Multiple Counts with single query in mongodb - mongodb

Question

I am new to Mongo Db and would appreciate some help with this query. I have been sifting through posts here for the past couple of days tearing my hair to see if I could find anything related to my query but with no luck.
I have a collection with documents similar in structure to below :
_id: xyz
Movieid: 123
MovieName: Titanic
ReleaseDate: 2000-01-01
_id: uvw
Movieid: 456
MovieName: Titanic II
ReleaseDate: 2018-01-01
_id: pqr
Movieid: 789
MovieName: Titanic III
ReleaseDate:
I would like to achieve the output as counts for totalmovies, movies with release date, and movies without release date in 3 seperate columns as below:
Total | Released | UnReleased
3 | 2 | 1
I was able to write individual queries to execute the counts, but I am unable to successfully consolidate all that into a single query. The end goal is to create one view producing these counts as output. I have tried using operators such as $and, but can't seem to get the query to work as desired....this is as far as I got :
db.getCollection("Movies").aggregate({
"$and": [
{ "$match": { "ReleaseDate": { "$exists": true } }},
{ "$count": "Total" },
{ "$match": { "ReleaseDate": { "$exists": true, "$nin": [""] } }},
{ "$count": "Released" },
{ "$match": { "ReleaseDate": { "$exists": true, "$in": [""] } }},
{ "$count": "Unreleased" }
]
})

Answer 1

You can try below $facet aggregation
$count aggregation will always give you the counts for only single matching ($match) condition. So you need to further divide your each count into multiple section and that's what the $facet provides by processes multiple aggregation pipelines within a single stage on the same set of input documents.
db.collection.aggregate([
{ "$facet": {
"Total": [
{ "$match" : { "ReleaseDate": { "$exists": true }}},
{ "$count": "Total" },
],
"Released": [
{ "$match" : {"ReleaseDate": { "$exists": true, "$nin": [""] }}},
{ "$count": "Released" }
],
"Unreleased": [
{ "$match" : {"ReleaseDate": { "$exists": true, "$in": [""] }}},
{ "$count": "Unreleased" }
]
}},
{ "$project": {
"Total": { "$arrayElemAt": ["$Total.Total", 0] },
"Released": { "$arrayElemAt": ["$Released.Released", 0] },
"Unreleased": { "$arrayElemAt": ["$Unreleased.Unreleased", 0] }
}}
])
Output
[{
"Total": 3,
"Released": 2,
"Unreleased": 1
}]

Answer 2

You can use below aggregation.
$gt > null - to check whether field exists or not in aggregation expressions.
$cond with $sum to output 0 and 1 based on release date filter.
$add to add both released and unreleased count to output total.
db.Movies.aggregate([
{"$group":{
"_id":null,
"Unreleased":{"$sum":{"$cond":[{"$and":[{"$gt":["$ReleaseDate",null]},{"$ne":["$ReleaseDate",""]}]},0,1]}},
"Released":{"$sum":{"$cond":[{"$and":[{"$gt":["$ReleaseDate",null]},{"$ne":["$ReleaseDate",""]}]},1,0]}}
}},
{"$addFields":{"Total":{"$add":["$Unreleased","$Released"]}}}
])

Answer 3

db.Movies.aggregate(
// Pipeline
[
// Stage 1
{
$group: {
_id: null,
Total: {
$sum: 1
},
docs: {
$push: '$$ROOT'
}
}
},
// Stage 2
{
$project: {
_id: 0,
Total: 1,
Released: {
$filter: {
input: "$docs",
as: "doc",
cond: {
$ne: ["$$doc.ReleaseDate", ""]
}
}
},
Unreleased: {
$filter: {
input: "$docs",
as: "doc",
cond: {
$eq: ["$$doc.ReleaseDate", ""]
}
}
},
}
},
// Stage 3
{
$project: {
Total: 1,
Released: {
$size: '$Released'
},
UnReleased: {
$size: '$Unreleased'
}
}
},
]
);