Is it a good idea writing multiple aggregate in mongodb? - node.js

Question

My schema looks like this
{
_id: ObjectID,
gender: "MALE", // MALE or FEMALE
status: "ACTIVE", // ACTIVE or INACTIVE
method: "A" // A or B
}
The API needs to return a total document count, total count by gender, total count by status and total count by method. My current approach is making multiple aggregate calls and one count method.
As such,
const genderCursor = db.collection(Collection.Sample).aggregate([
{"$group": { _id: "$gender", count: { $sum: 1 }}}
]);
const statusCursor = db.collection(Collection.Sample).aggregate([
{"$group": { _id: "$status", count: { $sum: 1 }}}
]);
const methodCursor = db.collection(Collection.Sample).aggregate([
{"$group": { _id: "$method", count: { $sum: 1 }}}
]);
const total = await db.collection(Collection.Sample).count();
await genderCursor.forEach(x => gender.push({ name: x._id, count: x.count}))
await statusCursor.forEach(x => statuses.push({ name: x._id, count: x.count}))
await methodCursor.forEach(x => methods.push({ name: x._id, count: x.count}))
Results,
{
"total": 100,
"gender": [
{
"name": "MALE",
"count": 30
},
{
"name": "FEMALE",
"count": 70
},
],
"statuses": [
{
"name": "APPROVED",
"count": 81
},
{
"name": "CREATED",
"count": 19
},
],
"methods": [
{
"name": "A",
"count": 50
},
{
"name": "B",
"count": 50
},
],
}
Is there a better and cost effective method to achieve the same thing as above?

Answer 1

You should combine all the queries into a single Aggregation Query since it will reduce your network roundtrip times and load on MongoDB servers.
There are two methods in doing this.
Method-1: Using null Group
You can group with _id null and apply $cond Operator. This is much
faster than the second method, but you have to apply all the outcomes required in the $cond.
Choose whichever method works best for your use case.
db.collection.aggregate([
{
"$group": {
"_id": null,
"male": {
"$sum": {
"$cond": {
"if": {
"$eq": [
"$gender",
"MALE"
]
},
"then": 1,
"else": 0,
},
},
},
"female": {
"$sum": {
"$cond": {
"if": {
"$eq": [
"$gender",
"FEMALE"
]
},
"then": 1,
"else": 0,
},
}
},
"active": {
"$sum": {
"$cond": {
"if": {
"$eq": [
"$status",
"ACTIVE"
]
},
"then": 1,
"else": 0,
},
}
},
"inactive": {
"$sum": {
"$cond": {
"if": {
"$eq": [
"$status",
"INACTIVE"
]
},
"then": 1,
"else": 0,
}
},
},
"methodA": {
"$sum": {
"$cond": {
"if": {
"$eq": [
"$method",
"A"
]
},
"then": 1,
"else": 0,
},
}
},
"methodB": {
"$sum": {
"$cond": {
"if": {
"$eq": [
"$method",
"B"
]
},
"then": 1,
"else": 0,
},
},
}
}
},
])
Mongo Playground Sample Execution
Method-2: Using $facet
You can also use the $facet stage, but it requires more computation on MongoDB compared with $group, but you don't have to write all the outcomes manually.
db.collection.aggregate([
{
"$facet": {
"gender": [
{
"$group": {
"_id": "$gender",
"count": {
"$sum": 1
}
}
},
],
"status": [
{
"$group": {
"_id": "$status",
"count": {
"$sum": 1
}
}
},
],
"method": [
{
"$group": {
"_id": "$method",
"count": {
"$sum": 1
}
}
},
],
}
}
])
Mongo Playground Sample Execution