mongoose aggregation $ avg $またはnull値を返します

Question

日付間の平均値を計算したいと思います。 これは、それは私がこのaggegration

を実行する最初のものはNULL値を持っていますが、それはそれを証明するために

{ "_id" : ObjectId("5761df5981fb3799edbeda88"), "avgTemperature" : null } 
{ "_id" : ObjectId("5761d3c681fb3799edbeda83"), "avgTemperature" : 16.323529411764707 } 

ヌル平均を持っているinpossibleだこれを返す集約

db.measurements.aggregate([{ 
    $match: { 
    $or: [{ 
     date: { 
     '$gte': ISODate('2016-06-01T22:52:46Z'), 
     '$lte': ISODate('2016-06-02T22:52:46Z') 
     } 
    }] 
    } 
}, { 
    $group: { 
    _id: "$workplace", 
    avgTemperature: { 
     $avg: "$temperature" 
    } 
    } 
}]); 

のコードです

db.measurements.aggregate([{ 
    $match: { 
    workplace: { 
     $in: [ObjectId("5761df5981fb3799edbeda88")] 
     }, 
    $or: [{ 
     date: { 
     '$gte': ISODate('2016-06-01T22:52:46Z'), 
     '$lte': ISODate('2016-06-02T22:52:46Z') 
     } 
    }] 
    } 
}]); 

応答データ

{ "_id" : ObjectId("576f1a7ab1a9cb96dbf74773"), "date" : ISODate("2016-06-02T11:28:56Z"), "temperature" : "11.6", "noise" : "19.0", "workplace" : ObjectId("5761df5981fb3799edbeda88") } 
{ "_id" : ObjectId("576f1a7ab1a9cb96dbf74785"), "date" : ISODate("2016-06-02T03:49:59Z"), "temperature" : "12.2", "noise" : "17.7", "workplace" : ObjectId("5761df5981fb3799edbeda88") } 
{ "_id" : ObjectId("576f1a7ab1a9cb96dbf74795"), "date" : ISODate("2016-06-02T01:39:06Z"), "temperature" : "12.6", "noise" : "55.6", "workplace" : ObjectId("5761df5981fb3799edbeda88") } 
{ "_id" : ObjectId("576f1a7ab1a9cb96dbf74797"), "date" : ISODate("2016-06-02T04:07:47Z"), "temperature" : "11.8", "noise" : "21.5", "workplace" : ObjectId("5761df5981fb3799edbeda88") } 
{ "_id" : ObjectId("576f1a7ab1a9cb96dbf747d8"), "date" : ISODate("2016-06-02T10:30:24Z"), "temperature" : "6.4", "noise" : "47.6", "workplace" : ObjectId("5761df5981fb3799edbeda88") } 
{ "_id" : ObjectId("576f1a7ab1a9cb96dbf7480b"), "date" : ISODate("2016-06-02T02:12:27Z"), "temperature" : "12.2", "noise" : "39.3", "workplace" : ObjectId("5761df5981fb3799edbeda88") } 
{ "_id" : ObjectId("576f1a7ab1a9cb96dbf74811"), "date" : ISODate("2016-06-02T10:01:12Z"), "temperature" : "23.8", "noise" : "29.3", "workplace" : ObjectId("5761df5981fb3799edbeda88") } 
{ "_id" : ObjectId("576f1a7ab1a9cb96dbf74816"), "date" : ISODate("2016-06-02T22:42:44Z"), "temperature" : "3.8", "noise" : "5.7", "workplace" : ObjectId("5761df5981fb3799edbeda88") } 
{ "_id" : ObjectId("576f1a7ab1a9cb96dbf74889"), "date" : ISODate("2016-06-02T17:16:12Z"), "temperature" : "4.3", "noise" : "67.4", "workplace" : ObjectId("5761df5981fb3799edbeda88") } 
{ "_id" : ObjectId("576f1a7ab1a9cb96dbf7488c"), "date" : ISODate("2016-06-02T01:59:37Z"), "temperature" : "24.4", "noise" : "55.2", "workplace" : ObjectId("5761df5981fb3799edbeda88") } 
{ "_id" : ObjectId("576f1a7ab1a9cb96dbf74899"), "date" : ISODate("2016-06-02T22:31:13Z"), "temperature" : "9.5", "noise" : "66.4", "workplace" : ObjectId("5761df5981fb3799edbeda88") } 
{ "_id" : ObjectId("576f1a7ab1a9cb96dbf748a9"), "date" : ISODate("2016-06-02T15:44:03Z"), "temperature" : "24.8", "noise" : "54.5", "workplace" : ObjectId("5761df5981fb3799edbeda88") } 
{ "_id" : ObjectId("576f1a7ab1a9cb96dbf748af"), "date" : ISODate("2016-06-02T16:46:51Z"), "temperature" : "2.7", "noise" : "14.8", "workplace" : ObjectId("5761df5981fb3799edbeda88") } 
{ "_id" : ObjectId("576f1a7ab1a9cb96dbf748d6"), "date" : ISODate("2016-06-02T19:37:01Z"), "temperature" : "13.0", "noise" : "22.2", "workplace" : ObjectId("5761df5981fb3799edbeda88") } 
{ "_id" : ObjectId("576f1a7ab1a9cb96dbf748f2"), "date" : ISODate("2016-06-02T07:30:30Z"), "temperature" : "5.7", "noise" : "16.9", "workplace" : ObjectId("5761df5981fb3799edbeda88") } 
{ "_id" : ObjectId("576f1a7ab1a9cb96dbf74912"), "date" : ISODate("2016-06-02T17:28:55Z"), "temperature" : "10.9", "noise" : "13.0", "workplace" : ObjectId("5761df5981fb3799edbeda88") } 
{ "_id" : ObjectId("576f1a7ab1a9cb96dbf74940"), "date" : ISODate("2016-06-02T12:07:37Z"), "temperature" : "18.4", "noise" : "64.4", "workplace" : ObjectId("5761df5981fb3799edbeda88") } 
{ "_id" : ObjectId("576f1a7ab1a9cb96dbf74946"), "date" : ISODate("2016-06-02T19:14:08Z"), "temperature" : "12.4", "noise" : "69.5", "workplace" : ObjectId("5761df5981fb3799edbeda88") } 
{ "_id" : ObjectId("576f1a7ab1a9cb96dbf74950"), "date" : ISODate("2016-06-02T22:19:55Z"), "temperature" : "16.3", "noise" : "22.4", "workplace" : ObjectId("5761df5981fb3799edbeda88") } 
{ "_id" : ObjectId("576f1a7ab1a9cb96dbf7495d"), "date" : ISODate("2016-06-02T06:23:00Z"), "temperature" : "16.2", "noise" : "51.8", "workplace" : ObjectId("5761df5981fb3799edbeda88") } 
Type "it" for more 

問題なく平均を計算するにはどうすれば修正できますか？または、コードは問題ありません。問題はコード関連ではありませんか？

Answer 1

私が知っている限り、aggregateは既存のデータ型を変更できません。$avgは数値（int、long、float、double、numberなど）で動作します。現在、MongoDBには、文字列を数値に解析する演算子がありません。

だから、temperatureフィールドのNumberにスキーマStringを変換し、数値に文字列をデータベースtemperature値を変換するために、その後、あなたのコードは完璧な結果を返すスクリプトを記述する必要があります。あなたの質問は完璧です。