You cannot get the desired result with the current structure using .aggregate(). You can “modify” the structure to use an array rather than named keys, and the operation is actually quite simple.
So, with a document like:
{
"_id" : "9aa072e4-b706-47e6-9607-1a39e904a05a",
"customerId" : "2164289-4",
"channelStatuses" : [
{
"channel": "FOO",
"status" : "done"
},
{
"channel": "BAR",
"status" : "error"
}
],
"channel" : "BAR",
}
$filter, $map $arrayElemAt:
{ "$group": {
"_id": {
"customerId" : "$customerId",
"channel" : "$channel",
"status": {
"$arrayElemAt": [
{ "$map": {
"input": { "$filter": {
"input": "$chanelStatuses",
"as": "el",
"cond": { "$eq": [ "$$el.channel", "$channel" ] }
}},
"as": "el",
"in": "$$el.status"
}},
0
]
}
},
"count": { "$sum": 1 }
}}
MongoDB $unwind .
MongoDB 2.6 " " , :
[
{ "$project": {
"customerId": 1,
"channel": 1,
"status": {
"$setDifference": [
{ "$map": {
"input": "$channelStatuses",
"as": "el",
"in": {
"$cond": [
{ "$eq": [ "$$el.channel", "$channel" ] },
"$$el.status",
false
]
}
}},
[false]
]
}
}},
{ "$unwind": "$status" },
{ "$group": {
"_id": {
"customerId": "$customerId",
"channel": "$channel",
"status": "$status"
},
"count": { "$sum": 1 }
}}
]
- "" $unwind :
[
{ "$unwind": "$channelStatuses" },
{ "$project": {
"customerId": 1,
"channel": 1,
"status": "$channelStatuses.status",
"same": { "$eq": [ "$channelStatuses.status", "$channel" ] }
}},
{ "$match": { "same": true } },
{ "$group": {
"_id": "$_id",
"customerId": { "$first": "$customerId" },
"channel": { "$first": "$channel" },
"status": { "$first": "$status" }
}},
{ "$group": {
"_id": {
"customerId": "$customerId",
"channel": "$channel",
"status": "$status"
},
"count": { "$sum": 1 }
}}
]
, MongoDB 2.6, $project , $match . "" $group, "channel" $first. $group , .
"" , , mapReduce:
db.collection.mapReduce(
function() {
emit({
"customerId": this.customerId,
"channel": this.channel,
"status": this.channelStatuses[this.channel].status
},1);
},
function(key,values) {
return Array.sum(values);
},
{ "out": { "inline": 1 } }
)
, ,