Creating measures in a mongodb aggregation pipeline - mongodb

Question

I have a report that has been developed in PowerBI. It runs over a collection of jobs, and for a given month and year counts the number of jobs that were created, due or completed in that month using measures.
I am attempting to reproduce this report using a mongoDB aggregation pipeline. At first, I thought I could just use the $group stage to do this, but quickly realised that grouping by a specific date would exclude jobs.
Some sample documents are below (most fields excluded as they are not relevant):
{
"_id": <UUID>,
"createdOn": ISODate("2022-07-01T00:00"),
"dueOn": ISODate("2022-08-01T00:00"),
"completedOn": ISODate("2022-07-29T00:00")
},
{
"_id": <UUID>,
"createdOn": ISODate("2022-06-01T00:00"),
"dueOn": ISODate("2022-08-01T00:00"),
"completedOn": ISODate("2022-07-24T00:00")
}
For example, if I group by created date, the record for July 2022 would show 1 created job and only 1 completed job, but it should show 2.
How can I go about recreating this report? One idea was that I needed to determine the minimum and maximum of all the possible dates across those 3 date fields in my collection, but I don't know where to go from there

Answer 1

I ended up solving this by using a facet. I followed this process:
Each facet field grouped by a different date field from the source document, and then aggregated the relevant field (e.g. counts, or sums as required). I ensured each of these fields in the facet had a unique name.
I then did a project stage where I took each of the facet stage fields (arrays), and concat them into a single array
I unwound the array, and then replaced the root to make it simpler to work with
I then grouped again by the _id field which was set to the relevant date during the facet field, and then grabbed the relevant fields.
The relevant parts of the pipeline are below:
db.getCollection("jobs").aggregate(
// Pipeline
[
// Stage 3
{
$facet: {
//Facet 1, group by created date, count number of jobs created
//facet 2, group by completed date, count number of jobs completed
//facet 3, group by due date, count number of jobs due
"created" : [
{
$addFields : {
"monthStarting" : {
"$dateFromString" : {
"dateString" : {
"$dateToString" : {
"date" : {
"$dateTrunc" : {
"date" : "$createdAt",
"unit" : "month",
"binSize" : 1.0,
"timezone" : "$timezone",
"startOfWeek" : "mon"
}
},
"timezone" : "$timezone"
}
}
}
},
"yearStarting" : {
"$dateFromString" : {
"dateString" : {
"$dateToString" : {
"date" : {
"$dateTrunc" : {
"date" : "$createdAt",
"unit" : "year",
"binSize" : 1.0,
"timezone" : "$timezone"
}
},
"timezone" : "$timezone"
}
}
}
}
}
},
{
$group : {
"_id" : {
"year" : "$yearStarting",
"month" : "$monthStarting"
},
"monthStarting" : {
"$first" : "$monthStarting"
},
"yearStarting" : {
"$first" : "$yearStarting"
},
"createdCount": {$sum: 1}
}
}
],
"completed" : [
{
$addFields : {
"monthStarting" : {
"$dateFromString" : {
"dateString" : {
"$dateToString" : {
"date" : {
"$dateTrunc" : {
"date" : "$completedDate",
"unit" : "month",
"binSize" : 1.0,
"timezone" : "$timezone",
"startOfWeek" : "mon"
}
},
"timezone" : "$timezone"
}
}
}
},
"yearStarting" : {
"$dateFromString" : {
"dateString" : {
"$dateToString" : {
"date" : {
"$dateTrunc" : {
"date" : "$completedDate",
"unit" : "year",
"binSize" : 1.0,
"timezone" : "$timezone"
}
},
"timezone" : "$timezone"
}
}
}
}
}
},
{
$group : {
"_id" : {
"year" : "$yearStarting",
"month" : "$monthStarting"
},
"monthStarting" : {
"$first" : "$monthStarting"
},
"yearStarting" : {
"$first" : "$yearStarting"
},
"completedCount": {$sum: 1}
}
}
],
"due": [
{
$match: {
"dueDate": {$ne: null}
}
},
{
$addFields : {
"monthStarting" : {
"$dateFromString" : {
"dateString" : {
"$dateToString" : {
"date" : {
"$dateTrunc" : {
"date" : "$dueDate",
"unit" : "month",
"binSize" : 1.0,
"timezone" : "$timezone",
"startOfWeek" : "mon"
}
},
"timezone" : "$timezone"
}
}
}
},
"yearStarting" : {
"$dateFromString" : {
"dateString" : {
"$dateToString" : {
"date" : {
"$dateTrunc" : {
"date" : "$dueDate",
"unit" : "year",
"binSize" : 1.0,
"timezone" : "$timezone"
}
},
"timezone" : "$timezone"
}
}
}
}
}
},
{
$group : {
"_id" : {
"year" : "$yearStarting",
"month" : "$monthStarting"
},
"monthStarting" : {
"$first" : "$monthStarting"
},
"yearStarting" : {
"$first" : "$yearStarting"
},
"dueCount": {$sum: 1},
"salesRevenue": {$sum: "$totalSellPrice"},
"costGenerated": {$sum: "$totalBuyPrice"},
"profit": {$sum: "$profit"},
"avgValue": {$avg: "$totalSellPrice"},
"finalisedRevenue": {$sum: {
$cond: {
"if": {$in: ["$status",["Finalised","Closed"]]},
"then": "$totalSellPrice",
"else": 0
}
}}
}
}
]
}
},
// Stage 4
{
$project: {
"docs": {$concatArrays: ["$created","$completed","$due"]}
}
},
// Stage 5
{
$unwind: {
path: "$docs",
}
},
// Stage 6
{
$replaceRoot: {
// specifications
"newRoot": "$docs"
}
},
// Stage 7
{
$group: {
_id: "$_id",
"monthStarting" : {
"$first" : "$monthStarting"
},
"yearStarting" : {
"$first" : "$yearStarting"
},
"monthStarting" : {
"$first" : "$monthStarting"
},
"createdCountSum" : {
"$sum" : "$createdCount"
},
"completedCountSum" : {
"$sum" : "$completedCount"
},
"dueCountSum" : {
"$sum" : "$dueCount"
},
"salesRevenue" : {
"$sum" : "$salesRevenue"
},
"costGenerated" : {
"$sum" : "$costGenerated"
},
"profit" : {
"$sum" : "$profit"
},
"finalisedRevenue" : {
"$sum" : "$finalisedRevenue"
},
"avgJobValue": {
$sum: "$avgValue"
}
}
},
],
);