Aggregate and calculate with mongoDB - mongodb

Question

Hello I heard that mongoDB was very good at aggregating data compared to, for example SQL server.
I tried to translate an SQL query to a mongoDB query but it's a complete failure :
For SQL server we had like 4 minutes which is manageable and now we top at 34 minutes for 128 days using this request in mongoDB :
function(thresholdObs, days)
{
var name = "period-" + days + "j"
var startDate = new Date('2020', '00', '01');
var endDate = new Date(startDate.getTime() + 1000 * 60 * 60 * 24 *[days]);
db.getCollection('measures').aggregate([
{
$match: {
$and: [
{
measureDate: {
$gte: startDate
}
},
{
measureDate: {
$lte: endDate
}
}
]
}
},
{
$addFields: {
multiplyIahobs: {
$cond: [
{$or: [
{$eq: ["$averageIAH", null]},
{$eq: ["$obs", null]}
]},
0,
{ $multiply: ["$averageIAH", "$obs"] }
]
},
multiplyPressionobs: {
$cond: [
{$or: [
{$eq: ["$averagePressure", null]},
{$eq: ["$obs", null]}
]},
0,
{ $multiply: ["$averagePressure", "$obs"] }
]
},
multiplyFuitesobs: {
$cond: [
{$or: [
{$eq: ["$averageLeakage", null]},
{$eq: ["$obs", null]}
]},
0,
{ $multiply: ["$averageLeakage", "$obs"] }
]
},
multiplyinspiratoryPressureobs: {
$cond: [
{$or: [
{$eq: ["$inspiratoryPressure", null]},
{$eq: ["$obs", null]}
]},
0,
{ $multiply: ["$inspiratoryPressure", "$obs"] }
]
},
multiplyexpiratoryPressureobs: {
$cond: [
{$or: [
{$eq: ["$expiratoryPressure", null]},
{$eq: ["$obs", null]}
]},
0,
{ $multiply: ["$expiratoryPressure", "$obs"] }
]
},
enoughDays: {
$cond: [ { $gte: ["$obs", thresholdObs ] }, 1, 0]
},
missingDays: {
$cond: [ { $lt: ["$obs", thresholdObs ] }, 1, 0]
},
daysWithoutUsage: {
$cond: [ { $eq: ["$obs", 0 ] }, 1, 0]
},
daysWithData: { $sum: 1 }
}
},
{
$group: {
_id: "$deviceID",
obsUsage: { $avg: "$obs" },
enoughDays: { $sum: "$enoughDays" },
missingDays: { $sum: "$missingDays" },
daysWithoutUsage: { $sum: "$daysWithoutUsage" },
daysWithData: { $sum: "$daysWithData" },
sumobs: { $sum: "$obs" },
sumMultiplyIahobs: { $sum: "$multiplyIahobs" },
sumMultiplyPressureObs: { $sum: "$multiplyPressionobs" },
sumMultiplyLeakageObs: { $sum: "$multiplyFuitesobs" },
sumMultiplyinspiratoryPressureobs: { $sum: "$multiplyinspiratoryPressureobs" },
sumMultiplyexpiratoryPressureobs: { $sum: "$multiplyexpiratoryPressureobs" },
}
},
{
$addFields: {
fullObs: { $divide: [ "$sumobs", days ] },
daysWithoutData: { $subtract: [ days, "$daysWithData" ]},
averageIAH: { $cond: [ { $eq: [ "$sumobs", 0 ] }, 0, { $divide: ["$sumMultiplyIahobs", "$sumobs"] } ] },
averagePressure: { $cond: [ { $eq: [ "$sumobs", 0 ] }, 0, { $divide: ["$sumMultiplyPressureObs", "$sumobs"] } ] },
averageLeakage: { $cond: [ { $eq: [ "$sumobs", 0 ] }, 0, { $divide: ["$sumMultiplyLeakageObs", "$sumobs"] } ] },
inspiratoryPressure: { $cond: [ { $eq: [ "$sumobs", 0 ] }, 0, { $divide: ["$sumMultiplyinspiratoryPressureobs", "$sumobs"] } ] },
expiratoryPressure: { $cond: [ { $eq: [ "$sumobs", 0 ] }, 0, { $divide: ["$sumMultiplyexpiratoryPressureobs", "$sumobs"] } ] },
}
},
{
$project: {
_id: 1,
[name] : {
obsUsage: "$obsUsage",
enoughDays: "$enoughDays",
missingDays: "$missingDays",
daysWithoutUsage: "$daysWithoutUsage",
daysWithData: "$daysWithData",
sumobs: "$sumobs",
fullObs: "$fullObs",
daysWithoutData: "$daysWithoutData",
averageIAH: "$averageIAH",
averagePressure: "$averagePressure",
averageLeakage: "$averageLeakage",
inspiratoryPressure: "$inspiratoryPressure",
expiratoryPressure: "$expiratoryPressure"
}
}
},
{
$merge: {
into: "periods",
on: "_id",
whenMatched: "merge",
whenNotMatched: "insert"
}
}
],{allowDiskUse: true})
}
Before throwing out the baby (mongoDB) with the bathwater (the query). I came here asking if my understanding on how to write a good query is off. Should I try to alter this query to make it work under 4 minutes ? Is it possible ? How ?
NB : measures collection contains 374.670.449 documents.
Sample documents :
{
_id: ObjectId('6127a15fef44a9ed52a5bf62'),
deviceId: 5,
measureDateAdded: ISODate('2013-03-15T10:30:35.753Z'),
measureDate: ISODate('2012-03-20T06:00:00.000Z'),
obs: 20,
averageIAH: NumberDecimal('5.50'),
averagePressure: NumberDecimal('6.30'),
averageLeakage: NumberDecimal('13.00'),
inspiratoryPressure: null,
expiratoryPressure: null
},
{
_id: ObjectId('6127a15fef44a9ed52a5bfc6'),
deviceId: 5,
measureDateAdded: ISODate('2013-03-15T10:30:40.063Z'),
measureDate: ISODate('2012-06-28T05:00:00.000Z'),
obs: 197,
averageIAH: NumberDecimal('5.30'),
averagePressure: NumberDecimal('6.90'),
averageLeakage: NumberDecimal('15.00'),
inspiratoryPressure: null,
expiratoryPressure: null
},
{
_id: ObjectId('6127aa2bef44a9ed52a0922a'),
deviceId: 367959,
measureDateAdded: ISODate('2019-01-19T14:13:19.620Z'),
measureDate: ISODate('2019-01-16T11:00:00.000Z'),
obs: 375,
averageIAH: NumberDecimal('2.00'),
averagePressure: NumberDecimal('9.60'),
averageLeakage: NumberDecimal('6.00'),
inspiratoryPressure: null,
expiratoryPressure: null
}
What cost the most seems to be the group with deviceId 4+minutes