Merge $lookup result into existing document array - node.js

Question

-room collection
_id: ObjectId("xxx")
bedspaces: Array
0:ObjectId("xx")
1:ObjectId("xx")
***
***
-bedspace collection
_id: ObjectId("xxxx");
number: 1
decks: Array
{
_id: ObjectId("xxx");
number: 1
status: "Vacant"
tenant: ObjectId("5c964ae7f5097e3020d1926c")
dueRent: 11
away: null
},
{
_id: ObjectId("xxx");
number: 2
status: "Vacant"
tenant: null
dueRent: 11
away: null
}
Under the decks array, is my tenant field, that have objectId, and i am going to lookup this object id, in the tenants, collection.
-tenant collection
_id: ObjectId("5c964ae7f5097e3020d1926c");
name: 'John Doe'
-expected output
/*room collection*/
_id: ObjectId("xxx")
bedspaces: [
{
_id: ObjectId("xxx")
number: 1
decks: [
{
_id: ObjectId("xxx")
number: 1
status: "Vacant"
tenant: {
name: 'John Doe'
}
dueRent: 11
away: null
},
{
_id: ObjectId("xxx");
number: 1
status: "Vacant"
tenant: null
dueRent: 11
away: null
}
]
}
]
There is also an instances, that deck array is equal to null.
In below aggregation it will only display the decks, that have tenant with object id, what i want is to display both the decks.
{
from: 'beds',
let: {bedspace: '$bedspaces'},
pipeline:[
{
$match: {
$expr: {
$in: ["$_id", "$$bedspace"]
}
}
},
{
$unwind: "$decks"
},
{
$lookup: {
from: 'tenants',
let: {tenant: "$decks.tenant"},
pipeline: [
{
$match: {
$expr: {
$eq: ["$_id", "$$tenant"]
}
}
}
],
as: "decks.tenant",
}
},
{
$unwind: "$decks.tenant"
},
{ $group: {
_id: "$_id",
decks: { $push: "$decks" },
number: {$first: "$number"}
}}
],
as: "bedspaces"
}
"how can i add condition on my second look up, to execute only if tenant is not null", so that i could retrieve both decks, or any work-around so i could achieved my desired result

Answer 1

Don't really have time for all the explanation right now (sorry),
Explanation
The basic issue here is that usage of $unwind is your problem and you don't need it. Use $map on the produced array content merging with the "decks" array instead. Then you can have nulls.
What you want to do here is have the values from the $lookup from your "tenants" collection transposed into the existing array within your "beds/bedspaces" collection for it's own existing "tenant" values which are the ObjectId references for the foreign collection.
The $lookup stage cannot do this by simply naming the field path within the "as" output where that path is already inside another array, and in fact the output of $lookup is always an array of results obtained from the foreign collection. You want singular values for each actual match, and of course you expect a null to be in place where nothing matches, and of course keeping the original document array of "decks" intact, but just including the foreign details where those were found.
Your code attempt seems partially aware of this point as you are using $unwind on the $lookup result on the ""tenants" collection into a "temporary array" ( but you put in in the existing path and that overwrites content ) and then attempting to "re-group" as an array through $group and $push. But the problem of course is the $lookup result does not apply to every array member within "decks", so you end up with less results than you want.
The real solution is not a "conditional $lookup", but instead to transpose the "temporary array" content from the result into the existing "decks" entries. You do this using $map to process the array members, and $arrayElemAt along with $indexOfArray in order to return the matching elements from the "temporary array" by the matching _id values to "tenant".
{ "$lookup": {
"from": Tenant.collection.name,
"let": { "tenant": "$decks.tenant" },
"pipeline": [
{ "$match": {
"$expr": { "$in": [ "$_id", "$$tenant" ] }
}}
],
"as": "tenant"
}},
{ "$addFields": {
"decks": {
"$map": {
"input": "$decks",
"in": {
"$mergeObjects": [
"$$this",
{
"tenant": {
"$cond": {
"if": {
"$eq": [
{ "$indexOfArray": ["$tenant._id", "$$this.tenant"] },
-1
]
},
"then": null,
"else": {
"$arrayElemAt": [
"$tenant",
{ "$indexOfArray": ["$tenant._id", "$$this.tenant"]}
]
}
}
}
}
Noting there we are using $mergeObjects inside the $map in order to keep the existing content of the "decks" array and only replace ( or "merge" ) an overwritten representation of "tenant" for each array member. You are using the expressive $lookup already and this like $mergeObjects is a MongoDB 3.6 feature.
Just for interest the same thing can be done by just specifying every field within the array. i.e:
"decks": {
"$map": {
"input": "$decks",
"in": {
"_id": "$$this._id",
"number": "$$this.number",
"tenant": {
// same expression
},
"__v": "$$this.__v" // just because it's mongoose
}
}
}
Much the same can be said for the $$REMOVE used in the $addFields which is also another MongoDB 3.6 feature. You can alternately just use $project and simply omit the unwanted fields:
{ "$project": {
"number": "$number",
"decks": {
"$map": { /* same expression */ }
},
"__v": "$__v"
// note we don't use the "tenant" temporary array
}}
But that's basically how it works. By taking the $lookup result and then transposing those results back into the original array within the document.
Example Listing
Also abstracting on your data from previous questions here, which is a bit better than what you posted in the question here. Runnable listing for demonstration:
const { Schema, Types: { ObjectId } } = mongoose = require('mongoose');
const uri = 'mongodb://localhost:27017/hotel';
const opts = { useNewUrlParser: true };
mongoose.set('useFindAndModify', false);
mongoose.set('useCreateIndexes', true);
mongoose.set('debug', true);
const tenantSchema = new Schema({
name: String,
age: Number
});
const deckSchema = new Schema({
number: Number,
tenant: { type: Schema.Types.ObjectId, ref: 'Tenant' }
});
const bedSchema = new Schema({
number: Number,
decks: [deckSchema]
});
const roomSchema = new Schema({
bedspaces: [{ type: Schema.Types.ObjectId, ref: 'Bed' }]
});
const Tenant = mongoose.model('Tenant', tenantSchema);
const Bed = mongoose.model('Bed', bedSchema);
const Room = mongoose.model('Room', roomSchema);
const log = data => console.log(JSON.stringify(data, undefined, 2));
(async function() {
try {
const conn = await mongoose.connect(uri, opts);
// Clean data
await Promise.all(
Object.entries(conn.models).map(([k, m]) => m.deleteMany())
);
// Insert data
let [john, jane, bilbo ] = await Tenant.insertMany([
{
_id: ObjectId("5c964ae7f5097e3020d1926c"),
name: "john doe",
age: 11
},
{
_id: ObjectId("5c964b2531bc162fdce64f15"),
name: "jane doe",
age: 12
},
{
_id: ObjectId("5caa5454494558d863513b24"),
name: "bilbo",
age: 111
}
]);
let bedspaces = await Bed.insertMany([
{
_id: ObjectId("5c98d89c6bd5fc26a4c2851b"),
number: 1,
decks: [
{
number: 1,
tenant: john
},
{
number: 1,
tenant: jane
}
]
},
{
_id: ObjectId("5c98d89f6bd5fc26a4c28522"),
number: 2,
decks: [
{
number: 2,
tenant: bilbo
},
{
number: 3
}
]
}
]);
await Room.create({ bedspaces });
// Aggregate
let results = await Room.aggregate([
{ "$lookup": {
"from": Bed.collection.name,
"let": { "bedspaces": "$bedspaces" },
"pipeline": [
{ "$match": {
"$expr": { "$in": [ "$_id", "$$bedspaces" ] }
}},
{ "$lookup": {
"from": Tenant.collection.name,
"let": { "tenant": "$decks.tenant" },
"pipeline": [
{ "$match": {
"$expr": { "$in": [ "$_id", "$$tenant" ] }
}}
],
"as": "tenant"
}},
{ "$addFields": {
"decks": {
"$map": {
"input": "$decks",
"in": {
"$mergeObjects": [
"$$this",
{
"tenant": {
"$cond": {
"if": {
"$eq": [
{ "$indexOfArray": ["$tenant._id", "$$this.tenant"] },
-1
]
},
"then": null,
"else": {
"$arrayElemAt": [
"$tenant",
{ "$indexOfArray": ["$tenant._id", "$$this.tenant"]}
]
}
}
}
}
]
}
}
},
"tenant": "$$REMOVE"
}}
],
"as": "bedspaces"
}}
]);
log(results);
} catch (e) {
console.error(e)
} finally {
mongoose.disconnect();
}
})()
Returns:
Mongoose: tenants.deleteMany({}, {})
Mongoose: beds.deleteMany({}, {})
Mongoose: rooms.deleteMany({}, {})
Mongoose: tenants.insertMany([ { _id: 5c964ae7f5097e3020d1926c, name: 'john doe', age: 11, __v: 0 }, { _id: 5c964b2531bc162fdce64f15, name: 'jane doe', age: 12, __v: 0 }, { _id: 5caa5454494558d863513b24, name: 'bilbo', age: 111, __v: 0 } ], {})
Mongoose: beds.insertMany([ { _id: 5c98d89c6bd5fc26a4c2851b, number: 1, decks: [ { _id: 5caa5af6ed3dce1c3ed72cef, number: 1, tenant: 5c964ae7f5097e3020d1926c }, { _id: 5caa5af6ed3dce1c3ed72cee, number: 1, tenant: 5c964b2531bc162fdce64f15 } ], __v: 0 }, { _id: 5c98d89f6bd5fc26a4c28522, number: 2, decks: [ { _id: 5caa5af6ed3dce1c3ed72cf2, number: 2, tenant: 5caa5454494558d863513b24 }, { _id: 5caa5af6ed3dce1c3ed72cf1, number: 3 } ], __v: 0 } ], {})
Mongoose: rooms.insertOne({ bedspaces: [ ObjectId("5c98d89c6bd5fc26a4c2851b"), ObjectId("5c98d89f6bd5fc26a4c28522") ], _id: ObjectId("5caa5af6ed3dce1c3ed72cf3"), __v: 0 })
Mongoose: rooms.aggregate([ { '$lookup': { from: 'beds', let: { bedspaces: '$bedspaces' }, pipeline: [ { '$match': { '$expr': { '$in': [ '$_id', '$$bedspaces' ] } } }, { '$lookup': { from: 'tenants', let: { tenant: '$decks.tenant' }, pipeline: [ { '$match': { '$expr': { '$in': [ '$_id', '$$tenant' ] } } } ], as: 'tenant' } }, { '$addFields': { decks: { '$map': { input: '$decks', in: { '$mergeObjects': [ '$$this', { tenant: [Object] } ] } } }, tenant: '$$REMOVE' } } ], as: 'bedspaces' } } ], {})
[
{
"_id": "5caa5af6ed3dce1c3ed72cf3",
"bedspaces": [
{
"_id": "5c98d89c6bd5fc26a4c2851b",
"number": 1,
"decks": [
{
"_id": "5caa5af6ed3dce1c3ed72cef",
"number": 1,
"tenant": {
"_id": "5c964ae7f5097e3020d1926c",
"name": "john doe",
"age": 11,
"__v": 0
}
},
{
"_id": "5caa5af6ed3dce1c3ed72cee",
"number": 1,
"tenant": {
"_id": "5c964b2531bc162fdce64f15",
"name": "jane doe",
"age": 12,
"__v": 0
}
}
],
"__v": 0
},
{
"_id": "5c98d89f6bd5fc26a4c28522",
"number": 2,
"decks": [
{
"_id": "5caa5af6ed3dce1c3ed72cf2",
"number": 2,
"tenant": {
"_id": "5caa5454494558d863513b24",
"name": "bilbo",
"age": 111,
"__v": 0
}
},
{
"_id": "5caa5af6ed3dce1c3ed72cf1",
"number": 3,
"tenant": null
}
],
"__v": 0
}
],
"__v": 0
}
]
Shows the null on the second entry of the second entry in the bedspaces array as expected.