Compare 2 count aggregations - mongodb

Question

I have a collection in MongoDB that looks something like the following:
{ "_id" : 1, "type" : "start", userid: "101", placementid: 1 }
{ "_id" : 2, "type" : "start", userid: "101", placementid: 2 }
{ "_id" : 3, "type" : "start", userid: "101", placementid: 3 }
{ "_id" : 4, "type" : "end", userid: "101", placementid: 1 }
{ "_id" : 5, "type" : "end", userid: "101", placementid: 2 }
and I want to group results by userid then placementid and then count the types of "start" and "end", but only when the two counts are different. In this particular example I would want to get placementid: 3 because when grouped and counted this is the only case where the counts don't match.
I've written a query that gets the 2 counts and the grouping but I can't do the filtering when counts don't match. This is my query:
db.getCollection('mycollection').aggregate([
{
$project: {
userid: 1,
placementid: 1,
isStart: {
$cond: [ { $eq: ["$type", "start"] }, 1, 0]
},
isEnd: {
$cond: [ { $eq: ["$type", "end"] }, 1, 0]
}
}
},
{
$group: {
_id: { userid:"$userid", placementid:"$placementid" },
countStart:{ $sum: "$isStart" },
countEnd: { $sum: "$isEnd" }
}
},
{
$match: {
countStart: {$ne: "$countEnd"}
}
}
])
It seems like I'm using the match aggregation incorrectly because I'm seeing results where countStart and countEnd are the same.
{ "_id" : {"userid" : "101", "placementid" : "1"}, "countStart" : 1.0, "countEnd" : 1.0 }
{ "_id" : {"userid" : "101", "placementid" : "2"}, "countStart" : 1.0, "countEnd" : 1.0 }
{ "_id" : {"userid" : "101", "placementid" : "3"}, "countStart" : 1.0, "countEnd" : 0 }
Can anybody point into the right direction please?

Answer 1

To compare two fields inside $match stage you need $expr which is available in MongoDB 3.6:
db.myCollection.aggregate([
{
$project: {
userid: 1,
placementid: 1,
isStart: {
$cond: [ { $eq: ["$type", "start"] }, 1, 0]
},
isEnd: {
$cond: [ { $eq: ["$type", "end"] }, 1, 0]
}
}
},
{
$group: {
_id: { userid:"$userid", placementid:"$placementid" },
countStart:{ $sum: "$isStart" },
countEnd: { $sum: "$isEnd" }
}
},
{
$match: {
$expr: { $ne: [ "$countStart", "$countEnd" ] }
}
}
])
If you're using older version of MongoDB you can use $redact:
db.myCollection.aggregate([
{
$project: {
userid: 1,
placementid: 1,
isStart: {
$cond: [ { $eq: ["$type", "start"] }, 1, 0]
},
isEnd: {
$cond: [ { $eq: ["$type", "end"] }, 1, 0]
}
}
},
{
$group: {
_id: { userid:"$userid", placementid:"$placementid" },
countStart:{ $sum: "$isStart" },
countEnd: { $sum: "$isEnd" }
}
},
{
$redact: {
$cond: { if: { $ne: [ "$countStart", "$countEnd" ] }, then: "$$KEEP", else: "$$PRUNE" }
}
}
])

Answer 2

You run do the following pipeline to get this - no need to use $expr or $redact or anything special really:
db.mycollection.aggregate({
$group: {
_id: {
"userid": "$userid",
"placementid": "$placementid"
},
"sum": {
$sum: {
$cond: {
if: { $eq: [ "$type", "start" ] },
then: 1, // +1 for start
else: -1 // -1 for anything else
}
}
}
}
}, {
$match: {
"sum": { $ne: 0 } // only return the non matching-up ones
}
})