You were not very far from the full solution with aggregation framework - you needed one more thing before the $group
step and that is something that would allow you to see if all the things that are being used match up with something that is owned.
Here is the full pipeline
> db.house.aggregate(
{'$unwind':'$uses'},
{'$unwind':'$rooms'},
{'$unwind':'$rooms.owns'},
{$project: { _id:0,
houseId:1,
uses:"$uses.name",
isOkay:{$cond:[{$eq:["$uses.name","$rooms.owns.name"]}, 1, 0]}
}
},
{$group: { _id:{house:"$houseId",item:"$uses"},
hasWhatHeUses:{$sum:"$isOkay"}
}
},
{$match:{hasWhatHeUses:0}})
and its output on your document
{
"result" : [
{
"_id" : {
"house" : 123,
"item" : "sofa"
},
"hasWhatHeUses" : 0
}
],
"ok" : 1
}
Explanation - once you unwrap both arrays you now want to flag the elements where used item is equal to owned item and give them a non-0 "score". Now when you regroup things back by houseId you can check if any used items didn't get a match. Using 1 and 0 for score allows you to do a sum and now a match for item which has sum 0 means it was used but didn't match anything in "owned". Hope you enjoyed this!