Aggregation Pipeline聚合管道

Calculate Total Order Quantity计算总订单数量

The following aggregation pipeline example contains two stages and returns the total order quantity of medium size pizzas grouped by pizza name:以下聚合管道示例包含两个阶段，并返回按披萨名称分组的中等大小披萨的总订单数量：

db.orders.aggregate( [

   // Stage 1: Filter pizza order documents by pizza size第1阶段：按披萨大小筛选披萨订单文档
   {
      $match: { size: "medium" }
   },

   // Stage 2: Group remaining documents by pizza name and calculate total quantity第2阶段：按披萨名称对剩余文档进行分组，并计算总数量
   {
      $group: { _id: "$name", totalQuantity: { $sum: "$quantity" } }
   }

] )

The $match stage:$match阶段：

• Filters the pizza order documents to pizzas with a size of medium.将披萨订单文档筛选size: medium的披萨。
• Passes the remaining documents to the $group stage.将剩余的文档传递到$group阶段。

The $group stage:$group阶段：

• Groups the remaining documents by pizza name.按披萨饼name对剩余文档进行分组。
• Uses $sum to calculate the total order quantity for each pizza name. 使用$sum计算每个披萨饼name的总订单quantity。The total is stored in the totalQuantity field returned by the aggregation pipeline.合计存储在聚合管道返回的totalQuantity字段中。

Example output:输出示例：

[
   { _id: 'Cheese', totalQuantity: 50 },
   { _id: 'Vegan', totalQuantity: 10 },
   { _id: 'Pepperoni', totalQuantity: 20 }
]

Calculate Total Order Value and Average Order Quantity计算订单总值和平均订单数量

The following example calculates the total pizza order value and average order quantity between two dates:以下示例计算两个日期之间的披萨订单总值和平均订单数量：

db.orders.aggregate( [

   // Stage 1: Filter pizza order documents by date range第1阶段：按日期范围筛选披萨订单文档
   {
      $match:
      {
         "date": { $gte: new ISODate( "2020-01-30" ), $lt: new ISODate( "2022-01-30" ) }
      }
   },

   // Stage 2: Group remaining documents by date and calculate results第2阶段：按日期对剩余文档进行分组并计算结果
   {
      $group:
      {
         _id: { $dateToString: { format: "%Y-%m-%d", date: "$date" } },
         totalOrderValue: { $sum: { $multiply: [ "$price", "$quantity" ] } },
         averageOrderQuantity: { $avg: "$quantity" }
      }
   },

   // Stage 3: Sort documents by totalOrderValue in descending order第3阶段：按totalOrderValue降序对文档进行排序
   {
      $sort: { totalOrderValue: -1 }
   }

 ] )

The $match stage:$match阶段：

• Filters the pizza order documents to those in a date range specified using $gte and $lt.将披萨订单文档筛选为使用$gte和$lt指定的日期范围内的文档。
• Passes the remaining documents to the $group stage.将剩余的文档传递到$group阶段。

The $group stage:$group阶段：

• Groups the documents by date using $dateToString.使用$dateToString按日期对文档进行分组。
• For each group, calculates:对于每组，计算：
  • Total order value using $sum and $multiply.使用$sum和$multiply的订单总值。
  • Average order quantity using $avg.使用$avg的平均订单数量。
• Passes the grouped documents to the $sort stage.将分组的文档传递到$sort阶段。

The $sort stage:$sort阶段：

• Sorts the documents by the total order value for each group in descending order (-1).按每组的总顺序值按降序（-1）对文档进行排序。
• Returns the sorted documents.返回已排序的文档。

Example output:输出示例：

[
   { _id: '2022-01-12', totalOrderValue: 790, averageOrderQuantity: 30 },
   { _id: '2021-03-13', totalOrderValue: 770, averageOrderQuantity: 15 },
   { _id: '2021-03-17', totalOrderValue: 630, averageOrderQuantity: 30 },
   { _id: '2021-01-13', totalOrderValue: 350, averageOrderQuantity: 10 }
]

Aggregation Pipeline Limitations聚合管道限制

An aggregation pipeline has limitations on the value types and the result size. 聚合管道对值类型和结果大小有限制。See Aggregation Pipeline Limits.请参阅聚合管道限制。

Aggregation Pipelines and Sharded Collections聚合管道和分片集合

An aggregation pipeline supports operations on sharded collections. 聚合管道支持对分片集合的操作。See Aggregation Pipeline and Sharded Collections.请参阅聚合管道和分片集合。

Aggregation Pipelines as an Alternative to Map-Reduce聚合管道作为Map Reduce的替代方案

Starting in MongoDB 5.0, map-reduce is deprecated:从MongoDB 5.0开始，不赞成使用map-reduce：

• Instead of map-reduce, you should use an aggregation pipeline. 您应该使用聚合管道，而不是map-reduce。Aggregation pipelines provide better performance and usability than map-reduce.聚合管道提供了比映射减少更好的性能和可用性。
• You can rewrite map-reduce operations using aggregation pipeline stages, such as $group, $merge, and others.您可以使用聚合管道阶段（如$group、$merge和其他阶段）重写map-reduce操作。
• For map-reduce operations that require custom functionality, you can use the $accumulator and $function aggregation operators, available starting in version 4.4. 对于需要自定义功能的map-reduce操作，可以使用$accumulator和$function聚合运算符，这些运算符从4.4版开始提供。You can use those operators to define custom aggregation expressions in JavaScript.您可以使用这些运算符在JavaScript中定义自定义聚合表达式。

For examples of aggregation pipeline alternatives to map-reduce, see:有关映射减少的聚合管道替代方案的示例，请参阅：

• Map-Reduce to Aggregation Pipeline到聚合管道
• Map-Reduce Examples示例