mongoDB updateMany based on nested array condition - mongodb

Question

I have following structure in users collection:
[
{ "name": "Ivan",
"payments": [
{"date": new Date("2019-01-01"), "details": [{"payment_system": "A", "spent": 95},
{"payment_system": "B", "spent": 123}]},
{"date": new Date("2019-01-03"), "details": [{"payment_system": "A", "spent": 12},
{"payment_system": "B", "spent": 11}]}]},
{ "name": "Mark",
"payments": [
{"date": new Date("2019-01-01"), "details": [{"payment_system": "D", "spent": 456},
{"payment_system": "B", "spent": 123}]},
{"date": new Date("2019-01-02"), "details": [{"payment_system": "A", "spent": 98},
{"payment_system": "C", "spent": 4}]}]}
]
Is it any way to add a field to users who spent more than, lets say 100 during the specific date range in specific payment system?
I tried updateMany, but have no idea how to filter "details" array element based on payment_system field.
For payment_system IN ("A", "C"), date >= "2019-01-02", spent_total >= 100 update should return
[
{ "name": "Ivan", ...},
{ "name": "Mark", "filter_passed": true, ... }
]

Answer 1

This this one:
db.collection.aggregate([
{
$set: {
payments: {
$filter: {
input: "$payments",
cond: { $gte: ["$$this.date", new Date("2019-01-02")] }
}
}
}
},
{
$set: {
spent_total: {
$reduce: {
input: "$payments.details.spent",
initialValue: [],
in: { $concatArrays: ["$$value", "$$this"] }
}
}
}
},
{ $set: { spent_total: { $sum: "$spent_total" } } },
{ $match: { "spent_total": { $gte: 100 } } }
])
Mongo Playground
Update:
Filter by payment_system is a bit longer. You have to $unwind and $group:
db.collection.aggregate([
{
$set: {
payments: {
$filter: {
input: "$payments",
cond: { $gte: ["$$this.date", new Date("2019-01-02")] }
}
}
}
},
{ $unwind: "$payments" },
{
$set: {
"payments.details": {
$filter: {
input: "$payments.details",
cond: { $in: ["$$this.payment_system", ["A", "C"]] }
},
},
}
},
{
$group: {
_id: { _id: "$_id", name: "$name", },
payments: { $push: "$payments" }
}
},
{
$set: {
spent_total: {
$reduce: {
input: "$payments.details.spent",
initialValue: [],
in: { $concatArrays: ["$$value", "$$this"] }
}
}
}
},
{ $set: { spent_total: { $sum: "$spent_total" } } },
{ $match: { "spent_total": { $gte: 100 } } },
{ // just some cosmetic
$project: {
_id: "$_id._id",
name: "$_id.name",
payments: 1
}
}
])
You cannot update your collection like db.collection.updateMany({}, [<the aggregation pipeline from above>]) because it contains $unwind and $group.
However, you can make $lookup or $out to save entire result into new collection.
If you need to sum up for each payment_system individually then try:
db.collection.aggregate([
{
$set: {
payments: {
$filter: {
input: "$payments",
cond: { $gte: ["$$this.date", new Date("2019-01-01")] }
}
}
}
},
{ $unwind: "$payments" },
{
$set: {
"payments.details": {
$filter: {
input: "$payments.details",
cond: { $in: ["$$this.payment_system", ["A", "B","C"]] }
},
},
}
},
{ $unwind: "$payments.details" },
{
$group: {
_id: {
_id: "$_id",
name: "$name",
payments: "$payments.details.payment_system"
},
spent_total: { $sum: "$payments.details.spent" }
}
},
{ $match: { "spent_total": { $gte: 100 } } },
{
$project: {
_id: "$_id._id",
name: "$_id.name",
payments: "$_id.payments",
spent_total: 1
}
}
])