$minN (aggregation accumulator)（聚合累加器）

Result Type结果类型

$minN compares input data following the BSON Comparison order to determine the appropriate output type. When the input data contains multiple data types, the $minN output type is the lowest in the comparison order.$minN按照BSON比较顺序比较输入数据，以确定适当的输出类型。当输入数据包含多种数据类型时，$minN输出类型在比较顺序中最低。

Null and Missing Valuesnull值和缺失值

• $minN filters out null and missing values.筛选掉null值和缺失值。

Consider the following aggregation that returns the minimum n documents from a group:考虑以下聚合，它从一个组中返回最少n个文档：

db.aggregate( [
   {
      $documents: [
         { playerId: "PlayerA", gameId: "G1", score: 1 },
         { playerId: "PlayerB", gameId: "G1", score: 2 },
         { playerId: "PlayerC", gameId: "G1", score: 3 },
         { playerId: "PlayerD", gameId: "G1" },
         { playerId: "PlayerE", gameId: "G1", score: null }
      ]
   },
   {
      $group:
      {
         _id: "$gameId",
         minimumThreeScores:
            {
               $minN:
                  {
                     input: "$score",
                     n: 4
                  }
            }
      }
   }
] )

In this example:在这个例子中：

• $documents creates the literal documents that contain player scores.创建包含玩家分数的文字文档。
• $group groups the documents by gameId. This example has only one gameId, G1.按gameId对文档进行分组。这个例子只有一个gameId，即G1。
• PlayerD has a missing score and PlayerE has a null score. These values are both ignored.缺少score，而PlayerE的score为空。这两个值都被忽略了。
• The minimumThreeScores field is specified as $minN with input : "$score" and returned as an array.minimumThreeScores字段被指定为$minN配合input : "$score"，并作为数组返回。
• Since there are only 3 documents with scores minN returns the minimum 3 score fields even though n = 4.由于只有3个文档具有scores，即使n=4，minN也会返回至少3个分数字段。

[
   {
   _id: 'G1',
   minimumThreeScores: [ 1, 2, 3 ]
   }
]

Comparison of $minN and $bottomN Accumulators$minN和$bottomN累加器的比较

Both $minN and $bottomN accumulators can accomplish similar results.$minN和$bottomN累加器都可以实现类似的结果。

In general:一般来说：

• $minN has the advantage of finding minimum values in no particular sort order. If you want to know the minimum values for n documents use $minN.具有在没有特定排序顺序的情况下找到最小值的优点。如果你想知道n个文档的最小值，请使用$minN。
• If guaranteing a particular sort order is a requirement use $bottomN.如果需要保证特定的排序顺序，请使用$bottomN。
• Use $bottomN if you don't intend on sorting on the output values.如果您不打算对输出值进行排序，请使用$bottomN。

Window Function and Aggregation Expression Support窗口函数和聚合表达式支持

You can use $minN as an accumulator.您可以使用$minN作为累加器。

$minN is supported as an aggregation expression.支持$minN作为聚合表达式。

$minN is supported as a window operator.支持$minN作为窗口运算符。

Memory Limit Considerations内存限制注意事项

Aggregation pipelines which call $minN are subject to the 100 MB limit. If this limit is exceeded for an individual group, the aggregation fails with an error.调用$minN的聚合管道受100MB限制。如果单个组超过此限制，聚合将失败并出现错误。

Find the Minimum Three Scores for a Single Game找到单场比赛的最低三分

You can use the $minN accumulator to find the minimum three scores in a single game.你可以使用$minN累加器来计算一场比赛中的最低三分。

db.gamescores.aggregate( [
   {
      $match : { gameId : "G1" }
   },
   {
      $group:
         {
            _id: "$gameId",
            minScores:
               {
                  $minN:
                  {
                     input: ["$score","$playerId"],
                     n:3
                  }
               }
         }
   }
] )

The example pipeline:示例管道：

• Uses $match to filter the results on a single gameId. In this case, G1.使用$match筛选单个gameId的结果。在这种情况下，G1。
• Uses $group to group the results by gameId. In this case, G1.使用$group按gameId对结果进行分组。在这种情况下，G1。
• Specifies the fields that are input for $minN with input : ["$score","$playerId"].使用input : ["$score","$playerId"]指定$minN的输入字段。
• Uses $minN to return the first three score elements for the G1 game with n : 3.使用$minN返回n:3的G1游戏的前三个得分元素。

The operation returns the following results:该操作返回以下结果：

[
   {
      _id: 'G1',
      minScores: [ [ 1, 'PlayerD' ], [ 31, 'PlayerA' ], [ 33, 'PlayerB' ] ]
   }
]

Finding the Minimum Three Documents Across Multiple Games在多个游戏中查找至少三个文档

You can use the $minN accumulator to find the minimum n scores in each game.您可以使用$minN累加器来找到每场比赛中的最小n分。

db.gamescores.aggregate( [
   {
      $group:
      {
         _id: "$gameId",
         minScores:
            {
               $minN:
                  {
                     input: ["$score","$playerId"],
                     n: 3
                  }
            }
      }
   }
] )

The example pipeline:示例管道：

• Uses $group to group the results by gameId.使用$group按gameId对结果进行分组。
• Uses $minN to return the minimum three score elements for each game with n: 3.使用$minN配合n:3返回每个游戏的最小三个分数元素。
• Specifies the fields that are input for $minN with input: ["$score","$playerId"].使用input: ["$score","$playerId"]指定$minN的输入字段。

The operation returns the following results:该操作返回以下结果：

[
   {
      _id: 'G2',
      minScores: [ [ 10, 'PlayerA' ], [ 14, 'PlayerB' ], [ 66, 'PlayerC' ] ]
   },
   {
      _id: 'G1',
      minScores: [ [ 1, 'PlayerD' ], [ 31, 'PlayerA' ], [ 33, 'PlayerB' ] ]
   }
]

Computing n Based on the Group Key for $group基于$Group的组键计算n

You can also assign the value of n dynamically. In this example, the $cond expression is used on the gameId field.您还可以动态地分配n的值。在这个例子中，$cond表达式用于gameId字段。

db.gamescores.aggregate([
   {
      $group:
      {
         _id: {"gameId": "$gameId"},
         gamescores:
            {
               $minN:
                  {
                     input: ["$score","$playerId"],
                     n: { $cond: { if: {$eq: ["$gameId","G2"] }, then: 1, else: 3 } }
                  }
            }
      }
   }
] )

The example pipeline:示例管道：

• Uses $group to group the results by gameId.使用$group按gameId对结果进行分组。
• Specifies the fields that input for $minN with input : ["$score","$playerId"].使用input : ["$score","$playerId"]为$minN指定输入的字段。
• If the gameId is G2 then n is 1, otherwise n is 3.如果gameId为G2，则n为1，否则n为3。

The operation returns the following results:该操作返回以下结果：

[
   { _id: { gameId: 'G2' }, gamescores: [ [ 10, 'PlayerA' ] ] },
   {
      _id: { gameId: 'G1' },
      gamescores: [ [ 1, 'PlayerD' ], [ 31, 'PlayerA' ], [ 33, 'PlayerB' ] ]
   }
]