MongoDB/Mongoose: append related records to each aggreation result - mongodb

Question

Given the following Mongo collection called "members"
{
{name: "Joe", hobby: "Food"}, {name: "Lyn", hobby: "Food"},
{name: "Rex", hobby: "Play"}, {name: "Rex", hobby: "Shop"},...
}
I have an aggregation query that returns a paged set of records along with metadata for the total records found:
db.members.aggregate([
{
$facet: {
pipe1: [{ $count: 'count' }],
pipe2: [{ $skip: 0 }, { $limit: 4 }],
},
},
{
$unwind: '$pipe1',
},
{
$project: {
count: '$pipe1.count',
results: '$pipe2',
},
},
])
This gives me:
{count: 454, results: [<First 4 records here>]}
I am now trying to add to each record, an array of all member names that have the same hobby. So for the collection above, something like:
{
count: 454,
results: [
{name: "Joe", hobby: "Food", fanClub: ["Joe", "Lyn", "Alfred"]},
{name: "Lyn", hobby: "Food", fanClub: ["Joe", "Lyn", "Alfred"]},
{name: "Rex", hobby: "Play", fanClub: ["Rex"]},
{name: "Rex", hobby: "Shop", fanClub: ["Rex", "Rita"]}
]
}
I can't figure out how to run the follow up query within the aggregate. I've tried:
db.members.aggregate([
{
$facet: {
pipe1: [{ $count: 'count' }],
pipe2: [
{ $skip: 0 },
{ $limit: 2 },
{
$lookup: {
from: 'members',
pipeline: [{ $match: { hobby: '$hobby' } }],
as: 'fanClub',
},
},
],
},
},
{
$unwind: '$pipe1',
},
{
$project: {
count: '$pipe1.count',
results: '$pipe2',
},
},
])
Alas, the fanClub array is always empty.
Update 1
If I hardcode the hobby, for instance replace
{ $match: { hobby: '$hobby' }
with
{ $match: { hobby: 'Food' }
Then I do get results and all the fanClub arrays contain the results for Joe, Lyn and Alfred. So I must not be referring to the value within the pipeline correctly

Answer 1

Please try this :
db.membersHobby.aggregate([
{
$facet: {
pipe1: [{ $count: 'count' }],
pipe2: [{
$lookup:
{
from: "membersHobby",
let: { hobby: "$hobby" },
pipeline: [
{
$match:
{ $expr: { $eq: ["$hobby", "$$hobby"] } }
},
{ $project: { name: 1, _id: 0 } }
],
as: "fanClub"
}
}, { $skip: 0 }, { $limit: 4 }]
}
},
{
$unwind: '$pipe1'
},
{
$project: {
count: '$pipe1.count',
results: '$pipe2'
}
}
])
Result :
/* 1 */
{
"count" : 4,
"results" : [
{
"_id" : ObjectId("5e20a63ed3c98f2a7100fd4a"),
"name" : "Joe",
"hobby" : "Food",
"fanClub" : [
{
"name" : "Joe"
},
{
"name" : "Lyn"
}
]
},
{
"_id" : ObjectId("5e20a63ed3c98f2a7100fd4b"),
"name" : "Lyn",
"hobby" : "Food",
"fanClub" : [
{
"name" : "Joe"
},
{
"name" : "Lyn"
}
]
},
{
"_id" : ObjectId("5e20a63ed3c98f2a7100fd4c"),
"name" : "Rex",
"hobby" : "Play",
"fanClub" : [
{
"name" : "Rex"
}
]
},
{
"_id" : ObjectId("5e20a63ed3c98f2a7100fd4d"),
"name" : "Rex",
"hobby" : "Shop",
"fanClub" : [
{
"name" : "Rex"
}
]
}
]
}

Answer 2

If #srinivasy's answer meets your requierements, please grant my points him :)
If you want to get such structure:
{
count: 454,
results: [
{name: "Joe", hobby: "Food", fanClub: ["Joe", "Lyn", "Alfred"]},
{name: "Lyn", hobby: "Food", fanClub: ["Joe", "Lyn", "Alfred"]},
{name: "Rex", hobby: "Play", fanClub: ["Rex"]},
{name: "Rex", hobby: "Shop", fanClub: ["Rex", "Rita"]}
]
}
Use this query ($reduce is used to return single value, in you case fanClub as array):
db.members.aggregate([
{
$facet: {
pipe1: [
{
$count: "count"
}
],
pipe2: [
{
$skip: 0
},
{
$limit: 4
},
{
$lookup: {
from: "members",
let: {
hobby: "$hobby"
},
pipeline: [
{
$match: {
$expr: {
$eq: [
"$hobby",
"$$hobby"
]
}
}
}
],
as: "fanClub"
}
}
]
}
},
{
$unwind: "$pipe1"
},
{
$project: {
count: "$pipe1.count",
results: {
$map: {
input: "$pipe2",
as: "pipe2",
in: {
_id: "$$pipe2._id",
hobby: "$$pipe2.hobby",
name: "$$pipe2.name",
fanClub: {
$reduce: {
input: "$$pipe2.fanClub",
initialValue: [],
in: {
$concatArrays: [
"$$value",
[
"$$this.name"
]
]
}
}
}
}
}
}
}
}
])
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