$group (aggregation)

Optimization to Return the First Document of Each Group优化以返回每组的第一个文档

If a pipeline sorts and groups by the same field and the $group stage only uses the $first accumulator operator, consider adding an index on the grouped field which matches the sort order. 如果管道按同一字段排序和分组，$group阶段仅使用$first累加器运算符，请考虑在分组字段上添加与排序顺序匹配的索引。In some cases, the $group stage can use the index to quickly find the first document of each group.在某些情况下，$group阶段可以使用索引快速查找每个组的第一个文档。

db.foo.aggregate([
  {
    $sort:{ x : 1, y : 1 }
  },
  {
    $group: {
      _id: { x : "$x" },
      y: { $first : "$y" }
    }
  }
])

Slot-Based Query Execution Engine基于时隙的查询执行引擎

Starting in MongoDB 5.2, MongoDB uses the slot-based execution query engine to execute $group stages when $group is either:从MongoDB 5.2开始，MongoDB使用基于时隙的执行查询引擎来执行$group阶段，当$group为：

• The first stage in the pipeline.管道中的第一阶段。
• Part of a series of stages executed by the slot-based engine that occurs at the beginning of the pipeline. 由基于时隙的引擎执行的一系列阶段的一部分，发生在管道的开始处。For example, if a pipeline begins with $match followed by $group, the $match and $group stages are executed by the slot-based engine.例如，如果管道以$match开头，后面跟着$group，则$match和$group阶段由基于插槽的引擎执行。

In most cases, the slot-based engine provides improved performance and lower CPU and memory costs compared to the classic query engine.在大多数情况下，与传统查询引擎相比，基于插槽的引擎提供了更好的性能和更低的CPU和内存成本。

See $group Optimization.请参见$group优化。

Group by Day of the Year按日分组

The following pipeline calculates the total sales amount, average sales quantity, and sale count for each day in the year 2014:以下管道计算2014年每天的总销售额、平均销售额和销售额：

db.sales.aggregate([
  // First Stage
  {
    $match : { "date": { $gte: new ISODate("2014-01-01"), $lt: new ISODate("2015-01-01") } }
  },
  // Second Stage
  {
    $group : {
       _id : { $dateToString: { format: "%Y-%m-%d", date: "$date" } },
       totalSaleAmount: { $sum: { $multiply: [ "$price", "$quantity" ] } },
       averageQuantity: { $avg: "$quantity" },
       count: { $sum: 1 }
    }
  },
  // Third Stage
  {
    $sort : { totalSaleAmount: -1 }
  }
 ])

First Stage:第一阶段：

The $match stage filters the documents to only pass documents from the year 2014 to the next stage.$match阶段筛选文档，仅将2014年的文档传递到下一阶段。

Second Stage:第二阶段：

The $group stage groups the documents by date and calculates the total sale amount, average quantity, and total count of the documents in each group.$group阶段按日期对文档进行分组，并计算每组文档的总销售额、平均数量和总计数。

Third Stage:第三阶段：

The $sort stage sorts the results by the total sale amount for each group in descending order.$sort阶段按每组的总销售额降序对结果进行排序。

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

{ "_id" : "2014-04-04", "totalSaleAmount" : NumberDecimal("200"), "averageQuantity" : 15, "count" : 2 }
{ "_id" : "2014-03-15", "totalSaleAmount" : NumberDecimal("50"), "averageQuantity" : 10, "count" : 1 }
{ "_id" : "2014-03-01", "totalSaleAmount" : NumberDecimal("40"), "averageQuantity" : 1.5, "count" : 2 }

This aggregation operation is equivalent to the following SQL statement:此聚合操作等效于以下SQL语句：

SELECT date,
       Sum(( price * quantity )) AS totalSaleAmount,
       Avg(quantity)
             AS averageQuantity,
       Count(*)
                  AS Count
FROM   sales
GROUP  BY Date(date)
ORDER  BY totalSaleAmount DESC

Group by null按null分组

The following aggregation operation specifies a group _id of null, calculating the total sale amount, average quantity, and count of all documents in the collection.以下聚合操作指定group_id为null，用于计算集合中所有文档的总销售额、平均数量和计数。

db.sales.aggregate([
  {
    $group : {
       _id : null,
       totalSaleAmount: { $sum: { $multiply: [ "$price", "$quantity" ] } },
       averageQuantity: { $avg: "$quantity" },
       count: { $sum: 1 }
    }
  }
 ])

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

{
  "_id" : null,
  "totalSaleAmount" : NumberDecimal("452.5"),
  "averageQuantity" : 7.875,
  "count" : 8
}

This aggregation operation is equivalent to the following SQL statement:此聚合操作等效于以下SQL语句：

SELECT Sum(price * quantity) AS totalSaleAmount,
       Avg(quantity)
         AS averageQuantity,
       Count(*)
              AS Count
FROM   sales

Group title by author按author分组title

The following aggregation operation pivots the data in the books collection to have titles grouped by authors.以下聚合操作将books集合中的数据透视为按作者分组的标题。

db.books.aggregate([
   { $group : { _id : "$author", books: { $push: "$title" } } }
 ])

The operation returns the following documents:操作将返回以下文档：

{ "_id" : "Homer", "books" : [ "The Odyssey", "Iliad" ] }
{ "_id" : "Dante", "books" : [ "The Banquet", "Divine Comedy", "Eclogues" ] }

Group Documents by author按author分组文档

The following aggregation operation groups documents by author:以下聚合操作按author对文档进行分组：

db.books.aggregate([
   // First Stage
   {
     $group : { _id : "$author", books: { $push: "$$ROOT" } }
   },
   // Second Stage
   {
     $addFields:
       {
         totalCopies : { $sum: "$books.copies" }
       }
   }
 ])

First Stage:第一阶段：

$group uses the $$ROOT system variable to group the entire documents by authors. 使用$$ROOT系统变量按作者对整个文档进行分组。This stage passes the following documents to the next stage:本阶段将以下文件传递给下一阶段：

{ "_id" : "Homer",
  "books" :
    [
       { "_id" : 7000, "title" : "The Odyssey", "author" : "Homer", "copies" : 10 },
       { "_id" : 7020, "title" : "Iliad", "author" : "Homer", "copies" : 10 }
    ]
 },
 { "_id" : "Dante",
   "books" :
     [
       { "_id" : 8751, "title" : "The Banquet", "author" : "Dante", "copies" : 2 },
       { "_id" : 8752, "title" : "Divine Comedy", "author" : "Dante", "copies" : 1 },
       { "_id" : 8645, "title" : "Eclogues", "author" : "Dante", "copies" : 2 }
     ]
 }

Second Stage:第二阶段：

$addFields adds a field to the output containing the total copies of books for each author.在输出中添加一个字段，该字段包含每个作者的图书总数。

Note注意

The resulting documents must not exceed the BSON Document Size limit of 16 megabytes.生成的文档不得超过16兆字节的BSON文档大小限制。

The operation returns the following documents:操作将返回以下文档：

{
  "_id" : "Homer",
  "books" :
     [
       { "_id" : 7000, "title" : "The Odyssey", "author" : "Homer", "copies" : 10 },
       { "_id" : 7020, "title" : "Iliad", "author" : "Homer", "copies" : 10 }
     ],
   "totalCopies" : 20
}
{
  "_id" : "Dante",
  "books" :
     [
       { "_id" : 8751, "title" : "The Banquet", "author" : "Dante", "copies" : 2 },
       { "_id" : 8752, "title" : "Divine Comedy", "author" : "Dante", "copies" : 1 },
       { "_id" : 8645, "title" : "Eclogues", "author" : "Dante", "copies" : 2 }
     ],
   "totalCopies" : 5
}