$unwind (aggregation)

Field Path Operand字段路径操作数

You can pass the array field path to $unwind. 您可以将数组字段路径传递给$unwind。When using this syntax, $unwind does not output a document if the field value is null, missing, or an empty array.使用此语法时，如果字段值为null、缺失或空数组，$unwind不会输出文档。

{ $unwind: <field path> }

When you specify the field path, prefix the field name with a dollar sign $ and enclose in quotes.指定字段路径时，在字段名称前面加上美元符号$，并用引号括起来。

Document Operand with Options带选项的文档操作数

You can pass a document to $unwind to specify various behavior options.您可以将文档传递给$unwind以指定各种行为选项。

{
  $unwind:
    {
      path: <field path>,
      includeArrayIndex: <string>,
      preserveNullAndEmptyArrays: <boolean>
    }
}

Non-Array Field Path非数组字段路径

Missing Field缺失字段

If you specify a path for a field that does not exist in an input document or the field is an empty array, $unwind, by default, ignores the input document and will not output documents for that input document.如果为输入文档中不存在的字段指定路径，或者该字段为空数组，则默认情况下，$unwind将忽略输入文档，并且不会输出该输入文档的文档。

To output documents where the array field is missing, null or an empty array, use the preserveNullAndEmptyArrays option.若要输出缺少数组字段、空或空数组的文档，请使用preserveNullAndEmptyArrays选项。

Unwind Array展开数组

In mongosh, create a sample collection named inventory with the following document:在mongosh中，使用以下文档创建名为inventory的样本集合：

db.inventory.insertOne({ "_id" : 1, "item" : "ABC1", sizes: [ "S", "M", "L"] })

The following aggregation uses the $unwind stage to output a document for each element in the sizes array:以下聚合使用$unwind阶段为sizes数组中的每个元素输出文档：

db.inventory.aggregate( [ { $unwind : "$sizes" } ] )

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

{ "_id" : 1, "item" : "ABC1", "sizes" : "S" }
{ "_id" : 1, "item" : "ABC1", "sizes" : "M" }
{ "_id" : 1, "item" : "ABC1", "sizes" : "L" }

Each document is identical to the input document except for the value of the sizes field which now holds a value from the original sizes array.每个文档都与输入文档相同，但sizes字段的值除外，该字段现在保存原始sizes数组中的值。

Missing or Non-array Values缺少或非数组值

Consider the clothing collection:以clothing集合为例：

db.clothing.insertMany([
  { "_id" : 1, "item" : "Shirt", "sizes": [ "S", "M", "L"] },
  { "_id" : 2, "item" : "Shorts", "sizes" : [ ] },
  { "_id" : 3, "item" : "Hat", "sizes": "M" },
  { "_id" : 4, "item" : "Gloves" },
  { "_id" : 5, "item" : "Scarf", "sizes" : null }
])

$unwind treats the sizes field as a single element array if:如果出现以下情况，$unwind将大小字段视为单个元素数组：

• the field is present,存在场，
• the value is not null, and该值不为空，并且
• the value is not an empty array.值不是空数组。

Expand the sizes arrays with $unwind:使用$unwind展开sizes数组：

db.clothing.aggregate( [ { $unwind: { path: "$sizes" } } ] )

The $unwind operation returns:$unwind操作返回：

{ _id: 1, item: 'Shirt', sizes: 'S' },
{ _id: 1, item: 'Shirt', sizes: 'M' },
{ _id: 1, item: 'Shirt', sizes: 'L' },
{ _id: 3, item: 'Hat', sizes: 'M' }

• In document "_id": 1, sizes is a populated array. 在文档"_id": 1中，sizes是一个填充数组$unwind returns a document for each element in the sizes field.$unwind为sizes字段中的每个元素返回一个文档。
• In document "_id": 3, sizes resolves to a single element array.在文档"_id": 3中，sizes解析为单个元素数组。
• Documents "_id": 2, "_id": 4, and "_id": 5 do not return anything because the sizes field cannot be reduced to a single element array.文档"_id": 2, "_id": 4和"_id": 5不返回任何内容，因为sizes字段不能缩减为单个元素数组。

db.clothing.aggregate( [ { $unwind: "$sizes" } ] )
db.clothing.aggregate( [ { $unwind: { path: "$sizes" } } ] )

preserveNullAndEmptyArrays and 和includeArrayIndex

The preserveNullAndEmptyArrays and includeArrayIndex examples use the following collection:preserveNullAndEmptyArrays和includeArrayIndex索引示例使用以下集合：

db.inventory2.insertMany([
   { "_id" : 1, "item" : "ABC", price: NumberDecimal("80"), "sizes": [ "S", "M", "L"] },
   { "_id" : 2, "item" : "EFG", price: NumberDecimal("120"), "sizes" : [ ] },
   { "_id" : 3, "item" : "IJK", price: NumberDecimal("160"), "sizes": "M" },
   { "_id" : 4, "item" : "LMN" , price: NumberDecimal("10") },
   { "_id" : 5, "item" : "XYZ", price: NumberDecimal("5.75"), "sizes" : null }
])

db.inventory2.aggregate( [
   { $unwind: { path: "$sizes", preserveNullAndEmptyArrays: true } }
] )

{ "_id" : 1, "item" : "ABC", "price" : NumberDecimal("80"), "sizes" : "S" }
{ "_id" : 1, "item" : "ABC", "price" : NumberDecimal("80"), "sizes" : "M" }
{ "_id" : 1, "item" : "ABC", "price" : NumberDecimal("80"), "sizes" : "L" }
{ "_id" : 2, "item" : "EFG", "price" : NumberDecimal("120") }
{ "_id" : 3, "item" : "IJK", "price" : NumberDecimal("160"), "sizes" : "M" }
{ "_id" : 4, "item" : "LMN", "price" : NumberDecimal("10") }
{ "_id" : 5, "item" : "XYZ", "price" : NumberDecimal("5.75"), "sizes" : null }

db.inventory2.aggregate( [
  {
    $unwind:
      {
        path: "$sizes",
        includeArrayIndex: "arrayIndex"
      }
   }])

{ "_id" : 1, "item" : "ABC", "price" : NumberDecimal("80"), "sizes" : "S", "arrayIndex" : NumberLong(0) }
{ "_id" : 1, "item" : "ABC", "price" : NumberDecimal("80"), "sizes" : "M", "arrayIndex" : NumberLong(1) }
{ "_id" : 1, "item" : "ABC", "price" : NumberDecimal("80"), "sizes" : "L", "arrayIndex" : NumberLong(2) }
{ "_id" : 3, "item" : "IJK", "price" : NumberDecimal("160"), "sizes" : "M", "arrayIndex" : null }

Group by Unwound Values按Unwound值分组

In mongosh, create a sample collection named inventory2 with the following documents:在mongosh中，使用以下文档创建名为inventory2的样本集合：

db.inventory2.insertMany([
  { "_id" : 1, "item" : "ABC", price: NumberDecimal("80"), "sizes": [ "S", "M", "L"] },
  { "_id" : 2, "item" : "EFG", price: NumberDecimal("120"), "sizes" : [ ] },
  { "_id" : 3, "item" : "IJK", price: NumberDecimal("160"), "sizes": "M" },
  { "_id" : 4, "item" : "LMN" , price: NumberDecimal("10") },
  { "_id" : 5, "item" : "XYZ", price: NumberDecimal("5.75"), "sizes" : null }
])

The following pipeline unwinds the sizes array and groups the resulting documents by the unwound size values:以下管道展开sizes数组，并根据展开的大小值对结果文档进行分组：

db.inventory2.aggregate( [
   // First Stage
   {
     $unwind: { path: "$sizes", preserveNullAndEmptyArrays: true }
   },
   // Second Stage
   {
     $group:
       {
         _id: "$sizes",
         averagePrice: { $avg: "$price" }
       }
   },
   // Third Stage
   {
     $sort: { "averagePrice": -1 }
   }
] )

First Stage:第一阶段：

The $unwind stage outputs a new document for each element in the sizes array. $unwind阶段为sizes数组中的每个元素输出一个新文档。The stage uses the preserveNullAndEmptyArrays option to include in the output those documents where sizes field is missing, null or an empty array. 该阶段使用preserveNullAndEmptyArrays选项在输出中包括缺少sizes字段、null或空数组的文档。This stage passes the following documents to the next stage:此阶段将以下文件传递到下一阶段：

{ "_id" : 1, "item" : "ABC", "price" : NumberDecimal("80"), "sizes" : "S" }
{ "_id" : 1, "item" : "ABC", "price" : NumberDecimal("80"), "sizes" : "M" }
{ "_id" : 1, "item" : "ABC", "price" : NumberDecimal("80"), "sizes" : "L" }
{ "_id" : 2, "item" : "EFG", "price" : NumberDecimal("120") }
{ "_id" : 3, "item" : "IJK", "price" : NumberDecimal("160"), "sizes" : "M" }
{ "_id" : 4, "item" : "LMN", "price" : NumberDecimal("10") }
{ "_id" : 5, "item" : "XYZ", "price" : NumberDecimal("5.75"), "sizes" : null }

Second Stage:第二阶段：

The $group stage groups the documents by sizes and calculates the average price of each size. $group阶段按sizes对文档进行分组，并计算每个大小的平均价格。This stage passes the following documents to the next stage:此阶段将以下文档传递到下一阶段：

{ "_id" : "S", "averagePrice" : NumberDecimal("80") }
{ "_id" : "L", "averagePrice" : NumberDecimal("80") }
{ "_id" : "M", "averagePrice" : NumberDecimal("120") }
{ "_id" : null, "averagePrice" : NumberDecimal("45.25") }

Third Stage:第三阶段：

The $sort stage sorts the documents by averagePrice in descending order. The operation returns the following result:$sort阶段按averagePrice按降序对文档进行排序。该操作返回以下结果：

{ "_id" : "M", "averagePrice" : NumberDecimal("120") }
{ "_id" : "L", "averagePrice" : NumberDecimal("80") }
{ "_id" : "S", "averagePrice" : NumberDecimal("80") }
{ "_id" : null, "averagePrice" : NumberDecimal("45.25") }

Unwind Embedded Arrays解开嵌入式数组

In mongosh, create a sample collection named sales with the following documents:在mongosh中，使用以下文档创建名为sales的样本集合：

db.sales.insertMany([
  {
    _id: "1",
    "items" : [
     {
      "name" : "pens",
      "tags" : [ "writing", "office", "school", "stationary" ],
      "price" : NumberDecimal("12.00"),
      "quantity" : NumberInt("5")
     },
     {
      "name" : "envelopes",
      "tags" : [ "stationary", "office" ],
      "price" : NumberDecimal("19.95"),
      "quantity" : NumberInt("8")
     }
    ]
  },
  {
    _id: "2",
    "items" : [
     {
      "name" : "laptop",
      "tags" : [ "office", "electronics" ],
      "price" : NumberDecimal("800.00"),
      "quantity" : NumberInt("1")
     },
     {
      "name" : "notepad",
      "tags" : [ "stationary", "school" ],
      "price" : NumberDecimal("14.95"),
      "quantity" : NumberInt("3")
     }
    ]
  }
])

The following operation groups the items sold by their tags and calculates the total sales amount per each tag.以下操作将按标签销售的项目分组，并计算每个标签的总销售额。

db.sales.aggregate([
  // First Stage
  { $unwind: "$items" },
  // Second Stage
  { $unwind: "$items.tags" },
  // Third Stage
  {
    $group:
      {
        _id: "$items.tags",
        totalSalesAmount:
          {
            $sum: { $multiply: [ "$items.price", "$items.quantity" ] }
          }
      }
  }
])

First Stage第一阶段

The first $unwind stage outputs a new document for each element in the items array:第一个$unwind阶段为items数组中的每个元素输出一个新文档：

{ "_id" : "1", "items" : { "name" : "pens", "tags" : [ "writing", "office", "school", "stationary" ], "price" : NumberDecimal("12.00"), "quantity" : 5 } }
{ "_id" : "1", "items" : { "name" : "envelopes", "tags" : [ "stationary", "office" ], "price" : NumberDecimal("19.95"), "quantity" : 8 } }
{ "_id" : "2", "items" : { "name" : "laptop", "tags" : [ "office", "electronics" ], "price" : NumberDecimal("800.00"), "quantity" : 1 } }
{ "_id" : "2", "items" : { "name" : "notepad", "tags" : [ "stationary", "school" ], "price" : NumberDecimal("14.95"), "quantity" : 3 } }

Second Stage第二阶段

The second $unwind stage outputs a new document for each element in the items.tags arrays:第二个$unwind阶段为items.tags数组中的每个元素输出一个新文档：

{ "_id" : "1", "items" : { "name" : "pens", "tags" : "writing", "price" : NumberDecimal("12.00"), "quantity" : 5 } }
{ "_id" : "1", "items" : { "name" : "pens", "tags" : "office", "price" : NumberDecimal("12.00"), "quantity" : 5 } }
{ "_id" : "1", "items" : { "name" : "pens", "tags" : "school", "price" : NumberDecimal("12.00"), "quantity" : 5 } }
{ "_id" : "1", "items" : { "name" : "pens", "tags" : "stationary", "price" : NumberDecimal("12.00"), "quantity" : 5 } }
{ "_id" : "1", "items" : { "name" : "envelopes", "tags" : "stationary", "price" : NumberDecimal("19.95"), "quantity" : 8 } }
{ "_id" : "1", "items" : { "name" : "envelopes", "tags" : "office", "price" : NumberDecimal("19.95"), "quantity" : 8 } }
{ "_id" : "2", "items" : { "name" : "laptop", "tags" : "office", "price" : NumberDecimal("800.00"), "quantity" : 1 } }
{ "_id" : "2", "items" : { "name" : "laptop", "tags" : "electronics", "price" : NumberDecimal("800.00"), "quantity" : 1 } }
{ "_id" : "2", "items" : { "name" : "notepad", "tags" : "stationary", "price" : NumberDecimal("14.95"), "quantity" : 3 } }
{ "_id" : "2", "items" : { "name" : "notepad", "tags" : "school", "price" : NumberDecimal("14.95"), "quantity" : 3 } }

Third Stage第三阶段

The $group stage groups the documents by the tag and calculates the total sales amount of items with each tag:$group阶段按标记对文档进行分组，并计算每个标记的项目的总销售额：

{ "_id" : "writing", "totalSalesAmount" : NumberDecimal("60.00") }
{ "_id" : "stationary", "totalSalesAmount" : NumberDecimal("264.45") }
{ "_id" : "electronics", "totalSalesAmount" : NumberDecimal("800.00") }
{ "_id" : "school", "totalSalesAmount" : NumberDecimal("104.85") }
{ "_id" : "office", "totalSalesAmount" : NumberDecimal("1019.60") }