$median (accumulator operator)（蓄能器运算符）

Type of Operation操作类型

In a $group stage, $median is an accumulator and calculates a value for all documents in the window.在$group阶段，$median是一个累加器，用于计算窗口中所有文档的值。

In a $project stage, $median is an aggregation expression and calculates values for each document.在$project阶段，$median是一个聚合表达式，用于计算每个文档的值。

In $setWindowFields stages, $median returns a result for each document like an aggregation expression, but the results are computed over groups of documents like an accumulator.在$setWindowFields阶段，$median像聚合表达式一样返回每个文档的结果，但结果是像累加器一样在文档组上计算的。

Calculation Considerations计算注意事项

In $group stages, $median always uses an approximate calculation method.在$group阶段，$median总是使用近似计算方法。

In $project stages, $median might use the discrete calculation method even when the approximate method is specified.在$项目阶段，即使指定了近似方法，$median也可能使用离散计算方法。

In $setWindowFields stages, the workload determines the calculation method that $median uses.在$setWindowFields阶段，工作负载决定了$median使用的计算方法。

The computed percentiles $median returns might vary, even on the same datasets. This is because the algorithm calculates approximate values.即使在相同的数据集上，计算出的百分位数$中值回报也可能有所不同。这是因为该算法计算近似值。

Duplicate samples can cause ambiguity. If there are a large number of duplicates, the percentile values may not represent the actual sample distribution. Consider a data set where all the samples are the same. All of the values in the data set fall at or below any percentile. A "50th percentile" value would actually represent either 0 or 100 percent of the samples.重复的样本可能会导致歧义。如果存在大量重复项，百分位值可能无法代表实际的样本分布。考虑一个所有样本都相同的数据集。数据集中的所有值都处于或低于任何百分位数。“第50百分位”值实际上表示样本的0%或100%。

Array Input数组输入

If you use $median as an aggregation expression in a $project stage, you can use an array as input. $median ignores non-numeric array values.如果在$project阶段使用$median作为聚合表达式，则可以使用数组作为输入。$median忽略非数字数组值。

The syntax is:

{
   $median:
      {
         input: [ <expression1, <expression2>, ..., <expressionN> ],
         method: <string>
      }
}

Window Functions窗口函数

A window function lets you calculate results over a moving "window" of neighboring documents. As each document passes though the pipeline, the $setWindowFields stage:窗口函数允许您在相邻文档的移动“窗口”上计算结果。当每个文档通过管道时，$setWindowFields阶段：

• Recomputes the set of documents in the current window重新计算当前窗口中的文档集
• calculates a value for all documents in the set计算集合中所有文档的值
• returns a single value for that document为该文档返回一个值

You can use $median in a $setWindowFields stage to calculate rolling statistics for time series or other related data.您可以在$setWindowFields阶段使用$median来计算时间序列或其他相关数据的滚动统计。

When you use $median in a $setWindowField stage, the input value must be a field name. If you enter an array instead of a field name, the operation fails.在$setWindowField阶段使用$median时，输入值必须是字段名。如果输入数组而不是字段名，则操作失败。

Use $median as an Accumulator使用$median作为累加器

Create an accumulator that calculates the median value:创建一个计算中值的累加器：

db.testScores.aggregate( [
   {
      $group: {
         _id: null,
         test01_median: {
            $median: {
               input: "$test01",
               method: 'approximate'
            }
         }
      }
   }
] )

Output:输出：

{ _id: null, test01_median: 62 }

The _id field value is null so $group selects all the documents in the collection._id字段值为空，因此$group选择集合中的所有文档。

The $median accumulator takes its input from the test01 field. $median calculates the median value for the field, 62 in this example.$median累加器从test01字段获取输入。$median计算字段的中值，在本例中为62。

Use $median in a $project Stage在$project阶段使用$median

In a $group stage, $median is an accumulator and calculates a single value for all documents. In a $project stage, $median is an aggregation expression and calculates values for each document.在$group阶段，$median是一个累加器，为所有文档计算一个值。在$project阶段，$median是一个聚合表达式，用于计算每个文档的值。

You can use a field name or an array as input in a $project stage.您可以在$project阶段使用字段名或数组作为输入。

db.testScores.aggregate( [
   {
      $project: {
         _id: 0,
         studentId: 1,
         testMedians: {
            $median: {
               input: [ "$test01", "$test02", "$test03" ],
               method: 'approximate'
            }
         }
      }
   }
] )

Output:输出：

{ studentId: '2345', testMedians: 80 },
{ studentId: '2356', testMedians: 79 },
{ studentId: '2358', testMedians: 78 },
{ studentId: '2367', testMedians: 72 },
{ studentId: '2369', testMedians: 60 }

When $median is an aggregation expression there is a result for each studentId.当$median是一个聚合表达式时，每个studentId都有一个结果。

Use $median in a $setWindowField Stage在$setWindowField阶段中使用$median

To base your percentile values on local data trends, use $median in a $setWindowField aggregation pipeline stage.要将百分位值基于本地数据趋势，请在$setWindowField聚合管道阶段使用$mediate。

This example creates a window to filter scores:此示例创建了一个窗口来筛选分数：

db.testScores.aggregate( [
   {
      $setWindowFields: {
         sortBy: { test01: 1 },
         output: {
            test01_median: {
               $median: {
                  input: "$test01",
                  method: 'approximate'
               },
               window: {
                  range: [ -3, 3 ]
               }
            }
         }
      }
   },
   {
      $project: {
         _id: 0,
         studentId: 1,
         test01_median: 1
      }
   }
] )

Output:输出：

{ studentId: '2356', test01_median: 60 },
{ studentId: '2369', test01_median: 60 },
{ studentId: '2345', test01_median: 60 },
{ studentId: '2367', test01_median: 64 },
{ studentId: '2358', test01_median: 64 }

In this example, the median calculation for each document also incorporates data from the three documents before and after it.在这个例子中，每个文档的中值计算还包含了之前和之后三个文档的数据。