Sie können eine Aggregationspipeline ausführen, die verwendet $filter
Operator auf die values
Reihe. Die folgende Mongo-Shell-Abfrage demonstriert dies:
var start = new Date("2016-10-28T07:00:00.000Z"),
end = new Date("2016-11-03T07:00:00.000Z");
db.metrics.aggregate([
{
"$match": {
"name": "Hello",
"values.date": { "$gt": start, "$lt": end }
}
},
{
"$project": {
"name": 1,
"values": {
"$filter": {
"input": "$values",
"as": "value",
"cond": {
"$and": [
{ "$gt": [ "$$value.date", start ] },
{ "$lt": [ "$$value.date", end ] }
]
}
}
}
}
}
])
Beispielausgabe
/* 1 */
{
"_id" : ObjectId("5845453145fda1298fa50db9"),
"name" : "Hello",
"values" : [
{
"value" : 1568,
"date" : ISODate("2016-10-29T07:00:00.000Z"),
"_id" : ObjectId("58453abfef7aaa15ac1fdee7")
},
{
"value" : 1547,
"date" : ISODate("2016-10-30T07:00:00.000Z"),
"_id" : ObjectId("58453abfef7aaa15ac1fdee6")
},
{
"value" : 1497,
"date" : ISODate("2016-10-31T07:00:00.000Z"),
"_id" : ObjectId("58453abfef7aaa15ac1fdee5")
},
{
"value" : 3031,
"date" : ISODate("2016-11-01T07:00:00.000Z"),
"_id" : ObjectId("58453abfef7aaa15ac1fdee4")
},
{
"value" : 2559,
"date" : ISODate("2016-11-02T07:00:00.000Z"),
"_id" : ObjectId("58453abfef7aaa15ac1fdee3")
}
]
}
Für MongoDB 3.0 gilt die folgende Problemumgehung:
var start = new Date("2016-10-28T07:00:00.000Z"),
end = new Date("2016-11-03T07:00:00.000Z");
db.metrics.aggregate([
{
"$match": {
"name": "Hello",
"values.date": { "$gt": start, "$lt": end }
}
},
{
"$project": {
"name": 1,
"values": {
"$setDifference": [
{
"$map": {
"input": "$values",
"as": "value",
"in": {
"$cond": [
{
"$and": [
{ "$gt": [ "$$value.date", start ] },
{ "$lt": [ "$$value.date", end ] }
]
},
"$$value",
false
]
}
}
},
[false]
]
}
}
}
])