$minN (aggregation accumulator)

Null and Missing Values

• $minN filters out null and missing values.

Consider the following aggregation that returns the minimum n documents from a group:

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:

• $documents creates the literal documents that contain player scores.

• $group groups the documents by gameId. This example has only one gameId, G1.

• PlayerD has a missing score and PlayerE has a null score. These values are both ignored.

• The minimumThreeScores field is specified as $minN with input : "$score" and returned as an array.

• Since there are only 3 documents with scores minN returns the minimum 3 score fields even though n = 4.

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

Comparison of $minN and $bottomN Accumulators

Both $minN and $bottomN accumulators can accomplish similar results.

In general:

• $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.

• If guaranteing a particular sort order is a requirement use $bottomN.

• Use $bottomN if you don't intend on sorting on the output values.

Window Function and Aggregation Expression Support

You can use $minN as an accumulator.

$minN is supported as an aggregation expression.

$minN is supported as a window operator.

Memory Limit Considerations

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.

Find the Minimum Three Scores for a Single Game

You can use the $minN accumulator to find the minimum three scores in a single game.

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

The example pipeline:

• Uses $match to filter the results on a single gameId. In this case, G1.

• Uses $group to group the results by gameId. In this case, G1.

• Specifies the fields that are input for $minN with input : ["$score","$playerId"].

• Uses $minN to return the first three score elements for the G1 game with n : 3.

The operation returns the following results:

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

Finding the Minimum Three Documents Across Multiple Games

You can use the $minN accumulator to find the minimum n scores in each game.

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

The example pipeline:

• Uses $group to group the results by gameId.

• Uses $minN to return the minimum three score elements for each game with n: 3.

• Specifies the fields that are input for $minN with input: ["$score","$playerId"].

The operation returns the following results:

[
   {
      _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

You can also assign the value of n dynamically. In this example, the $cond expression is used on the gameId field.

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:

• Uses $group to group the results by gameId.

• Specifies the fields that input for $minN with input : ["$score","$playerId"].

• If the gameId is G2 then n is 1, otherwise n is 3.

The operation returns the following results:

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