Mongo DB query for count with condition - mongodb

Question

I have the following documents stored in "Deployments" collection in MongoDB version 4.2.
I would like to achieve the following results group by productId and between a range of dates.
I have achieved execution times using this query.
db.getCollection('Deployments').aggregate([
{
$match : {$and:[{ "startedAt": { $gte: new ISODate("2021-10-01") } },
{ "startedAt": { $lte: new ISODate("2021-11-17") } }]}
},
{
$group : {
_id:"$productId",
count: { $sum: 1 },
minExecutionTime:
{
$min:
{
$divide:[{$subtract:["$completedAt", "$startedAt"]}, 1000 * 60]
}
},
maxExecutionTime:
{
$max:
{
$divide:[{$subtract:["$completedAt", "$startedAt"]}, 1000 * 60]
}
},
avgExecutionTime:
{
$avg:
{
$divide:[{$subtract:["$completedAt", "$startedAt"]}, 1000 * 60]
}
}
}
}
])
Any help to add the counts to this query please?
How to truncate the execution times to 2 decimal places?
Please suggest in case of any optimizations to this query.
Documents:
[
{
"productId": 1,
"deploymentStatus": "Succeeded",
"startedAt": ISODate("2021-01-21T14:00:19.782Z"),
"completedAt": ISODate("2021-01-21T14:03:55.789Z")
},
{
"productId": 2,
"deploymentStatus": "Failed",
"startedAt": ISODate("2021-01-21T15:00:19.782Z"),
"completedAt": ISODate("2021-01-21T15:03:55.789Z")
},
{
"productId": 3,
"deploymentStatus": "Cancelled",
"startedAt": ISODate("2021-01-21T16:00:19.782Z"),
"completedAt": ISODate("2021-01-21T16:03:55.789Z")
},
{
"productId": 1,
"deploymentStatus": "Failed",
"startedAt": ISODate("2021-01-21T17:00:19.782Z"),
"completedAt": ISODate("2021-01-21T17:03:55.789Z")
},
{
"productId": 2,
"deploymentStatus": "Failed",
"startedAt": ISODate("2021-01-21T18:00:19.782Z"),
"completedAt": ISODate("2021-01-21T18:03:55.789Z")
},
{
"productId": 3,
"deploymentStatus": "Succeeded",
"startedAt": ISODate("2021-01-21T19:00:19.782Z"),
"completedAt": ISODate("2021-01-21T19:03:55.789Z")
},
{
"productId": 1,
"deploymentStatus": "Cancelled",
"startedAt": ISODate("2021-01-21T20:00:19.782Z"),
"completedAt": ISODate("2021-01-21T20:03:55.789Z")
},
{
"productId": 2,
"deploymentStatus": "Failed",
"startedAt": ISODate("2021-01-21T21:00:19.782Z"),
"completedAt": ISODate("2021-01-21T21:03:55.789Z")
},
{
"productId": 3,
"deploymentStatus": "Succeeded",
"startedAt": ISODate("2021-01-21T22:00:19.782Z"),
"completedAt": ISODate("2021-01-21T22:03:55.789Z")
}
]
Mongo Playground

Answer 1

Your aggregation is actually on the right track. For your 3 questions:
Any help to add the counts to this query please?
Just break the count into 3 conditional count using $cond
How to truncate the execution times to 2 decimal places?
Use $round
Please suggest in case of any optimizations to this query.
I did a minor tweak to pre-compute the duration in minute instead of computing them again in the $group stage
db.collection.aggregate([
{
$match: {
$and: [
{
"startedAt": {
$gte: ISODate("2021-01-21")
}
},
{
"startedAt": {
$lte: ISODate("2021-01-22")
}
}
]
}
},
{
"$addFields": {
"durationInMin": {
$round: [
{
$divide: [
{
$subtract: [
"$completedAt",
"$startedAt"
]
},
60000
]
},
2
]
}
}
},
{
$group: {
_id: "$productId",
SucceedCount: {
$sum: {
"$cond": {
"if": {
$eq: [
"$deploymentStatus",
"Succeeded"
]
},
"then": 1,
"else": 0
}
}
},
FailedCount: {
$sum: {
"$cond": {
"if": {
$eq: [
"$deploymentStatus",
"Failed"
]
},
"then": 1,
"else": 0
}
}
},
CancelledCount: {
$sum: {
"$cond": {
"if": {
$eq: [
"$deploymentStatus",
"Cancelled"
]
},
"then": 1,
"else": 0
}
}
},
minExecutionTime: {
$min: "$durationInMin"
},
maxExecutionTime: {
$max: "$durationInMin"
},
avgExecutionTime: {
$avg: "$durationInMin"
}
}
}
])
Here is the Mongo playground for your reference.