versuchen Sie diese Aggregation
$match
- Filtern nach gameId$sort
- Dokumente nach Zeitstempel ordnen$group
- alle übereinstimmenden zu einem Array akkumulieren$addFields
-$reduce
Kills zu berechnen, zu filtern und Kills zu dokumentieren$unwind
- flaches Array, um die ursprüngliche Dokumentstruktur zu erhalten$replaceRoot
- Daten wie in Originalstruktur auf oberste Ebene verschieben
Leitung
db.games.aggregate([
{$match : {gameId : 1}},
{$sort : {timestamp : 1}},
{$group : {_id : "$gameId", data : {$push : "$$ROOT"}}},
{$addFields : {data : {
$reduce : {
input : "$data",
initialValue : {kills : [], data : [], count : 0},
in : {
count : {$sum : ["$$value.count", {$cond : [{$eq : ["$$this.type", "ENEMY_KILLED"]}, 1, 0]}]},
data : { $concatArrays : [
"$$value.data",
{$cond : [
{$ne : ["$$this.type", "ENEMY_KILLED"]},
[
{
_id : "$$this._id",
gameId : "$$this.gameId",
participantId : "$$this.participantId",
type : "$$this.type",
timestamp : "$$this.timestamp",
kills : {$sum : ["$$value.count", {$cond : [{$eq : ["$$this.type", "ENEMY_KILLED"]}, 1, 0]}]}
}
],
[]
]}
]}
}
}}
}},
{$unwind : "$data.data"},
{$replaceRoot : {newRoot : "$data.data"}}
]).pretty()
Sammlung
> db.games.find()
{ "_id" : 1, "gameId" : 1, "participantId" : 3, "type" : "ITEM_PURCHASED", "timestamp" : 656664 }
{ "_id" : 2, "gameId" : 1, "participantId" : 3, "victimId" : 9, "type" : "ENEMY_KILLED", "timestamp" : 745245 }
{ "_id" : 3, "gameId" : 1, "participantId" : 3, "victimId" : 7, "type" : "ENEMY_KILLED", "timestamp" : 746223 }
{ "_id" : 4, "gameId" : 1, "participantId" : 3, "type" : "ITEM_PURCHASED", "timestamp" : 840245 }
Ergebnis
{
"_id" : 1,
"gameId" : 1,
"participantId" : 3,
"type" : "ITEM_PURCHASED",
"timestamp" : 656664,
"kills" : 0
}
{
"_id" : 4,
"gameId" : 1,
"participantId" : 3,
"type" : "ITEM_PURCHASED",
"timestamp" : 840245,
"kills" : 2
}
>