Using the following data, how would I count the total number of yes and no votes for a collection of records with pollId "hr4946-113" using MongoDBs support for aggregate queries.
{ "_id" : ObjectId("54abcdbeba070410146d6073"), "userId" : "1234", "pollId" : "hr4946-113", "vote" : true, "__v" : 0 }
{ "_id" : ObjectId("54afe32fec4444481b985711"), "userId" : "12345", "pollId" : "hr2840-113", "vote" : true, "__v" : 0 }
{ "_id" : ObjectId("54b66de68dde7a0c19be987b"), "userId" : "123456", "pollId" : "hr4946-113", "vote" : false }
This would be the expected Result.
{
"yesCount": 1,
"noCount":1
}
The aggregation framework is your answer:
db.collection.aggregate([
{ "$match": { "pollId": "hr4946-113" } },
{ "$group": {
"_id": "$vote",
"count": { "$sum": 1 }
}}
])
Basically the $group
operator gathers all the data by "key", and "grouping operators" like $sum
work on the values. In this case, just adding 1
on the boundaries to indicate a count.
Gives you:
{ "_id": true, "count": 1 },
You can be silly and expand that into a single document response using the $cond operator to conditionally evaluate the field values:
db.collection.aggregate([
{ "$match": { "pollId": "hr4946-113" } },
{ "$group": {
"_id": "$vote",
"count": { "$sum": 1 }
}},
{ "$group": {
"_id": null,
"yesCount": {
"$sum": {
"$cond": [ "_id", 1, 0 ]
}
},
"noCount": {
"$sum": {
"$cond": [ "_id", 0, 1 ]
}
}
}},
{ "$project": { "_id": 0 } }
])
And the result:
{ "yesCount": 1, "noCount": 0 }