"features" : [ ],
"id_flight" : "CPA-001",
"id_airline" : "VOL-643",
"date_departure" : ISODate("2019-10-30T23:04:17.119Z"),
"date_arrival" : ISODate("2019-10-30T23:04:17.119Z"),
"name" : "CosPan",
"origin" : "Costa Rica",
"destination" : "Panamá",
"itinerary" : "50 breakfasts",
"price" : "125",
"status" : "On Time",
"max_capacity" : "50",
"createdAt" : ISODate("2019-10-30T23:04:17.119Z"),
"updatedAt" : ISODate("2019-10-30T23:04:17.119Z"),
"__v" : {
"$numberInt" : "0"
}
}
airlines
{
"_id" : ObjectId("5db3823718518043c40e3ece"),
"country" : [
"Panamá",
"El Salvador",
"Belice"
],
"id_airline" : "VOL-643",
"name_airport" : "Juan Santamaría",
"name_airline" : "Volaris",
"createdAt" : ISODate("2019-10-30T23:04:17.119Z"),
"updatedAt" : ISODate("2019-10-30T23:04:17.119Z"),
"__v" : {
"$numberInt" : "0"
}
}
sales
[{
"_id" : ObjectId("5db9b643b50c0d1540b8db89"),
"id_user" : "304780391",
"id_flight" : "CPA-001",
"origin" : "Costa Rica",
"destination" : "Panamá",
"date_departure" : ISODate("2019-10-30T23:04:17.119Z"),
"date_arrival" : ISODate("2019-10-30T23:04:17.119Z"),
"tickets" : 4,
"suitcases" : {
"$numberInt" : "1"
},
"status" : "Bought",
"seat" : -1,
"createdAt" : ISODate("2019-10-30T23:04:17.119Z"),
"updatedAt" : ISODate("2019-10-30T23:04:17.119Z"),
"__v" : {
"$numberInt" : "0"
}
},
{
"_id" : ObjectId("5db9b643b50c0d1540b8db8a"),
"id_user" : "304780391",
"id_flight" : "CPA-001",
"origin" : "Costa Rica",
"destination" : "Panamá",
"date_departure" : ISODate("2019-10-30T23:04:17.119Z"),
"date_arrival" : ISODate("2019-10-30T23:04:17.119Z"),
"tickets" : 4,
"suitcases" : {
"$numberInt" : "1"
},
"status" : "Bought",
"seat" : -1,
"createdAt" : ISODate("2019-10-30T23:04:17.119Z"),
"updatedAt" : ISODate("2019-10-30T23:04:17.119Z"),
"__v" : {
"$numberInt" : "0"
}
}]