Aggregation pipeline to lookup and merge nested documents - mongodb

Question

I am struggling with writing an aggregation pipeline to lookup nested documents by their _id and return a specific name without overwriting the existing keys/values in the data. I have managed to do this for the nested array, but am unable to do it for an array that is nested within the nested array.
So I want to lookup the _id of each ingredient and each subIngredient and merge them with the data for these ingredients that already exists (i.e. qty, measure).
Here is what I have so far:
https://mongoplayground.net/p/ft4oIMm_8wg
Products Collection:
[
{
"_id": {
"$oid": "5ecf269bceb735416db0b329"
},
"id": 36,
"title": "Product 1",
"description": {
"generalInformation": "Some information",
"activeIngredients": [
{
"_id": 1636,
"qty": 133.5,
"measure": "µg",
"subIngredient": [
{
"_id": 1626,
"qty": 16.6,
"measure": "µg"
}
],
},
{
"_id": 1234,
"qty": 133.5,
"measure": "µg",
"subIngredient": [
{
"_id": 1122,
"qty": 16.6,
"measure": "µg"
},
{
"_id": 1212,
"qty": 16.6,
"measure": "µg"
}
],
},
]
},
},
{
"_id": {
"$oid": "5ecf269bceb735416db0b346"
},
"id": 36,
"title": "Product 2",
"description": {
"generalInformation": "Some information",
"activeIngredients": [
{
"_id": 1234,
"qty": 133.5,
"measure": "µg",
"subIngredient": [
{
"_id": 1122,
"qty": 16.6,
"measure": "µg"
}
],
},
{
"_id": 1234,
"qty": 133.5,
"measure": "µg",
"subIngredient": [
{
"_id": 1122,
"qty": 16.6,
"measure": "µg"
},
{
"_id": 1212,
"qty": 16.6,
"measure": "µg"
}
],
},
]
},
}
]
Ingredients Collection:
[
{
"_id": 1234,
"name": "Ingredient 1",
},
{
"_id": 1122,
"name": "Ingredient 2",
},
{
"_id": 1212,
"name": "Ingredient 3",
},
{
"_id": 1636,
"name": "Ingredient 4",
},
{
"_id": 1626,
"name": "Ingredient 5",
}
]
What should be returned:
[
{
"_id": ObjectId("5ecf269bceb735416db0b329"),
"title": "Product 1"
"description": {
"activeIngredients": {
"_id": 1636,
"measure": "µg",
"name": "Ingredient 4",
"qty": 133.5,
"subIngredient": [
{
"_id": 1626,
"measure": "µg",
"qty": 16.6
}
]
},
"generalInformation": "Some information"
},
"ingredients": [
{
"_id": 1636,
"measure": "µg",
"name": "Ingredient 4",
"qty": 133.5,
"subIngredient": [
{
"_id": 1626,
"measure": "µg",
"qty": 16.6,
"name": "Ingredient 2"
}
]
},
{
"_id": 1234,
"measure": "µg",
"name": "Ingredient 1",
"qty": 133.5,
"subIngredient": [
{
"_id": 1122,
"measure": "µg",
"qty": 16.6,
"name": "Ingredient 2"
},
{
"_id": 1212,
"measure": "µg",
"qty": 16.6,
"name": "Ingredient 2"
}
]
}
]
},
]
My current pipeline:
[
{
"$unwind": {
"path": "$description.activeIngredients",
"preserveNullAndEmptyArrays": false
}
},
{
"$lookup": {
"from": "ingredients",
"localField": "description.activeIngredients._id",
"foreignField": "_id",
"as": "description.activeIngredients.name"
}
},
{
"$addFields": {
"description.activeIngredients.name": {
"$arrayElemAt": [
"$description.activeIngredients.name.name",
0
]
}
}
},
{
"$group": {
"_id": "$_id",
"ingredients": {
"$push": "$description.activeIngredients"
},
"description": {
"$first": "$description"
},
"title": {
"$first": "$title"
}
}
},
{
"$lookup": {
"from": "ingredients",
"localField": "ingredients.subIngredient._id",
"foreignField": "_id",
"as": "subIngredients"
}
}
]
Appreciate any help. Thanks.

Answer 1

You're not far off and you can achieve this result in multiple different ways, one of which is to just $unwind the subingredients array, $lookup on that and finally adding another $group stage to restructure the document.
As you've clearly shown you know how to do all these things i'll show a different way that utilizes operators like $map, $indexOfArray and Mongo's v3.6 $lookup syntax.
The strategy is instead of unwinding the subarray we just $lookup all the relevant sub-ingredients and then "merge" the two arrays using the operators i specified.
i.e taking:
[ {id: 5, name: "name"} ];
[ {id: 5, qty: 25} ]
And making them into:
[ {id: 5, name: "name", qty: 25} ]
Here's how we do it:
db.products.aggregate([
{
"$unwind": {
"path": "$description.activeIngredients",
"preserveNullAndEmptyArrays": false
}
},
{
"$lookup": {
"from": "ingredients",
"localField": "description.activeIngredients._id",
"foreignField": "_id",
"as": "description.activeIngredients.name"
}
},
{
"$addFields": {
"description.activeIngredients.name": {
"$arrayElemAt": [
"$description.activeIngredients.name.name",
0
]
}
}
},
{
"$lookup": {
"from": "ingredients",
"let": {
sub: "$description.activeIngredients.subIngredient"
},
"pipeline": [
{
$match: {
$expr: {
"$setIsSubset": [
[
"$_id"
],
{
$map: {
input: "$$sub",
as: "datum",
in: "$$datum._id"
}
}
]
}
}
}
],
"as": "subIngredients"
}
},
{
"$addFields": {
"description.activeIngredients.subIngredient": {
$map: {
input: "$description.activeIngredients.subIngredient",
as: "sub",
in: {
"$mergeObjects": [
"$$sub",
{
name: {
$arrayElemAt: [
"$subIngredients.name",
{
"$indexOfArray": [
"$subIngredients._id",
"$$sub._id"
]
}
]
}
}
]
}
}
}
}
},
{
"$group": {
"_id": "$_id",
"ingredients": {
"$push": "$description.activeIngredients"
},
"description": {
"$first": "$description"
},
"title": {
"$first": "$title"
}
}
}
])
MongoPlayground