Database Manual / Reference / Query Language / Aggregation Stages

$score (aggregation)（聚合）

New in version 8.2.在版本8.2中新增。

Definition定义

$score
$score computes and returns a new score as metadata. It also optionally normalizes the input scores, by default to a range between zero and one.计算并返回新的分数作为元数据。它还可以选择将输入分数标准化，默认情况下为0到1之间的范围。

Syntax语法

The stage has the following syntax:该阶段具有以下语法：

{
  $score: {
    score: <expression>,
    normalization: "none|sigmoid|minMaxScaler",
    weight: <expression>
  }
}

Fields字段

$score takes the following fields:采用以下字段：

Field字段Type类型Description描述
scoreExpression表达式Computes a new value from the input scores and stores the value in the $meta keyword searchScore. 根据输入分数计算一个新值，并将该值存储在$meta键searchScore中。All other scores are stored in the $meta keyword searchScoreDetails. Returns an error for non-numeric inputs.所有其他分数都存储在$meta键searchScoreDetails中。对于非数字输入返回错误。
normalizationString字符串

Optional. 可选。Normalizes the score to the range of 0 to 1. Value can be:将分数标准化为0到1的范围。值可以是：

  • none - Doesn't normalize.不正常。

  • sigmoid - Applies the following $sigmoid expression:应用以下$sigmoid表达式：

    1 / (1 + e^-x)

    Here, x is the score to normalize.这里，x是要归一化的分数。

    If omitted, defaults to none.如果省略，则默认为none。

  • minMaxScaler - to apply the $minMaxScaler window function:要应用$minMaxScaler窗口函数：

     (s - min_s) / (max_s - min_s)

    Where:其中：

    • s is the score.是分数。
    • min_s is the minimum score.是最低分数。
    • max_s is the maximum score.是最高分数。
weightDouble双精度浮点数Optional. 可选。Number to multiply the score expression by after normalization.归一化后将score表达式乘以的数字。

Behavior行为

The output documents from a $score are the same as the input documents, but includes additional computed score as metadata.$score的输出文档与输入文档相同，但包含额外的计算得分作为元数据。

If you specify multiple $score stages in the pipeline, the last $score stage in the pipeline overrides the score metadata from previous $score stages.如果在管道中指定了多个$score阶段，管道中的最后一个$score步骤将覆盖之前$score阶段的分数元数据。

Example示例

Consider the following documents in a collection named articles:考虑名为articles的集合中的以下文档：

{ "_id" : ObjectId("512bc95fe835e68f199c8686"), "author" : "dave", "score" : 80, "views" : 100 },
{ "_id" : ObjectId("512bc962e835e68f199c8687"), "author" : "dave", "score" : 85, "views" : 521 }
{ "_id" : ObjectId("55f5a192d4bede9ac365b257"), "author" : "ahn", "score" : 60, "views" : 1000 }
{ "_id" : ObjectId("55f5a192d4bede9ac365b258"), "author" : "li", "score" : 55, "views" : 5000 }
{ "_id" : ObjectId("55f5a1d3d4bede9ac365b259"), "author" : "annT", "score" : 60, "views" : 50 }
{ "_id" : ObjectId("55f5a1d3d4bede9ac365b25a"), "author" : "li", "score" : 94, "views" : 999 }
{ "_id" : ObjectId("55f5a1d3d4bede9ac365b25b"), "author" : "ty", "score" : 95, "views" : 1000 }

The following query uses the:以下查询使用：

  • $match stage to filter the documents where the views field value is greater than or equal to 1000.阶段用于筛选views字段值大于或等于1000的文档。
  • $score stage to compute a new score that is normalized using $sigmoid expression and then multiplied by the specified weight, 1.计算一个新的分数，该分数使用$sigmoid表达式进行归一化，然后乘以指定的权重1。
db.articles.aggregate([
   {
      $match: {
         views: { $gte: 1000 }
      }
   },
   {
      $score: {
         score: "$score",
         normalization: "sigmoid",
         weight: 1
      }
   },
   {
      "$project": {
         "_id": 0,
         "author": 1,
         "views": 1,
         "score": 1,
         "calculatedScore": { $meta: "score" }
      }
   }
])
[
   { author: 'ahn', score: 60, views: 1000, calculatedScore: 1 },
   { author: 'li', score: 55, views: 5000, calculatedScore: 1 },
   { author: 'ty', score: 95, views: 1000, calculatedScore: 1 }
]