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$rank (aggregation)

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Definition定义

New in version 5.0. 5.0版新增。

$rank

Returns the document position (known as the rank) relative to other documents in the $setWindowFields stage partition.返回文档相对于$setWindowFields阶段分区中其他文档的位置（称为排名）。

The $setWindowFields stage sortBy field value determines the document rank. $setWindowFields阶段sortBy字段值决定文档的级别。For more information on how MongoDB compares fields with different types, see BSON comparison order.有关MongoDB如何比较不同类型的字段的更多信息，请参阅BSON比较顺序。

If multiple documents occupy the same rank, $rank places the document with the subsequent value at a rank with a gap (see Behavior).如果多个文档占用相同的排名，$rank会将具有后续值的文档放在有间隙的排名中（请参见行为）。

$rank is only available in the $setWindowFields stage.仅在$setWindowFields阶段中可用。

$rank syntax:语法：

{ $rank: { } }

$rank does not accept any parameters.不接受任何参数。

Tip

See also: 另请参阅：

$denseRank

Behavior行为

$rank and $denseRank differ in how they rank duplicate sortBy field values. $rank和$denseRank对重复的sortBy字段值进行排名的方式不同。For example, with sortBy field values of 7, 9, 9, and 10:例如，如果sortBy字段值为7、9、9和10：

  • $denseRank ranks the values as 1, 2, 2, and 3. 将值排列为1、2、2和3。The duplicate 9 values have a rank of 2, and 10 has a rank of 3. There is no gap in the ranks.重复的9个值的排名为2，而10的排名为3。排名没有间隙。
  • $rank ranks the values as 1, 2, 2, and 4. The duplicate 9 values have a rank of 2, and 10 has a rank of 4. 将值排列为1、2、2和4。重复的9个值的排名为2，而10的排名为4。There is a gap in the ranks for 3.排名有3位的差距。

Documents with a null value for a sortBy field or documents missing the sortBy field are assigned a rank based on the BSON comparison order.sortBy字段为null值的文档或缺少sortBy字段的文档将根据BSON比较顺序分配一个排名。

See the example in Rank Partitions Containing Duplicate Values, Nulls, or Missing Data.请参阅包含重复值、null或缺少数据的排名分区中的示例。

Examples实例

Create a cakeSales collection that contains cake sales in the states of California (CA) and Washington (WA):创建一个包含加利福尼亚州（CA）和华盛顿州（WA）蛋糕销售的cakeSales集合：

db.cakeSales.insertMany( [
   { _id: 0, type: "chocolate", orderDate: new Date("2020-05-18T14:10:30Z"),
     state: "CA", price: 13, quantity: 120 },
   { _id: 1, type: "chocolate", orderDate: new Date("2021-03-20T11:30:05Z"),
     state: "WA", price: 14, quantity: 140 },
   { _id: 2, type: "vanilla", orderDate: new Date("2021-01-11T06:31:15Z"),
     state: "CA", price: 12, quantity: 145 },
   { _id: 3, type: "vanilla", orderDate: new Date("2020-02-08T13:13:23Z"),
     state: "WA", price: 13, quantity: 104 },
   { _id: 4, type: "strawberry", orderDate: new Date("2019-05-18T16:09:01Z"),
     state: "CA", price: 41, quantity: 162 },
   { _id: 5, type: "strawberry", orderDate: new Date("2019-01-08T06:12:03Z"),
     state: "WA", price: 43, quantity: 134 }
] )

Rank Partitions by an Integer Field按整数字段对分区进行排序

This example uses $rank in the $setWindowFields stage to output the quantity rank of the cake sales for each state:本例使用$setWindowFields阶段中的$rank来输出每个州蛋糕销售的quantity排名：

db.cakeSales.aggregate( [
   {
      $setWindowFields: {
         partitionBy: "$state",
         sortBy: { quantity: -1 },
         output: {
            rankQuantityForState: {
               $rank: {}
            }
         }
      }
   }
] )

In the example:在示例中：

  • partitionBy: "$state" partitions the documents in the collection by state. 按state对集合中的文档进行分区。There are partitions for CA and WA.CA和WA有分区。
  • sortBy: { quantity: -1 } sorts the documents in each partition by quantity in descending order (-1), so the highest quantity is first.按quantity降序（-1）对每个分区中的文档进行排序，因此quantity最高的是第一个。
  • output sets the rankQuantityForState field to the quantity rank using $rank, as shown in the following results.使用$rank将rankQuantityForState字段设置为quantity排名，如以下结果所示。
{ "_id" : 4, "type" : "strawberry", "orderDate" : ISODate("2019-05-18T16:09:01Z"),
  "state" : "CA", "price" : 41, "quantity" : 162, "rankQuantityForState" : 1 }
{ "_id" : 2, "type" : "vanilla", "orderDate" : ISODate("2021-01-11T06:31:15Z"),
  "state" : "CA", "price" : 12, "quantity" : 145, "rankQuantityForState" : 2 }
{ "_id" : 0, "type" : "chocolate", "orderDate" : ISODate("2020-05-18T14:10:30Z"),
  "state" : "CA", "price" : 13, "quantity" : 120, "rankQuantityForState" : 3 }
{ "_id" : 1, "type" : "chocolate", "orderDate" : ISODate("2021-03-20T11:30:05Z"),
  "state" : "WA", "price" : 14, "quantity" : 140, "rankQuantityForState" : 1 }
{ "_id" : 5, "type" : "strawberry", "orderDate" : ISODate("2019-01-08T06:12:03Z"),
  "state" : "WA", "price" : 43, "quantity" : 134, "rankQuantityForState" : 2 }
{ "_id" : 3, "type" : "vanilla", "orderDate" : ISODate("2020-02-08T13:13:23Z"),
  "state" : "WA", "price" : 13, "quantity" : 104, "rankQuantityForState" : 3 }

Rank Partitions by a Date Field按日期字段排列分区

This example shows how to use dates with $rank in the $setWindowFields stage to output the orderDate rank of the cake sales for each state:此示例显示如何在$setWindowFields阶段中使用带有$rank的日期来输出每个state蛋糕销售的orderDate排名：

db.cakeSales.aggregate( [
   {
      $setWindowFields: {
         partitionBy: "$state",
         sortBy: { orderDate: 1 },
         output: {
            rankOrderDateForState: {
               $rank: {}
            }
         }
      }
   }
] )

In the example:在示例中：

  • partitionBy: "$state" partitions the documents in the collection by state. 按state对集合中的文档进行分区。There are partitions for CA and WA.CA和WA有分区。
  • sortBy: { orderDate: 1 } sorts the documents in each partition by orderDate in ascending order (1), so the earliest orderDate is first.按orderDate按升序（1）对每个分区中的文档进行排序，因此最早的orderDate是第一个。
  • output sets the rankOrderDateForState field to the orderDate rank using $rank, as shown in the following results.output使用$rank将rankOrderDateForState字段设置为orderDate排名，如以下结果所示。
{ "_id" : 4, "type" : "strawberry", "orderDate" : ISODate("2019-05-18T16:09:01Z"),
  "state" : "CA", "price" : 41, "quantity" : 162, "rankOrderDateForState" : 1 }
{ "_id" : 0, "type" : "chocolate", "orderDate" : ISODate("2020-05-18T14:10:30Z"),
  "state" : "CA", "price" : 13, "quantity" : 120, "rankOrderDateForState" : 2 }
{ "_id" : 2, "type" : "vanilla", "orderDate" : ISODate("2021-01-11T06:31:15Z"),
  "state" : "CA", "price" : 12, "quantity" : 145, "rankOrderDateForState" : 3 }
{ "_id" : 5, "type" : "strawberry", "orderDate" : ISODate("2019-01-08T06:12:03Z"),
  "state" : "WA", "price" : 43, "quantity" : 134, "rankOrderDateForState" : 1 }
{ "_id" : 3, "type" : "vanilla", "orderDate" : ISODate("2020-02-08T13:13:23Z"),
  "state" : "WA", "price" : 13, "quantity" : 104, "rankOrderDateForState" : 2 }
{ "_id" : 1, "type" : "chocolate", "orderDate" : ISODate("2021-03-20T11:30:05Z"),
  "state" : "WA", "price" : 14, "quantity" : 140, "rankOrderDateForState" : 3 }

Rank Partitions Containing Duplicate Values, Nulls, or Missing Data包含重复值、null或缺少数据的排名分区

Create a cakeSalesWithDuplicates collection where:创建cakeSalesWithDuplicates集合，其中：

  • Cake sales are placed in the state of California (CA) and Washington (WA).加利福尼亚州（CA）和华盛顿州（WA）的蛋糕销售。
  • Documents 6 to 8 have the same quantity and state as document 5.文档6至文档8具有与文档5相同的quantity和state。
  • Document 9 has the same quantity and state as document 4.文档9具有与文档4相同的quantity和state。
  • Document 10 has a null quantity.文档10的quantity为null。
  • Document 11 is missing the quantity.文件11缺少quantity。
db.cakeSalesWithDuplicates.insertMany( [
   { _id: 0, type: "chocolate", orderDate: new Date("2020-05-18T14:10:30Z"),
     state: "CA", price: 13, quantity: 120 },
   { _id: 1, type: "chocolate", orderDate: new Date("2021-03-20T11:30:05Z"),
     state: "WA", price: 14, quantity: 140 },
   { _id: 2, type: "vanilla", orderDate: new Date("2021-01-11T06:31:15Z"),
     state: "CA", price: 12, quantity: 145 },
   { _id: 3, type: "vanilla", orderDate: new Date("2020-02-08T13:13:23Z"),
     state: "WA", price: 13, quantity: 104 },
   { _id: 4, type: "strawberry", orderDate: new Date("2019-05-18T16:09:01Z"),
     state: "CA", price: 41, quantity: 162 },
   { _id: 5, type: "strawberry", orderDate: new Date("2019-01-08T06:12:03Z"),
     state: "WA", price: 43, quantity: 134 },
   { _id: 6, type: "strawberry", orderDate: new Date("2020-01-08T06:12:03Z"),
     state: "WA", price: 41, quantity: 134 },
   { _id: 7, type: "strawberry", orderDate: new Date("2020-01-01T06:12:03Z"),
     state: "WA", price: 34, quantity: 134 },
   { _id: 8, type: "strawberry", orderDate: new Date("2020-01-02T06:12:03Z"),
     state: "WA", price: 40, quantity: 134 },
   { _id: 9, type: "strawberry", orderDate: new Date("2020-05-11T16:09:01Z"),
     state: "CA", price: 39, quantity: 162 },
   { _id: 10, type: "strawberry", orderDate: new Date("2020-05-11T16:09:01Z"),
     state: "CA", price: 39, quantity: null },
   { _id: 11, type: "strawberry", orderDate: new Date("2020-05-11T16:09:01Z"),
     state: "CA", price: 39 }
] )

This example uses $rank in the $setWindowFields stage to output the quantity rank from the cakeSalesWithDuplicates collection for each state:本例使用$setWindowFields阶段中的$rank从$setWindowFields集合中为每个state输出quantity排名：

db.cakeSalesWithDuplicates.aggregate( [
   {
      $setWindowFields: {
         partitionBy: "$state",
         sortBy: { quantity: -1 },
         output: {
            rankQuantityForState: {
               $rank: {}
            }
         }
      }
   }
] )

In the example:在示例中：

  • partitionBy: "$state" partitions the documents in the collection by state. 按state对集合中的文档进行分区。There are partitions for CA and WA.CA和WA有分区。
  • sortBy: { quantity: -1 } sorts the documents in each partition by quantity in descending order (-1), so the highest quantity is first.按quantity降序（-1）对每个分区中的文档进行排序，因此quantity最高的是第一个。
  • output sets the rankOrderDateForState field to the quantity rank using $rank.output使用$rank将rankOrderDateForState字段设置为quantity排名。

In the following example output:在以下输出示例中：

  • Documents with the same quantity and state have the same rank. quantity和state相同的文件具有相同的级别。If documents have the same rank, there is a gap between that rank and the next rank.如果文档具有相同的级别，则该级别与下一个级别之间存在差距。
  • The document with the null quantity and then the document with the missing quantity are ranked the lowest in the output for the CA partition. quantity为null的文档和quantity缺失的文档在CA分区的输出中排名最低。This sorting is the result of the BSON comparison order, which sorts null and missing values after number values in this example.这种排序是BSON比较顺序的结果，在本例中，它将null值和缺失值排序在数值之后。
{ "_id" : 4, "type" : "strawberry", "orderDate" : ISODate("2019-05-18T16:09:01Z"),
  "state" : "CA", "price" : 41, "quantity" : 162, "rankQuantityForState" : 1 }
{ "_id" : 9, "type" : "strawberry", "orderDate" : ISODate("2020-05-11T16:09:01Z"),
  "state" : "CA", "price" : 39, "quantity" : 162, "rankQuantityForState" : 1 }
{ "_id" : 2, "type" : "vanilla", "orderDate" : ISODate("2021-01-11T06:31:15Z"),
  "state" : "CA", "price" : 12, "quantity" : 145, "rankQuantityForState" : 3 }
{ "_id" : 0, "type" : "chocolate", "orderDate" : ISODate("2020-05-18T14:10:30Z"),
  "state" : "CA", "price" : 13, "quantity" : 120, "rankQuantityForState" : 4 }
{ "_id" : 10, "type" : "strawberry", "orderDate" : ISODate("2020-05-11T16:09:01Z"),
  "state" : "CA", "price" : 39, "quantity" : null, "rankQuantityForState" : 5 }
{ "_id" : 11, "type" : "strawberry", "orderDate" : ISODate("2020-05-11T16:09:01Z"),
  "state" : "CA", "price" : 39, "rankQuantityForState" : 6 }
{ "_id" : 1, "type" : "chocolate", "orderDate" : ISODate("2021-03-20T11:30:05Z"),
  "state" : "WA", "price" : 14, "quantity" : 140, "rankQuantityForState" : 1 }
{ "_id" : 5, "type" : "strawberry", "orderDate" : ISODate("2019-01-08T06:12:03Z"),
  "state" : "WA", "price" : 43, "quantity" : 134, "rankQuantityForState" : 2 }
{ "_id" : 6, "type" : "strawberry", "orderDate" : ISODate("2020-01-08T06:12:03Z"),
  "state" : "WA", "price" : 41, "quantity" : 134, "rankQuantityForState" : 2 }
{ "_id" : 7, "type" : "strawberry", "orderDate" : ISODate("2020-01-01T06:12:03Z"),
  "state" : "WA", "price" : 34, "quantity" : 134, "rankQuantityForState" : 2 }
{ "_id" : 8, "type" : "strawberry", "orderDate" : ISODate("2020-01-02T06:12:03Z"),
  "state" : "WA", "price" : 40, "quantity" : 134, "rankQuantityForState" : 2 }
{ "_id" : 3, "type" : "vanilla", "orderDate" : ISODate("2020-02-08T13:13:23Z"),
  "state" : "WA", "price" : 13, "quantity" : 104, "rankQuantityForState" : 6 }