$setWindowFields (aggregation)
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Definition定义
$setWindowFields
New in version 5.0. 5.0版新增。
Performs operations on a specified span of documents in a collection, known as a window, and returns the results based on the chosen window operator.对集合(称为窗口)中指定的文档范围执行操作,并根据所选窗口运算符返回结果。
For example, you can use the 例如,您可以使用$setWindowFields stage to output the:$setWindowFields阶段来输出:
Difference in sales between two documents in a collection.集合中两个文档之间的销售额差异。Sales rankings.销售排名。Cumulative sales totals.累计销售总额。Analysis of complex time series information without exporting the data to an external database.在不将数据导出到外部数据库的情况下分析复杂的时间序列信息。
Syntax语法
The $setWindowFields stage syntax:$setWindowFields阶段语法:
{
$setWindowFields: {
partitionBy: <expression>,
sortBy: {
<sort field 1>: <sort order>,
<sort field 2>: <sort order>,
...,
<sort field n>: <sort order>
},
output: {
<output field 1>: {
<window operator>: <window operator parameters>,
window: {
documents: [ <lower boundary>, <upper boundary> ],
range: [ <lower boundary>, <upper boundary> ],
unit: <time unit>
}
},
<output field 2>: { ... },
...
<output field n>: { ... }
}
}
}
The $setWindowFields stage takes a document with these fields:$setWindowFields阶段接受一个包含以下字段的文档:
partitionBy | $setWindowFields stage, the group of documents is known as a partition. Default is one partition for the entire collection. $setWindowFields阶段,文档组称为分区。默认值是整个集合的一个分区。 | |
sortBy | $sort stage. $sort阶段相同的语法。 | |
output | $setWindowFields stage. $setWindowFields阶段返回的输出中的文档的字段。$setWindowFields stage are the same as the $addFields and $set stages. $setWindowFields阶段中嵌入文档点符号的语义与$addFields和$set阶段相同。$addFields示例和嵌入式文档$set示例。
| |
window | documents窗口或range窗口。 | |
documents |
| |
range | sortBy字段的一系列值来定义下边界和上边界。
| |
unit | range窗口边界的单位。
range窗口边界。 |
See also: 另请参阅:
Behavior行为
The $setWindowFields stage appends new fields to existing documents. You can include one or more $setWindowFields stages in an aggregation operation.$setWindowFields阶段将新字段附加到现有文档中。您可以在聚合操作中包括一个或多个$setWindowFields阶段。
Starting in MongoDB 5.3, you can use the 从MongoDB 5.3开始,您可以将$setWindowFields stage with transactions and the "snapshot" read concern.$setWindowFields阶段用于事务和"snapshot"读取关注。
Window Operators窗口运算符
These operators can be used with the 这些运算符可以与$setWindowFields stage:$setWindowFields阶段一起使用:
Accumulator operators:累计运算符:$addToSet,$avg,$bottom,$bottomN,$count,$covariancePop,$covarianceSamp,$derivative,$expMovingAvg,$firstN,$integral,$lastN,$max,$maxN,$median,$min,$minN,$percentile,$push,$stdDevSamp,$stdDevPop,$sum,$top,$topN.$addToSet、$avg、$bottom、$bottomN、$count、$covariancePop、$covarianceSamp、$derivative、$expMovingAvg、$firstN,$integral、$lastN、$max、$maxN、$median、$min、$minN、$percentile、$push、$stdDevSamp、$stdDevPop、$sum、$top、$topN。
Gap filling operators:缺口填充运算符:$linearFilland$locf.$linearFill和$locf。
Rank operators:排名运算符:$denseRank,$documentNumber, and$rank.$denseRank、$documentNumber和$rank。
Restrictions限制
Restrictions for the $setWindowFields stage:$setWindowFields阶段的限制:
Prior to MongoDB 5.3, the在MongoDB 5.3之前,不能使用$setWindowFieldsstage cannot be used:$setWindowFields阶段:Within transactions.在事务中。With使用"snapshot"read concern."snapshot"读取关注。
sortBy is required for:sortBy用于:Range windows require all sortBy values to be numbers.range窗口要求所有sortBy值都是数字。Time range windows require all sortBy values to be dates.时间范围窗口要求所有sortBy值都是日期。Range and time range windows can only contain one sortBy field and the sort must be ascending.range和时间范围窗口只能包含一个sortBy字段,并且排序必须是升序。You cannot specify both a documents window and a range window.不能同时指定documents窗口和range窗口。These operators use an implicit window and return an error if you specify a window option:如果指定window选项,这些运算符将使用隐式窗口并返回错误:For range windows, only numbers in the specified range are included in the window. Missing, undefined, and对于nullvalues are excluded.range窗口,窗口中只包含指定范围内的数字。将排除缺失值、未定义值和null值。For time range windows:对于时间范围窗口:Only date and time types are included in the window.窗口中只包括日期和时间类型。Numeric boundary values must be integers. For example, you can use 2 hours as a boundary but you cannot use 1.5 hours.数值边界值必须是整数。例如,可以使用2小时作为边界,但不能使用1.5小时。
For empty windows or windows with incompatible values (for example, using对于空窗口或具有不兼容值的窗口(例如,在字符串上使用$sumon strings), the returned value depends on the operator:$sum),返回的值取决于运算符:
Examples实例
Create a 创建一个包含加利福尼亚州(cakeSales collection that contains cake sales in the states of California (CA) and Washington (WA):CA)和华盛顿州(WA)蛋糕销售的cakeSales系列:
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 }
] )
The following examples use the 以下示例使用cakeSales collection.cakeSales集合。
Documents Window Examples文档窗口示例
Use Documents Window to Obtain Cumulative Quantity for Each State使用文档窗口获取每个状态的累计数量
This example uses a documents window in 本例使用$setWindowFields to output the cumulative cake sales quantity for each state:$setWindowFields中的documents窗口来输出每个state的累计蛋糕销售quantity:
db.cakeSales.aggregate( [
{
$setWindowFields: {
partitionBy: "$state",
sortBy: { orderDate: 1 },
output: {
cumulativeQuantityForState: {
$sum: "$quantity",
window: {
documents: [ "unbounded", "current" ]
}
}
}
}
}
] )
In the example:在示例中:
partitionBy: "$state"partitions the documents in the collection by按状态对集合中的文档进行分区。state.There are partitions forCAandWA.CA和WA有分区。sortBy: { orderDate: 1 }sorts the documents in each partition by按orderDatein ascending order (1), so the earliestorderDateis first.orderDate按升序(1)对每个分区中的文档进行排序,因此最早的orderDate是第一个。
output:输出:Sets the将cumulativeQuantityForStatefield to the cumulativequantityfor eachstate, which increases by successive additions to the previous value in the partition.cumulativeQuantityForState字段设置为每个state的累计quantity,该数量通过连续添加分区中的上一个值而增加。Calculates the cumulative使用在quantityusing the$sumoperator run in a documents window.documents窗口中运行的$sum运算符计算累计quantity。The window contains documents between an该unboundedlower limit and thecurrentdocument.window包含介于unbounded下限和current文档之间的文档。This means这意味着$sumreturns the cumulativequantityfor the documents between the beginning of the partition and the current document.$sum返回分区开始和当前文档之间文档的累计quantity。
In this example output, the cumulative 在此示例输出中,quantity for CA and WA is shown in the cumulativeQuantityForState field:CA和WA的累计quantity显示在cumulativeQuantityForState字段中:
{ "_id" : 4, "type" : "strawberry", "orderDate" : ISODate("2019-05-18T16:09:01Z"),
"state" : "CA", "price" : 41, "quantity" : 162, "cumulativeQuantityForState" : 162 }
{ "_id" : 0, "type" : "chocolate", "orderDate" : ISODate("2020-05-18T14:10:30Z"),
"state" : "CA", "price" : 13, "quantity" : 120, "cumulativeQuantityForState" : 282 }
{ "_id" : 2, "type" : "vanilla", "orderDate" : ISODate("2021-01-11T06:31:15Z"),
"state" : "CA", "price" : 12, "quantity" : 145, "cumulativeQuantityForState" : 427 }
{ "_id" : 5, "type" : "strawberry", "orderDate" : ISODate("2019-01-08T06:12:03Z"),
"state" : "WA", "price" : 43, "quantity" : 134, "cumulativeQuantityForState" : 134 }
{ "_id" : 3, "type" : "vanilla", "orderDate" : ISODate("2020-02-08T13:13:23Z"),
"state" : "WA", "price" : 13, "quantity" : 104, "cumulativeQuantityForState" : 238 }
{ "_id" : 1, "type" : "chocolate", "orderDate" : ISODate("2021-03-20T11:30:05Z"),
"state" : "WA", "price" : 14, "quantity" : 140, "cumulativeQuantityForState" : 378 }
Use Documents Window to Obtain Cumulative Quantity for Each Year使用文档窗口获取每年的累计数量
This example uses a documents window in 本例使用$setWindowFields to output the cumulative cake sales quantity for each $year in orderDate:$setWindowFields中的documents窗口输出orderDate中每$year的累计蛋糕销售quantity:
db.cakeSales.aggregate( [
{
$setWindowFields: {
partitionBy: { $year: "$orderDate" },
sortBy: { orderDate: 1 },
output: {
cumulativeQuantityForYear: {
$sum: "$quantity",
window: {
documents: [ "unbounded", "current" ]
}
}
}
}
}
] )
In the example:在示例中:
partitionBy: { $year: "$orderDate" }partitions the documents in the collection by按$yearinorderDate. There are are partitions for2019,2020, and2021.orderDate中的$year对集合中的文档进行分区。有2019年、2020年和2021年的分区。sortBy: { orderDate: 1 }sorts the documents in each partition by按orderDatein ascending order (1), so the earliestorderDateis first.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:输出:Sets the将cumulativeQuantityForYearfield to the cumulativequantityfor each year, which increases by successive additions to the previous value in the partition.cumulativeQuantityForYear字段设置为每年的累计数量,该数量通过连续添加分区中的上一个值而增加。Calculates the cumulative使用在quantityusing the$sumoperator run in a documents window.documents窗口中运行的$sum运算符计算累计quantity。The window contains documents between an该窗口包含介于unboundedlower limit and thecurrentdocument.unbounded下限和current文档之间的文档。This means这意味着$sumreturns the cumulativequantityfor the documents between the beginning of the partition and the current document.$sum返回分区开始和当前文档之间文档的累计quantity。
In this example output, the cumulative 在此示例输出中,每年的累计quantity for each year is shown in the cumulativeQuantityForYear field:quantity显示在cumulativeQuantityForYear字段中:
{ "_id" : 5, "type" : "strawberry", "orderDate" : ISODate("2019-01-08T06:12:03Z"),
"state" : "WA", "price" : 43, "quantity" : 134, "cumulativeQuantityForYear" : 134 }
{ "_id" : 4, "type" : "strawberry", "orderDate" : ISODate("2019-05-18T16:09:01Z"),
"state" : "CA", "price" : 41, "quantity" : 162, "cumulativeQuantityForYear" : 296 }
{ "_id" : 3, "type" : "vanilla", "orderDate" : ISODate("2020-02-08T13:13:23Z"),
"state" : "WA", "price" : 13, "quantity" : 104, "cumulativeQuantityForYear" : 104 }
{ "_id" : 0, "type" : "chocolate", "orderDate" : ISODate("2020-05-18T14:10:30Z"),
"state" : "CA", "price" : 13, "quantity" : 120, "cumulativeQuantityForYear" : 224 }
{ "_id" : 2, "type" : "vanilla", "orderDate" : ISODate("2021-01-11T06:31:15Z"),
"state" : "CA", "price" : 12, "quantity" : 145, "cumulativeQuantityForYear" : 145 }
{ "_id" : 1, "type" : "chocolate", "orderDate" : ISODate("2021-03-20T11:30:05Z"),
"state" : "WA", "price" : 14, "quantity" : 140, "cumulativeQuantityForYear" : 285 }
Use Documents Window to Obtain Moving Average Quantity for Each Year使用文档窗口获取每年的移动平均数量
This example uses a documents window in 本例使用$setWindowFields to output the moving average for the cake sales quantity:$setWindowFields中的documents窗口来输出蛋糕销售quantity的移动平均值:
db.cakeSales.aggregate( [
{
$setWindowFields: {
partitionBy: { $year: "$orderDate" },
sortBy: { orderDate: 1 },
output: {
averageQuantity: {
$avg: "$quantity",
window: {
documents: [ -1, 0 ]
}
}
}
}
}
] )
In the example:在示例中:
partitionBy: "$orderDate"partitions the documents in the collection by按$yearinorderDate. There are are partitions for2019,2020, and2021.orderDate中的$year对集合中的文档进行分区。有2019年、2020年和2021年的分区。sortBy: { orderDate: 1 }sorts the documents in each partition by按orderDatein ascending order (1), so the earliestorderDateis first.orderDate按升序(1)对每个分区中的文档进行排序,因此最早的orderDate是第一个。output:输出:Sets the将averageQuantityfield to the moving averagequantityfor each year.averageQuantity字段设置为每年的移动平均quantity。Calculates the moving average使用在quantityusing the$avgoperator run in a documents window.documents窗口中运行的$avg运算符计算移动平均quantity。The window contains documents between该-1and0. This means$avgreturns the moving averagequantitybetween the document before the current document (-1) and the current document (0) in the partition.window包含介于-1和0之间的文档。这意味着$avg返回分区中当前文档(-1)之前的文档和当前文档(0)之间的移动平均数量。
In this example output, the moving average 在本示例输出中,移动平均quantity is shown in the averageQuantity field:quantity显示在averageQuantity字段中:
{ "_id" : 5, "type" : "strawberry", "orderDate" : ISODate("2019-01-08T06:12:03Z"),
"state" : "WA", "price" : 43, "quantity" : 134, "averageQuantity" : 134 }
{ "_id" : 4, "type" : "strawberry", "orderDate" : ISODate("2019-05-18T16:09:01Z"),
"state" : "CA", "price" : 41, "quantity" : 162, "averageQuantity" : 148 }
{ "_id" : 3, "type" : "vanilla", "orderDate" : ISODate("2020-02-08T13:13:23Z"),
"state" : "WA", "price" : 13, "quantity" : 104, "averageQuantity" : 104 }
{ "_id" : 0, "type" : "chocolate", "orderDate" : ISODate("2020-05-18T14:10:30Z"),
"state" : "CA", "price" : 13, "quantity" : 120, "averageQuantity" : 112 }
{ "_id" : 2, "type" : "vanilla", "orderDate" : ISODate("2021-01-11T06:31:15Z"),
"state" : "CA", "price" : 12, "quantity" : 145, "averageQuantity" : 145 }
{ "_id" : 1, "type" : "chocolate", "orderDate" : ISODate("2021-03-20T11:30:05Z"),
"state" : "WA", "price" : 14, "quantity" : 140, "averageQuantity" : 142.5 }
Use Documents Window to Obtain Cumulative and Maximum Quantity for Each Year使用文档窗口获取每年的累计数量和最大数量
This example uses a documents window in 本例使用$setWindowFields to output the cumulative and maximum cake sales quantity values for each $year in orderDate:$setWindowFields中的documents窗口来输出orderDate中每个$year的累计和最大蛋糕销售数量值:
db.cakeSales.aggregate( [
{
$setWindowFields: {
partitionBy: { $year: "$orderDate" },
sortBy: { orderDate: 1 },
output: {
cumulativeQuantityForYear: {
$sum: "$quantity",
window: {
documents: [ "unbounded", "current" ]
}
},
maximumQuantityForYear: {
$max: "$quantity",
window: {
documents: [ "unbounded", "unbounded" ]
}
}
}
}
}
] )
In the example:在示例中:
partitionBy: "$orderDate"partitions the documents in the collection by按$yearinorderDate. There are are partitions for2019,2020, and2021.orderDate中的$year对集合中的文档进行分区。有2019年、2020年和2021年的分区。sortBy: { orderDate: 1 }sorts the documents in each partition by按orderDatein ascending order (1), so the earliestorderDateis first.orderDate按升序(1)对每个分区中的文档进行排序,因此最早的orderDate是第一个。output:输出:Sets the将cumulativeQuantityForYearfield to the cumulativequantityfor each year.cumulativeQuantityForYear字段设置为每年的累计quantity。Calculates the cumulative使用在quantityusing the$sumoperator run in a documents window.documents窗口中运行的$sum运算符计算累计quantity。The window contains documents between an该unboundedlower limit and thecurrentdocument. This means$sumreturns the cumulative quantity for the documents between the beginning of the partition and the current document.window包含介于unbounded下限和current文档之间的文档。这意味着$sum返回分区开始和当前文档之间文档的累计数量。Sets the将maximumQuantityForYearfield to the maximumquantityfor each year.maximumQuantityForYear字段设置为每年的最大数量。Calculates the maximum使用在quantityof all the documents using the$maxoperator run in a documents window.documents窗口中运行的$max运算符计算所有文档的最大quantity。The window contains documents between an该unboundedlower andupperlimit.window包含介于unbounded下限和上限之间的文档。This means这意味着$maxreturns the maximum quantity for the documents in the partition.$max将返回分区中文档的最大数量。
In this example output, the cumulative 在此示例输出中,累计quantity is shown in the cumulativeQuantityForYear field and the maximum quantity is shown in the maximumQuantityForYear field:quantity显示在cumulativeQuantityForYear字段中,最大quantity显示在maximumQuantityForYear字段中:
{ "_id" : 5, "type" : "strawberry", "orderDate" : ISODate("2019-01-08T06:12:03Z"),
"state" : "WA", "price" : 43, "quantity" : 134,
"cumulativeQuantityForYear" : 134, "maximumQuantityForYear" : 162 }
{ "_id" : 4, "type" : "strawberry", "orderDate" : ISODate("2019-05-18T16:09:01Z"),
"state" : "CA", "price" : 41, "quantity" : 162,
"cumulativeQuantityForYear" : 296, "maximumQuantityForYear" : 162 }
{ "_id" : 3, "type" : "vanilla", "orderDate" : ISODate("2020-02-08T13:13:23Z"),
"state" : "WA", "price" : 13, "quantity" : 104,
"cumulativeQuantityForYear" : 104, "maximumQuantityForYear" : 120 }
{ "_id" : 0, "type" : "chocolate", "orderDate" : ISODate("2020-05-18T14:10:30Z"),
"state" : "CA", "price" : 13, "quantity" : 120,
"cumulativeQuantityForYear" : 224, "maximumQuantityForYear" : 120 }
{ "_id" : 2, "type" : "vanilla", "orderDate" : ISODate("2021-01-11T06:31:15Z"),
"state" : "CA", "price" : 12, "quantity" : 145,
"cumulativeQuantityForYear" : 145, "maximumQuantityForYear" : 145 }
{ "_id" : 1, "type" : "chocolate", "orderDate" : ISODate("2021-03-20T11:30:05Z"),
"state" : "WA", "price" : 14, "quantity" : 140,
"cumulativeQuantityForYear" : 285, "maximumQuantityForYear" : 145 }
Range Window Example范围窗口示例
This example uses a range window in 本例使用$setWindowFields to return the sum of the quantity values of cakes sold for orders within plus or minus 10 dollars of the current document's price value:$setWindowFields中的range窗口,返回当前文档price值的正负10美元范围内订单销售的蛋糕quantity值的总和:
db.cakeSales.aggregate( [
{
$setWindowFields: {
partitionBy: "$state",
sortBy: { price: 1 },
output: {
quantityFromSimilarOrders: {
$sum: "$quantity",
window: {
range: [ -10, 10 ]
}
}
}
}
}
] )
In the example:在示例中:
partitionBy: "$state"partitions the documents in the collection by按state. There are partitions forCAandWA.state对集合中的文档进行分区。CA和WA有分区。sortBy: { price: 1 }sorts the documents in each partition by按pricein ascending order (1), so the lowestpriceis first.price升序(1)对每个分区中的文档进行排序,因此最低price是第一位的。outputsets the将quantityFromSimilarOrdersfield to the sum of thequantityvalues from the documents in a range window.quantityFromSimilarOrders字段设置为range窗口中文档的quantity值之和。The window contains documents between a lower limit of该窗口包含介于-10and an upper limit of10. The range is inclusive.-10的下限和10的上限之间的文档。范围包括在内。$sumreturns the sum of返回当前文档quantityvalues contained in a range of plus or minus 10 dollars of the current document'spricevalue.price值的正负10美元范围内包含的quantity值的总和。
In this example output, the sum of the 在此示例输出中,窗口中文档的quantity values for documents in the window is shown in the quantityFromSimilarOrders field:quantity值之和显示在quantityFromSimilarOrders字段中:
{ "_id" : 2, "type" : "vanilla", "orderDate" : ISODate("2021-01-11T06:31:15Z"),
"state" : "CA", "price" : 12, "quantity" : 145, "quantityFromSimilarOrders" : 265 }
{ "_id" : 0, "type" : "chocolate", "orderDate" : ISODate("2020-05-18T14:10:30Z"),
"state" : "CA", "price" : 13, "quantity" : 120, "quantityFromSimilarOrders" : 265 }
{ "_id" : 4, "type" : "strawberry", "orderDate" : ISODate("2019-05-18T16:09:01Z"),
"state" : "CA", "price" : 41, "quantity" : 162, "quantityFromSimilarOrders" : 162 }
{ "_id" : 3, "type" : "vanilla", "orderDate" : ISODate("2020-02-08T13:13:23Z"),
"state" : "WA", "price" : 13, "quantity" : 104, "quantityFromSimilarOrders" : 244 }
{ "_id" : 1, "type" : "chocolate", "orderDate" : ISODate("2021-03-20T11:30:05Z"),
"state" : "WA", "price" : 14, "quantity" : 140, "quantityFromSimilarOrders" : 244 }
{ "_id" : 5, "type" : "strawberry", "orderDate" : ISODate("2019-01-08T06:12:03Z"),
"state" : "WA", "price" : 43, "quantity" : 134, "quantityFromSimilarOrders" : 134 }
Time Range Window Examples时间范围窗口示例
Use a Time Range Window with a Positive Upper Bound使用具有正上限的时间范围窗口
The following example uses a window with a positive upper bound time range unit in 以下示例在$setWindowFields. $setWindowFields中使用一个具有正上限时间范围unit的window。The pipeline outputs an array of 管道为每个与指定时间范围匹配的orderDate values for each state that match the specified time range.state输出一个orderDate值数组。
db.cakeSales.aggregate( [
{
$setWindowFields: {
partitionBy: "$state",
sortBy: { orderDate: 1 },
output: {
recentOrders: {
$push: "$orderDate",
window: {
range: [ "unbounded", 10 ],
unit: "month"
}
}
}
}
}
] )
In the example:在示例中:
partitionBy: "$state"partitions the documents in the collection by按state. There are partitions forCAandWA.state对集合中的文档进行分区。CA和WA有分区。sortBy: { orderDate: 1 }sorts the documents in each partition by按orderDatein ascending order (1), so the earliestorderDateis first.orderDate按升序(1)对每个分区中的文档进行排序,因此最早的orderDate是第一个。output:输出:Sets the将每个orderDateArrayForStatearray field toorderDatevalues for the documents in eachstate.state下文档的orderDateArrayForState数组字段设置为orderDate值。The array elements are expanded with additions to the previous elements in the array.数组元素是通过添加数组中先前的元素来展开的。Uses使用$pushto return an array oforderDatevalues from the documents in a range window.$push返回range窗口中文档的orderDate值数组。
The window contains documents between an该unboundedlower limit and an upper limit set to10(10 months after the current document'sorderDatevalue) using a time range unit.window包含unbounded下限和使用时间范围单位设置为10(当前文档的orderDate值后10个月)的上限之间的文档。$pushreturns the array oforderDatevalues for the documents between the beginning of the partition and the documents withorderDatevalues inclusively in a range of the current document'sorderDatevalue plus10months.$push返回文档的orderDate值数组,该数组位于分区的开头和orderDate值包含在当前文档的orderDate值加上10个月的范围内的文档之间。
In this example output, the array of 在此示例输出中,orderDate values for CA and WA is shown in the recentOrders field:CA和WA的orderDate值数组显示在recentOrders字段中:
{ "_id" : 4, "type" : "strawberry", "orderDate" : ISODate("2019-05-18T16:09:01Z"),
"state" : "CA", "price" : 41, "quantity" : 162,
"recentOrders" : [ ISODate("2019-05-18T16:09:01Z") ] }
{ "_id" : 0, "type" : "chocolate", "orderDate" : ISODate("2020-05-18T14:10:30Z"),
"state" : "CA", "price" : 13, "quantity" : 120,
"recentOrders" : [ ISODate("2019-05-18T16:09:01Z"), ISODate("2020-05-18T14:10:30Z"), ISODate("2021-01-11T06:31:15Z") ] }
{ "_id" : 2, "type" : "vanilla", "orderDate" : ISODate("2021-01-11T06:31:15Z"),
"state" : "CA", "price" : 12, "quantity" : 145,
"recentOrders" : [ ISODate("2019-05-18T16:09:01Z"), ISODate("2020-05-18T14:10:30Z"), ISODate("2021-01-11T06:31:15Z") ] }
{ "_id" : 5, "type" : "strawberry", "orderDate" : ISODate("2019-01-08T06:12:03Z"),
"state" : "WA", "price" : 43, "quantity" : 134,
"recentOrders" : [ ISODate("2019-01-08T06:12:03Z") ] }
{ "_id" : 3, "type" : "vanilla", "orderDate" : ISODate("2020-02-08T13:13:23Z"),
"state" : "WA", "price" : 13, "quantity" : 104,
"recentOrders" : [ ISODate("2019-01-08T06:12:03Z"), ISODate("2020-02-08T13:13:23Z") ] }
{ "_id" : 1, "type" : "chocolate", "orderDate" : ISODate("2021-03-20T11:30:05Z"),
"state" : "WA", "price" : 14, "quantity" : 140,
"recentOrders" : [ ISODate("2019-01-08T06:12:03Z"), ISODate("2020-02-08T13:13:23Z"), ISODate("2021-03-20T11:30:05Z") ] }
Use a Time Range Window with a Negative Upper Bound使用具有负上限的时间范围窗口
The following example uses a window with a negative upper bound time range unit in 以下示例在$setWindowFields. $setWindowFields中使用一个具有负上限时间范围unit的window。The pipeline outputs an array of 管道为每个与指定时间范围匹配的orderDate values for each state that match the specified time range.state输出一个orderDate值数组。
db.cakeSales.aggregate( [
{
$setWindowFields: {
partitionBy: "$state",
sortBy: { orderDate: 1 },
output: {
recentOrders: {
$push: "$orderDate",
window: {
range: [ "unbounded", -10 ],
unit: "month"
}
}
}
}
}
] )
In the example:在示例中:
partitionBy: "$state"partitions the documents in the collection by按state. There are partitions forCAandWA.state对集合中的文档进行分区。CA和WA有分区。sortBy: { orderDate: 1 }sorts the documents in each partition by按orderDatein ascending order (1), so the earliestorderDateis first.orderDate按升序(1)对每个分区中的文档进行排序,因此最早的orderDate是第一个。output:输出:Sets the将每个orderDateArrayForStatearray field toorderDatevalues for the documents in eachstate.state下文档的orderDateArrayForState数组字段设置为orderDate值。The array elements are expanded with additions to the previous elements in the array.数组元素是通过添加数组中先前的元素来展开的。Uses使用$pushto return an array oforderDatevalues from the documents in a range window.$push返回range窗口中文档的orderDate值数组。
The window contains documents between an该unboundedlower limit and an upper limit set to-10(10 months before the current document'sorderDatevalue) using a time range unit.window包含unbounded下限和使用时间范围单位设置为-10(当前文档的orderDate值之前10个月)的上限之间的文档。$pushreturns the array of返回位于分区开头和orderDatevalues for the documents between the beginning of the partition and the documents withorderDatevalues inclusively in a range of the current document'sorderDatevalue minus10months.orderDate值包含在当前文档的orderDate值减去10个月的范围内的文档的orderDate值的数组。
In this example output, the array of 在此示例输出中,orderDate values for CA and WA is shown in the recentOrders field:CA和WA的orderDate值数组显示在recentOrders字段中:
{ "_id" : 4, "type" : "strawberry", "orderDate" : ISODate("2019-05-18T16:09:01Z"),
"state" : "CA", "price" : 41, "quantity" : 162,
"recentOrders" : [ ] }
{ "_id" : 0, "type" : "chocolate", "orderDate" : ISODate("2020-05-18T14:10:30Z"),
"state" : "CA", "price" : 13, "quantity" : 120,
"recentOrders" : [ ISODate("2019-05-18T16:09:01Z") ] }
{ "_id" : 2, "type" : "vanilla", "orderDate" : ISODate("2021-01-11T06:31:15Z"),
"state" : "CA", "price" : 12, "quantity" : 145,
"recentOrders" : [ ISODate("2019-05-18T16:09:01Z") ] }
{ "_id" : 5, "type" : "strawberry", "orderDate" : ISODate("2019-01-08T06:12:03Z"),
"state" : "WA", "price" : 43, "quantity" : 134,
"recentOrders" : [ ] }
{ "_id" : 3, "type" : "vanilla", "orderDate" : ISODate("2020-02-08T13:13:23Z"),
"state" : "WA", "price" : 13, "quantity" : 104,
"recentOrders" : [ ISODate("2019-01-08T06:12:03Z") ] }
{ "_id" : 1, "type" : "chocolate", "orderDate" : ISODate("2021-03-20T11:30:05Z"),
"state" : "WA", "price" : 14, "quantity" : 140,
"recentOrders" : [ ISODate("2019-01-08T06:12:03Z"), ISODate("2020-02-08T13:13:23Z") ] }
See also: 另请参阅:
For an additional example about IOT Power Consumption, see the Practical MongoDB Aggregations有关IOT功耗的其他示例,请参阅实用MongoDB聚合电子书。 e-book.