• Reference >
• Operators >
• Aggregation Pipeline Operators >
• $topN (aggregation accumulator)

$topN (aggregation accumulator)

Definition

$topN

New in version 5.2.

Returns an aggregation of the top n elements within a group, according to the specified sort order. If the group contains fewer than n elements, $topN returns all elements in the group.

Syntax

{
   $topN:
      {
         n: <expression>,
         sortBy: { <field1>: <sort order>, <field2>: <sort order> ... },
         output: <expression>
      }
}

• n limits the number of results per group and has to be a positive integral expression that is either a constant or depends on the _id value for $group.
• sortBy specifies the order of results, with syntax similar to $sort.
• output represents the output for each element in the group and can be any expression.

Behavior

Null and Missing Values

• $topN does not filter out null values.
• $topN converts missing values to null which are preserved in the output.

copy

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",
         playerId:
            {
               $topN:
                  {
                     output: [ "$playerId", "$score" ],
                     sortBy: { "score": 1 },
                     n: 3
                  }
            }
      }
   }
] )

In this example:

• $documents creates the literal documents that contain player scores.
• $group groups the documents by gameId. This example has only one gameId, G1.
• PlayerD has a missing score and PlayerE has a null score. These values are both considered as null.
• The playerId and score fields are specified as output : ["$playerId"," $score"] and returned as array values.
• Because of the sortBy: { "score" : 1 }, the null values are sorted to the front of the returned playerId array.

[
   {
      _id: 'G1',
      playerId: [ [ 'PlayerD', null ], [ 'PlayerE', null ], [ 'PlayerA', 1 ] ]
   }
]

BSON Data Type Sort Ordering

When sorting different types, the order of BSON data types is used to determine ordering. As an example, consider a collection whose values consist of strings and numbers.

• In an ascending sort, string values are sorted after numeric values.
• In a descending sort, string values are sorted before numeric values.

copy

db.aggregate( [
   {
      $documents: [
         { playerId: "PlayerA", gameId: "G1", score: 1 },
         { playerId: "PlayerB", gameId: "G1", score: "2" },
         { playerId: "PlayerC", gameId: "G1", score: "" }
      ]
   },
   {
      $group:
         {
            _id: "$gameId",
            playerId: {
               $topN:
               {
                  output: ["$playerId","$score"],
                  sortBy: {"score": -1},
                  n: 3
               }
            }
         }
   }
] )

In this example:

• PlayerA has an integer score.
• PlayerB has a string "2" score.
• PlayerC has an empty string score.

Because the sort is in descending { "score" : -1 }, the string literal values are sorted before PlayerA’s numeric score:

[
   {
      _id: "G1",
      playerId: [ [ "PlayerB", "2" ], [ "PlayerC", "" ], [ "PlayerA", 1 ] ]
   }
]

Restrictions

Window Function and Aggregation Expression Support

$topN is not supported as a aggregation expression.

$topN is supported as a window operator.

Memory Limit Considerations

Groups within the $topN aggregation pipeline are subject to the 100 MB limit pipeline limit. If this limit is exceeded for an individual group, the aggregation fails with an error.

Examples

Consider a gamescores collection with the following documents:

copy

db.gamescores.insertMany([
   { playerId: "PlayerA", gameId: "G1", score: 31 },
   { playerId: "PlayerB", gameId: "G1", score: 33 },
   { playerId: "PlayerC", gameId: "G1", score: 99 },
   { playerId: "PlayerD", gameId: "G1", score: 1 },
   { playerId: "PlayerA", gameId: "G2", score: 10 },
   { playerId: "PlayerB", gameId: "G2", score: 14 },
   { playerId: "PlayerC", gameId: "G2", score: 66 },
   { playerId: "PlayerD", gameId: "G2", score: 80 }
])

Find the Three Highest Scores

You can use the $topN accumulator to find the highest scoring players in a single game.

copy

db.gamescores.aggregate( [
   {
      $match : { gameId : "G1" }
   },
   {
      $group:
         {
            _id: "$gameId",
            playerId:
               {
                  $topN:
                  {
                     output: ["$playerId", "$score"],
                     sortBy: { "score": -1 },
                     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.
• Uses sort by { "score": -1 } to sort the results in descending order.
• Specifies the fields that are output from $topN with output : ["$playerId"," $score"].
• Uses $topN to return the top three documents with the highest score for the G1 game with n : 3.

The operation returns the following results:

[
   {
      _id: 'G1',
      playerId: [ [ 'PlayerC', 99 ], [ 'PlayerB', 33 ], [ 'PlayerA', 31 ] ]
   }
]

The SQL equivalent to this query is:

SELECT T3.GAMEID,T3.PLAYERID,T3.SCORE
FROM GAMESCORES AS GS
JOIN (SELECT TOP 3
         GAMEID,PLAYERID,SCORE
         FROM GAMESCORES
         WHERE GAMEID = 'G1'
         ORDER BY SCORE DESC) AS T3
            ON GS.GAMEID = T3.GAMEID
GROUP BY T3.GAMEID,T3.PLAYERID,T3.SCORE
   ORDER BY T3.SCORE DESC

Finding the Three Highest Score Documents Across Multiple Games

You can use the $topN accumulator to find the highest scoring players in each game.

copy

db.gamescores.aggregate( [
      {
         $group:
         { _id: "$gameId", playerId:
            {
               $topN:
                  {
                     output: [ "$playerId","$score" ],
                     sortBy: { "score": -1 },
                     n: 3
                  }
            }
         }
      }
] )

The example pipeline:

• Uses $group to group the results by gameId.
• Specifies the fields that are output from $topN with output : ["$playerId", "$score"].
• Uses sort by { "score": -1 } to sort the results in descending order.
• Uses $topN to return the top three documents with the highest score for each game with n: 3.

The operation returns the following results:

[
   {
      _id: 'G1',
      playerId: [ [ 'PlayerC', 99 ], [ 'PlayerB', 33 ], [ 'PlayerA', 31 ] ]
   },
   {
      _id: 'G2',
      playerId: [ [ 'PlayerD', 80 ], [ 'PlayerC', 66 ], [ 'PlayerB', 14 ] ]
   }
]

The SQL equivalent to this query is:

SELECT PLAYERID,GAMEID,SCORE
FROM(
   SELECT ROW_NUMBER() OVER (PARTITION BY GAMEID ORDER BY SCORE DESC) AS GAMERANK,
   GAMEID,PLAYERID,SCORE
   FROM GAMESCORES
) AS T
WHERE GAMERANK <= 3
ORDER BY GAMEID

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.

copy

db.gamescores.aggregate([
   {
      $group:
      {
         _id: {"gameId": "$gameId"},
         gamescores:
            {
               $topN:
                  {
                     output: "$score",
                     n: { $cond: { if: {$eq: ["$gameId","G2"] }, then: 1, else: 3 } },
                     sortBy: { "score": -1 }
                  }
            }
      }
   }
] )

The example pipeline:

• Uses $group to group the results by gameId.
• Specifies the fields that are output from $topN with output : "$score".
• If the gameId is G2 then n is 1, otherwise n is 3.
• Uses sort by { "score": -1 } to sort the results in descending order.

The operation returns the following results:

[
   { _id: { gameId: 'G1' }, gamescores: [ 99, 33, 31 ] },
   { _id: { gameId: 'G2' }, gamescores: [ 80 ] }
]

←   $top (aggregation accumulator) $toString (aggregation)  →

© MongoDB, Inc 2008-present. MongoDB, Mongo, and the leaf logo are registered trademarks of MongoDB, Inc.