从文档中的子数组中查找最高值



假设我有以下集合:

{ _id: 1, Array: [
  { K: "A", V: 8 },
  { K: "B", V: 5 },
  { K: "C", V: 13 } ] }
{ _id: 2, Array: [
  { K: "D", V: 12 },
  { K: "E", V: 14 },
  { K: "F", V: 2 } ] }

我想运行一个查询,返回具有最高"V"的子文档,所以在这种情况下,我会得到:

{ _id: 1, Array: [ { K: "E", V: 14 } ] }

或者简单地说:

{ K: "E", V: 14 }

重要的是,我希望Mongo服务器上的内存使用率为O(1)(无论我处理多少文档,内存使用率都是恒定的),我只想检索到一个具有所需值的子文档(我不想下载超过必要数量的子文档)。

我的首选方法是使用简单的查找查询,但我不确定这是否可行。我怀疑这也可以通过聚合框架(或者map reduce?)来实现,但不知道如何实现。我不希望结果存储在临时集合中,而是直接返回给我的客户端(就像普通查询一样)。

下面的加积集返回您需要的内容。

db.letters.aggregate([
    {$project:{"Array.K":1, "Array.V":1}},
    {$unwind:"$Array"},
    {$sort:{"Array.V":-1}},
    {$limit:1}
]);

退货:

{"_id":2, "Array":{"K":"E","V":14}}

享受吧!:)

正如@JohnnyHK所说:

db.col.aggregate([
    {$unwind: '$Array'},
    {$group: {_id: '$_id', Array: {K: {$max: '$K'}, V: {$max: '$V'}}}}
])

类似的东西。

IN Simple Words,如果您有mongo查询响应类似以下内容-并且您只想要Array->"Wish_CreatedDate"中的最高值

{
  "_id": "57ee5a708e117c754915a2a2",
  "TotalWishs": 3,
  "Events": [
    "57f805c866bf62f12edb8024"
  ],
  "wish": [
    "Cosmic Eldorado  Mountain Bikes, 26-inch (Grey/White)",
    "Asics Men's Gel-Nimbus 18 Black, Snow and Fiery Red Running Shoes - 10 UK/India (45 EU) (11 US)",
    "Suunto Digital Black Dial Unisex Watch - SS018734000"
  ],
  "Wish_CreatedDate": [
    "2017-03-05T00:00:00.000Z",
    "2017-02-13T00:00:00.000Z"
  ],
  "UserDetails": [
    {
      "createdAt": "2016-09-30T12:28:32.773Z",
      "jeenesFriends": [
        "57edf8a96ad8f6ff453a384a",
        "57ee516c8e117c754915a26b",
        "58a1644b6c91d2af783770b0",
        "57ef4631b97d81824cf54795"
      ],
      "userImage": "user_profile/Male.png",
      "email": "roopak@small-screen.com",
      "fullName": "Roopak Kapoor"
    }
  ],
},

***然后你必须添加

最晚创建日期:{$max:"$Wish_CreatedDate"},

像下面这样的东西-

{ 
                $project : { _id: 1,
                             TotalWishs : 1 ,
                              wish:1 ,
                               Events:1, 
                               Wish_CreatedDate:1,
                               Latest_Wish_CreatedDate: { $max: "$Wish_CreatedDate"},
                            } 
            } 

最终查询响应将低于

{
  "_id": "57ee5a708e117c754915a2a2",
  "TotalWishs": 3,
  "Events": [
    "57f805c866bf62f12edb8024"
  ],
  "wish": [
    "Cosmic Eldorado  Mountain Bikes, 26-inch (Grey/White)",
    "Asics Men's Gel-Nimbus 18 Black, Snow and Fiery Red Running Shoes - 10 UK/India (45 EU) (11 US)",
    "Suunto Digital Black Dial Unisex Watch - SS018734000"
  ],
  "Wish_CreatedDate": [
    "2017-03-05T00:00:00.000Z",
    "2017-02-13T00:00:00.000Z"
  ],
  "UserDetails": [
    {
      "createdAt": "2016-09-30T12:28:32.773Z",
      "jeenesFriends": [
        "57edf8a96ad8f6ff453a384a",
        "57ee516c8e117c754915a26b",
        "58a1644b6c91d2af783770b0",
        "57ef4631b97d81824cf54795"
      ],
      "userImage": "user_profile/Male.png",
      "email": "roopak@small-screen.com",
      "fullName": "Roopak Kapoor"
    }
  ],
  "Latest_Wish_CreatedDate": "2017-03-05T00:00:00.000Z"
},

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