$replaceWith (aggregation)

Example 1

An example collection sales is populated with the following documents:示例集合sales由以下文档填充：

db.sales.insertMany([
   { "_id" : 1, "item" : "butter", "price" : 10, "quantity": 2, date: ISODate("2019-03-01T08:00:00Z"), status: "C" },
   { "_id" : 2, "item" : "cream", "price" : 20, "quantity": 1, date: ISODate("2019-03-01T09:00:00Z"), status: "A" },
   { "_id" : 3, "item" : "jam", "price" : 5, "quantity": 10, date: ISODate("2019-03-15T09:00:00Z"), status: "C" },
   { "_id" : 4, "item" : "muffins", "price" : 5, "quantity": 10, date: ISODate("2019-03-15T09:00:00Z"), status: "C" }
])

Assume that for reporting purposes, you want to calculate for each completed sale, the total amount as of the current report run time. 假设出于报告目的，您希望为每个已完成的销售计算截至当前报告运行时的总金额。The following operation finds all the sales with status C and creates new documents using the $replaceWith stage. 以下操作查找状态为C的所有销售，并使用$replaceWith阶段创建新文档。The $replaceWith calculates the total amount as well as uses the variable NOW to get the current time.$replaceWith计算总额，并使用变量NOW获取当前时间。

db.sales.aggregate([
   { $match: { status: "C" } },
   { $replaceWith: { _id: "$_id", item: "$item", amount: { $multiply: [ "$price", "$quantity"]}, status: "Complete", asofDate: "$$NOW" } }
])

The operation returns the following documents:该操作返回以下文档：

{ "_id" : 1, "item" : "butter", "amount" : 20, "status" : "Complete", "asofDate" : ISODate("2019-06-03T22:47:54.812Z") }
{ "_id" : 3, "item" : "jam", "amount" : 50, "status" : "Complete", "asofDate" : ISODate("2019-06-03T22:47:54.812Z") }
{ "_id" : 4, "item" : "muffins", "amount" : 50, "status" : "Complete", "asofDate" : ISODate("2019-06-03T22:47:54.812Z") }

Example 2

An example collection reportedsales is populated with the reported sales information by quarter and regions:示例集合reportedsales按季度和地区填充报告的销售信息：

db.reportedsales.insertMany( [
   { _id: 1, quarter: "2019Q1", region: "A", qty: 400 },
   { _id: 2, quarter: "2019Q1", region: "B", qty: 550 },
   { _id: 3, quarter: "2019Q1", region: "C", qty: 1000 },
   { _id: 4, quarter: "2019Q2", region: "A", qty: 660 },
   { _id: 5, quarter: "2019Q2", region: "B", qty: 500 },
   { _id: 6, quarter: "2019Q2", region: "C", qty: 1200 }
] )

Assume that for reporting purposes, you want to view the reported sales data by quarter; e.g.假设出于报告目的，您希望按季度查看报告的销售数据；例如。

{ "_id" : "2019Q1", "A" : 400, "B" : 550, "C" : 1000 }

To view the data grouped by quarter, you can use the following aggregation pipeline:要查看按季度分组的数据，可以使用以下聚合管道：

db.reportedsales.aggregate( [
   { $addFields: { obj:  { k: "$region", v: "$qty" } } },
   { $group: { _id: "$quarter", items: { $push: "$obj" } } },
   { $project: { items2: { $concatArrays: [ [ { "k": "_id", "v": "$_id" } ], "$items" ] } } },
   { $replaceWith: { $arrayToObject: "$items2" } }
] )

First stage:第一阶段：

The $addFields stage adds a new obj document field that defines the key k as the region value and the value v as the quantity for that region. $addFields阶段添加一个新的obj文档字段，该字段将键k定义为区域值，将值v定义为该区域的数量。For example:例如：

{ "_id" : 1, "quarter" : "2019Q1", "region" : "A", "qty" : 400, "obj" : { "k" : "A", "v" : 400 } }

Second stage:第二阶段：

The $group stage groups by the quarter and uses $push to accumulate the obj fields into a new items array field. $group阶段按季度分组，并使用$push将obj字段累积到一个新的items数组字段中。For example:例如：

{ "_id" : "2019Q1", "items" : [ { "k" : "A", "v" : 400 }, { "k" : "B", "v" : 550 }, { "k" : "C", "v" : 1000 } ] }

Third stage:第三阶段：

The $project stage uses $concatArrays to create a new array items2 that includes the _id info and the elements from the items array:$project阶段使用$concatArrays创建一个新的数组items2，其中包括_id信息和items数组中的元素：

{ "_id" : "2019Q1", "items2" : [ { "k" : "_id", "v" : "2019Q1" }, { "k" : "A", "v" : 400 }, { "k" : "B", "v" : 550 }, { "k" : "C", "v" : 1000 } ] }

Fourth stage:第四阶段：

The $replaceWith uses the $arrayToObject to convert the items2 into a document, using the specified key k and value v pairs and outputs that document to the next stage. $replaceWith使用$arrayToObject将items2转换为文档，使用指定的键k和值v对，并将该文档输出到下一阶段。For example:例如：

{ "_id" : "2019Q1", "A" : 400, "B" : 550, "C" : 1000 }

The aggregation returns the following document:聚合返回以下文档：

{ "_id" : "2019Q1", "A" : 400, "B" : 550, "C" : 1000 }
{ "_id" : "2019Q2", "A" : 660, "B" : 500, "C" : 1200 }